case study for product life cycle

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What is Product Life Cycle (PLC)?

Product Life Cycle (PLC) is a model that illustrates how a product progresses through stages during its time on the market. It serves as a tool for businesses to understand how their products evolve and how to manage them efficiently. This concept plays a role in making decisions regarding product development, marketing strategies, pricing strategies, and distribution channels. In today’s paced world of business and innovation, it is crucial to grasp the Product Life Cycle (PLC).

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Stages of Product Life Cycle (PLC)

Case study of product life cycle of apple, key takeaways from product life cycle (plc):.

• The PLC is a concept in marketing and product management that helps businesses plan strategically and make informed decisions about their products.
• This cycle represents the stages that a product goes through starting from its introduction to its decline in the market.
• Understanding these stages allows companies to adapt their strategies effectively maximizing profits and ensuring long-term success for their products.

1. Introduction

The introduction stage signifies the entry of a product into the market. The initial stage is typically associated with an increase in sales since it involves introducing the product to consumers. During this phase, businesses incur expenses for marketing and research and development (R&D) as they strive to raise awareness and stimulate demand for their product. Companies need to invest in marketing and create distribution channels to ensure that their product is easily accessible to customers. The objective is to establish a presence in the market and generate interest. During this phase, pricing strategies often revolve around two approaches:

• Penetration pricing, where a lower price is initially offered to gain market share,
• Skimming pricing, where a higher price is charged at first to recover development costs.

The growth stage witnesses a surge in sales as consumers become more aware of the product’s existence and its advantages. This growth is fueled by word-of-mouth favourable reviews and effective marketing campaigns. In this phase, businesses strive to expand their market share by scaling up production and distribution. With the increasing demand, competition may intensify as new players try to capitalise on the opportunity. As the product gains recognition, pricing strategies might shift towards a competitive approach. Companies may also introduce variations or extensions of the product aimed at market segments.

3. Maturity

The maturity stage represents the peak of sales and market penetration for the product. Competition typically reaches its point during this period, and attention shifts from attracting customers to retaining existing ones. Price stability and product differentiation become a feature of this stage. Ongoing marketing endeavours aimed at maintaining both market share and brand loyalty. Companies frequently make investments in improving their products, adding features, and implementing marketing campaigns to ensure their products remain relevant and competitive. Furthermore, they may explore opportunities in markets.

In the decline phase, sales of the product start to decrease due to changing consumer preferences, market saturation, or the emergence of alternatives. Companies must decide whether to discontinue the product or continue selling, it with marketing efforts. As existing inventory price reductions or discounts may be necessary, some companies may choose to reinvent or rebrand the product or find markets to extend its life cycle. Ultimately, the decision to withdraw or revive the product depends on its profitability and how well it aligns with the company’s strategy.

Introduction Phase

During the phase from 2007 to 2008, Apple introduced the iPhone, which brought about a significant transformation in the smartphone industry. To generate awareness and create excitement surrounding their product, Apple invested heavily in marketing and promotional activities. The innovative design and user-friendly interface of the iPhone captured the interest of tech enthusiasts. Capitalising on this wave of enthusiasm, Apple implemented a pricing strategy that involved charging prices initially.

Growth Stage

In the years that followed from 2009 to 2012, the iPhone experienced growth. Apple expanded its range of offerings by introducing models like the iPhone 3G, 4, and 4S. The launch of the App Store in 2008 played a role in fueling this growth by creating an ecosystem that catered to both developers and users alike. To meet increasing demand, Apple focused on scaling up production and distribution, while establishing partnerships with telecom carriers worldwide. Product differentiation also played a role during this stage as Apple offered storage capacities and introduced new features such as improved cameras and faster processors.

Maturity Phase

By 2013, the iPhone had reached maturity as it faced competition from Android-based smartphones. The market became saturated with options for consumers to choose from. To keep its position in the market, Apple put a lot of emphasis on improving its products. Released a series of iPhones, including the 5, 6, 7, and 8 models. They also introduced the Plus and SE versions. Alongside this, Apple carried on with its marketing campaigns that aimed to build brand loyalty and make sure customers were satisfied. Moreover, they expanded into markets, which helped solidify their position as a leading smartphone company.

Declining Stage

In years (2019 onwards), the iPhone entered a stage of decline where it faced obstacles, like market saturation and the rise of competitors. To tackle these challenges, Apple has adjusted its pricing strategies and introduced the affordable iPhone SE. Additionally, the company has heavily invested in services, like Apple Music, Apple TV+, and Apple Arcade to diversify its revenue streams and keep customers engaged. By focusing on refreshing its products and building an ecosystem around its devices, Apple has been able to prolong the lifespan of the iPhone and minimize the impact of market decline.

The Product Life Cycle (PLC) is a framework that helps businesses navigate their product’s complex journey in the market. By understanding the four stages of introduction, growth, maturity, and decline, companies can make choices regarding product development, pricing, marketing, and distribution. Effectively managing a product throughout its life cycle can lead to success and a competitive advantage in today’s dynamic business environment.

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The 6 Stages of the Product Life Cycle [+Examples]

Published: September 14, 2023

When I was 12 years old, I used to be confused about my cousin's CD collection. Why have CDs when I could go on iTunes and listen to all my favorite songs? This is a perfect example of a product life cycle (PLC) in action.

No one wants their product to become “obsolete” and reach the end of its product life cycle. That’s why it’s important to understand what stage your product is in so you can make better marketing and business decisions.

Below, we’ll learn about the product life cycle inside and out. If you’re in a pinch, use the links below to jump straight to what you need:

What is the product life cycle?

What are the stages of the product life cycle, importance of the product life cycle, breaking down the product life cycle theory, product life cycle marketing strategies, product life cycle examples, international product life cycle, when to use the product life cycle.

The product life cycle is the succession of stages that a product goes through during its existence, starting from development and ultimately ending in decline. Business owners and marketers use the product life cycle to make important decisions and strategies on advertising budgets, product prices, and packaging.

In the marketing industry, the typical depiction of the product life cycle only has four main stages — Introduction, Growth, Maturity, and Decline. At HubSpot, we agree that these are vital for a product, but the two stages “Development” and “Decline” aren’t nearly covered enough.

This phase can last for a long time, depending on the complexity of the product, how new it is, and the competition. For a completely new product, the development stage is particularly difficult because the first pioneer of a product isn’t always as successful as later iterations.

Before full-scale production, the product may be released in a limited market or region for testing purposes. This allows companies to assess market acceptance, gather user feedback, and make necessary adjustments before a wider launch.

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2. Introduction

The introduction stage happens when a product is launched in the marketplace. This is when marketing teams begin building product awareness and targeting potential customers. Typically, when a product is introduced, sales are low and demand builds slowly.

In this phase, marketers focus on advertising and marketing campaigns. They also work on testing distribution channels and building product and brand awareness.

This stage is crucial because companies have the opportunity to shake up the status quo and capture the attention and loyalty of early adopters. The positive experiences and word-of-mouth recommendations from these early customers can influence the broader target market and accelerate product adoption.

Some examples of products currently in the introduction stage include:

• Generative AI
• Self-driving cars
• 3D televisions

Ultimately, the success of this stage sets the foundation for the product’s future growth and success in subsequent stages of the product life cycle.

During the growth stage, consumers have accepted the product in the market and customers are beginning to truly buy in. That means demand and profits are growing, hopefully at a steadily rapid pace. This momentum is crucial for sustaining business operations, funding further product development, and generating returns on investment.

As companies scale, they can benefit from lower per-unit production costs, improved supplier relationships, and optimized distribution networks.

However, there are some challenges that come with the growth stage. As the market for the product expands, competition grows. Potential competitors will see your success and will want in.

Some products that are currently in the growth stage are:

• Smartwatches
• Electric cars

During this stage, it’s important to keep attracting new customers and solidify your brand image so you can stay ahead of the competition.

4. Maturity

The maturity stage is when the sales begin to level off from the rapid growth period. At this point, companies begin to reduce their prices so they can stay competitive amongst the growing competition. Streamlining production processes, negotiating favorable supplier contracts, and optimizing distribution networks also become important considerations.

This is the phase where a company begins to become more efficient and learns from the mistakes made in the introduction and growth stages. Marketing campaigns are typically focused on differentiation rather than awareness. This means that product features might be enhanced, prices might be lowered, and distribution becomes more intensive.

During the maturity stage, products begin to enter the most profitable stage. The cost of production declines while the sales are increasing.

• Smartphones
• Video game consoles

5. Saturation

During the product saturation stage, competitors have begun to take a portion of the market and products will experience neither growth nor decline in sales.

Typically, this is the point when most consumers are using a product, but there are many competing companies. At this point, you want your product to become the brand preference so you don't enter the decline stage. To achieve this, you’ll want to focus on providing exceptional service and building strong relationships with your customers.

In a saturated market, innovation also becomes essential to stay relevant. Businesses must continuously invest in research and development to improve products and offer new features. Failure to do so may lead to product obsolescence and loss of market share.

Some examples of products in the saturation stage are:

• Streaming services
• Breakfast cereals
• Soft drinks

Unfortunately, if your product doesn‘t become the preferred brand in a marketplace, you’ll typically experience a decline. Sales will decrease during the heightened competition, which is hard to overcome.

Decline also occurs when products become outdated or less relevant as newer technologies enter the market. Consumers may turn to more advanced options, rendering the declining product less desirable.

If a company is at this stage, it'll either discontinue its product, sell the company, or innovate and iterate on its product in some way.

Here are a few examples of products in the decline stage:

• CDs and cassette tapes
• Landline telephones

The best companies will usually have products at several points in the product life cycle at any given time. Some companies look to other countries to begin the cycle anew.

The product life cycle is important because it informs an organization’s management and decision-makers how well a product is performing and what strategic actions it will take to succeed. This helps companies allocate resources like staff, budgets, shows which products should be prioritized, and where the company should innovate next.

Other benefits of using the product life cycle include:

• Make better marketing investments and decisions
• Easier to make long-term plans
• Allows for better decision making with accurate information on performance
• Easier to streamline current processes within your company

Product Life Cycle Limitations

While using the PLC method certainly helps stakeholders plan, it does have limitations. The cycle breaks down performance over several stages, but unfortunately there is no way to tell how long each stage will last.

Complicating things further, not all products will move through these stages at the same pace. For example, a product may take longer to decline than others. Plus product managers run the risk of not dedicating enough effort and resources into a particular product if they think the product will decline, creating planned obsolescence – even if customers still use it.

In the late ‘60s, Harvard Business School professor Raymond Vernon developed this marketing theory in response to an economic model that failed to account for trends present in international trade – that’s why it was originally called the international product life cycle theory.

It stated that products developed in an international market had three phases:

• New product
• Maturing product
• Standardized product

Here’s a quick breakdown of his theory.

Vernon theorized a new product would perform best in its country of origin to keep manufacturing and production costs low. Once the product gained demand, companies could begin exporting to other countries and continue building local production plants in each new location.

Having these local plants would offer the flexibility to make changes to the product without incurring huge costs.

The standardized phase would involve an influx of competitors, which would lead the company to focus on driving down production and manufacturing costs to remain competitive. As the market becomes saturated and a new product gets introduced, the company loses its relevance in its home country and shifts gears to create something new, with the cycle beginning again.

Since then, the product life cycle theory has evolved to focus less on geography and more on marketing. Let’s dive into it next.

You can use this template to map out your own product's life cycle phases.

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Product Lifecycle

A product strategy is dynamic and evolves alongside the product. The Product Owner adjusts it over time to reflect changes in the market and customer behaviors. From the initial introduction of a product to eventual decline, each phase of the product life cycle presents unique challenges and opportunities. By understanding in which stage a product is in its life cycle, organizations and Scrum Teams can apply and adapt their product strategy allowing them to stay competitive and serve their customer’s needs.

One way to do this is by using the product life cycle model as a guide to track the different stages a product goes through from market introduction to market withdrawal. 

                                                                  Image Source: Red Tangerine

Though the model appears to be linear, products do not always move from one stage to the next one. In reality, they tend to shift back and forward between stages, depending on the goals that are being pursued and the product strategy that is being applied. Just like a dying tree could be nourished back to good health with the right care, a product strategy could create new opportunities for a mature or declining product. What strategy to use at what stage depends on context as shown in the following examples.

Introduction Product Launch! At this stage there are many unknowns and demand for the product will still need to be created. Questions to explore as part of the product strategy might be focusing on the launch of your new product such as:

• How to launch the product?
• How do we create demand for our product?
• How to penetrate the market? 
• How to achieve product-market fit?
• What audience are we targeting?

Growth In this phase the product is growing, there is an increasing demand for the product, the number of users is getting larger and sales are growing. At this stage, the product strategy might focus on questions such as: 

• How can we increase our market share? 
• What can we do to ensure our product stays attractive and therefore preserve its growth? 
• What audience are we targeting? Has our audience changed? What audience could we target to expand?  

Maturity A sign that a product has entered the mature stage is when it has stopped growing, meaning it has stagnated and there is a struggle to increase the number of users and the benefits the product creates for the organization. As part of the strategy questions such as below can be worth exploring:

• How deep is our product in maturity? Has it only recently stagnated or has this been going on for some time?
• Is it worth adapting our product or product offering to increase desirability and attract new users?
• Is it worth introducing our product to new markets? 
• Should we let the product mature and plan on how to transition to new product development?
• Who is our current audience? How do we maintain market share with them?  

Decline When a product is not benefiting the company and customer anymore or taking away from another product that the company thinks is superior, it is time to consider retiring the product. When a Product Owner has decided to retire a product, they should plan how they will discontinue it. An important step is to identify the audience who is still using the product. This helps with developing new products, and formulating a new product onboarding approach. It also helps you provide a plan for your current customers and user to move to other options so that they are not left sidelined. Some questions to explore as you consider retiring your product are:

• What data and information do we have to support the case for retiring our product?
• Has the market changed? How much unrealized (potential) value is there left to pursue?
• Does our product still benefit our organization?
• Does our product still benefit our customers?
• Is this product still aligned with the organization’s strategic goals?
• Who is our audience? What are their needs? Are they worth satisfying with this product or another solution?  

Knowing where a product is in its life cycle enables the Product Owner to make informed decisions that drive the product's success and ensure its relevance in the market.  

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Case Studies for Product Management: A Deep Dive

We can all agree that applying real-world product management strategies is crucial for success.

This comprehensive guide dives deep into illuminating case studies across various industries, providing actionable insights on critical decision-making frameworks.

Introduction to Product Management Case Studies

Product management involves overseeing a product from conception to production to ensure it meets customer needs. Frameworks like the Product Development Life Cycle provide structure for taking a product through different stages like planning, prototyping, development, and growth.

Studying real-world examples is invaluable for gaining insight into successful product strategies across industries. By analyzing concrete case studies, product managers can understand how top companies conceptualize, develop, and improve their offerings.

Defining Product Management and its Frameworks

The role of a product manager is to understand customer needs and guide development of solutions. This involves research, planning, coordination across teams, and analysis.

Some key frameworks provide processes for product managers:

• Product Development Life Cycle - Conceptualization, Development, Growth, Maturity Decline
• Jobs To Be Done - Focusing on the job the customer aims to get done
• Design Thinking - Empathizing, Defining, Ideating, Prototyping, Testing

These frameworks help structure product decisions and strategy.

Importance of Best Case Studies for Product Management

Analyzing detailed examples of product management in action provides:

• Real-world demonstrations of frameworks
• Examples of product development decisions
• Insights into product successes and failures
• Strategies across industries and product types

By studying case studies, product managers can learn best practices to apply in their own work.

Overview of Industries and Product Case Study Examples

Upcoming sections will explore product management case studies from:

• Technology - Software, hardware, apps
• Retail & ecommerce - Online and brick-and-mortar stores
• Financial services - Banks, investment platforms
• Healthcare - Electronic medical records, patient apps

Specific companies like Apple, Nike, Intuit, Kaiser Permanente will be used to demonstrate product decisions.

What are case studies for Product management?

Case studies provide in-depth analyses of how real products were developed, launched, and iterated on over time in order to achieve success. They offer product managers valuable insights into proven product management strategies across various industries.

By examining case studies, product managers can learn how top companies approached critical activities like:

• Conducting market research
• Defining product requirements based on user needs
• Prioritizing features and functionality
• Developing prototypes and minimum viable products (MVPs)
• Designing effective user experiences
• Iterating based on user feedback
• Tracking key metrics and optimizing
• Developing go-to-market strategies
• Scaling successfully

Additionally, case studies allow readers to understand the reasoning behind key decisions, including both successes and failures. They provide a unique inside look at product development processes through real examples.

Overall, product management case studies enable new and experienced product managers to enhance their approach by learning from past experiences across a diverse range of companies, products, and industries.

How to make structure in case studies for Product management?

Studying product management case studies is a key step to understanding real-world examples of product strategies and decision-making. When analyzing case studies, having a clear framework helps extract key insights. Here are four steps to structure your analysis:

Evaluate the Need

• What customer problem does the product solve?
• How was the need validated through research?
• What metrics indicate the market size and demand?

Validate the Solution

• How does the product solution address the key pain points?
• Were experiments and prototypes done to validate assumptions?
• What early traction or usage metrics demonstrate solution fit?

Set Goals and KPIs

• What key goals and objectives guide the product roadmap?
• How do key performance indicators track progress towards goals?
• What metrics align to the customer and business goals?

Evaluate Decisions and Outcomes

• What key decisions shaped the product strategy and features?
• How did experiments and iterations impact the product direction?
• What final business and customer results were achieved?

Using this structure ensures you gather insights across the product lifecycle - from identifying needs, defining solutions, to measuring outcomes. Analyzing case studies this way quickly reveals the key decisions and strategies behind a product's success.

What are the 4 types of case study?

Case studies are an effective way to showcase examples of successful product management strategies and provide valuable insights into real-world scenarios. There are four main types of case studies:

Illustrative Case Studies

These provide a descriptive overview of a product, business, or industry. They tell the story of a product's development, struggles and successes. Illustrative case studies help set the scene and provide context.

Exploratory Case Studies

Also known as pilot case studies, these are condensed case studies performed before implementing a large scale investigation. They aim to gather preliminary data and help determine the focus, design and feasibility of a larger case study.

Cumulative Case Studies

These aggregate quantitative information from several sites or sources. They compile data in order to answer a research question, like assessing the performance of a product across a variety of markets.

Critical Instance Case Studies

These examine a single instance of intense interest. They provide valuable insights from a business success or failure. For product managers, these help illustrate how even minor details can impact product adoption and performance.

How to prepare for case study interview for product manager?

Preparing for a case study interview as a product manager candidate requires focused preparation across four key areas:

Understanding the Case Study

• Research the company, product, industry, and business context thoroughly to identify potential issues and scenarios the case study may present.
• Review your knowledge of key product management frameworks like market sizing, PRD writing, prioritization matrices, and financial modeling to brush up on core competencies.

Knowing the Interviewers

• Understand the background and seniority level of the interviewers. More senior panelists may expect more strategic thinking vs tactical execution.
• Identify any particular viewpoint an interviewer may bring given their role - engineering, design, growth, etc.

Setting Assumptions

• Clarify any assumptions you can make about the case details upfront instead of getting derailed later.
• Be ready to set limitations around scope, resources, timelines, budgets, or success metrics if not explicitly provided.

Applying Strategy

• Use an open-ended, discovery-based approach for broad business challenges without an obvious solution path.
• Leverage a more narrow, focused analytical strategy for executional cases with clearer parameters.

Following this four-step approach when preparing for a case study interview enables product manager candidates to systematically evaluate the situation, tailor their approach, and demonstrate strong analytical abilities sought after in PMs. The ability to clarify, strategize, and execute under ambiguity is what interviewers look for.

Product Development Case Studies

This section features examples of innovative and user-focused product development processes that led to successful outcomes.

Apple iPod's Intuitive Design Principles

Apple's development of the iPod is a great case study for simple, intuitive product design centered around understanding user needs. When Apple was developing the iPod, they focused extensively on the user experience and identifying pain points in existing MP3 players.

Some key insights that guided the iPod's design:

• Users wanted to easily carry their whole music library with them
• Managing and scrolling through huge song libraries was tedious
• Existing players had complex, confusing controls

To address these issues, Apple designed the click wheel interface to make scrolling through songs incredibly simple and fast. The intuitive menu system also made adding songs easy. And using a compact, hard drive-based design allowed the iPod to store thousands of songs so users could carry their whole library.

The end result was a revolutionary product that felt almost magical to use because it understood and solved core user needs so well. The iPod's intuitive design shows how focusing on user experience over specs can lead to market-defining products.

Iterative Improvement in Google Maps

Google Maps exemplifies a data-driven, iterative approach to product improvement. After launching Maps in 2005, Google constantly monitored usage metrics and user feedback to guide improvements.

Some key iterative changes:

• Added more business information and integrated reviews after seeing people search for places
• Improved driving directions with features like traffic data and alternative routes based on user complaints
• Added Street View and walking directions to address user needs beyond just driving

This methodical improvement process, driven by real user data, allowed Google Maps to completely dominate digital mapping and navigation despite strong competition from established players like MapQuest early on.

The ongoing success of Google Maps highlights that launching the perfect product out of the gate is nearly impossible - you need an iterative process fueled by usage metrics and user input.

Amazon Kindle: Filling the Market Gap

The Amazon Kindle provides an excellent case study in identifying and addressing gaps in existing markets. The Kindle team realized there were no truly great hardware devices focused exclusively on long-form reading.

They saw an opportunity to create a better reading experience by analyzing pain points with physical books:

• Books can be heavy and bulky during travel
• Finding new books means physically going to stores
• Paying for individual books adds up in cost

To solve these user problems, Amazon designed the Kindle ereader hardware to be extremely portable while giving on-demand access to Amazon's massive ebook library.

Additionally, they offered subscriptions and cheaper pricing models for digital content through the Kindle Store ecosystem. This revolutionary approach filled the market gap for dedicated digital reading hardware and content delivery that consumers were waiting for.

The runaway success of Kindle highlights the opportunities in understanding pain points with current solutions and addressing them with innovative new products.

Product Management Case Study Framework

Case studies provide invaluable insights into real-world applications of product management best practices. By analyzing examples of successful and failed product launches, product managers can identify effective frameworks to guide strategic decision-making. This section explores key frameworks evident across product management case studies and how cross-functional teams, market validation techniques, and lean principles contribute to positive outcomes.

Utilizing Cross-Functional Teams

Collaborative teams comprising diverse expertise increase the likelihood of creating products that effectively solve customer needs. Case studies demonstrate that supporting collaboration between product managers, engineers, designers, and business stakeholders leads to:

• Enhanced understanding of customer problems
• Validation of product solutions against real user needs
• Improved transparency and buy-in across organizations

For example, the case study XYZ shows that increased coordination between product and engineering during development boosted software quality by 34%. Similarly, early designer inclusion at ACME refined the user interface and improved conversion rates after launch.

Market Research and Validation

Case studies consistently highlight the importance of upfront market analysis and continuous customer validation to create successful products. Common factors include:

• Comprehensive competitor analysis to identify market white space
• Dedicated qualitative and quantitative market research around problem/solution fit
• Multiple rounds of prototype tests with target users at each product stage gate

The case study for 123Workforce illustrates this. By gathering over 500 customer discovery interviews, the product validated strong demand for a new employee scheduling tool. This market validation supported business case approval to build an MVP.

Lean Product Development Techniques

Case studies demonstrate that lean principles enable effective product iteration based on real user feedback versus internal assumptions. Specifically:

• Minimum viable product (MVP) releases help fail fast and cheaply
• Continuous build-measure-learn loops rapidly incorporate user inputs
• Evidence-based prioritization focuses on the highest customer value features

For example, PlanHub’s early MVP launch gathered inputs from initial users to refine core features rather than overinvesting upfront. This lean approach facilitated quicker time-to-market and product-market fit.

In summary, case study analysis provides frameworks to help product managers incorporate cross-functional participation, customer validation, and lean methods for successful product outcomes.

Product Launch and Marketing Case Studies

This section highlights creative, strategic product launches and marketing initiatives that generated significant consumer interest.

Dropbox's Innovative Referral Program

Dropbox pioneered referral marketing in the SaaS industry with its onboarding flow that rewarded users for sharing the product. This helped Dropbox rapidly acquire customers in a capital-efficient way in the early stages.

Some key aspects of Dropbox's referral scheme that made it effective:

• Frictionless sharing: Users could easily access a unique referral link to share Dropbox with friends and family. The seamless referral integration incentivized sharing.
• Reward structure: Both referrer and referee got extra storage space for signing up, appealing to primary needs of users.
• Virality: Strong incentive structure combined with easy sharing options enabled Dropbox's impressive viral coefficient.

The referral program strategy supported Dropbox's rapid user base growth and helped establish it as a leading file hosting/sharing SaaS application.

Leveraging Slack's Freemium Model

Slack employed a tactical shift from a paid-only model to a freemium pricing strategy. This opened doors for viral enterprise adoption by allowing teams to try Slack's communication software for free up to a usage limit.

Key aspects that made Slack's freemium work:

• Generous free tier: The free version provided enough value for small teams to collaborate. This established stickiness.
• Self-service signup: Smooth self-service signup enabled easy adoption by businesses without sales interaction.
• Virality features: Free teams could invite other free teams, propagating usage. Upgrades were natural with business growth.

Enabling teams to try the product risk-free via the freemium version supported Slack's rapid business growth . It helped position Slack for success in the team communication software market.

Peloton's Premium Positioning

Peloton pioneered the high-tech fitness bike concept with integrated digital content. Its marketing focused on positioning Peloton as a premium product to justify the $2000+ pricing.

Strategic aspects of Peloton's positioning:

• Targeted high-income consumers who valued premium brands as status symbols. This supported the elevated pricing.
• Curated aspirational brand content around exclusive lifestyles to promote product desire. Raked in sales despite pricing.
• Stimulated engagement via leaderboards and social features to lock in recurring subscription revenue.

The premium marketing positioning strategy enabled Peloton to drive rapid sales growth despite its high ticket prices relative to traditional exercise bikes.

Product Management Case Study Interview Insights

Case study interviews are a crucial part of the product management interview process. They allow candidates to demonstrate their analytical thinking, problem-solving abilities, and understanding of user experience best practices. Preparing for case study questions and mastering methods like the STAR approach can help PM candidates stand out.

Mastering the STAR Method

The STAR method is an effective framework for structuring responses to case study interview questions. STAR stands for:

• Situation - Set the context by concisely outlining the background of the case study.
• Task - Describe the problem you need to solve or goals you need to achieve.
• Action - Explain the step-by-step process you would take to address the situation. Show your analytical approach.
• Result - Share the outcome of your proposed actions and how they achieve the desired goals. Quantify the impact if possible.

Using the STAR method demonstrates you can methodically break down complex issues and drive towards solutions. When executed well, it highlights critical PM skills like prioritization, metrics-driven thinking, and cross-functional collaboration .

Analytical Thinking and Problem-Solving

Case study interviews evaluate your comfort with ambiguity and your capacity to structure unclear problems. Interviewers look for analytical thinking - your ability to synthesize data, identify root causes, and balance tradeoffs.

Shine a light on your analytical abilities by:

• Asking clarifying questions before diving into solutions
• Mapping out all stakeholders and components of the system
• Determining which metrics are most important and relevant to track
• Proposing hypotheses before making decisions
• Quantifying the impact of your recommendations with estimates

This showcases your aptitude for breaking down and solving complex product challenges.

Highlighting User Experience Outcomes

While analytics are crucial, PMs must balance quantitative rigor with qualitative empathy. Case studies let you demonstrate user centricity - evaluating ideas through the user's eyes.

To highlight UX sensibilities, discuss how your solutions:

• Simplify or improve key user flows
• Reduce friction during onboarding
• Increase retention by solving pain points
• Improve satisfaction via new delighters

This underscores the customer value created and your ability to advocate for users. Quantify improvements to showcase your user focus.

Ongoing Product Management Case Studies

This section focuses on outstanding examples of continually evolving products by listening to users and proactively addressing their needs.

Duolingo: Mastering App Gamification

Duolingo has refined their app over time to balance user enjoyment and motivation to drive engagement. For example, they introduced timed practice sessions and streak bonuses to incentivize daily use. They also gamified the experience with virtual rewards and levels to make language learning fun. As a result, Duolingo has over 500 million downloads and has become the world's most popular language learning app. Their case demonstrates the value of continually optimizing gamification elements based on usage data.

Amazon: A Culture of Customer Obsession

Amazon's customer-centric culture focuses on constant refinement of the user experience. For example, they use customer feedback and behavior data to surface relevant products and recommendations. They also optimize delivery speed and convenience through initiatives like Prime and same-day delivery. This obsession with understanding and serving customers has helped Amazon dominate multiple industries online. Product teams can learn from Amazon's disciplined approach of aggregating signals from users and translating insights into interface improvements.

Uber: Strategic Market Expansion

Rather than rapidly expanding globally, Uber tailored its rollout strategy city-by-city. This allowed them to adapt their product and operations to address local needs. For example, they integrated cash payments in India where credit card use is lower. They also customized promotions and subsidies by market to balance growth and profitability. Uber's patient but deliberate expansion enabled sustainable gains that a rushed, untargeted strategy may have compromised. Their expansion playbook demonstrates the merits of crafting versatile products that serve regional variations.

Key Takeaways and Best Practices

The product management case studies explored demonstrate several essential insights and best practices:

The Centrality of User-Centricity

Deep understanding of user needs and putting the customer first were critical success factors across many examples. Companies that made user research and testing core to their process were best able to refine their offerings.

The Power of Continuous Iteration

Few companies got their product right from day one. The most effective demonstrated a commitment to constant iteration based on user feedback rather than striving for perfection at launch.

Innovative Strategies in Action

We saw clever approaches to pricing, promotion and user acquisition. For example, one company offered free plans to students to drive adoption and another used influencer campaigns on social media to increase awareness.

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This comprehensive guide promises to equip you with a structured approach to tackling product case studies. You'll gain frameworks to methodically analyze prompts and craft insightful solutions.

Through real-world application, valuable feedback, and community engagement with groups like The Product Folks, PMs can significantly accelerate their skill development and expertise in the dynamic field of product management.

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What Is the Product Life Cycle?

• How It Works
• Limitations

Product Life Cycle vs. BCG Matrix

• Introduction and Maturity

The Bottom Line

• Small Business

Product Life Cycle Explained: Stage and Examples

Ariel Courage is an experienced editor, researcher, and former fact-checker. She has performed editing and fact-checking work for several leading finance publications, including The Motley Fool and Passport to Wall Street.

The term product life cycle refers to the length of time from when a product is introduced to consumers into the market until it's removed from the shelves. This concept is used by management and by marketing professionals as a factor in deciding when it is appropriate to increase advertising, reduce prices, expand to new markets, or redesign packaging. The process of strategizing ways to continuously support and maintain a product is called product life cycle management .

Key Takeaways

• A product life cycle is the amount of time a product goes from being introduced into the market until it's taken off the shelves.
• There are four stages in a product's life cycle—introduction, growth, maturity, and decline.
• A company often incurs higher marketing costs when introducing a product to the market but experiences higher sales as product adoption grows.
• Sales stabilize and peak when the product's adoption matures, though competition and obsolescence may cause its decline.
• The concept of product life cycle helps inform business decision-making, from pricing and promotion to expansion or cost-cutting.

Investopedia / Xiaojie Liu

How the Product Life Cycle Works

Products, like people, have life cycles. The life cycle of a product is broken into four stages—introduction, growth, maturity , and decline.

A product begins with an idea, and within the confines of modern business, it isn't likely to go further until it undergoes research and development (R&D) and is found to be feasible and potentially profitable. At that point, the product is produced, marketed, and rolled out. Some product life cycle models include product development as a stage, though at this point, the product has not yet been brought to customers.

As mentioned above, there are four generally accepted stages in the life cycle of a product. Here are details about each one.

Introduction Stage

The introduction phase is the first time customers are introduced to the new product. A company must generally includes a substantial investment in advertising and a marketing campaign focused on making consumers aware of the product and its benefits, especially if it is broadly unknown what the item will do.

During the introduction stage, there is often little-to-no competition for a product, as competitors may just be getting a first look at the new offering. However, companies still often experience negative financial results at this stage as sales tend to be lower, promotional pricing may be low to drive customer engagement, and the sales strategy is still being evaluated.

Growth Stage

If the product is successful, it then moves to the growth stage. This is characterized by growing demand , an increase in production, and expansion in its availability. The amount of time spent in the introduction phase before a company's product experiences strong growth will vary from between industries and products.

During the growth phase, the product becomes more popular and recognizable. A company may still choose to invest heavily in advertising if the product faces heavy competition. However, marketing campaigns will likely be geared towards differentiating its product from others as opposed to introducing the goods to the market. A company may also refine its product by improving functionality based on customer feedback.

Financially, the growth period of the product life cycle results in increased sales and higher revenue. As competition begins to offer rival products, competition increases, potentially forcing the company to decrease prices and experience lower margins.

Maturity Stage

The maturity stage of the product life cycle is the most profitable stage, the time when the costs of producing and marketing decline. With the market saturated with the product, competition now higher than at other stages, and profit margins starting to shrink, some analysts refer to the maturity stage as when sales volume is "maxed out".

Depending on the good, a company may begin deciding how to innovate its product or introduce new ways to capture a larger market presence. This includes getting more feedback from customers, and researching their demographics and their needs.

During the maturity stage, competition is at the highest level. Rival companies have had enough time to introduce competing and improved products, and competition for customers is usually highest. Sales levels stabilize, and a company strives to have its product exist in this maturity stage for as long as possible.

A new product needs to be explained, while a mature product needs to be differentiated.

Decline Stage

As the product takes on increased competition as other companies emulate its success, the product may lose market share and begin its decline. Product sales begin to drop due to market saturation and alternative products, and the company may choose to not pursue additional marketing efforts as customers may already have determined whether they are loyal to the company's products or not.

Should a product be entirely retired , the company will stop generating support for it and will entirely phase out marketing endeavors. Alternatively, the company may decide to revamp the product or introduce a next-generation, completely overhauled model. If the upgrade is substantial enough, the company may choose to re-enter the product life cycle by introducing the new version to the market.

The stage of a product's life cycle impacts the way in which it is marketed to consumers. A new product needs to be explained, while a mature product needs to be differentiated from its competitors.

Advantages of Using the Product Life Cycle

The product life cycle better allows marketers and business developers to better understand how each product or brand sits with a company's portfolio. This enables the company to internally shift resources to specific products based on those products' positioning within the product life cycle.

For example, a company may decide to reallocate market staff time to products entering the introduction or growth stages. Alternatively, it may need to invest more cost of labor in engineers or customer service technicians as the product matures.

The product life cycle naturally tends to have a positive impact on economic growth, as it promotes innovation and discourages supporting outdated products. As products move through the life cycle stages, companies that use the product life cycle can realize the need to make their products more effective, safer, efficient, faster, cheaper, or better suited to client needs.

Limitations of Using the Product Life Cycle

Despite its utility for planning and analysis, the product life cycle doesn't pertain to every industry and doesn't work consistently across all products. Consider popular beverage lines whose primary products have been in the maturity stage for decades, while spin-offs or variations of these drinks from the same company have failed.

The product life cycle also may be artificial in industries with legal or trademark restrictions. Consider the new patent term of 20 years from which the application for the patent was filed in the United States. Though a drug may be just entering their growth stage, it may be adversely impacted by competition when its patent ends regardless of which stage it is in.

Another unfortunate side effect of the product life cycle is prospective planned obsolescence. When a product enters the maturity stage, a company may be tempted to begin planning its replacement. This may be the case even if the existing product still holds many benefits for customers and still has a long shelf life. For producers who tend to introduce new products every few years, this may lead to product waste and inefficient use of product development resources.

Notification messages such as Microsoft's alert that Windows 8.1 will sunset on January 2023 is an example of decline. Due to obsolescence of the operating system, Microsoft is choosing to no longer support the product and instead focus resources on newer technologies.

A similar analytical tool to determine the market positioning of a product is the Boston Consulting Group (BCG) Matrix . This four-square table defines products based on their market growth and market share:

• "Stars" are products with high market growth and high market share.
• "Cash cows" are products with low market growth and high market share.
• "Question marks," also known as "problem children," are products with high market growth and low market share.
• "Dogs" are products with low market growth and low market share.

Although there is no direct relationship between the matrix and the product life cycle concept, both analyze a product's market growth and saturation. However, the BCG Matrix does not traditionally communicate the direction in which a product will move. For example, a product that has entered the maturity stage of the product life cycle will likely experience decline next; the BCG Matrix does not communicate this product flow in its visual depiction.

Introduction and Maturity: Special Considerations

Companies that have a good handle on all four stages can increase profitability and maximize their returns . Those that aren't able to may experience an increase in their marketing and production costs, ultimately leading to the limited shelf life for their product(s).

Back in 1965, Theodore Levitt, a marketing professor, wrote in the Harvard Business Review that the innovator is the one with the most to lose because so many truly new products fail at the first phase of their life cycle—the introductory stage. The failure comes only after the investment of substantial money and time into research, development, and production. This fact prevents many companies from even trying anything really new. Instead, he said, they wait for someone else to succeed and then clone the success.

To cite an established and still-thriving industry, television program distribution has related products in all stages of the product life cycle. OLED TVs are in the mature phase, programming-on-demand is in the growth stage, DVDs are in decline, and the videocassette is extinct.

Many of the most successful products on earth are suspended in the mature stage for as long as possible, undergoing minor updates and redesigns to keep them differentiated. Examples include Apple computers and iPhones, Ford's best-selling trucks, and Starbucks' coffee—all of which undergo minor changes accompanied by marketing efforts—are designed to keep them feeling unique and special in the eyes of consumers.

Examples of Product Life Cycles

Many brands that were American icons have dwindled and died. Better management of product life cycles might have saved some of them—or perhaps their time had just come.

Oldsmobile began producing cars in 1897. After merging with General Motors in 1908, the company used the first V-8 engine in 1916. By 1935, the one millionth Oldsmobile had been built. In 1984, Oldsmobile sales peaked, selling more cars in that year than any other year. By 2000, General Motors announced it would phase out the automobile and, on April 29th, 2004, the last Oldsmobile was built.

Woolworth Co.

In 1905, Frank Winfield Woolworth incorporated F.W. Woolworth Co., a general merchandise retail store. By 1929, Woolworth had about 2,250 outlet stores across the United States and Britain, Decades later, due to increased competition from other discount retailors, Woolworth closed the last of its variety stores in the United States in 1997 to increasingly focus on sporting goods.

On April 23, 1985, Coca-Cola announced a new formula for its popular beverage, referred to as "new Coke." Coca-Cola's market-share lead had been decreasing over the past 15 years, and the company decided to launch a new recipe in hopes of reinvigorating product interest. After its launch, Coca-Cola's phone line began receiving 1,500 calls per day, many of which were to complain about the change. Protest groups recruited 100,000 individuals to support their cause of bringing "old" Coke back.

A stunning 79 days after its launch, "new Coke's" full product life cycle was complete. Though the product didn't experience much growth or maturity, its introduction to the market was met with heavy protest. Less than three months after it announced its new recipe, Coca-Cola announced it would revert its product back to the original recipe.

What Are the Stages of the Product Life Cycle?

The product life cycle is defined as four distinct stages: product introduction, growth, maturity, and decline. The amount of time spent in each stage will vary from product to product, and different companies have different strategic approaches to transitioning from one phase to the next.

What Are Product Life Cycle Strategies?

Depending on the stage a product is in, a company may adopt different strategies along the product life cycle. For example, a company is more likely to incur heavy marketing and R&D costs in the introduction stage. As the product becomes more mature, companies may then turn to improving product quality, entering new segments, or increasing distribution channels. Companies also strategically approach divesting from product lines including the sale of divisions or discontinuation of goods.

What Is Product Life Cycle Management?

Product life cycle management is the act of overseeing a product's performance over the course of its life. Throughout the different stages of product life cycle, a company enacts strategies and changes based on how the market is receiving a good.

Why Is Product Life Cycle Important?

Product life cycle is important because it informs management of how its product is performing and what strategic approaches it may take. By being informed of which stage its product(s) are in, a company can change how it spends resources, which products to push, how to allocate staff time, and what innovations they want to research next.

Which Factors Impact a Product's Life Cycle?

Countless factors can affect how a product performs and where it lies within the product life cycle. In general, the product life cycle is heavily impacted by market adoption, ease of competitive entry, rate of industry innovation, and changes to consumer preferences. If it is easier for competitors to enter markets, consumers change their mind frequently about the goods they consume or the market becomes quickly saturated. Then, products are more likely to have shorter lives throughout a product life cycle.

Broadly speaking, almost every product sold undergoes the product life cycle. This cycle of market introduction, growth, maturity, and decline may vary from product to product—or industry to industry. However, this cycle informs a company of how to best utilize its resources, what the future outlook of their product is, and how to strategically plan for bringing new products to market.

Food and Drug Administration. " Frequently Asked Questions on Patents and Exclusivity ."

Microsoft. " Windows 8 and Windows 8.1 End of Support and Office ."

Harvard Business Review. " Exploit the Product Life Cycle ."

Oldsmobile Club of America. " History of Oldsmobile ."

Britannica. " Woolworth Co. "

The Coca-Cola Company. " The Story of One of the Most Memorable Marketing Blunders Ever ."

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Please note you do not have access to teaching notes, the product life cycle revisited: an integrative review and research agenda.

European Journal of Marketing

ISSN : 0309-0566

Article publication date: 7 January 2022

Issue publication date: 2 February 2022

This paper aims to respond to calls in academia for an update of the product lifecycle (PLC). Through a systematic literature review, the authors provide an updated agenda, which aims to advance the PLC concept in research, teaching and practice.

Design/methodology/approach

The authors started by surveying 101 marketing academics globally to ascertain whether a PLC update was viewed necessary and beneficial in the marketing community and thereafter conducted citation analysis of marketing research papers and textbooks to ascertain PLC usage. The subsequent literature review methodology was split into two sections. First, 97 empirical articles were reviewed based on an evaluative framework. Second, research pertaining to the PLC determinants were assessed and discussed.

From the results of this review and primary data from marketing academics, the authors find that the method of predicting the PLC based on past sales has been largely unsuccessful and perceived as somewhat outdated. However, a new stream of PLC literature is emerging, which takes a consumer-centric perspective to the PLC and has seen more success at modeling lifecycles in various industries.

Research limitations/implications

First, the study outlines the most contemporary and successful methodological approaches to modeling the PLC. Namely, the use of artificial intelligence, big data, demand modeling and consumer psychological mechanisms. Second, it provides several future research avenues using modern market trends such as sustainability, globalization, digitization and Covid-19 to push the PLC into the 21st century.

Originality/value

The PLC has shown to be resolutely popular in management application and education. However, without a continued effort in academic PLC research to update the knowledge around the concept, its use as a productive management tool will likely become outdated. This study provides a necessary and comprehensive literature update resulting in actionable future research and teaching agendas intended to advance the PLC concept into the modern market context.

• Product lifecycle
• Research agenda

Iveson, A. , Hultman, M. and Davvetas, V. (2022), "The product life cycle revisited: an integrative review and research agenda", European Journal of Marketing , Vol. 56 No. 2, pp. 467-499. https://doi.org/10.1108/EJM-08-2020-0594

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Table of Content

Understanding the product life cycle: a comprehensive guide.

Understanding the product life cycle, or the stages a product goes through from its launch to its sunset can help you understand how to market it at every stage to create the most optimal marketing strategies.

Ever wondered why your favourite gadget from childhood that you saw everywhere suddenly seems to have disappeared? The answer lies in the fascinating concept of the product life cycle. This framework explores the stages a product goes through, from its initial launch to its eventual decline. Understanding this cycle is crucial for businesses that want to develop effective marketing strategies and maximize success for their products.

What is the product life cycle?

The product life cycle is a concept that describes the stages a product goes through from its introduction to its eventual decline and removal from the market. It consists of four main stages: introduction, growth, maturity, and decline.

What are the stages of a product life cycle?

A product development life cycle typically consists of four distinct stages. They are:

The introduction stage

This initial phase marks the launch of the new product into the market. During this phase, companies look at strategies to build awareness about the product and establish a market presence. Companies rely on promotional activities to generate initial interest and typically experience limited sales, high marketing costs, and employ pricing strategies like skimming (high initial prices) or penetration (low prices) to capture early adopters. The product’s success heavily depends on effective product positioning, targeted marketing, and generating positive initial reviews.

The growth stage

The growth stage of a product sees its rapid growth, as it has been accepted into the market. During this phase, the focus is on expanding the reach of the product and maximizing profit. Companies often tend to look at new distribution channels and modify their marketing strategies to capture even more users or customers. To achieve success in the growth stage, companies need to look at maintaining the standard of their product, increasing the supply to meet the demand, and differentiating the product from the competitors.

The maturity stage

The maturity stage is marked by stable sales growth and market saturation. Sales growth rates stabilize as the product reaches its peak popularity. However, competition is still fierce, and companies focus on maintaining market share and profitability. Marketing efforts may shift towards customer retention and brand loyalty strategies. Companies may also explore product diversification or international expansion to sustain growth.

The decline stage

In the decline stage, sales begin to decline as consumer demand reduces or shifts towards newer products or technologies. Sales and profitability decline as the product reaches peak market saturation. Companies may face pricing pressure and a reduction in the margin. Strategies such as cost reduction, or targeting niche markets may be used to extend the product's life cycle. Eventually, the product is phased out (discontinued) or replaced by newer offerings.

What are some of the factors that can influence the product life cycle?

Changes in technology.

New technologies can disrupt existing industries and markets, making established products redundant or less desirable. For example, the introduction of smartphones revolutionized the mobile phone industry, leading to the decline of traditional handheld phones. Additionally, technological innovations can accelerate the pace of product development and adoption, shortening life cycles as newer, more advanced products enter the market. This also means that innovations can extend product life cycles by introducing new features, functionalities, or applications that enhance product value and meet evolving consumer needs.  

Market trends and customer preferences

As consumer preferences and market trends evolve, digital products must adapt to remain relevant and competitive. Changes in user interface design trends or the emergence of new platforms and technologies can influence consumer expectations and demand for digital products. For example, the rise of mobile apps has led to shorter life cycles for desktop software products, as consumers increasingly prefer mobile-friendly solutions. Additionally, shifts in consumer behavior, such as the growing preference for subscription-based services over one-time purchases, can also influence the life cycle of digital products. 

Competition

Companies continuously strive to gain a competitive edge by introducing new features, improving user experiences , and capturing market share. This intense competition often rushes the pace of product development and evolution, leading to shorter life cycles as companies compete for consumer attention and loyalty. For example, in the smartphone market, leading manufacturers such as Apple, Samsung, and Google release frequent product launches and upgrades to keep up with the market. Additionally, the presence of startups and disruptive technologies fuelled by AI forces established players to innovate and adapt to changing market conditions to maintain their competitiveness.

Changes in regulation

Changes in regulation can significantly impact the product life cycle of digital products by introducing new compliance requirements, standards, or restrictions. For instance, the implementation of data privacy regulations such as GDPR in the European Union has forced digital product providers to enhance data protection measures and update privacy policies. Additionally, changes in intellectual property laws or digital rights management regulations may influence product design, distribution channels, and licensing agreements, impacting the development and distribution of digital products.

Economic conditions

During periods of economic downturns or recessions, consumers may prioritize needs over wants, leading to reduced demand for digital products such as subscription-based services, software applications, or digital entertainment platforms. Alternatively, during economic expansions, rising disposable incomes can encourage demand for digital products, driving sales growth and market expansion. Additionally, fluctuations in currency exchange rates, inflation levels, and interest rates can affect production costs, pricing strategies, and profit margins for digital product developers.

Product innovation

Product innovation allows digital product developers to introduce new features, functionalities, and improvements that enhance user experiences and address emerging needs. For example, the introduction of augmented reality (AR) or virtual reality (VR) technologies has transformed gaming experiences, social media interactions, and e-commerce platforms, creating new avenues for user engagement and monetization.  

Distribution channels

Digital products rely on various distribution channels, such as online platforms, app stores, social media, and digital marketplaces, to reach their target audiences effectively. Changes in distribution channels can impact product availability, visibility, and discoverability, thereby influencing adoption rates and market penetration. However, disruptions in distribution channels, such as changes in platform policies, algorithm updates, or distribution partner agreements, can adversely affect product distribution and sales, leading to shorter life cycles.

Why should brands understand the product life cycle for their product?

Strategic planning.

Understanding the product life cycle helps businesses develop strategic plans for each stage, including product development, marketing, pricing, and distribution strategies. By aligning product strategies with the characteristics of each stage, businesses can maximize opportunities for growth and reduce risks associated with each stage.

Allocation of resources

The product life cycle informs resource allocation decisions, such as investment in research and development, marketing budgets, and production capacity. Businesses can allocate resources more effectively by focusing investments on high-growth stages and optimizing costs during the maturity or decline stages.

Competitive advantage

Understanding the product lifecycle enables businesses to anticipate market trends, customer preferences, and competitor behavior, giving them an advantage in the market. By staying ahead of the curve, businesses can innovate, differentiate their offerings, and capture market share more effectively.

Risk management

The product life cycle provides insights into potential risks and challenges at each stage, allowing businesses to proactively identify and avoid risks. By understanding the factors that influence the product's growth, businesses can develop contingency plans, diversify their product portfolios, and minimize exposure to market fluctuations.

Long-term planning

Understanding the product life cycle enables businesses to plan for the long term, including product extensions, upgrades, or diversification into new markets or product categories. By anticipating future opportunities and challenges, businesses can position themselves for the future and adapt to changing market conditions more effectively.

How can user research help you at each stage of the product life cycle?

During the introduction stage of the product life cycle, user research plays a critical role in shaping the product's success by providing valuable insights into target audiences and their needs. Here's how user research can help products in the introduction stage:

• Identifying the target audience: User research helps identify the primary target audience for the product by understanding their demographics, preferences, behaviors, and pain points. By conducting market research, surveys, and user interviews , companies can gain insights into who their potential users are, and what they are looking for in a product.
• Validating product concepts: Before investing significant resources into product development, user research can validate the product concept to ensure it resonates with the target audience. By gathering feedback on initial ideas, prototypes, or mock-ups, companies can gauge user interest, uncover potential concerns, and refine concepts.
• Understanding user needs: User research helps uncover the underlying needs, motivations, and desires of the target audience. By conducting user interviews, usability testing , and ethnographic studies, companies can gain a deeper understanding of what users are trying to accomplish and the challenges they face. This can inform product features and functionality.
• Refining user experience: User research informs the design and User Experience (UX) of the product to ensure it meets user expectations and preferences. By gathering feedback on usability, navigation, and visual design, companies can identify areas for improvement and iterate on the product to create a more intuitive and engaging user experience.
• Setting product priorities: User research helps prioritize features and functionality based on user needs and preferences. By understanding what features are most important to users and what would provide the most value, companies can focus their efforts on developing the core functionality that will resonate the most with the target audience.

During the growth stage of the product life cycle, user research continues to play a crucial role in driving product success and sustaining momentum. Here's how user research can help in this stage:

• Understanding user behavior: User research helps companies understand how users are interacting with the product during the growth stage. By analyzing user behavior, engagement metrics, and usage patterns, companies can identify areas of success and opportunities for improvement to optimize the product experience and drive continued growth.
• Identifying user needs and pain points: User research allows companies to track evolving user needs and preferences as the product gains popularity. By conducting surveys , interviews, and feedback sessions, companies can gather insights into emerging user needs, pain points, and feature requests, informing product developments to meet changing user expectations.
• Optimizing user onboarding and adoption: User research helps companies optimize user onboarding processes to drive higher adoption. By understanding the friction points in the user journey, companies can refine onboarding experiences to make it easier for new users to get started with the product and realize its value quickly.
• Testing new features and iterations: As the product grows, user research helps companies test new features, iterations, and enhancements to ensure they resonate with users and drive continued engagement. Through usability testing and A/B testing , companies can gather feedback on new features, gather insights into user preferences, and validate design decisions before full-scale rollouts.
• Personalization for different segments: User research enables companies to segment their user base and personalize the product experience to better meet the needs of different user segments. By understanding user demographics, behaviors, and preferences, companies can tailor features, content, and messaging to specific user groups, driving deeper engagement and loyalty.

In the maturity stage of the product lifecycle, user research remains essential for maintaining product relevance, competitiveness, and sustained success. Here's how user research can help in the maturity stage:

• Improving user experience and satisfaction: User research allows companies to continuously monitor user satisfaction and identify areas for improvement in the product experience. By gathering feedback through user surveys, satisfaction metrics , and usability testing, companies can pinpoint pain points and usability issues, to improve on them and enhance user satisfaction and loyalty.
• Optimizing product performance and stability: User research helps companies identify and address performance issues, bugs, and technical challenges affecting the product. By gathering feedback on performance metrics, error rates, and user-reported issues, companies can prioritize bug fixes, and product optimizations to ensure product quality, thereby enhancing user trust and satisfaction.
• Exploring product diversification and expansion: User research informs decisions about product diversification and expansion opportunities to sustain growth in the maturity stage. By understanding user needs and preferences, companies can identify adjacent markets, new use cases, or additional features that align with user interests and complement the existing product offering, enabling strategic expansion and revenue diversification.
• Fostering customer loyalty: User research helps companies nurture customer loyalty and advocacy by understanding what drives user engagement, retention, and advocacy. By gathering feedback on user motivations, satisfaction drivers, and loyalty metrics, companies can identify opportunities to reward loyal customers and incentivize referrals to foster long-term customer relationships.

In the decline stage of the product life cycle, user research can still play a part in understanding the reasons behind declining sales and user interest. Here's how user research can help products in the decline stage:

• Identifying user sentiment : User research helps companies gather feedback from existing users and churned customers to understand their reasons for disengagement or discontinuing the use of the product. By conducting user surveys, interviews, and feedback sessions, companies can uncover the factors contributing to user dissatisfaction and dropoff.
• Assessing competitive landscape: User research allows companies to assess the competitive landscape and understand how market dynamics and competitive offerings have contributed to the product's decline. By conducting competitor analysis, market research, and benchmarking studies , companies can identify shifts in user preferences, emerging competitors, or disruptive technologies impacting the product's relevance and competitiveness.
• Exploring alternative use cases or markets: User research informs decisions about exploring alternative use cases or markets to extend the product's relevance and lifespan. By understanding user needs and preferences, companies can identify alternative markets, niche segments, or new applications for the product that still address user needs, enabling product adaptations that extent its life cycle.
• Gathering insights for future initiatives: User research enables companies to capture lessons learned from the decline stage to inform future product development initiatives or new product launches. By conducting a thorough analysis of the product, companies can get valuable insights, identify areas for improvement, and apply learnings to future projects, ensuring continuous innovation.

What is stage 4 of the product development process?

Stage 4 of the product development process typically involves product testing and validation before market launch. This stage ensures that the product meets quality standards and addresses any issues or concerns identified during development.

What are the 4 Ps of marketing with examples?

The 4 Ps of marketing are Product, Price, Place, and Promotion. For example, a smartphone (Product) may be priced competitively (Price) and distributed through retail stores (Place) with promotional campaigns (Promotion) to attract customers.

What is the PLC in marketing?

PLC stands for Product Life Cycle in marketing. It refers to the stages a product goes through from introduction to decline in the market. These stages include introduction, growth, maturity, and decline.  

What is the full form of PLM?

PLM stands for Product Lifecycle Management. It encompasses the processes, tools, and strategies used to manage the entire lifecycle of a product, from ideation and design to manufacturing, distribution, and end-of-life disposal. PLM systems help streamline product development, improve collaboration, and optimize efficiency throughout the product lifecycle.

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Exploit the Product Life Cycle

• Theodore Levitt

How to convert a tantalizing concept into a managerial instrument of competitive power

Most alert and thoughtful senior marketing executives are by now familiar with the concept of the product life cycle. Even a handful of uniquely cosmopolitan and up-to-date corporate presidents have familiarized themselves with this tantalizing concept. Yet a recent survey I took of such executives found none who used the concept in any strategic way whatever, and pitifully few who used it in any kind of tactical way. It has remained—as have so many fascinating theories in economics, physics, and sex—a remarkably durable but almost totally unemployed and seemingly unemployable piece of professional baggage whose presence in the rhetoric of professional discussions adds a much-coveted but apparently unattainable legitimacy to the idea that marketing management is somehow a profession. There is, furthermore, a persistent feeling that the life cycle concept adds luster and believability to the insistent claim in certain circles that marketing is close to being some sort of science. 1

• TL Theodore Levitt was a professor emeritus of marketing at Harvard Business School and former editor of Harvard Business Review.

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The Product Life Cycle Simplified using Amul Products

• September 2, 2022
• Financial Statement Analysis , General Finance and Business resources , Technical & Research

Since more than a thousand years ago, we have lived in a consumerist civilization. Products are, of course, one of the foundations supporting materialism and the “more is good” mindset. Items are being made, sold, marketed, traded, and even thrown away everywhere you look or go, and milk is one of them. In this article, we will discuss about the product life cycle of amul in a detailed case study.

INTRODUCTION TO PRODUCT LIFE CYCLE OF AMUL

Since more than a thousand years ago, we have lived in a consumerist civilization.

Products are, of course, one of the foundations supporting materialism and the “more is good” mindset. Items are being made, sold, marketed, traded, and even thrown away everywhere you look or go, and milk is one of them.

With a capacity of 115 million tonnes, India produces more milk than any other country. Milk consumption in India is still increasing, driven by stable population growth and increased wealth. The dairy industry is now expanding at a volume-based yearly growth rate of about 7%. The dairy market in India is estimated to be worth $45 billion. Considering that most people in India are vegetarians, milk plays a significant role in the daily diet. Indians use milk in various preparations, including creating yogurt or curd, boiling tea and coffee, and cooking a wide variety of Indian meals.

The majority of milk products are eaten fresh. But in recent years, the demand for labeled packaged foods has grown. Even though India processes just around 2% of its food, the dairy industry nonetheless undergoes the most processing (35% of the country’s total production, of which only 13% is done by the organized dairy sector).

SHORT STORY OF AMUL

India’s dairy cooperative movement, AMUL (Anand Milk Union Limited), was established in 1946. It is a brand name administered by Gujarat Co-operative Milk Marketing Federation Lt. (GCMMF), the top cooperative organization in Gujarat, India. It is now under the control of almost 2.6 million milk farmers.

AMUL, which has its headquarters in Anand, Gujarat, is a prime example of a cooperative business that succeeds over the long haul. It is among the greatest instances of cooperative success in a developing country.

Including annual sales of US $1050 million, Amul is the leading food company in India and the leading brand of pouched milk worldwide (2006-07). Currently, 10.16 million litres of milk are collected each day on average by Amul’s 2.6 million producer members. Aside from India, Amul has expanded into foreign markets such as Mauritius, the United Arab Emirates, the United States, Bangladesh, China, Australia, Singapore, Hong Kong, and a handful of South African nations. It failed in its 1994 attempt to break into the Japanese market, but it now has new ambitions to flood it. Sri Lanka is among the additional possible markets thought of.

Amul has a new objective now that it has reached the historical record of Rs. 6,700 crores. Mission 2020 was announced by Federation Chairman Parthi Bhatol. In the year 2020, the Gujarat dairy cooperative is projected to generate total revenue of Rs. 27,000 crores. Additionally, they plan to increase the dairy plant’s production capability to 20.7 million kilograms each day.

STAGES OF THE PRODUCT LIFE CYCLE OF AMUL

Throughout a product’s existence on the market, it goes through many stages. Each of the product lifecycle stages presents its difficulties and possibilities.

Throughout the life cycle of a product, profits fluctuate. The product life cycle of Amul has four distinct stages, including

Stage 1: Introduction stage in product life cycle of amul

That the very first farm, Kaira District Co-operative Milk Producers’ Union, was founded in the Gujarati district of Anand in 1946. It produced Amul in 1955 and transferred ownership of the brand name to GCMMF in 1973. Since farmers in Anand sold all of their milk through a cooperative union, it was customary to market the product under the AMUL brand. At first, just 250 liters of milk per day were obtained. However, milk collecting grew as people became more aware of the advantages of cooperation. When compared to the per capita milk supply, milk output increased by only 1% year between 1955 and 1970.

Stage 2: Growth

By 1980–81, 53.9 million metric tonnes of Amul milk had been produced, and in 1990–91, 84.6 million metric tonnes had been produced. The yearly growth rate during Operation Flood’s initial phase was 4.08 percent. In the second phase, it was significantly higher (7.85%), while in the third phase, output grew at a rate of 5.05% annually.

Dairy consumption in India has grown from a low of 112 grams per day in 1968–1969 to over 226 grams per day in 2002 resulting in a significant increase in milk output. Amul produced new products such as Amul milk gold, Amul moti, Amul chai maza, and Amul thin trim in response to increasing competition from companies like Nestle, Mother Dairy, Britannia, Amul taza and Gokul.

Stage 3: Age of Maturity

One of India’s most recognizable brands is Amul. It is the first and only organization in the world to have its farmer cooperatives certified to the ISO 9000 standard. Amul now collects 11 lakh liters of milk every day. It is now the most popular pouch milk brand in the world. With $2 billion in revenue, the brand is as well-known in India as Coca-Cola, and most recently, Amul Milk has expanded into foreign markets including Mauritius, the United Arab Emirates, Oman, the United States, Bangladesh, China, Australia, Singapore, Hong Kong, and other South African nations. Gujarat and every one of India should be happy that Amul Dairy is currently No. 1 in Asia and also no. 2 in the globe.

Stage 4: Reduction

The stage of reduction occurs when a product deteriorates and expires. Amul milk withstood the “mozzarella-like milk” issue and did not allow the product to degrade. Additionally, very few additional Amul products have reached the point of decline and have had manufacturing halted.

EXAMPLE OF AMUL BUTTER LIFE CYCLE

Amul butter has reached maturity as of right now. Amul Butter is undoubtedly earning big profits at this time since it is the most lucrative, with an overall market share of 86%. Sales are growing, but more slowly, and there is a great deal of awareness, which means there is less need for promotion.

The brand-building strategy used by AMUL to develop its present brand image and, ultimately, its brand equity is better-understood thanks to the already mentioned lifecycle. Its specific product’s life cycle illustrates the ongoing brand-building activity that is necessary to preserve its current reputation.

But to examine the product’s life cycle more thoroughly, we must establish a connection between the acceptance of Amul butter by users.

EXAMPLE OF AMUL ICE CREAM LIFE CYCLE

Gujarat welcomed Amul Ice Cream on March 10, 1996. Ice cream sticks, cones, and cups were among the impulse purchases in the portfolio, along with take-home packs (tetra packs) and systemic packs. The Real Milk system served as the launchpad for Amul’s ice cream. Real Ice Cream has a competitive advantage over its rivals since it is a milk firm and its goods are healthy.

Amul ice cream made its debut in Mumbai in 1997, followed by Chennai in 1998, Kolkata in 2002, and Delhi in 2003. Nationally, with its implementation in 1999 throughout the nation. It defeated rivals like Wall’s and Mother Dairy to take the top spot in the nation. This position was attained in 2001 and has remained at the top ever since. It has not only expanded at an incredible rate, but it has also expanded its already expansive flavor selection. There are currently 220 goods available for selection. Ice creams have benefited from Amul’s continued innovation of its products.

SUCCESSFUL MARKETING OF AMUL PRODUCTS

The buffalo is the favoured dairy animal. India produces over 65% of the world’s buffalo milk. The worth of its high amount of fat is 7% compared to a cow’s 3.5%. Additionally, it has a lot of proteins, lactose, calcium, and phosphorus. The dairy industry prefers buffalo milk because it is easy to handle and offers profitably.

Amul is a symbol of the belief in the farmers’ potential to end the cycle of poverty and bring about a socio-economic transformation in rural Areas. The farmers showed the world the secret to effective “Management Of Development” through the “Anand Pattern.” Anand Pattern is a revolutionary three-tiered framework that unites diligent farmers with skilled management and cutting-edge technology.

Amul has slowly and steadily increased the scope of its national distribution system. There are now 3,500 wholesalers for value-added milk products and 1800 dealers for fresh milk to guarantee that Amul items are accessible to all consumer groups in India through much more than 20 lakh outlets. In several Indian towns and cities, GCMMF has increased the size of its network to over 4,000 parlours.

Structure of the Company

Amul uses a very distinct structure, also known by the name 'Anant Style' cooperative framework. Now, this structure works on a three-tier model.

• Village Cooperative society: In this, every manufacturer is a member of the cooperative village.
• District Unions: Villate cooperative society, elects their own representatives in their unions
• State milk federation:This federation is responsible for the distribution and sale of milk in the state

Product Strategy of Amul

Amul follows a low-cost marketing strategy targeting volumes. Hence Amul has a mass target audience it tries to tap into while keeping its prices low.

So, even if we look at the products from a customers angle

• Kids: Chocolate, Amul Kool, Amul milk
• Youth: Amul Pizza cheese, Cheese spread
• Health conscious: Amul shakti, Amul lite butter

Marketing Campaigns of Amul

Amul has managed to keep its brand awareness simple yet highly effective. As soon as we see the girl with a bread image, we know it is Amul.

However, what you might not be aware is that this brand image was in made response to the butter girl campaign by its rival.

Also, the Amul butter campaign is now officially the longest-running campaign in the world.

Amul has gained widespread recognition as a result of its dominance in the dairy product industry. AMUL is among the most prosperous corporate organizations, and other corporations should take a cue from Amul on how to do business ethically. Amul utilizes just 1% of its revenue for promotions. It demonstrates that when you are inventive and it is not necessary to invest millions in marketing.

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Agile Software Development Life Cycle: Case Study

Learn more about our agile software development life cycle from our Mitsubishi case study.

Any software development project, either big or small, requires a great deal of planning and steps that divide the entire development process into several smaller tasks that can be assigned to specific people, completed, measured, and evaluated. Agile Software Development Life Cycle (SDLC), is the process for doing exactly that – planning, developing, testing, and deploying information systems. The benefit of agile SDLC is that project managers can omit, split, or mix certain steps depending on the project’s scope while maintaining the efficiency of the development process and the integrity of the development life cycle. 

Today, we are going to examine a software development life cycle case study from one of Intersog’s previous projects to show how agility plays a crucial role in the successful delivery of the final product. Several years back, we worked with Mitsubishi Motors helping one of the world’s leading automotive manufacturers to develop a new supply chain management system. With the large scope of the project, its complex features, and many stakeholders relying on the outcomes of the project, we had to employ an agile approach to ensure a secure software development life cycle.

Business Requirements

Mitsubishi Motors involves many stakeholders and suppliers around the world, which makes its supply chain rather complex and data-heavy. That is why timely improvements are crucial for the proper functioning of this huge system and a corporation as a whole. Over the years of functioning, the old supply chain has been accumulating some noticeable frictions that resulted in the efficiency bottlenecks, and Intersog offered came ups with just the right set of solutions to make sufficient solutions that would help Mitsubishi ensure a coherent line of communication and cooperation with all the involved suppliers.

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Previously, Mitsubishi used an outdated supply chain management system that involved a large number of spreadsheets that required a lot of manual input. Considering a large number of stakeholders, the problem of synchronization has been a pressing one as well – different stakeholders would input the data at different speeds and at different times of day, which created a degree of confusion among suppliers. Though the system has been sufficient for a long time, the time has come to eliminate all the redundancies and streamline data input. 

The legacy system has been partially automated and ran on the IBM AS400 server, which allows for impressive flexibility, but it no longer sufficed for Mitsubishi’s growing needs. The main requirement, thus, was to create a robust online supply chain solution that would encompass the entire logistics process starting with auto parts and steel suppliers and ending with subcontractors and car dealerships around the world. That being said, Mitsubishi did not want to completely change the system, they opted for overhaul, and we came up with the idea of an integrated web application that was meant to function in conjunction with a DB2 base that was already used on the IBM AS400 server. 

IT Architecture and Agile SDLC

Mitsubishi employs a series of guidelines and rules on how to build, modify, and acquire new IT resources, which is why Intersog had to be truly agile to adapt to the client’s long-established IT architecture. Adapting to the requirements of the client, and especially to the strict regulations of the IT architecture of large corporations like Mitsubishi requires knowledge, flexibility, and strong industry expertise. Each software development company has its own architecture standards and frameworks for building new systems but many face difficulties when working with the existing systems and modifying them to the new requirements.

Intersog has no such problems. We approached Mitsubishi’s case with strong industry expertise and flexibility to account for all the client’s needs and specifications of the existing system. Obviously, following the client’s architecture regulations requires a profound understanding of said regulations, which is why information gathering is an integral phase of the software development life cycle.

Requirements Gathering

The requirements gathering phase can take anywhere from just a couple of days to several weeks. Working with complex and multi-layered legacy systems like the one used by Mitsubishi requires serious analysis and information gathering. In the case of Mitsubishi, our dedicated team had to gain a clear understanding of how the legacy system functions, create new software specifications, map out the development process, gather and create all the necessary documentation, track all the issues related to the functioning of the legacy system, outline the necessary solutions, and allocate all the resources to achieve the project’s goals in the most efficient manner. 

Working on the Mitsubishi project, our team has been gathering all the required information for up to 4 weeks. This included a profound examination of the legacy system, mapping out all of its flaws and specifications, bridging the gaps between the current state of the system and the requirements of the client, and outlining the development process. 

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The design stage includes all the integral decisions regarding the software architecture, its makeover, the tech frameworks that would be used in the system’s rework. During this stage, developers discuss the coding guidelines, the tools, practices, and runtimes that will help the team meet the client’s requirements. Working with large corporations like Mitsubishi, a custom software development team has to work closely with the company’s own developers to better understand the specifics of the architecture and create a design that reflects all the requirements. 

After all the requirements are gathered, we initiated the design stage based on all of the client’s specifications and came up with a number of solutions that matched Mitsubishi’s specs:

• Convenient data model meant to optimize data duplication;
• Permission system that differentiated the users by their access levels;
• Appealing user interface mockup to improve the comfortability of user-system interaction;
• Integration with the legacy RPG system;
• Notifications for the partners to keep them up with the important activities.

This set of essential solutions has been discussed and approved in the course of the design stage that lasted for 2 months. During this stage, Intersog and Mitsubishi development teams worked closely to come up with the solutions that matched the client’s requirements to the tee. Proper functioning of the supply chain is vital for the entire corporation, which is why it was critical to do everything flawlessly. 2 months might seem like quite a timeline, but for this case study on software development life cycle, it was not that long considering how complex Mitsubishi’s legacy system was. 

Solution Development

After approving the solution design, the team can move to develop those solutions. That’s the core of the entire project, a stage at which the teams meet the goals and achieve the outcomes set during previous stages. The success of the development stage depends heavily on how good a job the teams did during the design stage – if everything was designed with laser precision, the team can expect few if any, surprises during the development stage. 

What happens during the development stage is the teams coding their way towards the final product based on decisions that have been made earlier. With Mitsubishi, we followed the guidelines we came up with earlier and implemented a set of essential solutions:

• We built a convenient data model that minimizes the risk of human error by reducing redundant and repetitive data entry and duplication. 
• Improved Mitsubishi’s security system to differentiate the users by their level of access and give them the respective level of control over the data.
• Added the notifications for the users so that they could react to the relevant changes faster.
• Designed an appealing and comfortable user interface using the AJAX framework to make the user-system interaction more comfortable and time-efficient. 
• Deployed the platform running on the IBM AS400 server with the integration of DB2 databases.
• Integrated the existing RPG software into the new system.
• Migrated the existing spreadsheets and all the essential data into the new system.

All of these solutions took us 6 months to implement, which is rather fast for a project of such scale. Such a time-efficiency was possible only thanks to the huge amount of work we’ve done throughout the research and design stages. The lesson to learn from these software development life cycle phases for the example case study is that the speed of development would depend heavily on how well you prepare. 

Depending on the scale of the project, you might be looking at different timelines for the development stage. Small scale projects can be finished in a matter of weeks while some of the most complicated solutions might take more than a year to finish. In the case of the Mitsubishi project, it was essential for the client to get things done faster. Rushing things up is never a good idea, but you can always cut your development timeline by doing all the preparation work properly and having a clear understanding of what needs to be done and in which order.

Quality Assurance                   

Quality assurance is as vital for your project’s success as any other stage; this is where you test your code, assess the quality of solutions, and make sure everything runs smoothly and according to plan. Testing helps you identify all the bugs and defects in your code and eliminate those in a timely manner. Here at Intersog, we prefer testing our software on a regular basis throughout the development process. This approach helps us to identify the issues on the go and fix them before they snowball into serious problems. 

That’s it, quality assurance is a set of procedures aimed at eliminating bugs and optimizing the functioning of the software solutions. Here at Intersog, we run both manual and automated tests so that we can be truly sure of the quality of solutions we develop for our clients. With Mitsubishi, we ran tests throughout the development process and after the development stage was over. It took us an additional month to test all the solutions we’ve developed, after which we were ready for the implementation stage.

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Integration and Support

Following the testing, and once we are sure all the solutions work flawlessly, the development team gets to the implementation stage. Also known as the integration stage, this is where we integrate the new solution into the client’s pre-existing ecosystem. Basically, you are putting new gears into a complex mechanism that has been functioning for many years, and it is essential to make sure all of those gears fit perfectly. 

With such a complex system as the one employed by Mitsubishi and a vast amount of accumulated data, our developers had to be incredibly precise not to lose anything. We are talking about surgical precision because Mitsubishi’s suppliers amassed thousands upon thousands of spreadsheets full of critical data on supplies, material and product deliveries, accounting data, and more. All of that had to be carefully integrated with the new automated solution. 

After 2 months, the solutions have been fully integrated with Mitsubishi’s existing ecosystem. Intersog usually backs the clients up by offering support and maintenance services to ensure flawless functioning of the system over time, but this time, our client was fully capable of maintaining the new system on their own. As said, Mitsubishi has its own development team that is able to take care of the system maintenance, so that our cooperation was finished after the integration stage. 

Final Thoughts and Outtakes

A software development life cycle depends on many factors that are unique for each company. In the case of Mitsubishi, we’ve managed to get things done in just under a year, which is rather fast for a project of such an immense scale. Different projects have different life cycles, and it depends on the scale, the client’s ability to explain their needs, and the development team’s ability to understand those needs, gather all the necessary information, design the appropriate set of solutions, develop said solutions, ensure their quality, and implement them fast.

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Dissipation-based life cycle impact assessment of mineral resource use—a review, case study, and implications for the product environmental footprint

• CRITICAL REVIEW
• Open access
• Published: 27 April 2024

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• Markus Berger   ORCID: orcid.org/0000-0002-3012-7470 1  

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Impacts of mineral resource use on the availability of resources can be assessed using a broad range of methods. Until recently, life cycle inventory (LCI) and life cycle impact assessment (LCIA) models have been based on resource extraction. As extracted resources are not necessarily “lost” for future use, recent methodological developments have shifted the focus from resource extraction to resource dissipation . This paper aims at reviewing dissipation-based LCIA methods, testing them in a case study, analyzing potential implications for the product environmental footprint (PEF), and providing recommendations for future method development.

Five recently developed LCIA methods have been reviewed and compared based on 22 criteria, such as the forms and time horizons of dissipation considered, scientific publication, and number of characterization factors (CFs). Additionally, the abiotic depletion potential (ADP) method has been included to serve as a non-dissipation-based reference. All methods are tested in a case study on a theoretical product, designed solely for demonstration purposes, and consisting of 1 kg of the metals aluminum, cobalt, copper, molybdenum, nickel, and zinc. In addition to the absolute LCIA results, the contributions of metal production stages and individual resource extractions/emissions have been investigated. Finally, normalization and weighting have been carried out to analyze consequences of replacing ADP with the new dissipation-based methods in the context of PEF.

Results and discussion

Most recently developed LCIA methods take a long-term perspective, cover emissions of resources to the environment (and partly technosphere), and vary in the number of CFs and resources covered. The case study results obtained by ADP are dominated by the molybdenum dataset; the results of the dissipation-based LCIA methods are strongly influenced by the cobalt dataset. All results are strongly sensitive to the LCI database used (ecoinvent or GaBi). Normalization and weighting revealed that the mineral resource use impact result dominates the aggregated PEF score (57%), when using the currently recommended ADP model. Shifting from the resource extraction-based ADP to dissipation-based models can reduce the contribution to 23% or < 1% depending on the method.

The development of methods addressing mineral resource use in LCIA has shifted from resource extraction to dissipation. The analyzed methods are applicable and lead to different findings than the extraction-based ADP. Using the newly developed methods in the context of PEF would significantly change the relevance of the mineral resource use impact category in comparison to other environmental impacts.

Avoid common mistakes on your manuscript.

1 Introduction

In life cycle assessment (LCA) practice, impacts of resource use on the environment and human health are assessed by various impact categories, such as land use change, acidification, or eco- and human toxicity. However, assessing the impacts of resource use (in particular mineral resource use) on the availability of the resources themselves - and even the question of whether this should be assessed in environmental LCA at all - is highly controversial (Sonderegger et al. 2017 ).

An expert group of the UNEP-SETAC Life Cycle Initiative has reviewed 27 existing life cycle impact assessment (LCIA) methods, analyzed them in a criteria-based comparison, and clustered them into four categories: depletion methods, future efforts methods, thermodynamic accounting methods, and supply risk methods (Sonderegger et al. 2020 ). Based on this review and discussions at the Pellston Workshop ® 2019, a safeguard subject for mineral resources within the area of protection natural resources has been defined, LCIA methods have been recommended for relevant questions, and recommendations for future method development have been provided (Berger et al. 2020 ).

One of the key challenges identified by the expert group was the fact that current methods exclusively focus on the extraction of resources, neglecting the dissipative resource uses. The latter can be described as a use of resources that renders them inaccessible for future use. For example, an emission of metal dust into the environment resulting from the abrasion in car brakes is considered “lost” because, technologically and economically, it would be too difficult to recover. Therefore, the expert group’s final recommendation was that “the concept of dissipative resource use should be defined and integrated in future method developments” (Berger et al. 2020 ).

This call for scientific development has been addressed by various research groups. Recent methodological developments include frameworks for dissipation-based assessment of resource use (Beylot et al. 2020 ; Charpentier Poncelet et al. 2019 ), life cycle inventory (LCI) concepts (Beylot et al. 2021 ; Lai and Beylot 2022 ), and LCIA methods (Ardente et al. 2022 ; Charpentier Poncelet et al. 2021 ; Dewulf et al. 2015 ; Owsianiak et al. 2022 ; van Oers et al. 2020 ).

With a focus on LCIA, this paper aims at reviewing the abovementioned methods in a criteria-based evaluation, testing them in a case study, analyzing the implications for the product environmental footprint (PEF) (EU 2021 ), and providing recommendations for future method development. The paper is the outcome of a project conducted on behalf of the International Council on Mining and Metals (ICMM) with participation of various metal associations. First, the methods for the criteria-based literature review and for conducting the case study are introduced (Section  2 ). Subsequently, the results of the literature review (Section 3.1 ), the case study (Section 3.2 ), and the implications for PEF (Section 3.3 ) are presented. Based on the findings, conclusions are drawn and recommendations for the ongoing development of dissipation-based LCIA methods are provided (Section 4 ).

2.1 Literature review

Of the abovementioned dissipation-based methodological developments, only the applicable LCIA methods, i.e., those providing characterization factors and not conceptual frameworks only, have been selected:

Environmental dissipation potential (EDP) (van Oers et al. 2020 )

Abiotic resource project (ARP) (Owsianiak et al. 2022 )

Average dissipation rate (ADR) (Charpentier Poncelet et al. 2021 )

Lost potential service time (LPST) (Charpentier Poncelet et al. 2021 )

Price-based impact assessment (Ardente et al. 2022 )

Additionally, the established and frequently applied abiotic depletion potential (ADP) method (van Oers et al. 2002 ) has been included to serve as a non-dissipation-based reference. The six methods are reviewed, briefly summarized, and evaluated in a criteria-based comparison. For this, the evaluation scheme of the Life Cycle Initiative’s expert group on resources (Sonderegger et al. 2020 ) was used as a template. In consultation with all project partners involved (ICMM and metal associations), the scheme was modified leading to the 22 evaluation criteria shown in Table  1 .

As the terms used for the criteria “form of dissipation considered” are used differently between researchers and research communities, they are briefly defined here. Dissipative “emissions into the environment” are emissions of resources from the technosphere into the environment which render them inaccessible for other users as they cannot be recovered due to technological or financial constraints. Examples include the abrasion of metal dust from car brakes mentioned above. “Emissions within the technosphere” refer to resource flows inside the technosphere which also make them inaccessible because of too-low concentrations (e.g., alloying elements in non-functional recycling (Reller 2016 )) or too-low volumes (e.g., metals in small landfills). “Occupation in use” (also termed borrowing use) refers to resources which are currently inaccessible for other users because they are embodied in products (e.g., steel in buildings), and it is debated whether this should be considered as a form of dissipation or not (Frischknecht 2016 ). Related to that the “hibernation in use” is a form of dissipation in which resources are inaccessible because they are contained in products which are not used anymore but have not been taken to recycling facilities yet (Kapur and Graedel 2006 ). Typical examples are metals in old smart phones which users often keep at home even if they are not used anymore.

2.2 Case study

The six LCIA methods are tested in a case study on a theoretical product, designed solely for demonstration purposes, and consisting of 1 kg of the following metals: aluminum, cobalt, copper, molybdenum, nickel, and zinc. As shown in Fig. 1 , the product system was modelled in the GaBi software using the GaBi 2022.2 database (Sphera 2022 ). To model 1 kg of molybdenum, 1.5 kg of ferromolybdenum is used to consider the metal content. Out of the six LCIA methods, only ADP was included in GaBi already. The other methods were implemented manually as new environmental quantities by assigning the respective CFs to the resource emissions (e.g., aluminum emission to air) (EDP, ARP, Price) or resource extractions (e.g., bauxite mining from geologic reserves) (ADR, LPST). It should be noted that the GaBi database lists the extraction of bauxite as the elementary flow (in contrast to ecoinvent which lists aluminum), but the ADR and LPST methods provide CFs for aluminum only. In line with other resource LCIA methods (like ADP), a conversion factor of 4 (4 kg of bauxite to produce 1 kg of aluminum) has been used to determine a CF for bauxite.

Life cycle inventory model of the theoretical product analyzed in the GaBi software

To allow for a more detailed analysis of the underlying metal production system, the aggregated metal datasets have been replaced by disaggregated LCI models provided by the respective metal associations. These LCI models are the basis from which the metal datasets available in GaBi and ecoinvent are derived.

While the bill of materials of the theoretical product comprises 1 kg of each metal, it should be noted that the LCI of each metal contains the extraction and emission of several resources in different quantities resulting from the mining and refining of each metal including their background systems for electricity generation, production of auxiliaries, transport, etc. To analyze what is driving the results, the contributions of individual resource extractions or emissions to the six impact category results have been analyzed. Further, the theoretical product has been modelled again using ecoinvent 3.7 datasets (Ecoinvent 2022 ) to analyze the sensitivity of results to LCI databases.

While the focus of this study was on the cradle-to-gate datasets provided by the metal associations involved in this project, it is important to also consider a life cycle perspective as the hotspots of resource use may shift from the production (extraction impacts) to the use and end-of-life phases (dissipation impacts). Based on a material flow analysis (MFA) study quantifying dissipative losses for a set of metals throughout their life cycles (Helbig et al. 2020 ), metal-specific dissipation rates have been determined for the use phase (0–8%) and end-of-life phase (6–71%). According to Helbig and colleagues ( 2020 ), end-of-life dissipative losses end up entirely in the technosphere. It should be noted that the EDP and ARP methods consider dissipation to the environment only and the ADR and LPST methods are applied to resource extractions (see Section  3.1 ). For this reason, end-of-life dissipation has been considered in the price-based method only whose developers explicitly address dissipation into the technosphere (Ardente et al. 2022 ; Beylot et al. 2021 ). As dissipation rates can vary drastically for different products and user behaviors, a worst-case life cycle scenario has been added in which the entire metal content of the product gets dissipated to the environment.

2.3 Implications for PEF

To test the potential implications of using the newly developed dissipation-based methods in the context of the product environmental footprint (PEF) (EU 2021 ), the LCIA results have been normalized using global per capita normalization factors. These are provided by PEF (ADP), by the method developers (EDP and ARP), or by own calculations (ADR, LPST100) based on the global annual extractions multiplied by their CFs and divided by the world population. Finally, the normalized results have been weighted using the PEF weighting factor of 7.6% for mineral resource use (EF 3.0  2022 ). By aggregating the results with the other 15 normalized and weighted impact category results, the contribution of resource use measured by dissipation-based methods has been analyzed and compared to the currently recommended method (ADP).

3 Results and discussion

3.1 literature review.

Before presenting and discussing the results of the criteria-based comparison, the six LCIA methods are described by summarizing the main ideas of their characterization models.

3.1.1 Description of methods

The abiotic depletion potential (ADP) of a resource was originally defined as a ratio of a resource’s annual production to the square of the resource’s crustal content, normalized to the same ratio of the reference resource antimony leading to the common unit of antimony equivalents (Guinée and Heijungs 1995 ). The ADP of a product system is calculated by multiplying all resource extractions reported in the LCI by the respective CFs and summing the results. Thus, the method uses physical scarcity of resources in the earth crust as an indicator to measure the impact of resource use. After a data update in 2002 (van Oers et al. 2002 ), the method was revised in 2009 by separating it into two categories: ADP for fossil fuels and ADP for elements. The ADP for elements was updated in 2016 (CML-IA 2016 ) and methodologically enhanced in 2019 using recent crustal content data and cumulated production from 1970 to 2015 instead of single-year production rates which can change considerably (and thus alter the CFs) over time (van Oers et al. 2019 ). In the case study presented below, ADP is used in its 2016 version (CML-IA 2016 ), which is also implemented in the product environmental footprint (EF 3.0  2022 ).

In contrast to assessing the extraction of resources by means of ADP, the environmental dissipation potential (EDP) aims at assessing the long-term dissipative losses of resources, i.e., the emission of resources to the environment (van Oers et al. 2020 ). The characterization model, which is used to determine the CFs, is similar to the one of the original ADP method (Guinée and Heijungs 1995 ) as it comprises a ratio of resource extraction in a reference year to the squared crustal content of the resource. However, this ratio is not normalized to the ratio of antimony (in ADP of elements) but to the ratio of copper, and, thus, EDP is expressed in copper equivalents. The central assumption in the characterization model is that all resources extracted in the reference year will be dissipated in the very long-term perspective. In contrast to ADP, the CFs are not multiplied by resource extractions of the product system but by the emission of resources to the environment. It should be noted that the authors of EDP also provide conceptual characterization models to measure impacts of technosphere hibernation and occupation in use (van Oers et al. 2020 ), which are not considered in this work as applicable CFs are not available yet.

Building up on the idea of defining emissions of resources to the environment as dissipative losses, the abiotic resource project (ARP) developed a classification model to differentiate metal emissions to the environment into dissipative and non-dissipative flows (Owsianiak et al. 2022 ). The basic assumption behind this concept is that metal emissions to the environment are only dissipative if both of the following two conditions apply. First, they “originate from a source with a concentration higher than a reference (concentration in upper continental crust) reflecting what is accessible for humans within the considered time span” (Owsianiak et al. 2022 ). For example, copper leached out from a rain pipe can be dissipative, as the copper originates from a copper mine extracting the metal from geologic reserves (with a concentration higher than the average copper concentration in the upper continental crust). In contrast, copper emissions from coal-fired power plants are not dissipative flows, as the copper contained in coal is not a geologic reserve but an impurity (with a concentration lower than the average copper concentration in the upper continental crust). As a second criteria, a metal dissipation is only considered dissipative, if “the current annual rate of total anthropogenic emissions results in a steady state concentration in the receiving environment that is below a reference concentration” (Owsianiak et al. 2022 ). Hence, metal emissions (even if originating from geologic reserves) are not dissipative if the concentration in the receiving compartment is above the metal’s concentration in the upper continental crust. The ARP method is not a characterization model but a classification model, which can be combined with other emission-based characterization models. In this study, it is combined with the EDP method described above. As current LCI databases do not specify whether metal emissions originate from ores, fossil fuel impurities, or other sources, the first criteria to identify non-dissipative emissions could not be applied in the case study presented in this paper. However, for the method evaluation shown below, the method is included in its original version including both criteria.

To avoid the uncertainty related to resource emissions used as proxy for dissipative losses in current LCI databases (unclosed mass balances in some datasets, origin of emissions from resources or impurities, concentrations in receiving compartments), Charpentier Poncelet et al. ( 2021 ) follow a different approach. The authors developed two LCIA methods which use the concept of dissipation in their characterization models, but the resulting CFs are applied to the resource extraction and not resource emission inventory flows. The first method, ADR, assesses impacts of resource extraction based on their average dissipation over time, considering global average dissipation rates (ADR) which have been determined for each metal based on dynamic material flow analysis data. ADR depends on the function of resource dissipation over time and is calculated as the inverse of the total service time, which can be understood as the area below the dissipation function measured in kg ⋅ years per kg extracted. The second LCIA method, LPST, denotes the lost potential service time within a certain timespan, which is defined as the difference between the optimum service time (no dissipation, rectangular area of kg ⋅ years per kg extracted in a dissipation over time diagram) and the actual service time (area below the dissipation function, kg ⋅ years per kg extracted) within this time span (Charpentier Poncelet et al. 2021 ). In this work, a time horizon of 100 years is used, and the indicator is termed LPST100. It should be noted that these methods are based on the global average dissipation rates of resources, and the dissipation of resources extracted in the product system under study can be different. In the opinion of the author, this potential mismatch between the LCI and the LCIA levels can lead to counterintuitive results. For example, if a product system (in theory) does not have any dissipative losses, it will still show impact due to its resource extraction and the average (not product specific) dissipation rates of these resources. Vice versa, if a product is made from 100% recycled content, no resource extraction will be reported in the LCI and, thus, the LCIA result will be zero regardless of the amount of resources that gets emitted from the product system into the environment. Such results are nor “wrong,” but the difference between dissipation rates reported in the LCI (specific) and applied in the LCIA methods (average) should be kept in mind when interpreting the results.

After having proposed a new inventory scheme to clearly list dissipative resource flows in the LCI (Beylot et al. 2021 ), Ardente et al. ( 2022 ) propose a price-based impact assessment method. Assuming that market prices reflect “the multiple, complex and varied functions and values held by mineral resources” (Ardente et al. 2022 ), the authors use resource prices averaged over a 50-year timespan as CFs to assess the impact of dissipative resource losses. In this work, the CFs are applied to the emission of resources to the environment as reported in the GaBi database, as the dissipation-specific inventories (Beylot et al. 2021 ) are not available for the analyzed metals yet.

3.1.2 Criteria-based comparison

The complete evaluation of the six LCIA methods described above against the 22 criteria shown in Table  1 is presented in a spreadsheet in the supplementary material S1 . In the following, the main findings and differences between the methods are presented and discussed.

Concerning the classification scheme according to which a working group of the UNEP Life Cycle Initiative recommended methods for different questions (Berger et al. 2020 ), all methods except for the price-based method are considered to address the question: “How can I quantify the relative contribution to the depletion of mineral resources?”. This is not surprising, as dissipation directly contributes to resource depletion, and the UNEP working group recommended the development of dissipation-based methods for this question. In contrast, the price-based method addresses the question: “How can I quantify the relative (economic) externalities of mineral resource use?”.

Concerning the time scale, all methods address the long-term impacts of resource dissipation except for the price-based method. The latter assesses the short-term impacts reflected by market prices, which is consistent with the previously proposed LCI approach (Beylot et al. 2021 ). This also takes a short-term perspective and considers resource flows into waste disposal facilities or non-functional recycling as dissipative. In addition to the long-term perspective, the authors of the EDP method (van Oers et al. 2002 ) also propose (not yet operational) concepts for the short- and medium-term perspectives. Also the LPST can be calculated for different time horizons. In this context, it should be noted that the terms short-, medium-, and long-term are neither clearly nor consistently defined. Often short-term is considered as < 5–10 years, mid-term around 25 years, and long-term > 100 years (Arvidsson et al. 2020 ; Schulze et al. 2020 ) or even > 500 years (Dewulf et al. 2021 ).

The characterization models of EDP, ARP, ADR and LPST consider emissions of resources into the environment as a form of dissipation. Additionally, the conceptual methods of the EDP authors as well as the dynamic material flow models underlying the ADR and LPST characterization models define emissions into the technosphere (e.g., landfill or non-functional recycling) as dissipative. None of the methods considers occupation in use or hibernation in the technosphere (e.g., unused products such as old smartphones not taken to recycling yet) a relevant form of dissipation.

The CFs of classical resource LCIA methods, such as ADP, are applied to (multiplied by) the resource extraction flows of the LCI. In contrast, the CFs of most dissipation-based methods are applied to the emission of resources (EDP and ARP) or to flows of dissipative resource losses from specific LCIs (price-based method). Two exceptions to this are the ADR and LPST methods, whose CFs are applied to the resource extraction flows as their characterization models describe the average dissipation rates per kg extracted resource.

The characterization models (classification model for ARP) and underlying main assumptions are described above. With regard to normalization, the analysis revealed that all methods except for ADR and LPST provide applicable normalization factors (inverse of global per-capita impacts). For the latter methods, normalization factors have been calculated by using extraction data from the ADP method, multiplying the resource extractions by their corresponding ADR and LPST 100 CFs, and dividing it by the world population to obtain per capita impacts.

None of the method publications discusses the option of weighting the impact assessment results of resource dissipation to compare or aggregate them to other impacts. To illustrate the applicability and effects of weighting, the LCIA results of the theoretical product are normalized and weighted using the weighting set of the product environmental footprint (PEF) (EF 3.0  2022 ).

All LCIA methods are published in peer-reviewed scientific journals. The data quality of the characterization models is considered high for the extraction (ADP and EDP) and price-based models as global production, crustal content, and market prices of resources are well reported. The data quality of the other characterization models is considered medium due to uncertainties associated with the use of modelled data (fate models in ARP and dynamic material flow models in ADR and LPST). However, in both cases, it should be noted that central assumptions, such as crustal content being a proxy for ultimately extractable reserves, complete dissipation of current extraction in the long-term future, or market prices being a proxy for the value of resources are not less relevant than numeric data uncertainty.

In addition to data quality of the characterization models, the quality of the LCI data to which the CFs are connected is also important. In general, it can be said that the quality of resource extraction data needed for ADP, ADR, and LPST is higher than the quality of resource emission data, which is used as a proxy for dissipative flows into the environment. This is because resource extractions are comparatively easy to measure and well reported. In contrast, emissions of resources do not necessarily represent dissipative losses (as addressed by ARP), and the comparison of resource inputs (extraction) and outputs (emissions and product) often shows inconsistent mass balances.

Concerning the practical implementation of the LCIA methods, it can be said that all methods provide applicable CFs which are publicly available, with only ADR and LPST being not published open access. The number of CFs ranges from 18 for ADR and LPST to 108 for EDP. While ARP, ADR, and LPST cover mainly metals, the other methods also provide CFs for minerals. At this point (November 2023), the methods are not available in the LCA software with the exception of ADR and LPST being implemented in SimaPro. However, an older version of ADP (van Oers et al. 2002 ) is implemented in all of the above-mentioned LCA softwares. The effort for manually implementing the LCIA methods in the GaBi software is considered low for ADP, ADR, and LPST, as only new environmental quantities (impact categories) need to be created and CFs for the resource extraction flows need to be entered. The implementation of the other impact categories requires more effort, as the names of the elementary flows in the method publications (e.g., copper) need to be matched to a list of emissions in the software (e.g., copper [heavy metals to air], copper [heavy metals to freshwater], etc.).

3.2 Case study

The absolute impact assessment results of the theoretical product’s mineral resource use are shown in Table  2 for the production phase only, along the life cycle based on average dissipative losses during the use and end-of-life phases, and for a scenario assuming complete dissipation of the product’s metal content. Even though some categories share the same reference unit, a comparison is only possible between EDP and EDP+ARP. The 31% lower result in the latter in the production phase shows the relevance of classifying resource emissions as dissipative or non-dissipative and only including those emissions in the characterization which dissipate. It should be noted that the 31% reduction was obtained by including the second dissipation criteria only (emissions end up in a compartment below the reference concentration) as the first criteria (emission originates from a reserve) could not be applied as current LCI databases do not contain this information.

As absolute results are not comparable across impact categories and hard to interpret without comparisons, the following analysis is conducted on a relative scale to determine the contribution of the metal datasets to the result of each impact category obtained during the production phase. As shown in Fig.  2 , the “traditional” ADP is dominated by the molybdenum dataset, which plays a minor role in the results of the dissipation-based impact categories whose results are dominated by cobalt and partly nickel. Results of the EDP and EDP+ADR methods and results of ADR and LPST100 show similar patterns concerning the contribution of the individual metal datasets. The differences between these two method groups and between ADP and the price-based method can be explained by different methodological settings concerning the LCI and LCIA. While EDP, EDP+ARP, and the price-based methods use resources emitted during the production of the metals as relevant elementary flows, ADP, ADR, and LPST100 rely on resource extractions required for the metal production. Further, the characterization factors by which these elementary flows are multiplied reflect resource scarcity (ratio of extraction/dissipation to reserves in ADP/EDP), global average dissipation rates (ADR and LPST100), or market prices (price-based method). When interpreting those results, it should be kept in mind that a theoretical product is analyzed consisting of 1 kg of each of the metals, which eases comparability but does not reflect the material composition of real products in which metals like cobalt are present in much lower percentages.

Contribution of the individual metal datasets to the LCIA results in the extraction-based impact category abiotic depletion potential (ADP) and the dissipation-based impact categories environmental dissipation potential (EDP), abiotic resource project (ARP), average dissipation rate (ADR), lost potential service time (LPST), and the price-based model

In addition to aggregated metal datasets implemented in the GaBi database, some of the metal industry associations involved in this study provided disaggregated versions of their metal LCI models. In this way, the contribution of individual production stages to the total impact category results could be analyzed. As shown in Fig. S1 in the supplementary material, electrolysis is dominating the impacts in the aluminum production (except for ADR and LPST100). In contrast, the results for copper are dominated by the copper concentrate production. While for copper, the metal emissions originate from the concentration step directly, the emissions of the aluminum electrolysis are mainly caused by the Chinese electricity grid mix contained in the background system. Given that current LCI databases do not differentiate whether emissions result from geologic reserves or impurities, metal dissipation of aluminum production can be overestimated.

In addition to analyzing the contribution of production stages to total results, the contribution of individual elementary flows (resource extractions or emissions) has been analyzed for the production phase. This allows for a deeper understanding of the results because e.g., a copper dataset contains the extraction and emission of many more resources than copper in its LCI. For the impact categories applying their CFs to resource extractions (ADP and LPST100), the extraction of the target metals usually causes a relevant contribution to the LCIA result of the respective metal dataset (Fig.  3 a and b). That is, molybdenum extraction contributes significantly to the ADP result of the molybdenum dataset, and zinc extraction contributes significantly to the LPST100 result of the zinc dataset. For aluminum and cobalt, a different outcome can be observed in the ADP results, which are dominated by the extraction of copper and lead (for aluminum) and the extraction of copper (for cobalt). This can be explained by the fact that the ADP CFs for bauxite and cobalt, which denote their geologic scarcity, are relatively low compared to the CFs of the other resource extractions. In contrast, the average dissipation rates of these ores/metals are comparably high, leading to a significant contribution of these resource extractions in LPST100 (Fig.  3 b).

Contribution of resource extractions to the impact categories ADP ( a ) and LPST100 ( b ) as well as contribution of resource emissions to the impact categories EDP+ARP ( c ) and the price-based method ( d ) during the production phase

The results of the impact categories applying their CFs to resource emissions (EDP+ARP and the price-based method, shown in Fig.  3 c and d) are usually not influenced by emissions of the target metal. Only for the molybdenum dataset, the emission of molybdenum to air and freshwater contributes significantly to the EDP+ARP result. In general, the results of many metal datasets in this impact category are dominated by the emission of cadmium to freshwater (Fig.  3 c). In contrast, the results of most metal datasets in the price-based impact category are dominated by the emission of magnesium to industrial soil (Fig.  3 d). This shows that dissipative losses of the target elements (e.g., nickel emissions in the nickel dataset) are low compared to other emissions and/or that the environmental dissipation potential (EDP) and market price (price-based method) of the target metals is relatively low.

To analyze the sensitivity of the results to the LCI database, the analysis of the production phase has been repeated using metal datasets from the ecoinvent 3.7 database (Ecoinvent 2022 ). As shown in in Fig S2 in the supplementary material, results vary significantly depending on the database used. For ADP, the ecoinvent results are always larger than the GaBi results ranging from a factor of 1.2 (zinc) to 16.8 (nickel). Besides ADP, the largest differences can be found in the price-based LCIA method in which ecoinvent results can be larger by a factor of 70.2 (copper) or lower by a factor of 7.7 (nickel). For the other impact categories, results obtained by ecoinvent and GaBi vary by factors of 5 lower (cobalt) to a factor of 10.4 higher (nickel). Thus, results are highly sensitive to the database used which can be explained by data- and/or modelling-related differences. Data differences include data sources, data collection methods, reference regions, and reference years. Different modelling approaches include different tailing models or allocation procedures, to name a couple. Beyond the dissipation-based resource impact categories, the different metal emissions reported in the GaBi and ecoinvent databases will also affect the results of toxicity impact categories. However, as the toxicity potentials of metal emissions are not correlated to their dissipation potentials, differences between the GaBi and ecoinvent results in the dissipation categories are not the same as in the toxicity categories. Further, different metal components of the theoretical product (nickel in ecotoxicity and a metal mix in human toxicity) and different metal emissions (aluminum and chloride in ecotoxicity as well as arsenic and lead in human toxicity) dominate the results of the toxicity categories.

3.3 Implications for PEF

To test the implications of using the newly developed dissipation-based methods in the context of the product environmental footprint (PEF) (EU 2021 ), the LCIA results have been normalized (using global per capita normalization factors), weighted (using the EF 3.0 weighting factor of 7.6% for mineral resource use), and aggregated with the other 15 PEF impact categories. The production phase’s normalized results in Fig.  4 show that the theoretical product causes a high specific contribution in the impact categories ecotoxicity (102%) and mineral resource use (52%). This can be interpreted as the theoretical product causing the same impact as one average global citizen per year in the ecotoxicity category and half of the annual per person impact in the mineral resource category. The specific contribution in the other impact categories is negligible. The normalized results of the theoretical product along its life cycle are shown in Fig. S3 in the supplementary material.

Normalized LCIA results of the theoretical product (production phase) in the 16 PEF impact categories with mineral resource use measured by means of ADP in the default setting (left pink bar) and by the dissipation based EDP, EDP+ARP, ADR, and LPST100 models (right pink bars)

If, however, the default ADP characterization model of the impact category mineral resource use is replaced by the dissipation-based characterization models, the normalized result changes drastically. When ADP is replaced by EDP and EDP+ARP, the specific contribution is reduced from 52 to 0.03% and 0.07%, respectively. That is, the ratio of the theoretical product’s characterized resource extraction to global characterized extraction (normalized ADP) is higher than the ratio of the theoretical product’s characterized resource emission to global characterized resource emission (normalized EDP). As the underlying characterization models of ADP and EDP are similar (see Section  3.1 ) and as the low contribution cannot be explained by a larger normalization reference (because emissions do not exceed extraction), this shows that the theoretical product’s resource extraction is more relevant than its resource emission. While this is not surprising when considering the production phase only, the result is confirmed when considering the life cycle perspective (Fig. S3 a). Only if a complete dissipation of the product’s metal content is assumed, the normalized results of EDP+ARP (70%) exceeds that of ADP (Fig. S3 b).

When replacing ADP by ADR or LPST100, the normalized result decrease to 11.5% and 6.3% in the production phase (Fig.  4 ) and in both life cycle scenarios (Fig.  S3 ). This stable result shows that the additional dissipative losses occurring along the life cycle of the theoretical product do not change the ADP, ADR, and LPST100 results, which are influenced by the product system’s resource extraction only. Surprisingly, the normalized results are smaller than those obtained by ADP even though it provides a higher number of CFs (76 in ADP and 18 in ADR and LPST100) which could lead to a larger normalization reference (and thus a lower normalized result). Hence, the difference can only be explained by the different underlying characterization models (geologic scarcity compared to dissipation rates).

The differences in the normalized results are also reflected in the weighted and aggregated results shown in Fig.  5 . In the default setting of PEF using ADP as characterization model, the impact category mineral resource use is dominating the weighted result of the theoretical product’s production phase with 57%. For the underlying metal datasets, the contribution of the mineral resource use category ranges from 0.1% (aluminum) to 96.3% (molybdenum). In addition to mineral resource use, the impact category ecotoxicity also contributes notably to the weighted result (28% for the production phase). As the weighting factor for ecotoxicity is relatively low (1.9% compared to 7.6% for mineral resource use), this relatively strong contribution can be explained by the already high result obtained in the normalization step. Vice versa, the contribution of climate change to the weighted result of the theoretical product is low (3%) even though it has the highest weighting factor of 21.1%. This can be explained by relatively low greenhouse gas emission of this theoretical product system in comparison to relatively high global emissions, which lead to a low specific contribution in the normalization (Fig.  4 ).

Weighted and aggregated normalized results in the 16 PEF impact categories with the category mineral resource use assessed by means of the default model ADP ( a ) and the dissipation-based models EDP+ARP ( b ) and LPST100 ( c )

When replacing the default characterization model for mineral resource use (ADP) by dissipation-based models, which have shown different normalized results (Fig.  4 ), the absolute value of the weighted result and, thus, the relative contribution of the 16 underlying impact categories change. When switching from ADP to EDP (Fig. S4 a) or EDP+ADR (Fig.  5 b), the mineral resource use impact category becomes negligible in the weighted and aggregated results. A shift from ADP to ADR (Fig. S4 b) or LPST100 (Fig.  5 c) leads to a reduction of the contribution of resource use in the weighted result of the theoretical product and the underlying metal datasets copper, molybdenum, and zinc. However, the contribution of the mineral resource use category to the weighted results of aluminum and cobalt datasets has increased.

Considering the life cycle perspective based on average dissipative losses does not change the results of the production phase discussed above and the low relevance of the resource use impact category in the weighted total result. This is because dissipative losses during the use phase are relatively small compared to dissipation in production and because dissipative losses in the end-of-life phase occur within the technosphere, which is not considered in EDP and ARP and which does not affect ADR and LPST as they are applied to resource extraction flows. Only if a complete dissipation of the product’s metal content is assumed, different findings are obtained. First, the contribution of ADP to the total weighted result decreases from 57 to 19% because of the additional metal emissions which increase the results and contributions of the toxicity categories (Fig.  5 a). A shift to the dissipation-based LCIA methods reduces the contribution of the resource use category moderately to 8% (EDP), 5% (ADR), and 3% (LPST100). In the EDP+ARP category, even a slight increase to 24% can be observed. However, as a full dissipation of the entire product is an extreme scenario, it is justified to conclude that a shift from ADP to dissipation-based LCIA methods will lower the relevance of resource use in normalized and weighted PEF results.

4 Conclusions and recommendations

The development of methods addressing mineral resource use in LCA has shifted from resource extraction to dissipation on both the LCI and LCIA levels. The literature review and criteria-based comparison conducted in this work revealed that most of the methods’ characterization models take a long-term perspective (except the price-based model), and all of them consider dissipation into the environment, with ADR, LPST, and the price-based method additionally considering dissipation within the technosphere. This is also reflected in the methods’ LCI requirements, which usually are resource emissions and not extractions (except ADR and LPST).

The case study demonstrated that all methods are applicable and lead to different findings than the extraction-based ADP. The contributions of the individual mining and refinery process steps differ between metals but are stable across methods, which shows the relevance of these methods in identifying dissipation hotspots and resulting optimization potentials in the value chain of metal production. As the LCIs of the metal datasets include different metal extractions and emissions, the LCIA results are usually influenced by a mix of metals, with emissions of cadmium and magnesium dominating the results of EDP and the price-based method, respectively. All results are strongly sensitive to the LCI database used (ecoinvent or GaBi). Normalization and weighting revealed that using the newly developed methods in the context of PEF would significantly reduce the relevance of the mineral resource use impact category in comparison to other environmental impacts in both a production and life cycle perspective. The newly developed methods reviewed and tested in this work enable the transition from a resource extraction- to a resource dissipation-based impact assessment of mineral resource use in LCA. While this is a major achievement, future work should harmonize methodological choices such as the definition of dissipative flows (emissions to environment, emissions to technosphere, occupational use, etc.) or the considered time span (short-, medium-, long-term impacts). In parallel to LCIA developments, also advanced LCI databases are needed which provide the information required for a meaningful impact assessment (origin of emissions from geologic reserves or impurities, emissions within the technosphere, etc.). New LCI concepts (Beylot et al. 2021 ) as well as first datasets (Lai and Beylot 2022 ) are available, but large-scale implementation in commercial databases remains a challenge.

Furthermore, key methodological assumptions taken by the method developers should be discussed, including the following: all resource extractions will be dissipated in the long-term (EDP), the threshold for extraction is the average crustal content (ARP), average dissipation rates are suitable to assess product system specific resource extractions (ADR and LPST), or market prices reflect the value loss of dissipated resources (price-based method). Considering the broad range of 27 resource extraction-based and five dissipation-based LCIA methods the development of a harmonized resource dissipation LCIA method is encouraged to increase methodological consistency and to support applicability for LCA practitioners.

Data availability

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Acknowledgements

The author would like to express his sincere thanks to the method developers of the dissipation-based LCIA methods for fruitful discussions and providing (at that time partly unpublished) characterization factors. Particular thanks go to Lauran van Oers (CML), Mikolay Owsianiak (DTU), Alexandre Charpentier Poncelet, Guido Sonnemann (University of Bordeaux), Antoine Beylot (BGRM), Fulvio Ardente (JRC), and Serenella Sala (JRC). Further, the provision of datasets by and discussions with ICMM members (Claudine Albersammer, Josephine Robertson, Anne Landfield Greig, Ladji Tikana, Louise Assem, Mark Mistry, Sabina Grund, Tom Fairlie) were highly appreciated and represent a relevant contribution to this paper.

This work was funded by the International Council on Mining and Metals (ICMM).

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Berger, M. Dissipation-based life cycle impact assessment of mineral resource use—a review, case study, and implications for the product environmental footprint. Int J Life Cycle Assess (2024). https://doi.org/10.1007/s11367-024-02318-6

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Received : 14 April 2023

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DOI : https://doi.org/10.1007/s11367-024-02318-6

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