Intro
Executive summary
Why does one business earn a premium or produce at lower cost than another serving the same customers?
The answer often lies in the activities the business performs: how it designs, sources, produces, sells, delivers and supports its offering—and how those activities fit together.
Michael Porter’s value chain is a way to examine those activities systematically. Developed in Competitive Advantage (1985), it divides a business into primary and support activities so that managers can locate the sources of cost and differentiation. Its purpose is to explain competitive advantage and inform choices, not simply to produce a process diagram. [1]
A valuable analysis connects customer value, relative economics, the fit between activities, management choices and the evidence supporting a claimed advantage. It asks which activities influence customers’ willingness to pay, what they cost, how much capital they consume, and how the answers compare with alternatives. For Global Advisors, the value chain becomes most useful when it is quantified. Yet an apparently precise allocation can conceal uncertain assumptions, and a local saving can destroy more value elsewhere. The goal is to improve the economics of the whole business.
Introduction
Key insights
Competitive advantage resides in activities and in the way they reinforce one another.
A lower cost in one activity can create larger costs elsewhere. Analyse the full system, including customers and partners.
Customer value, value capture, operating costs and capital employed must be understood together.
The right unit of analysis is a defined customer, offering, market and decision—not an average across unrelated businesses.
Services and platforms may need value-shop or value-network lenses alongside the traditional chain.
Quantify uncertainty and test the assumptions that could reverse the decision.
What is Porter's value chain?
A value chain describes the strategically relevant activities a business performs to create, deliver and support an offering. Porter’s framework asks how activities influence relative cost and the value customers perceive, and how their configuration supports a distinctive position. [1]
Porter’s contribution was to change the level at which competitive advantage is examined. “Operations”, “marketing” and “technology” are useful organisational labels, but each can contain activities with very different economics. A manufacturer’s operations include production planning, changeovers, quality control and maintenance. A retailer’s include forecasting, distribution-centre picking, store replenishment and online-order fulfilment. A consultancy’s include problem diagnosis, staffing, analysis, expert review and client workshops.
The appropriate level of detail is the one at which the answer begins to change. Split an activity when it has a different cost driver, influences customer value in a different way, uses different assets or skills, or is performed materially differently by a competitor. A map that shows every process step may be comprehensive but unusable; a map that shows only departments may be attractive but explain very little.
The generic model groups activities into two categories:
- Primary activities concern creating, selling, delivering and supporting an offering: inbound logistics, operations, outbound logistics, marketing and sales, and service.
- Support activities enable the primary activities: procurement, technology development, human resource management and firm infrastructure.
These are starting categories, not a mandatory organisation chart. A strategically important activity can span departments and should be broken down far enough to reveal its economics. A bank might examine credit assessment, onboarding and collections; a manufacturer might separate product design, sourcing, production scheduling and quality assurance.
Value chain and supply chain: a supply chain usually emphasises the flow of materials, information and products among suppliers, producers and customers. A value-chain analysis asks how a business’s activities contribute to cost or differentiation. The two overlap, but sales, service and technology can matter even when they fall outside a narrow supply-chain view.
The wider value system: a company operates alongside suppliers, channels and customers whose activities influence its economics. The boundary matters: a saving achieved by transferring cost to customers or suppliers may not be sustainable, and an outsourced activity can still be strategically decisive. [1]
Value chain components
The five primary activities
1. Inbound logistics
Receiving, storing and managing inputs, including material handling, inventory, supplier deliveries and—in information-intensive businesses—the acquisition and quality control of data.
Questions: Where do delays, quality failures or excess stock originate? Does privileged access to an input create an advantage? What would supplier coordination save across the whole system?
2. Operations
Transforming inputs into the product or service: manufacturing, assembly, fulfilment, underwriting, software operations or execution of a professional service.
Questions: Which steps drive cost, quality, speed and reliability? Are differences caused by scale, learning, process design, complexity or utilisation? What happens to quality and flexibility when capacity is pushed harder?
3. Outbound logistics
Getting the offering to the customer, including warehousing, order processing, distribution, delivery scheduling and digital delivery.
Questions: What does it cost to serve different customers and channels? Where do delivery performance and availability affect conversion or retention? Are network design and service promises aligned?
4. Marketing and sales
Helping customers understand and buy the offering: pricing, channel selection, marketing, sales, proposals and customer acquisition.
Questions: Which segments are valuable after acquisition and service costs? What supports the price premium? Who controls the customer relationship, and what does the channel capture?
5. Service
Maintaining and enhancing value after purchase through installation, training, support, repairs, upgrades and issue resolution.
Questions: What is the cost of failure and repeat contact? Does service increase retention or willingness to pay? Which customer problems should be prevented upstream rather than handled more efficiently downstream?
Value chain components
The four support activities
A. Procurement
Receiving, storing and managing inputs, including material handling, inventory, supplier deliveries and—in information-intensive businesses—the acquisition and quality control of data.
Questions: Where do delays, quality failures or excess stock originate? Does privileged access to an input create an advantage? What would supplier coordination save across the whole system?
B. Technology development
Product design, research and development, data, software and process improvement. Technology matters when it changes activities or their connections—not merely because the business owns a system. An investment may reduce cost, improve customer experience or enable a distinctive offer; each claim requires evidence.
C. Human resource management
Recruitment, development, incentives, retention and deployment. The critical question is how people and capabilities support the chosen position. A service promise requiring expert judgement may fail if incentives reward only volume and speed.
D. Firm infrastructure
Management, finance, legal, planning, governance and other activities that support the business. Infrastructure can create control, resilience and speed, but poorly designed processes can delay decisions and add avoidable cost.
The book Key Management Models uses these categories and highlights their relevance to outsourcing and acquisitions. It also warns that objectively assessing relative strengths can demand substantial effort. [2] The categories are prompts; the analytical work begins when they are adapted to a specific business.
How the value chain creates competitive advantage
Cost advantage
A cost advantage exists when a business performs the activities required for a comparable offering at lower cost than relevant competitors, while meeting the value customers require. Cost drivers may include scale, capacity utilisation, learning, location, procurement terms, product design and links between activities.
The distinction between cost reduction and cost advantage matters. If everyone uses the same available software to reduce costs, all may become more efficient while no one gains a lasting relative advantage. A saving that increases warranty claims, churn or working capital may make the business worse off.
Cost drivers also interact. Greater scale may reduce the unit cost of a distribution centre while increasing distance to some customers. Higher utilisation can spread fixed costs across more output but leave less capacity to absorb disruption. Vertical integration may reduce transaction and coordination costs while adding fixed capital and limiting flexibility. A cost comparison that holds these effects outside the frame can misidentify the source of the advantage.
The practical test is therefore relative and conditional: relative to which competitor, for which customer, at what service level, and over what time horizon? A low cost per transaction is valuable only if the business can deliver an acceptable proposition and earn adequate returns on the resources required to do so.
Differentiation advantage
Differentiation arises when activities create attributes customers value sufficiently to improve willingness to pay, preference, conversion or retention. Evidence might include price realisation, customer research, win/loss analysis, retention by segment and the customer’s own cost savings.
An improvement is not automatically differentiation: customers must notice and value it, the business must capture a share of that value, and the resulting economics must justify the cost. Premium features customers do not use can destroy value.
Value creation and value capture
Creating value and capturing it are related but different. A useful economic lens defines total value created as the difference between a buyer’s willingness to pay and the opportunity cost of the resources supplied. The share retained by the business depends on prices and bargaining alternatives. A business can deliver considerable customer value yet struggle to capture enough of it to earn attractive returns. [9]
This distinction changes the questions asked of a value chain. Does a service improvement increase customers’ willingness to pay, and can any of that value be captured through price, volume or retention? Does a purchasing concession reduce the total cost of supplying a product, or merely transfer surplus from the supplier? Both can affect a company’s profits, but they are different sources of value.
Fit across activities
The strongest insight is often found between activities. Product design can reduce production complexity; better data can improve demand planning; sales promises can create costly fulfilment and service obligations. The effect of one change depends on what happens elsewhere. Harvard’s Institute for Strategy and Competitiveness describes this interaction as fit across the value chain. [3]
A set of mutually reinforcing activities may be harder to copy than one isolated practice. That is a hypothesis to investigate, not proof that an advantage is permanent.
Consider the difference between an isolated operational improvement and a system designed around a proposition. A company can improve delivery speed by adding vehicles. It can also redesign product availability, inventory location, order cut-off times, routing, customer communication and exception handling so that speed is delivered reliably. The second approach involves more decisions, but it reveals the economics that a simple delivery-cost benchmark misses.
Fit does not mean that every activity must be unique. Many activities can be conventional, purchased or shared. The test is whether the activities that matter to the chosen position work together—and whether an apparently attractive change to one of them weakens the proposition elsewhere.
Case Studies
Three value-chain examples
Case study
Shoprite: the store network, delivery and data as an activity system
Shoprite’s South African grocery business illustrates the value-chain question in a digital setting. Stores can serve walk-in customers and support picking for online orders; distribution replenishes those stores; the Sixty60 channel adds demand; and interactions with customers can inform ranging, promotions and service. These activities require coordination across the physical network, technology, inventory, staff and last-mile delivery.
For the 52 weeks ended 28 June 2026, Shoprite reported R270,8 billion in sales from continuing operations and R25,5 billion in Sixty60 sales, up 34,5%. [10] These are company-reported outcomes, not proof that any one component of the configuration caused the result. Shoprite’s published report describes the use of the store network for fulfilment and its data and loyalty capabilities. The claim that this configuration has a lower cost-to-serve than centralised online fulfilment is a company assertion; independent comparable unit-cost evidence would be needed to establish the size of the advantage. [11]
The trade-off is important: proximity and convenience can improve the customer proposition, but picking capacity, inventory, technology and delivery all consume resources. The question for an analyst is whether the combined incremental economics—including service quality, working capital and investment—support attractive returns by customer and order type.
A practical map would start with the customer promise and follow an order through assortment, stock availability, in-store picking, dispatch and delivery. It would then trace the information flowing back: substitutions, stock-outs, delivery exceptions and customer responses can inform subsequent operating decisions. The store is both a retail destination and a fulfilment point; that dual role can create useful proximity while placing demands on shelf availability, labour and store layout.
Management would need to distinguish the economics of an incremental order from those of the whole channel. A store may already exist, but its picking staff, congested aisles or scarce delivery slots may have an opportunity cost. Equally, allocating all store rent to online orders would overstate the cost that would disappear if the service were withdrawn. An evidence-based analysis would compare order density, basket size, picking time, substitutions, delivery distance, customer retention and the capital tied up in stock.
The analytical lesson is not that every retailer should fulfil online orders from stores. It is that a physical network, digital channel and customer data can be mutually reinforcing when designed together. Whether that configuration wins against alternatives depends on the economics of the market and the evidence for each link—not simply on the presence of an app.
Case study
Inditex: responsiveness depends on more than fast production
Inditex’s Zara and other brands show how design, sourcing, logistics, stores and online channels can be analysed as a coordinated system. Inditex reported €39,9 billion of revenue, a 58,3% gross margin and €6,2 billion of net profit for its 2025 financial year. Its reporting describes the group’s integrated operating model and investment in logistics capacity. [12]
The strategic hypothesis is that better information and responsiveness can help align the offer with demand. Faster replenishment or closer sourcing might cost more in an individual activity but could reduce forecast risk or support full-price sales elsewhere. Those benefits and trade-offs need to be measured rather than assumed. Inditex’s results are consistent with a successful overall configuration; public group accounts cannot isolate the causal contribution of each activity or establish its cost position against every competitor.
Responsiveness can carry environmental and transport costs too. Reuters reported higher transport emissions in 2024 as Inditex used more air freight during Red Sea disruption. This demonstrates a trade-off; it does not establish the exact revenue or profit protected by that choice. [13]
Look at the decision from the perspective of the whole activity system. A more distant supplier may quote a lower manufacturing price; a closer supplier may offer shorter lead times and allow the retailer to make later decisions with better demand information. Centralised logistics might involve expenditure that looks unattractive in a single transport comparison, yet support more frequent product flows and coordination across channels. Neither choice is automatically superior. The question is whether any extra sourcing or logistics cost is justified by lower inventory, fewer markdowns, faster response or a stronger customer proposition.
That analysis needs a counterfactual. What would the same customer demand, assortment and service level have cost under an alternative configuration? How much capital would each option require? How much of any gross-margin difference is attributable to product mix, brand, geography, pricing or exchange rates rather than the activity under examination? Published financial performance gives the analyst a starting point, not a controlled experiment.
Case study
Boeing 787: outsourcing the activity does not outsource integration
Boeing’s 787 programme provides a counterexample to the idea that moving an activity outside a firm automatically removes its complexity. In its 2008 annual filing, Boeing described challenges involving its extended global supply chain, travelled work, systems integration and assembly. [14] Research on the programme examines the difficulties of managing a global partnership model and Boeing’s subsequent changes to coordination and governance. [15]
The evidence supports the conclusion that supply-chain and integration problems were material. It does not support attributing every programme delay to outsourcing alone: new technology, design, supplier work, production and other factors also mattered. The broader lesson is that make-or-buy decisions must include interface management, schedule risk, capability, asset ownership and incentives—not only a comparison of the supplier’s price with an internal cost allocation.
In a distributed development programme, the hand-off is itself an activity. Partners must work to compatible specifications, exchange design information, manage changes and deliver components whose interfaces work together. If work arrives incomplete, activity and cost can reappear downstream as inspection, rework and integration. The firm may own fewer of the underlying activities while remaining accountable for the performance of the system.
This changes the make-or-buy calculation. The visible supplier price should be considered alongside the cost of engineering oversight, information exchange, quality assurance, change control, schedule buffers and the risk of supplier failure. The potential benefits remain real: specialised capability, shared investment and access to scale can be valuable. The decision is whether the chosen boundary leaves the company with the control and coordination capabilities needed to realise those benefits.
How to conduct a value-chain analysis
1. Define the decision and unit of analysis
Begin with a decision: improve the economics of a product, defend a segment, redesign service, evaluate make-or-buy or assess an acquisition. Define the customer segment, offering, geography, channel, time period and relevant competitors. A group-wide map can hide differences between businesses that compete in different ways.
A useful boundary is narrow enough that the customer proposition and economics are reasonably comparable, but broad enough to include material linkages. An urban premium delivery order and a rural store-replenishment order may sit within the same group and yet have very different cost drivers, service expectations and competitive alternatives. Blending them into one average can conceal both an attractive segment and an uneconomic one.
Write down the decision before gathering data. “Should we fulfil this customer segment from stores or a central facility?” is more useful than “map the e-commerce value chain”, because it determines which activities, assumptions and alternatives deserve attention.
2. Map the activities that matter
Start with Porter’s categories, then disaggregate activities that influence the decision. Trace flows and hand-offs across functions and organisational boundaries. Record who performs each activity, its inputs and outputs, the decisions involved and links to suppliers, channels and customers. Focus detail where economics, customer value, constraints or competitive differences appear material.
3. Establish the economics
Allocate revenues and costs to relevant products, customers and activities using transparent assumptions. Distinguish variable from fixed costs, cash expenditure from allocated overhead, and operating costs from investment and working capital. Use activity-based costing when its additional precision will change a decision; avoid treating arbitrary allocation keys as facts. Time-driven activity-based costing can estimate resource capacity costs and the time required for transactions, while making unused capacity visible. [16]
Allocated costs are accounting shares; avoidable costs disappear if an activity is removed over the relevant horizon; incremental costs arise because of a particular decision. They are not interchangeable. A segment may look unprofitable after an overhead allocation even though closing it would leave most overhead in place. Equally, using existing capacity is not free if it displaces a more valuable opportunity. [17]
Track cost drivers as well as totals: for example cost per order, cost per resolved issue, rework, stock days, utilisation or time to decision. Use consistent periods, units and accounting definitions for comparisons, and state where competitor estimates are uncertain.
For each resource, distinguish the capacity supplied from the capacity used. A warehouse designed for peak demand will appear expensive per unit in a quiet month; its apparent cost disadvantage may partly be the price of service resilience. Conversely, spare capacity does not justify every new product if accepting it prevents the business from serving a more attractive opportunity.
The same discipline applies to customer profitability. The cost to serve can vary with order size, frequency, delivery location, returns, support requests and payment terms. Segment averages are useful starting points, but the variation within a segment may be precisely where a strategic choice is hidden.
4. Test customer value and relative position
Identify which activities influence customer outcomes and how. Test the proposition with customer evidence rather than internal opinion alone. Where feasible, combine observed behaviour, price-response data, win/loss evidence, experiments or choice modelling. Different willingness-to-pay methods can produce different answers, so show the method and uncertainty rather than implying a single estimate is exact. [18] Compare relevant competitors’ offers, costs and performance on a like-for-like basis where data permits. A competitor may be cheaper because it offers less, serves a different segment or records costs differently.
For each claimed advantage, ask: What is the evidence? How large is the difference? Is it material? Can it be sustained? Separate measured facts from estimates and hypotheses.
Competitor activity costs are seldom visible directly. Public disclosures, product design, facilities, delivery promises, customer evidence and observable operating choices can nevertheless support a reasoned comparison. Set out our configuration, the competitor’s observed configuration, the likely cost and customer-value effects, investment implications and confidence level. A range with a clear evidential basis is more useful than a precise but unsupported benchmark.
Willingness to pay also needs careful interpretation. Interviews can reveal what customers say they value, while observed choices, experiments and pricing evidence may show what they will actually trade off. A premium service feature that does not affect buying behaviour or avoid an economic loss may still be necessary, but its value should not be assumed.
5. Analyse linkages and trade-offs
Map consequences across the system. Consider a lower-cost component that raises warranty claims, a faster sales process that increases credit losses, or faster delivery that requires more inventory. Include customer and supplier effects as well as internal costs. A cost may move rather than disappear.
Linkages often hide at organisational interfaces. A sales incentive may encourage promises that operations cannot fulfil economically. A procurement saving may require a larger inventory buffer because the cheaper supplier is less reliable. A design change may increase component cost but simplify assembly and improve repairability. Each proposition needs to be traced to the activities and actors it affects.
The balance sheet belongs on the map as well. Inventory, receivables, payables, facilities, equipment and software can be central to the decision. Automation may reduce labour cost and add fixed assets; a more generous payment term may increase sales while consuming working capital; supplier financing can improve the company’s balance sheet while increasing strain elsewhere in the value system. These effects belong in the investment case, not in a separate discussion after the operating choice has already been made.
6. Evaluate strategic options
Compare redesign, automation, selective outsourcing, supplier development, integration or a different service promise. Estimate incremental cash flows, investment, capacity and implementation costs, and effects on customer value and risk. Test scenarios and sensitivities; include a credible alternative and the cost of doing nothing.
The strongest business case makes uncertainty visible. Record a base case, a plausible range and the status of each material input: measured, estimated, modelled or hypothesised. For example, unit-cost savings might come from a timed process sample, capital expenditure from supplier quotations, and the customer-volume effect from an untested hypothesis. Those are not equally reliable inputs merely because they appear in adjacent spreadsheet cells.
Test which assumptions could reverse the choice and direct research or a pilot towards those uncertainties first. A proposal with a small expected benefit and a highly uncertain retention effect calls for a different response from one where the economics remain attractive across a wide range.
7. Decide, implement and review
Assign an owner, investment, milestones and measures linked to the hypothesis. Establish a baseline, leading indicators and outcomes such as contribution, retention, working capital and returns. Revisit assumptions as customer behaviour, technology and competitors change.
In a management workshop, these steps should culminate in a choice: defend, redesign, partner, invest, stop or investigate further. For each option, document which activities change, which linkages are affected, the expected customer outcome, the incremental economics, the capital required and the evidence that would change the decision. The output is a set of accountable choices and tests—not a finished diagram placed in a presentation.
Illustration
A quantified illustration: the cost saving, the capital and the customer
Consider a hypothetical online retailer handling 1 million orders per year. All figures below are invented. Management proposes a dispatch redesign that saves R10 per delivered order. It requires R4 million in additional annual fixed operating cost, R12 million in technology and equipment, and six extra days of stock. Annual cost of goods sold is assumed to be R300 million and the extra inventory is calculated on a 365-day year.
| At unchanged volume | Calculation | Annual or invested amount |
|---|---|---|
| Gross annual delivery saving | 1 million × R10 | R10,00m |
| Less incremental fixed operating cost | -R4,00m | |
| Annual operating benefit before tax | R6,00m | |
| Extra inventory | R300m × 6 / 365 | R4,93m |
| Technology and equipment | R12,00m | |
| Incremental invested capital | R16,93m | |
| Illustrative pre-tax incremental return | R6.00m / R16.93m | 35,4% |
At an illustrative 18% pre-tax annual return hurdle, R16,93 million of capital requires approximately R3,05 million of annual operating benefit. With R4 million of added fixed cost, gross savings must be approximately R7,05 million. If the R10 saving per order is the only uncertain input and all other assumptions hold, the initiative needs savings on roughly 705 000 orders to meet the hurdle. This is a savings sensitivity, not a demand-loss break-even calculation.
Now suppose slower service loses orders that would otherwise have contributed R80 each before the proposed delivery saving. Each lost order also loses the R10 saving. Assuming the added capital and fixed costs remain unchanged, the loss of each order therefore reduces the incremental case by R90. The R6 million base benefit exceeds the R3,05 million capital charge by about R2,95 million; R2,95 million divided by R90 is approximately 32 800 lost orders, or 3,3% of the original volume. At that point the initiative falls to the assumed hurdle. This deliberately conservative simplification holds the extra inventory fixed; if lower volume changes inventory, fixed costs or customer lifetime value, the break-even result changes.
The 35,4% figure is a simple annual pre-tax operating return, not a discounted project return. A real investment decision should model cash flow timing, tax, depreciation, capital recovery, capacity and demand scenarios. The point is to bring the customer proposition, the profit and loss account and the balance sheet into the same decision.
Value networks
Beyond the linear chain: services, platforms and networks
Porter’s generic diagram describes activities that often look sequential. It remains a powerful lens, but not every business creates value in a straight line. Stabell and Fjeldstad propose two additional configurations alongside the value chain: the value shop, which solves individual customer problems, and the value network, which connects customers through a mediating service. [4]
A consulting firm, hospital or specialist engineering practice may be better understood as a value shop: diagnose a problem, develop alternatives, choose, execute and evaluate, often with iteration. Reputation, access to expertise, problem selection and learning across engagements may matter more than a conventional outbound-logistics box.
A payments network or marketplace may be better understood as a value network: recruit and serve participants, establish rules and trust, and operate infrastructure that enables interactions. The economics depend on the quality and balance of participation, the platform’s role and how value is shared.
These are analytical lenses, not mutually exclusive labels. A business can contain several value-creation logics. Map the activities that explain the economics rather than forcing reality into a diagram. A value-grid perspective might help when relationships among businesses become more complex. [2]
The distinction matters when choosing measures. In a value shop, diagnosis quality, expertise, staffing, knowledge reuse and the outcome for the customer may be more revealing than a sequential distribution measure. In a network, participation on one side can affect the value of participation on another; trust, matching quality, access, pricing and network liquidity can therefore matter as much as the cost of processing a transaction.
Many businesses combine these logics. A bank can operate transaction-processing chains, solve individual client problems and mediate relationships among participants. Analysing one logic does not eliminate the others. The choice of lens should follow the way value is created, and the interfaces between those logics may be strategically important in their own right.
AI and the value chain
AI and the value chain: an amplifier and a potential source of disruption
AI can affect individual activities, the links between them and the business model itself. A customer-service assistant may help staff resolve issues; forecasting may change inventory decisions; AI-supported underwriting may alter how risk is assessed and priced. Ask where a measurable advantage could arise, which complementary capabilities are needed, and who captures the benefit.
In a study of 5 172 customer-support agents, researchers found that access to a generative-AI assistant increased issues resolved per hour by about 15% on average, with larger gains among less experienced and lower-skilled workers. [19] This is evidence from a particular deployment, not a universal forecast for every service function. A business applying the lesson should measure resolution quality, customer outcomes, error rates and full implementation costs alongside speed.
The analysis should examine effects on labour time, quality, error costs, cycle time, capacity, customer value and risk, including downstream review or escalation. A more consequential question is whether AI changes the configuration of activities: could it move advice closer to the customer, shift work to a distribution partner, or make an intermediary less necessary? Widely available models can make some capabilities easier for competitors to acquire. Proprietary context, reliable workflows, data rights, human judgement and customer trust may matter—but their contribution must be demonstrated for the business concerned.
The links are often where the economic result changes. Faster document production can create more review work downstream. Automated service may lower handling costs yet damage the proposition if escalation fails. Better forecasting can reduce both stock and markdowns, but only if procurement and replenishment can respond to the forecast. An AI-assisted engineering team might produce designs faster while verification becomes the new constraint. Each is a hypothesis to test across the activity system.
The boundary of the firm can change too. AI may make an activity easier to perform internally, or make a specialist provider with superior scale and capability more attractive. Neither direction follows automatically from the technology. The make-buy-partner decision still rests on relative economics, quality, data rights, risk, coordination and the capabilities required to deliver the customer promise.
See Global Advisors’ discussion of AI and business models for related questions about the location of intelligence and ownership of the customer relationship. [5]
When the value chain is useful—and where it can mislead
The framework is useful when a team needs to understand why performance differs, identify the sources of a price premium, evaluate make-or-buy decisions, integrate an acquisition, or convert strategy into operating choices.
It can mislead when:
- The analysis stops at a diagram. Naming activities does not demonstrate advantage.
- The wrong comparison is used. Company averages can conceal differences in segments, offerings or service levels.
- Cost is confused with value. An activity can be expensive because it enables differentiation that customers reward.
- Allocations are mistaken for economics. A fully allocated cost is not necessarily the avoidable cost of changing an activity.
- Customer and partner costs are ignored. Savings transferred elsewhere can weaken the offer or reappear in another form.
- Capabilities are assumed to be defensible. A seemingly distinctive activity may be easy to reproduce.
- A linear model is imposed on a non-linear business. Use a shop or network lens where it explains value creation more clearly.
- The result is treated as static. Technology, regulation, competitors and customer expectations can alter the configuration’s value.
How it connects to other strategy tools
| Tool | Primary question | Connection to the value chain |
| Five Forces | Why is industry profitability distributed as it is? | Tests the external economics in which the chain must compete. |
| 7S framework | Are the organisation’s elements aligned? | Tests whether structure, systems, people and culture support the intended activities. |
| Activity-based costing | What drives the cost of activities and outputs? | Offers a measurement method where conventional accounting obscures economics. |
| Growth, profit and returns | Is growth creating attractive economic returns? | Connects activity choices to outcomes and the capital they require. |
| SWOT | What strengths, weaknesses, opportunities and threats matter? | Helps examine where claimed strengths and weaknesses arise. |
See Global Advisors’ guides to Porter’s Five Forces, the 7S framework and growth, profit or returns. [6–8]
Conclusion
Questions for leadership teams
- Which customer segments and offerings are we analysing—and who is the relevant competitor for each?
- Which activities explain our relative cost or the value customers are willing to pay for?
- Where are our claimed strengths supported by evidence, and where are they assumptions?
- Which links between activities create the most value or the greatest friction?
- What costs are we transferring to customers, suppliers or other parts of the business?
- Which activities need to be distinctive, and which could be standardised or sourced externally?
- How might AI, a new entrant or a change in distribution alter the configuration?
- What decision will we take, what economics support it, and how will we know whether it worked?
A value-chain analysis is complete when it changes the quality of a decision. The best map helps management understand the economics of its position and choose a coherent set of activities to create customer value and returns for the business.
Conclusion
References and further reading
- Harvard Business School, Institute for Strategy and Competitiveness, The Value Chain. Michael E. Porter, Competitive Advantage: Creating and Sustaining Superior Performance, Free Press, 1985.
- Gerben van den Berg and Paul Pietersma, Key Management Models: The 75+ Models Every Manager Needs to Know, third edition, FT Publishing International, 2015, chapter 24.
- Harvard Business School, Fit Across the Value Chain.
- Charles B. Stabell and Øystein D. Fjeldstad, Configuring value for competitive advantage: on chains, shops, and networks, Strategic Management Journal, 19(5), 1998, 413–437.
- Global Advisors, AI as a Business Model, 2026.
- Global Advisors, Porter’s Five Forces, 2026.
- Global Advisors, The 7S Framework – A Comprehensive Guide, 2026.
- Global Advisors, Growth, Profit or Returns?, 2020.
- Adam M. Brandenburger and Harborne W. Stuart Jr., Value-Based Business Strategy, Journal of Economics & Management Strategy, 1996.
- Shoprite Holdings, Group results for the 52 weeks ended 28 June 2026, 1 September 2026.
- Shoprite Holdings, 2026 integrated annual report, hosted by FinancialFilings.
- Inditex, 2025 annual report: letter from the CEO; FY2025 results.
- Reuters, Inditex transport emissions, March 2025, hosted by MarketScreener.
- Boeing, 2008 Form 10-K, US Securities and Exchange Commission.
- Suresh Kotha, Managing a global partnership model: lessons from the Boeing 787 “Dreamliner” program, Global Strategy Journal, 2013.
- Robert S. Kaplan and Steven R. Anderson, Time-Driven Activity-Based Costing, Harvard Business Review, November 2004.
- ACCA, Relevant costs.
- Klaus M. Miller et al., How Should Consumers’ Willingness to Pay Be Measured?, Journal of Marketing Research, 2011.
- Erik Brynjolfsson, Danielle Li and Lindsey R. Raymond, Generative AI at Work, The Quarterly Journal of Economics, 2025.
