A different offer becomes a credible investment when leaders can connect customer demand to a workable delivery model and attractive economics. A value curve helps expose those choices. The next task is to decide whose needs to serve, what work must change and how much commitment the evidence supports.
Consider a hypothetical team proposing faster service with fewer choices and a lower price. Customer interest gives it a reason to test the offer, but operations still handles custom work behind every order. The team must decide which requests to exclude and whether the simpler operation can deliver the promised speed at the proposed price. Those choices put value innovation into practice.
From a different offer to a defined customer
In Blue Ocean Strategy, W. Chan Kim and Renée Mauborgne ask leaders to reconsider the factors on which an industry competes. Their eliminate–reduce–raise–create framework gives equal attention to what an organization could stop providing or provide less of and what it could improve or introduce. That matters because a company cannot usually fund a better experience simply by adding benefits. Removing work that buyers do not value can help pay for what they do.
For the hypothetical faster service, an extensive menu of options might be a candidate for reduction. Standard requests could become easier to handle, allowing a quicker response. Yet that logic depends on the buyer. A customer with an unusual problem may value the options most. Before removing them, the team needs to know whose problem the simpler offer is meant to solve and when that customer would choose it over an alternative.
Kim and Mauborgne’s account of Cirque du Soleil makes the customer decision concrete. It identifies adults and corporate clients willing to pay more than traditional circus audiences as important customers for its different form of entertainment. The point is not that every company should seek a premium audience. Cirque’s example shows why a new combination of benefits gains direction only when leaders can say whose expectations they intend to meet—and which familiar expectations they will leave behind.
Those exclusions have operational consequences. If the faster-service team promises a standard offer but lets sales negotiate exceptions for every prospective customer, operations may retain the complexity the new model was supposed to remove. If it refuses all exceptions without checking what its intended buyers need, it may strip away the reason they would choose it. The boundary has to work for both the customer and the people delivering the service.
Blue-ocean strategy does not ignore this business-model problem. Kim and Mauborgne’s sequence for assessing an idea moves from buyer utility through price and target cost to adoption hurdles. It asks whether the proposition can work, not just whether it sounds appealing. The leadership task is to make those tests specific: which customers would buy, what work can genuinely be removed, and what would make the promised price and speed possible together?
The operation behind the promise
A.G. Lafley and Roger L. Martin describe five linked strategic choices in Playing to Win: How Strategy Really Works: a winning aspiration, where to play, how to win, the capabilities required, and the management systems that support them. Their approach helps carry a new value curve into decisions about the organization. “People who want simplicity” is too broad a where-to-play choice if different buyers require different advice, delivery channels, and levels of support.
Suppose the faster-service team chooses people with routine requests who are willing to accept standard options. It can then design the offer around those requests and direct complex cases elsewhere. That exclusion may protect response time, but only if the intended customers accept it and the referral does not impose an unexpected burden on them. The team has to test the whole experience, not merely whether customers like the advertised price.
The how-to-win choice reaches further inside the company. A quicker answer may require simpler approvals, clearer authority for frontline employees, or a different way to route incoming requests. These are possibilities for the hypothetical business, not prescriptions for every service. The dependency is the important part: raising a benefit on the value curve creates a delivery obligation. Unless leaders also remove or redesign work, the new promise may sit on top of the old cost structure.
Resources make that obligation real. A pilot staffed by people whose time and performance measures remain tied entirely to the existing business may tell leaders little about whether the new model can work. Funding a permanent operation before customers demonstrate demand would create the opposite problem. At OutcomesLab, we use the Focus Multiplier principle to emphasize concentrating complementary resources on a small number of priorities. Here, give a defined trial enough capacity and decision authority to test the promise, while naming what will receive less attention during the trial.
A viable offer is not necessarily an attractive investment. In Competitive Strategy: Techniques for Analyzing Industries and Competitors, Michael E. Porter examines how entrants, substitutes, buyers, suppliers, and rivalry shape an industry’s economics. For the faster-service team, customer interest would not settle whether a supplier could capture much of the value or whether competitors could quickly match the price. The company needs an estimate of the returns available to it, not just evidence that buyers like the idea.
Porter makes a related argument about imitation in his later article “What Is Strategy?” A position supported by trade-offs and activities that fit together can be harder to copy than a single attractive feature. In the hypothetical service, a narrower offer might permit simpler workflows; those workflows might support reliable speed; and the sales approach might bring in customers comfortable with standard options. A rival could advertise faster service, but matching that combination might require changes to its own operation. Whether it would is something to investigate, not an advantage to assume.
What to decide before committing more
The proposed OutcomesLab Blue-to-Coherent Test connects these choices. It asks five questions of a proposed value curve: Which buyers will change behavior? Whose needs will the first offer exclude? What work must stop or change to deliver it? Which capabilities and resources must be committed, and what must the economics show? What could a rival copy, and what would the company do in response? The test is an OutcomesLab synthesis of these distinct ideas, not a step claimed by their authors.
Its usefulness lies in the conflicts it can expose. If the intended buyers need the options slated for elimination, the customer choice contradicts the offer. If speed requires new decision authority but the trial cannot obtain it, the operating plan contradicts the promise. If the price works only when acquisition and support costs are left out, expressed interest has not established a viable model. Each finding suggests a decision: narrow the customer group, change the offer, redesign the trial, or stop investing.
There is a serious reason not to demand complete coherence at the outset. Blue-ocean strategy already calls for cost choices, adoption planning, and alignment between buyer value, profit, and the people needed to execute. More importantly, an unfamiliar market cannot be planned into certainty. Requiring a fully developed operating system and a convincing defense against imitation before testing buyer behavior could prevent the discovery that makes the investment worth considering.
The distinction is between the commitments needed to learn and those needed to scale. The faster-service team could offer a bounded trial to a specified group, with standard options it can actually deliver, a spending limit, and a decision rule for expanding, revising, or closing it. It need not rebuild the entire operation first. If customers choose the offer and delivery costs look workable, leaders have a stronger reason to invest in the processes and management systems that would make the service repeatable.
At OutcomesLab, we use Optionality to mean preserving a credible future choice without spreading present resources across every possibility. A focused trial can preserve the option to scale by resolving uncertainty about demand and cost. Keeping numerous versions of the service alive would consume capacity while making it harder to tell which offer customers want. A trial should buy information that changes the next decision.
Even a well-chosen customer and a coherent operation cannot guarantee lasting advantage. Cirque du Soleil’s company history reports that pandemic shutdowns eliminated its revenue in 2020, followed by creditor protection and a relaunch under new owners in 2021. That shock does not show that competitors copied its offer or that its original customer choice was mistaken. It does set a limit on what a celebrated market-creation example can prove about durability.
The decision after drawing a new value curve, then, is how much commitment the evidence supports now. An untested buyer insight may warrant a bounded trial. Demonstrated demand may justify building the capabilities that make delivery reliable. Further investment depends on whether the likely returns, including the risk of imitation and disruption, are worth the resources at stake. The curve opens a path; leaders still have to choose what to build along it.