At one company we worked with, we mapped more than 70 needs. Of those, 25 were selected for deeper investigation. One revealed Leverage potential and guided the creation of a solution to test. Within 60 days, that solution had customers in eight countries.
The case highlights a central issue in strategy: needs are abundant, but strategic potential is not evenly distributed among them.
The fact that a need is real does not mean it is a strategic priority.
This distinction is central to Need-Based Decision Science. A company may identify dozens or hundreds of real customer needs and still find only a few with enough shared relevance to preserve the Core or create Leverage. The rest form a long tail of needs that may be legitimate for individuals or small groups but, in that context, do not justify the same concentration of resources.
The problem is not finding needs. It is surviving their abundance.
In a typical application of the process, 70 to 150 needs may be discovered per stakeholder. The organization then selects approximately 25 for investigation. Only then is that set taken back to customers for prioritization and assessment of fulfillment.
This creates a fundamental distinction among three things that are often confused:
| Stage | What it answers |
|---|---|
| Discovery | Which needs exist? |
| Prioritization | Which needs are sufficiently shared and important when customers must choose? |
| Strategic classification | Which ones justify preserving, expanding, testing, or removing resources? |
The mistake appears when the organization jumps directly from discovery to solution: “if a need exists, an opportunity exists.” That leap turns an abundance of information into an abundance of initiatives.
Where Power Law enters the discussion
A power law describes distributions in which a few high values can have disproportionate weight across the whole set, while a large number of occurrences remain in the tail.[1]
It is this logic of concentration that matters strategically: many needs can exist, but few tend to concentrate the potential to sustain or leverage value for a relevant share of the market served.
The Need Gap 2026 is not presented as mathematical proof that the distribution of needs follows a power law. Demonstrating that would require specific statistical tests.[3] Power law is used here as a reference for interpreting an observed management pattern: strategic potential is far scarcer than the universe of needs available for selection.
The data shows a tail much larger than the head
The Need Gap 2026 consolidates studies conducted by 59 companies. The 1,423 analyzed needs correspond to observations that reached the quantitative stage after a preliminary selection made by the organizations themselves.[2]
80.32%, approximately eight out of ten needs, were not prioritized by 30% of participants in their respective respondent bases. In other words, even after the company chose which needs seemed worthy of investigation, most remained restricted to smaller portions of customers.
45.33%, approximately one out of every 2.2 needs, did not show enough significance in the cross-analysis between volume and fulfillment level to advance into the model’s strategic classifications.
37.1%, approximately one out of every 2.7 needs, received no selections when participants were required to prioritize.
The percentages are different cuts of the same base and may overlap. They should not be added together or read as successive stages of a funnel. Even so, together they reinforce an important conclusion: even after an initial filter, most investigated needs do not demonstrate enough shared relevance to receive the same strategic weight.
The risk begins when the tail becomes a priority
A need with low shared relevance does not create complexity simply by existing. Complexity begins when the organization decides to treat it as a strategic priority.
To serve a limited need, the organization typically has to create some combination of functionality, service, process, message, channel, commercial rule, or operational adaptation. If the audience that values that delivery also has other specific needs, new adaptations begin to emerge around the first decision.
This is how an apparently small choice can start a chain of dispersion:
| Prioritize a concentrated Need | Prioritize a long-tail Need |
|---|---|
| Reinforces a need shared by a relevant portion of the customer base. | Serves a smaller group and tends to create exceptions. |
| Strengthens an already relevant promise, product, and experience. | May require a new promise, product adaptation, or operational change. |
| Concentrates resources on what preserves or expands value. | Divides resources across new fronts and specific demands. |
| Tends to increase Core coherence. | May attract new profiles that bring new needs and new exceptions. |
The effect does not have to be linear. A new adaptation may attract a new customer profile; that profile introduces other needs; those needs require new solutions, messages, and processes. When this repeats, the organization does not merely add initiatives. It multiplies decision and maintenance surfaces.
The long tail is not a problem because it contains infrequent needs. It becomes a problem when the company starts funding the tail as if every need had equivalent strategic potential.
Core and Leverage sit at the head of the distribution
After validation, the cross-analysis between volume and fulfillment guides the distribution of needs into four strategic directions.
| Quadrant | Decision direction |
|---|---|
| Core | Preserve and strengthen relevant, well-served needs that sustain value already recognized by customers. |
| Leverage | Investigate relevant, insufficiently served needs that may increase value creation and capture. |
| Educate | Assess whether there is justification for investing in market education. In our applications, this quadrant generally loses priority when it requires high effort to create relevance. |
| Eliminate | Remove low-relevance needs from the investment agenda in the context being analyzed. |
The four quadrants do not represent four equally desirable destinations. Core and Leverage concentrate the needs that justify strategic attention. Educate and Eliminate function mainly as mechanisms to prevent resources from being absorbed by needs without sufficient shared relevance.
This changes the role of prioritization. It stops being merely a way to order initiatives and becomes a mechanism to protect the organization from dispersion.
Efficient execution does not fix a bad priority
The cost of a poor choice does not appear only in the initial investment. It remains in what must be maintained afterward: code, operations, support, training, communication, integrations, processes, metrics, and future decisions.
A team can execute perfectly on an initiative that should never have received resources. In that scenario, operational efficiency only accelerates the creation of complexity.
That is why, before asking “how can we execute better?”, there is an earlier question: does this need have enough relevance to justify the organization adapting to it?
The cases show the effect of concentration
In the case that opened this article, one need among dozens guided a solution that found customers in eight countries within 60 days.
At another company, we identified a misalignment between positioning and the main purchase driver of the best customers. The need that led them to buy was different from the one highlighted in the company’s communication. The positioning was adjusted. Within nine months, the company doubled revenue.
At Profissionais SA, we identified that the needs of speakers and buyers required different approaches. The work led to the formation of an innovation committee based on the mapped opportunities. In less than three months, initiatives derived from the process accounted for 10% of all revenue generated during the period.
We also identified needs that competitors were failing to serve and structured account-migration plans. In other applications, the mapping made it possible to cut budgets allocated to misaligned initiatives.
The cases do not prove a universal causal relationship. They do, however, show a recurring characteristic of the method: the gain does not come from responding to more needs. It comes from concentrating resources on the few needs capable of moving a relevant share of value.
The Need-Based Decision Science thesis
Value creation occurs when an organization improves an outcome that is relevant to the customer. Capture depends on how it converts part of that benefit into sustainable economic results. Teece and Linden highlight the importance of balancing value creation and capture in the business model, considering revenue, costs, and delivery capabilities.[4]
Need-Based Decision Science adds a question that comes before allocation: among all existing needs, which ones truly deserve to transform the organization?
That is why a real Need is not automatically an opportunity. First, we need to understand its shared relevance, who it is relevant to, how well it is served, and what role it can play in preserving or expanding value.
A low-frequency need across the total customer base can still be central to a deliberately strategic segment. In that case, it must be analyzed within that segment, not elevated to a general priority merely because it was identified. The principle remains the same: the correct denominator matters.
The discipline therefore does not exist to discover the largest possible number of needs. It exists to prevent an abundance of needs from becoming an abundance of priorities.
Power Law helps explain why a few Needs can carry a disproportionate share of value. Need-Based Decision Science exists to identify which ones they are before the organization wastes resources building everything else.
When a company concentrates resources on Needs that preserve the Core or show real Leverage potential, it tends to strengthen coherence, value proposition, and execution capacity. When it turns the long tail into the roadmap, it begins funding exceptions, expanding operational surfaces, and accumulating complexity.
The strategic problem is not having too few ideas. It is having too many options and not knowing which ones truly justify resources to create, preserve, and capture value without disproportionately increasing business complexity.
George Eich is the founder of the George Eich Institute and creator of the ICAN metric and Need-Based Decision Science.
References
[1] Newman, M. E. J. (2005). Power laws, Pareto distributions and Zipf's law. Contemporary Physics, 46, 323–351. Access article.
[2] George Eich Institute (2026). The Need Gap 2026: The Challenge of Prioritizing What Truly Matters to Customers. Each observation corresponds to one need in one company context; the 1,423 observations are not necessarily semantically unique needs. Access study and methodology.
[3] Clauset, A.; Shalizi, C. R.; Newman, M. E. J. (2009). Power-law distributions in empirical data. SIAM Review, 51, 661–703. Access article.
[4] Teece, D. J.; Linden, G. (2017). Business models, value capture, and the digital enterprise. Journal of Organization Design, 6, artigo 8. Access article.