Aligning Developers’ and Customers’ Thought-Worlds

Green Head Idea to Need


“Thought-worlds consist of tacit and taken-for-granted assumptions about what is important, relevant, or necessary” (2014, McQuarrie)

“You have got to start with the customer experience and work backwards toward the technology ” (1997, Jobs).

A study of unsuccessful product concepts found that developers in “leap before you look” thought-worlds take a solution to the market, not a product (1987, Dougherty). Without a comprehensive understanding of customers’ thought-worlds, unproductive surprises crop up in late stages of concept commercialization.

Unproductive surprises include:

  • Investment of scarce resources … people, time, money … in development of unnecessary benefits
  • Expensive rework when necessary benefits surface in the late stages
  • Value proposition fails to attract profitable customers

Customers’ Uncertainties About A Product Concept

Customers’ Thought-World … Key Uncertainty

Technical … How do we fit this concept into our product platform?

Manufacturing …. What shift in production systems do we need?

Field … Will end users adopt our new product incorporating this concept?

Planning … What is the market forecast for our new product?

Conducting hypothesis experiments in customers’ thought-worlds provides the data developers need for dealing with customers’ uncertainties … and for validating assumptions.

Don’t Think Solution … Think Hypothesis

Frequently developers treat a product concept as a solution and take a running leap into the market. They implicitly assume that customers think the same way the developers do about the problem the concept is designed to solve.

Implicit assumptions are dangerous if they are “load-bearing” (2002, Dewar). In new product development systems, failure to validate load-bearing assumptions in the front end leads to significant changes and expense in a development’s late stages.

In a lean product development system, before beginning commercial development developers treat a product concept as a hypothesis , an educated guess (2015, Blank). Hypotheses require experimentation and data to validate or invalidate their assumptions .

Some load-bearing assumptions in the front end are:

  • Who are the right customers?
  • What’s their distinctive value proposition?
  • How much will they pay to capture the distinctive value?

Validating a product hypothesis’ assumptions

As one of the successful developers interviewed by Dougherty said:

“You have to get into the ears and minds of users. If you can’t explain the product (hypothesis) in 30 seconds, you’re dead (1992, Dougherty)

Between 25-50 interviews with prospective customers are recommended to gather data for validating assumptions about product concepts (1993, Griffen; 2002, Castellion; 2014, Blank; 2012, Maurya). The individuals interviewed are decision makers within the product concept’s value chain. They are chosen randomly from a sample of two hundred or more decision makers.

Good data gathered through elicitation methods during 25-50 interviews provides the clues to validating load-bearing assumptions. The central limit theorem of statistics (2013, Wheelan) makes it possible to generalize from these clues and validate assumptions with a strong probability that they represent the thinking of all decision makers in the value chain.

Interviews can be either face-to-face or by phone. I prefer to interview by phone, using my elicitation skills and my practitioner experience as a technology manager and marketing manager to gather good data. Also, decision makers are more open about their thought-world uncertainties than they are in face-to-face interviews.


(1987 ) Dougherty, D., New Products in Old Organizations Ph.D Thesis, MIT

(1993) Griffin, A., and Hauser, J., Voice of the Customer Marketing Science 12: 1-27

(1992) Dougherty, D., Interpretive Barriers to Successful Product Innovation Organization Science 3 #2 p. 193

(1997) Jobs, S. , World Wide Developers Conference, accessed 5/23/15

(2002) Castellion, G., Telephoning Your Way to Compelling Value Propositions The PDMA ToolBook for New Product Development, John Wiley & Sons, NY, NY

(2003) Dewar, J., Assumption-Based Planning A tool for reducing avoidable surprises Cambridge University Press Cambridge UK

(2012) Maurya, A., Running Lean 2nd Edition O’Reilly,Sebastopol, CA

(2013) Wheelan, C., Naked Statistics W. W Norton & Company, NY, NY

(2014) McQuarrie, E., Customer Visits: Building a Better Market Focus Rutledge

(2015) Blank, S., Why Build, Measure, Learn isn’t just throwing things against the wall to see if they work accessed 5/11/15

When Customers Shade the Truth About Marketplaces

Truth Squeezed

“I’ve got a problem” the innovation leader admitted. “Two years ago a major customer suggested a product idea to an executive in our company. The idea would use our unique technology. The customer said developing the idea would result in a key part of a new product for their marketplace.

After hard work we met their first needs, Then they made significant changes in the needs. We met those. Now they’ve changed needs again.

What’s going on here? This is a politically sensitive issue. How do I find out in a way that doesn’t cause trouble with the customer or our executive?”

Shading the truth, consciously or unconsciously, is common in business (2012, Askenas)

Doubts about the marketplace are plentiful in prospective customers’ thought-worlds. Some customers believe it’s proper to shade the truth to sell developers on devoting people, time, and money to commercialize the idea.

Two politically sensitive situations where prospective customers shade the truth:

  • The customer’s marketplace gatekeeper ignores or does not know the truth of  marketplace value to end-users.
  • The product idea fulfills, in a unique way, a valuable hidden need in the customer’s marketplace. The customer is concerned that developers, learning the truth will charge a premium price for the product developed from the idea.

For the first situation, discovering the truth about the marketplace prevents waste of developer’s time, and money. For the second situation, discovering the truth may lead to a new product with exceptional profit.

Discovering truth shading

To gain the benefits of resolving the above situations and avoid to political risks. developers should gather reliable marketplace information from interviews with 25-40 primary sources. In analyzing the data, the central limit theorem of statistics helps validate the assumption that the customer shaded the truth (2015, Castellion).

As an external expert, I’ve completed seventeen client projects where the two situations were major problems. Analysis of interviews with primary sources included a set of practical choices for dialogue with the developers’ executives on how to communicate the analysis’ results to the customer. In these seventeen projects, anonymity and neutrality in information gathering and analysis, paid off in positive outcomes for the client with the customer.


(2012) Ashkenas, R. Why We Don’t Always Tell The Truth Harvard Business Review [ Accessed 6/16/15)]

(2015) Castellion, G. Aligning Developers’ and Customers’ Thought-Worlds