I’d like to document the evolution of concepts and techniques of the fitness-for-purpose analysis. Fitness for purpose has been a hot topic in the Kanban community in the last several years, particularly at the Leadership Retreat level. It is also a key and still evolving concept in Enterprise Services Planning. This story will take a series of blog posts, perhaps one post for each incremental innovation.

With fitness-for-purpose analysis, we try to get our customers stories, understand why they choose to buy or not to buy our products and services, how fit the customers find our products for their (customers’) purposes, and how we can make our products fitter.

Why do we want our products fitter? Because that would mean happiness for the customers, success for the business owners, and pride of workmanship for the workers making and delivering the products to customers.

The journey began several years ago when many discovered the Net Promoter Score (NPS) and started applying it in their business. The credit for NPS belongs to Fred Reichheld, a management consultant who developed it after many years of investigation of customer loyalty and its business impact. Management guru Steve Denning further popularized NPS in his speeches, columns, and his book The Leader’s Guide to Radical Management: Reinventing the Workplace for the 21st Century.

What is NPS? Every time a company delivers some product or service to its customer, it asks a simple question (seemingly simple, but it took Reichheld years of experimentation to come up with its precise wording): How likely is it that you will recommend this firm or service or product to a colleague or friend? Many of us as consumers have seen this question in recent years, especially after making an online purchase or a travel reservation.

The range of possible answers is an eleven-point scale, from 0 (not at all likely) to 10 (extremely likely). Customers answering 9 or 10 are promoters, 7 or 8 neutral or passively satisfied, 6 or less detractors. Now we know what percentage of our customers are promoter, what percentage are detractors. The difference between the two is the NPS. It’s a number between -1 and +1, +1 of course meaning our product delights all our customers without exception and -1 meaning the opposite. Many NPS surveys produce scores above zero, but notably short of 1.

Understanding of NPS’ limitations, criticisms, and wishing something better appeared eventually. Said a bank executive from a Central European country (which should remain unnamed): “We conduct NPS surveys regularly. The score goes up and down, but it doesn’t let us understand what we did to move it or what we should do to make it go up or stay at a higher level. It is not actionable!” David J Anderson captured this bank’s story.

NPS was probably never intended to meet this executive’s needs. But there was, no doubt, desire for a better technique.

The first incremental improvement was so obvious that many discovered it started using it independently. Simply add a second question to the survey: “Why did you choose this particular answer (on the scale from 0 to 10)?” and give the customer some space to explain their choice. The customer would get a chance to explain their choice and give their story, perhaps unexpected and insightful from the company’s point of view.

I’d like to share two experiences with this simple NPS+narrative format, one when I was the customer and one when I was the service provider.

As a customer, I remember filling out an NPS survey in this format after taking part in the week-long Problem Solving Leadership (PSL) workshop taught by Esther Derby and Jerry Weinberg. I noticed during the workshop that about half of its participants were having a life-changing experience. (I know several people who would describe their PSL experience this way.) I belonged however to another subgroup, to whom the workshop was simply very useful. So I scored it a 9 and used the provided space to explain my choice briefly.

On the other side, I once taught a one-day workshop on process metrics. The participants seemed to be quite engaged, but my NPS survey produced a disappointing result: -0.3. When I read the participants’ stories, they all went basically like this. Alexei, I took this workshop because I wanted guidance on the topic and have a high comfort level with math. And the workshop very useful! But most my colleagues aren’t like me. Out of all people in my company, I should be the one taking this workshop and not them. So, while I personally found the workshop very useful, I wouldn’t recommend it to them.

I was relieved to read such comments and I learned several things from them. First, I was lucky to attract the right type of customer to my offering, and, perhaps more importantly, avoid attracting the wrong type of customer. Second, I needed better techniques to understand both different components of my offerings and different customer segments.

Thus the next improvement could be summarized in one word: segmentation. But that’s a story for another blog post.

  • This post begins to document the evolution of fitness-for-purpose (F4P) analysis techniques leading up to today’s F4P cards and box scores.
  • NPS was the starting point of this journey.
  • The first incremental improvement was obvious: give customers space to tell a short story.

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