The Product Factory
Have you ever had that feeling? When you've just delivered something amazing and thought "everyone needs this!" Maybe it was a perfect consulting project, a game-changing analysis, or an innovative solution to a thorny problem. That moment when you're convinced you've cracked the code for an entire industry.
Then several months (or years) and countless hours later, you come to a very important realization: success with one customer does not predict market success.
The problem is that most things that make a solution perfect for a customer are nearly impossible to scale. And after many attempts (including some of my own) and observing others, here’s an approach to product development that seems to work.
The Pipeline Problem
When building products from services, everything I thought was a strength was actually a weakness. The metrics used for tracking - customer satisfaction, delivery excellence, project profitability – mask a deeper problem.
In my last engagement, every successful project felt like validation to productize. But each "success" was actually making it harder to build something scalable because we kept customizing, saying yes to unique requests, perfecting our solutions.
Seeing the true product potential of a solution requires a different set of metrics. Instead of tracking project-by-project success, start measuring patterns across projects:
How often do similar problems appear?
What percentage of the solution can be reused?
How much does implementation time decrease with each iteration?
This change in solution metrics help discern which solutions have true product potential and which are just good consulting work.
“But every customer is different." And yes, at the surface level, they are. But dig deeper and patterns will start to appear. Not the obvious ones - but deeper similarities in the problems you’re trying to solve.
Pattern Recognition in Practice
Here’s an example from personal experience – in the last 24 months I had 3 different executives come to us with a specific request:
One executive needed site selection for improved clinical trial diversity
Another was focused on physician targeting
Another wanted to build stronger patient support programs
But squint your eyes and a common pattern emerges. All three executives want to:
Identify underserved populations
Map where care access/quality challenges exist
Target resources to areas of greatest need
Stated simply, all three want to identify and understand care gaps at a geographic level. The key is systematic pattern recognition, reviewing every project through three lenses:
Problem frequency (appears in >40% of engagements)
Solution similarity (>60% of code/components are reusable)
Time compression (delivery time decreases by >30% with each iteration)
From these seemingly disparate requests could emerge a common solution - perhaps a geospatial analytical tool that could help:
Find diverse trial sites in underserved areas
Target physicians in regions with care gaps
Deploy support programs where patients face access barriers
Building the Factory
For years I struggled to define for people what I meant by “strategy” until a mentor summed it up perfectly: "strategy is choosing what not to do."
The hardest part of productizing great ideas? Learning to say no to good ideas that don't fit the pattern.
But once you spot patterns, you need a system to convert them into products. Think of it like a factory - raw materials (project insights) go in, finished products come out.
The factory has three stations:
Pattern Validation - Testing if what works for some clients works for most
Solution Standardization - Building the 80% that serves 80% of needs
Market Testing - Proving scalability before full investment
The First Product Test
The most counterintuitive lesson is to not start with your most sophisticated work.
I’ve long been nervous about presenting "simple" solutions to sophisticated customers. But the results speak for themselves:
Implementation times drop
Customer satisfaction improves
Margins increase
The journey from services to products isn't about building perfect solutions or finding one big winner. It's about creating a systematic way to identify and scale solutions that solve common problems uncommonly well and having the discipline to keep things simple.
Sometimes the best innovations come from just paying attention to what your customers are really asking for, not what you think they need.
