Petr SkodaAccording to a 2026 CB Insights analysis, 43% of startups fail because of poor product-market fit. The product works technically, but nobody wants it in the form it was built. For custom software and internal systems built for manufacturing and logistics companies, the risk is exactly the same, it's just talked about less: the development budget gets approved, the vendor delivers a working application or AI assistant, and six months later nobody uses it, because it doesn't solve a problem people in the company actually have.
Validating an idea is not the same as validating a product
Idea validation happens before development starts and checks three things: whether the identified problem actually exists, whether the target group perceives it as serious enough, and whether they are willing to pay for a solution in time or money. Product validation happens during development and checks whether the specific implementation actually matches user needs. Most failed projects skip the first phase entirely. The company and the vendor jump straight into building, because "it's obvious what's needed."
Two mistakes almost everyone makes
The first is confirmation bias: people naturally seek out and interpret information in a way that confirms what they already believe. If you ask colleagues or clients whether they'd use a new tool, "sure, that would be handy" is easy to read as proof of demand, even though it's often just politeness, known as courtesy bias. Real customers want to be nice and don't want to criticize someone's idea to their face.
The second mistake is a sequential approach to development: building the complete solution first and only then showing it to the market. In an environment where a prototype is relatively cheap compared to full development, this is one of the costliest mistakes a team can make. It maximizes the time and money spent before any real feedback arrives.
How to ask questions that get you the truth
The Customer Discovery method recommends focusing strictly on past behaviour rather than hypothetical preferences. "Would you use a tool that automatically tracked your warehouse stock levels?" generates unreliable data, because people answer based on what they think you want to hear. "How did you last find out you were running low on stock, and what was the most annoying part of that?" reveals actual behaviour and actual pain instead.
The Jobs to be Done framework is useful here too: customers don't buy a product for its own sake, they "hire" it to get a specific job done in a specific context. Once you understand the job, you often discover that your future system's real competitor isn't other software. It's a spreadsheet, a paper logbook, or a phone call to the shift supervisor. That's the alternative your product actually has to beat.
Why we insist on this ourselves
This is exactly why we start every engagement with a fixed-price audit of processes and automation or AI opportunities before any decision to build is made. The point isn't to sell an extra add-on. It's to confirm that the problem you're bringing to us is really worth the investment, and that the proposed solution will have real users from day one, not just technical documentation.
If you're planning an internal system, an AI assistant, or process automation and you're not sure you're solving the right problem, we're happy to talk it through before a single line of code gets written.
Sources
- Ries, E. (2011). The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses. Crown Business.
- Maurya, A. (2012). Running Lean: Iterate from Plan A to a Plan That Works (2nd ed.). O'Reilly Media.
- Blank, S. (2013). The Four Steps to the Epiphany: Successful Strategies for Products That Win (2nd ed.). K. & S. Ranch.
- Fitzpatrick, R. (2013). The Mom Test: How to Talk to Customers and Learn if Your Business Is a Good Idea When Everyone Is Lying to You. Robfitz.
- Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). Competing Against Luck: The Story of Innovation and Customer Choice. HarperCollins.
- Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220.
- CB Insights. (2026). The Top Reasons Startups Fail. Retrieved from cbinsights.com.