Opportunity v. Business Model at MRAIL

Is there an opportunity for an automated system that uses high-precision laser-based measurements to predict rail track failure? Absolutely. In fact, some colleagues and I reviewed that opportunty with the inventor, Professor Shane Farritor. We used a process very similar to Mullins’ New Business Road Test to figure out whether the opportunity was attractive or not. We concluded that the market in the U.S. was no more than about $10 million per year. On the other hand, the industry dynamics were relatively attractive. A proven solution could become a de facto standard, and there was not a lot of other innovation in play in the industry. The opportunity based on the innovation was moderately attractive. This opportunity analysis took approximately three months. We interviewed rail executives, examined industry data and trends, investigated the underlying cost structure of various rail-related services, and ultimately built a hypothetical operational model to examine possible financial outcomes.

So the opportunity was at least marginally interesting; was there a viable business model?

Evaluating the business model required addressing the resources and transactions required to generate value for customers. We had retained a key assumption: revenues would be generated by selling a rail car, including the measuring equipment, to the rail operators. We tried to limit how much of that was built into the opportunity analysis, precisely because it has business model elements baked into it. But some assumptions were required to do the basic analysis.

The idea of buying, retrofitting, and selling rail cars was clearly at odds with the core capabilities of the inventing and development team. The financial model that incorporated the limited business model elements already in place clearly showed a relatively capital intensive business, which also seemed unnecessary and inefficient.

That prompted our business model re(design). We set aside one full week of creative sessions and brainstorming discussions. In the first two days, we quickly hit on the crux of the business model challenge. The problem was not the underlying innovation; it was the transaction. Rail operators did not want to buy more rail cars, and MRail did not want to be in the business of buying and selling them. The essential unit of value was not the rail car or the measurement system; it was the knowledge of rail segments at high risk of failure. More specifically, it was the information on relative track conditions that would allow the rail operator to prioritize costly visual inspections and ultimately track section repair.

We spent the remainder of the week developing a business model in which the core activities of the organization focused on data management rather than manufacturing the measurement system. In the new business model, the process of producing the systems was obviously important, but not as critical as managing and selling the information from the resulting data. The business model was a data services venture. Once we saw that, we completely rebuilt the financial model as well as the venturing development plan. There were still many challenges, including how the measurement system would be manufactured and installed for use, but the core business model challenge would revolve around the organization’s ability to manage, interpret, and sell information.