The result was uncomfortable, and it is the reason the instrument works the way it does.
I run an engineering services business. We were early to this — earlier than most of our competitors and considerably earlier than most of our clients. We had agents in production doing real work while the firms around us were still circulating policy documents about whether staff could use a chatbot. I was, if I am honest, quite pleased with us.
Then I built the diagnostic this book is organised around, and before showing it to anyone else I ran it on my own company. Properly: three people interviewed separately, evidence demanded for every high score, only the previous ninety days counted.
I had expected somewhere in the sixties. We came in materially lower, and the shortfall was almost entirely in two places. We could not evidence that any of our internal automation had moved a number our own clients or bankers would recognise. And when the questions turned to whether what we sold would survive the same technology we were so pleased to be using internally, we had no answers at all. Not bad answers. No answers.
That is why the instrument has ceilings, why economics and business-model exposure carry more weight than technology, and why the book spends a whole part on a question most transformation programmes never ask.
I work with technology and professional services organisations on measurement, autonomy and business-model exposure — the calibrated assessment, and the work that follows it.
I write research on decision lineage, trust propagation, reputation under coordination cost, and the dynamic boundary of the firm. Based in Bengaluru.