Updated: May 17, 2019
Using the same set of matrices to monitor the success of a current product/service and estimating the potential of a new business idea hurts our creative effort.
Quantitative and historical data is useful in measuring the success of an existing product. We can monitor the sales quarterly and predict ‘with good discretion’ how the product will perform in the next future.
While human interaction is welcome in this kind of evaluation, an elaborated algorithm (comprehensive of the relevant variables) can better and faster spots trends and patterns.
It’s difficult for us, humans, to beat the machine at this kind of prediction, this is for the same reason I wouldn’t feel confident to play chess against a computer.
Given a clear set of rules, computers are much better than us to discover information hidden in data. Machines are a great help to predict our sales in the next quarter.
What about testing the potential of a new business idea? Well, this will always require a human touch.
While many large organisations developed great software to analyse current and projected sales, they fall short of resources to test the potential of new business growth.
As humans, we can’t compete with computers to remember/analyse data and but we have (among many others) two significant advantages:
1) we can forget; 2) we can feel (emotion).
We don't avail of data to support a new business idea (and not a better version of our, or worse our competitors’ current proposition). Therefore it requires our best judgment, which we develop by forgetting and feeling.
Since management was born - as the byproduct of the industrial revolution - knowledge has been the most critical requirement (knowledge management) in running organisation.
Transitioning from an industrial to a connection economy requires us, as managers, to rediscover our ability to develop our best judgment about new possibilities for value creation. It comes without saying that this belongs to our ability to feel rather than to analyse.