Underlying formula for the digital economy

In an earlier post I talked about the various ways in which value can be created in the digital economy. However, formula by which data turns into value is something that is less clear. Reviewing many digital economy businesses, three questions seem to consistently describe this journey:

1) Data + Analysis = Information

2) Information + Context = Insight

3) Insight + Action = Outcome

The first equation is one that is commonly understood in the IT industry and underpins the various management information systems and data warehouses that are in use. These systems have relied on managers or knowledge workers to have the context in the heads to be able to make the leap from information to outcome. In some cases these leaps have been profound and the classical example that comes to mind is to place the beer near the diapers so that new fathers pick buy beer on the way home. The insight that new fathers typically buy diapers on the way home from work and the opportunity for selling beer was the context that a smart knowledge worker or manager was able to use to create this outcome.

The advances in cognitive computing mean it is possible for computer systems to create the context and so make connections between information to automate the creation of new insights. This creates a wide range of opportunities to optimise processes and potentially create new outcomes. The simple example of finding the optimal route between two locations based on your personal preferences follows this same logic and creates many new business opportunities.

One or more business will emerge to handle each of the elements in these three equations.

For a business leader wanting to achieve an outcome, working backwards through these equations creates a valuable way to identify the data needed.

These equations can also help in understanding how to assess the value of a “pile of data”..

Does this make sense?

Do you have examples of business or project that fit this model? or “challenge” these equations?


How do you estimate the value of a “pile of data”?

A very common question people ask is how to measure the latent value of data that the own. We typically explore this question by simply force fitting our particular situation into an existing business model (e.g. Google or Azure etc..). However, many of the ways in which data will turn into new value are not understood today.

The paper that some colleagues from IBM Research shared with me were very valuable in helping think through this question..

More ideas to come soon…