There is a shortage of digitally-enabled people.

The ‘people dimension’ in the new digital economy is all-too-often not properly understood. They are usually valued but they can be a breed not traditionally seen in, or around the C-Suite.

We encounter managers who believe – and, indeed, there is a widespread view – that progress in the digital economy is being held back by a lack of digital skills.

This is, of course, true . . . but only to a limited extent.


Data analytics require four key ingredients

  1. Access to statistical skills.
  2. Unfettered access to data – both internal and external, structured and un-structured, big and small
  3. An ability to interpret (statistical) results in context.
  4. An ability to communicate the results.


Statistical skills can be internal or external – in-house, or obtained from a specialised supplier of analytics services.

However, items, 2, 3 & 4 above all require what is called ‘domain knowledge’. It is here that we observe the greatest deficiency: this is either data analysts (or statisticians) that aren’t able to interpret their results in the required context, or managers that may be good communicators but aren’t able to properly understand or interpret the statistical results.


There is actually a fifth people component – sponsorship

Time-after-time, we observe digital initiatives that founder for lack of active sponsorship from the Chief Executive or, at a minimum, from the C-suite.

Overall, and all-too-frequently, the lack of digital skills isn’t related to those that manipulate the data but, rather those required to direct and interpret the results.


Thinking of data as ‘gold’

Those that dig and extract the gold. These are the data artisans and statisticians that extract meaning from a myriad of data sources – those that extract the nuggets.

Those that turn the gold into a thing of beauty. These are the data scientists.

Those who combine the gold and jewels and turn them into a precious object. In practice, these people have domain insight and personal abilities to communicate and ‘sell’ the results in a relevant business context.

There is a possibility that any two of the above may be combined but it is singularly rare that goldminers make good jewellers.


According to NESTA, the hardest skills to find

Domain knowledge, or an understanding of the function of data inside a particular business or industry: what are the ‘real world’ processes that generate it (the data), what are its limitations, what important questions can it help answer?

The right mix of skills, or the combination of coding skills (to get and work with the data) and analytical skills (to extract insight from it) that one finds in data scientists.

Experience working with big &/or messy data, and with the appropriate tools and technologies.