Have some sympathy for the manager of the corporate analytics department. Everyone, it seems, is talking Big Data this and Big Data that. We hear there is a worldwide shortage of data scientists.
Analytics is the new oil. There's not enough of it and we all need more. This should be good news and for many managers it is because it means bigger budgets and more people.
My view is that such enthusiasm is misplaced. The strategic problem is not too few data scientists, poor data quality or keeping track of the spread of open source analytics. These things can all be solved using existing management techniques. The problem is not technical, technological or financial. The problem is historical. The problem is functional. The problem is managerial. These things require new techniques and ways of working.
The corporate analytics manager runs a business unit built on the functional principle of organisation. Henri Fayol pioneered functional organisation in the 1870s, in the era when work was predominantly physical. The analytics business unit is also likely to be part of a decentralised enterprise structure, which Alfred Sloan developed in the 1920s.
The functional model started breaking down in the 1960s and is hopelessly out-of-date in the 2010s. The decentralised enterprise structure began its decline in the 1970's with the growth of multi-product service businesses. The manager of the internal analytics department is working with a 140-year old model originally designed for the mining industry and in a parent organisation derived from the automobile industry.
This wouldn’t be a problem if internal demand for analytics services was predictable and regular. Even then it wouldn’t be too great a problem if quality enterprise analytics wasn’t a minimum condition for the success of digital transformation programs of large organisations over the coming decades.
But analytics demand is unpredictable and irregular, and large organisations that don't get their enterprise analytics sorted out won't be large for long.
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