A few days ago, while discussing with colleagues why many organizations were still fumbling at what’s typically called the “last mile” in data science, the conversation veered towards the birthing of a new breed of professionals called ‘Data Translators’.
This class, now increasing in numbers, is being seen in the analytics world as the Darwinian equivalent of the missing link in the evolution of man from apes.
Or look at it this way. Think of an outlet terminal in an oil pipeline network. Without it, the refined oil will not reach the intended end-user, despite the sophistication of the system, from drilling for crude oil to its refinement to its pumping, thus failing in its intended purpose.
Data and its analytics are comparable to this process. The outlet terminal represents the last-mile connectivity. Raw data is collected in the field, analyzed, and the result is refined oil that needs to be “pumped” or used by the end-user. Unfortunately, for decades, we’ve seen companies falter at this last step. Collecting vast amounts of data and refining it is something that most have achieved, yet many still find it difficult to derive insights and use them in their daily decision-making. A recent survey by Harvard Business Review Analytic Services, for example, found that 44% of executives admitted their organizations were not effective at deriving market insights from analytics.
Data translators are now seen as the new conduit between data analysts and the key decision-makers within an organization. Call them “gap fillers”, if you may. Sometimes a profession is born out of market needs; a data translator is one such. But before we go deeper into that, let’s first understand the reasons why companies falter at the crucial last step.
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Like many other “systems” in our professional lives, a nimble data analytics system requires the right combination of people and technology. But what’s even more crucial, and this, we feel, is the fundamental reason why the “last mile” still bugs organizations, is Process.
If the above has to be explained straightforwardly, it would be this:
