Workplace Analytics Blues

Is the modern workplace anti-analytic?

At first glance this might seem to be an otherworldly question – after all, we have more data, more databases, more analytics, more visualizations, more predictive models than ever.

Where’s the lack of analytics in that? And the answer is: context.

A friend of mine consults in the realm of personal productivity, and he tells me that his clients report more problems than ever getting things done.  Large amounts of data and analytics can be a hindrance more than a help, as people respond to more things in a shorter span of time, and end up doing almost none of them really well.  We can become near-constant context shifters – always changing gears as they move from one task to another. Context shifting is a process that consumes our finite resources of time and energy, and only the time and energy that remain can be devoted to productive work.

Although my friend works mostly with IT security personnel, analysts frequently describe the same pressures.  For analysts the consequences are, if anything, worse, for even the best analytics models are fractional representations of reality, and for us to accurately interpret the results we see requires the additional context and experience we bring to the job.

We can get away with “at a glance” analysis only when context stands still: the result means just what it did the last time we glanced.  Otherwise, we can easily find ourselves interpreting a number in the light of what it once was, or in the light of the last thing we were thinking about.  Does this cause all interpretive problems? Certainly not.  Does it cause many problems? In my experience, it does.

Workplace environment becomes a factor when we lack the time to shift our mental context from one analysis problem, clear our heads, and seriously consider an unrelated problem.   When our workplace combines demands for “multi-tasking” information processing with insufficient time for “task switching” yes, it is anti-analytic.

The cost of “task switching” depends on the task, of course – however my friend argues a minimum of 30 minutes for each task-switch, and many of my coworkers report similar times. Interpreting data is a context-intensive task.   That may seem like a long time to “just look at a chart,”  and it is a long time to “just look” at information, but not a long time to understand that information.

Is it easier to reply “it will take more than just a minute” to the next urgent request that “will only take a minute,” or to sing the Workplace Analytics Blues?   For sure, it can be uncomfortable to offer that kind of “push back” – a breakdown of the time costs for moving task-switching often helps. On the other hand, I can’t sing, so for me there isn’t really a choice.

 

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