Why the Soft Side of Analytics Is So Hard to Manage

I’m borrowing both inspiration and content from two good friends and long-time supply chain professionals, Scott Sykes and Mike Okey.  They deserve the credit for the seminal thoughts.  Any blame for muddling the ideas or poorly articulating them is all mine.

If you are an analyst, operations researcher or quantitative consultant, you probably enjoy the “hard” side of analytics.  What we often struggle with as analysts is what you might call the “soft” side of analytics which is always more challenging than the “hard” stuff.  Here are a few of the reasons why.

Many times, the problem is not insufficient data, defective data, inadequate data models, or even incompetent analysis.  Often, the reason that better decisions are not made in less time is that many companies of all sizes have some, if not many, managers and leaders who struggle to make decisions with facts and evidence . . . even when it is spoon-fed to them.  One reason is that regardless of functional or organizational orientation, some executives tend not to be analytically competent or even interested in analysis.  As a result, they tend to mistrust any and all data and analyses, regardless of source.

In other situations, organizations still discount robust analysis because the resulting implications require decisions that conflict or contrast with “tribal knowledge”, institutional customs, their previous decisions, or ideas that they or their management have stated for the record.  Something to keep in mind is that at least some of the analysis may need to support the current thinking and direction of the audience that is analytically supportable if you want the audience to listen to the part of your analysis that challenges current thinking and direction.

Understanding the context or the “Why?” of analysis is fundamental to benefiting from it.  However, there are times when the results of an analysis can be conflicting or ambiguous.  When the results of analysis don’t lead to a clear, unarguable conclusion, then managers or executives without the patience to ask and understand “Why?” may assume that the data is bad or, more commonly, that the analyst is incompetent.

Perhaps the most difficult challenge an organization must overcome in order to raise the level of its analytical capability, is the natural hubris of senior managers who believe that their organizational rank defines their level of unaided analytical insight.  Hopefully, as we grow older, we also grow wiser.  The wiser we are, the slower we are to conclude and the quicker we are to learn.  The same ought to be true for us as we progress up the ranks of our organization, but sometimes it isn’t.

So, if these are the reasons for the organizational malady of failing to fully leverage analytics to make higher quality decisions in less time, what is the remedy?

The remedy for this is the subject of next week’s post, so please “stay tuned”!

Thanks for having a read.  Whether you are an executive decision-maker, a manager, or an analyst, I hope these ideas have made you stop and think about how you can help your organization make higher quality decisions in less time.

A final thought comes from T.S. Eliot, “The only wisdom we can hope to acquire is the wisdom of humility—humility is endless.”

Have a wonderful weekend!

Advertisements

About Arnold Mark Wells
Industry, software, and consulting background. I help companies do the things about which I write. If you think it might make sense to explore one of these topics for your organization, I would be delighted to hear from you. I am employed by Opalytics.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s

%d bloggers like this: