Big Data, Advanced Analytics and Black Swans

black swanCan advanced analytics be as much a threat as an opportunity? It seems quite plausible: it’s complicated.  The near wipe-out of a leading Wall Street brokerage in just two hours demonstrated how complexity can be financially catastrophic, to take just one example.

McKinsey’s latest advice to organizations investing in advanced analytics highlights the value of simplicity, which enables the business stakeholders to be engaged:

“Two guiding principles can help. First, business users should be involved in the model-building process; they must understand the analytics and ensure that the model yields actionable results. Second, the modeling approach should aim for the least complex model that will deliver the needed insights.”

McKinsey quotes a case where the complexity of a model prevented the business users from spotting its flaws, and so correcting its grossly misleading conclusions. It took the creation of a new simplified model by different authors to realise the mistakes that were being made. I suspect that many of us know of similar instances.

Looking at how companies can turn valid data-driven insights into effective action on the front line, McKinsey notes how user engagement becomes crucial:

“Companies must define new processes in a way that managers and frontline workers can readily understand and adopt.”

I’m not a big data and analytics skeptic.  When data-and-analytics is done well, it has huge potential, especially perhaps for consumer-facing organizations.  But it seems to me that there’s an essential enabling infrastructure that’s required to ensure that fast-paced data-driven agility is managed safely and sustainably.

It’s an infrastructure characterized in three ways:

it’s process-based and leverages the power of visualization and personalization to simplify and engage

it provides 360 degree visibility; joined-up and comprehensive perspectives where roles and responsibilities, linkages and dependencies are always readily apparent

it enables a rich and effective collaboration across silos, within a unified and robust governance framework.

It adds up to an enterprise process management platform.  And it’s an approach that was reinforced, looking at this from a different angle, by a Deloitte webinar this week on the new COSO 2013 Enterprise Risk Management Framework.  Deloitte’s key messages to senior stakeholders included the need to adopt holistic perspectives, to ensure traceable connectivity between policies and everyday practice, and to ensure ongoing engagement with control owners across the enterprise.

Related Posts

02 Apr 2013   A Simplification Bandwagon Begins To Roll

26 Mar 2013   A Litmus Test For Process Craft  

One thought on “Big Data, Advanced Analytics and Black Swans

  1. You make some great points here, thanks for posting. I think the thing that all businesses must keep top of the mind is that the advanced analytics are only as good as the data being used, and the assumptions made during programming and are Not a substitution for human review, analysis and close questioning to ensure that the results are logical.

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