“Contextual Intelligence is the ability to understand the uniqueness of a person or circumstance and convert that understanding into an opportunity” Heavy Reading White Paper, June 2012
Big data is here to stay. While there has been a lot of hype in the news over the past couple of years about it across every media channel (digital, social and print publications), underlying all this interest is a genuine desire to better harness enterprise manufacturing intelligence to operate with greater efficiency, quality and performance.
Today’s business challenges are more complex – spanning multiple sites, regions and cultures while operating with greater flexibility – so new solutions are being actively sought to try and make sense out of all the chaos.
It seems to me that “big data” can be visualized as stacks of paper stored in warehouses, from back in the second half of last century – lots of information, lots of good insights, all within neatly (or not so neatly) stacked articles, reports, books, but good luck trying to locate the right info within a reasonable period of time. Workers responsible for managing and maintaining this information likely worked in fear that someone (likely their boss) asks for a particular number or trend or analysis, at which point they would be left standing in front of the stacks of paper, hoping to pull the right report …
Big Data, or a Data Tomb?
Big data is literally unorganized chaos, or a data “tomb,” as I have heard it called. This chaos becomes organized and begins to make sense only when you can extract intelligence that is the right insight within the right context at the right time, for the right purpose. This is not a small feat!
Just think how big data is collected – every piece of information is extracted from a variety of sources, which is not always homogeneous, which is then stored in a database or data warehouse. Regardless of where this data is stored – physically on a local server, on a data farm, or on the cloud – it is still just raw information that really can’t be leveraged to improve business performance without further cleansing and processing.
Effectively harnessing, processing and leveraging big data can offer unprecedented opportunities for discovery, insight and quality improvement – provided the means exist to effectively work through the information in the right way. Effectively extracting the intelligence to explain what happened, why it happened or what might happen tomorrow is an exciting prospect. This capability could help us improve flexibility in manufacturing to foresee problems and potential solutions through correlations and connections we weren’t even aware of.
As we enter the scary world of big data, we are being driven towards the prospect of understanding our business better through extensive analysis. Numbers are supposedly uncontaminated by bias, judgement or opinion. Numbers are objective. Objectivity is scientific. Scientific equals robust. Or is it?
Context is the Key
Without context, data is meaningless, irrelevant and even dangerous. Effectively harnessing big data for a competitive edge requires a new type of intelligence: contextual intelligence. Applying context to data and delivering intelligence quickly with automated alerts and trigger mechanisms can yield significant competitive edge. And, not to mention some pretty stellar customer satisfaction! Being data-savvy, but not data-obsessed is the driver to extract the right intelligence out of big data. The most important thing is giving meaning to data, and making it easy to extract and see the results, which can then be readily acted upon. And meaning comes from applying contextual intelligence to the problem and delivering results.
Here is a good manufacturing quality intelligence video that shows how you can utilize big data, displayed in the right context, to yield impressive results and make a difference in letting you manage your manufacturing operations with greater precision, efficiency and operational excellence.
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