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First the data, then the decision, then the profit.

Working and valorising Big Data is business-as-usual for companies that have built their business model on it. For companies that don’t compete on analytics, that is for whom analytics is not a core element of their strategy, it’s a huge challenge.

But Big Data is the talk of town nowadays. I think that a part of the growing management interest is due to two factors:

  1. The relentness search for cost efficiency and growth in the current economic downturn;
  2. A revived interest in the field of Business Intelligence, fueled by non-traditional BI technologies that are demonstrating cheaper, more flexible,  and visually more appealing alternatives to traditional enterprise-wide BI solutions.

In a recent article in SAS magazine, John Knowles from Allianz insurance gives his view on the  challenges  to effectively embrace Big Data in existing business models:

  1. a company culture that struggles to grasp the meaning of analytical strategies,
  2. CIO’s tied up in firefighting rather than thinking forward on how data can be their organisation’s ‘new oil’. He funnily calls them KLTO (Keeping The Lights On)CIO’s .
  3. lack of just-in-time data (the article speaks of real-time data, but I challenge that notion – not all data really needs to flow in real-time through an organisation),

I especially agree with the first two arguments. Dashboards, metrics, segmentations, propensity scores,.. -  no matter how attractive or good - require a deep understanding of the business process in which they are supposed to play a role. Data doesn’t speak for itself. Data doesn’t propose a decision. Data  itself doesn’t bring profit.

Instead, considering the right (amount and type of) data for supporting the right decision at the right time is essential to make any investment in a (Big) Data initiative profitable. Said otherwise, relevant Big Data as well as analytical outcomes from it should be fed back into daily business decisions (do I contact this customer, do we increase our sales target in region x,..).

First the data, then the decision, then the profit.

 

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Tags: data-driven, decision, making

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