Do You Really Need a Big Data Strategy?

Do You Really Need a Big Data Strategy?

Do You Really Need a Big Data Strategy?

With increasing frequency, CIOs are being asked by their senior management, “What’s our big data strategy?”  But do you really need a big data strategy?

In our view, companies should instead focus on data governance and data management.  If data is a company’s most important asset then a formal data governance program and data management best practices are among the most strategic investments it can make.  The absence of either is why companies are challenged to harvest their existing data resources – no less the torrent of big data that will continue to inundate the enterprise.

Data governance and data management together demonstrate how a firm understands and uses its data assets as well as how those assets are managed over time.  Data governance and data management become more strategic as firms evolve from static, database-centric systems of record that report on historical results toward dynamic, real-time systems of engagement that generate insights faster and inform better decisions on fresher, more accurate data.

Tech-Tonics believes that investments in newer big data technologies should be a puzzle piece of data governance and data management strategies – and budgets.  Get these strategies right and it will be easier to integrate big data into analytics workflows to improve decision outcomes.  Modern systems allow IT to develop the framework that business users can access without having to rely on knowledge of what may be needed.

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A formal data governance program coupled with effective data management represents a better path to improving return on data assets (RDA).  Companies with higher RDAs are more competitive.  They outperform their peer groups in achieving corporate return on investment (ROI) and risk management objectives.  In turn, these factors drive higher market valuations.

Raising RDA is hard, time-consuming and political.  It requires a commitment by all stakeholders – especially senior management.  Successful execution is nothing short of cultural change.  But the payback on becoming a truly data-driven enterprise is compelling because it can yield tangible gains in productivity, end-user satisfaction (both employee and customer) and sustainable competitive advantage.  

Tech-Tonics recommends that companies take a holistic approach to data governance and data management.  A well-executed data governance program with unified data management provides a structure that supports flexible access to consistently accurate, high-quality data and analytics.

The purpose of data governance is to ensure that information accessed by users is consistently valid and accurate to improve performance and reduce risk exposure.  The more users trust the quality of the data they are working with the more reliable and predictable their models and decision outcomes will be.

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There is a direct relationship between data governance and operational performance.  As more companies expand the use of associative search and data visualization tools to a wider user community the value they derive from analytics is proportional to the quality of their data.  Data quality supports data governance by making sure that data assets are reflected correctly within data stores and throughout business processes.

As analytics and decision-making bifurcate throughout the organization, assessing and managing the risks associated with data lurking within the enterprise – and coming from external sources – becomes more complex.  Data governance also provides consistency to data that is strewn across departmental and organization silos.  As users’ appetite for data sources continues to grow, a framework that emphasizes data quality facilitates integration of existing data sources with external ones, including newer big data formats.

While many companies have made substantial infrastructure investments to speed data delivery, bad data at the speed of light is still bad data.

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