Want To Get Ahead Of The Competition? Put Big Data Analytics At The Heart Of Your Corporate Strategy

Jessops (photographic retailing), JJB Sports (British Sports retailer), Comet Group (Electrical retail chain), Habitat (retailer of household furniture) and Borders (international book and music retailer) have all recently entered into administration. Perhaps the one commonality is that they failed to remain tuned to their environment and changing customer requirements, so simply couldnt survive in their current form. Some subsequently have been rescued in full or part by realigning the business model to meet customer needs. Mission critical refers to any factor of a system (equipment, process, procedure, software) whose failure will result in the failure of business operations. Software designed to analyze big data insights from structured and unstructured data is not yet defined as mission critical, like say Enterprise Resource Planning (ERP) as its failure would not stall business operations. It is however arguably more critical than that as not acting on market insights and intent from competitors, customers, partners and suppliers can result in failure of the entire system. Large-scale data gathering and analytics are quickly becoming critical in competitive differentiation. The facts speak for themselves – an estimated 2.5 zettabytes of data were generated in 2012 alone (Oracle, 2012) and trends indicate that the volume of business data will grow significantly every year. Organizations who have access to key data, draw insights from it and translate it into action financially outperform those that dont according to a recent IBM study. It would perhaps be fair to say that organizations have not yet fully embraced the true potential value of big data. Even the most sophisticated global organizations have barely scratched the surface of utilising insights from big data to secure competitive advantage and turn data into a strategic company asset. My view is that a companys data strategy needs to be moved from the periphery to the center of how business strategy is designed and implemented. For corporate strategy this changes how it is both constructed and implemented as the following table illustrates: Figure 1 Corporate strategy changes with big data

*Actionable, statistically supported insights from data that help drive competitive advantage.  By 2014, 30% of analytic applications will use proactive, predictive and forecasting capabilities Gartner Forecast 2011.  An organizations biggest challenge is creating a plan for how they can utilize big data to secure competitive advantage.  The role of corporate strategy therefore becomes to:

1. Establish what data is needed to formulate a company wide strategy considering customers, market trends, competitors, suppliers and partners.
2. Determine with business stakeholders what data is available, how to access it and plan to address gaps.
3. Determine investment priorities with business to prioritize which data insights will drive value first.
4. Work out how to extract, prioritize and analyze, report and action data, working with the CIO office to determine the best models and tools, balancing cost, speed and adoption.
5. Determine how the data will be used to drive company wide decisions and actions.
6. Agree the frequency of insights to maintain a competitive edge.
7. Facilitate a process for all business functions to map out what is required, when and how often and what respective roles are.
8. Recommend changes to the organizations business model for data to become an enabler will transform how each function operates independently and how they interact together.
9. Establish a process for ongoing review and refinement and plan for scale up.

Having big data at the heart of how corporate strategy is formulated and executed is mission critical in staying in tune with environment in which companies are operating and ultimately their survival. It is a big undertaking but organizations have to start small and somewhere and the best place is figuring out what they need to achieve from their data, aligned to investment priorities and then working on moving from insight to action.

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