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Making Big Data Manageable: Four Steps to Implementation

Big data means different things to different people.  At its purest form, for me, it is about enabling the right decisions to solve business challenges by correlating often disparate and complex data to key business levers.  The most successful business leaders are those who understand the levers they hold to improve performance.  Big data mapped to those levers can enhance decision making, enabling real performance improvement.

It starts with an understanding of what problems need to be addressed.   What are the business levers I have available to me to truly transform my operations and performance?  For example, when faced with eliminating tens of millions in operating costs, a COO doesn’t just look at operating budgets and cut discriminately.  COOs look beneath the OPEX and attempt to understand what the cost drivers are, and what steps can be taken to eliminate non-productive costs while maintaining or improving overall customer experience.

Big data mapped to those cost drivers can dramatically enhance the outcomes, especially when organizations are faced with the need for major transformations in how they operate.

Once you’ve determined your business levers, follow a predetermined, yet flexible, implementation roadmap to ensure that leveraging big data provides the visibility needed to make the right decisions. 

Collect

The first step seems simple, but there’s a caveat: Look beyond your immediate data sources and immediate needs when collecting and compiling data. Big data is, by definition, as comprehensive as you can make it. Cross-functional awareness of features and capabilities will make or break the collection stage.  Incorporate external data, augmenting the view created from your internal data sources.

Validate

Raw data should be complete and consistent. Too often, companies will use data that lacks integrity, believing that analysis will gloss over deficiencies. Strong project management is needed in this stage to ensure the accuracy of the data is up to the task. When taking the first step in tackling big data, invest in human capital, not just technology.

This is also a good time to validate processes. Do you have the right scorecards and the right team in place to meet your goals?

Analyze

Examine the end goal before examining the data. A good manager or consultant will be able to provide you with more than “artificial intelligence” – data that has been simply rearranged. It may look impressive in chart or graph form, but it often lacks context.

The ultimate test of data analysis is whether the process can be quickly and easily repeated. If you’re struggling to draw parallels between sets of information or, if the raw data is difficult to obtain, the insights from the analysis stage won’t be consistently actionable or meaningful.

Find Your Golden Thread

Often multiple data sources need to be linked to provide the performance insights needed to manage results. The common link becomes the golden thread – a commonality that, once discovered, links large amounts of data in a manner that allows your management team to accomplish goals they weren’t able to previously.

Finding the golden thread in a sea of data requires a systemic process and considerable data analytics.  It requires a real understanding of the internal data sources and often requires augmenting with external data to provide a complete picture.

Big data isn’t a fix-all, but with a proper implementation roadmap, big data solutions can ultimately provide the visibility to your company’s true business levers, enabling management to drive change that directly impacts your goals and objectives.

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