Turning Big Data From A Liability To An Asset – Point 4: Creating Repeatable and Measurable Impact

Richard Sharpe Analytics & Big Data

Turning Big Data From A Liability To An Asset – Point 4: Creating Repeatable and Measurable Impact

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This posting is the final in a series focused on turning Big Data from a liability to an asset. Earlier in the series, I have discussed the importance of gaining Organizational ConsensusTaking An Enterprise Wide Approach and the need to have effective Data Governance in addressing effective ways to get value from your Big Data initiative.   I hope these areas of focus have been helpful.  Today, we will focus on Creating Repeatable and Measurable Impact.

To effectively tackle Big Data, the strategy must be intentional with regard to the business need that the effort will support.  All too often I hear someone suggest that the way to address Big Data is to hire a few very smart data scientist, put them in a room with access to enormous amounts of data and see what they can discover.  I totally disagree with this approach.  Sure, they may find interesting business patterns or correlations but deriving financial value from the effort may be difficult.  Instead, a far better strategy is to focus your Big Data initiative on a specific business strategy(s) where the insights gained from Big Data can be used to make actionable decisions that can be tracked with regard to a measurable improvement in the business meeting its objectives.

Tackling Big Data requires the investment of time and resources.  Like any business investment, the initial justification for tackling Big Data needs to be financially justified, but getting value from Big Data in an intentional way is not a one-time event.  It needs to continue to provide value that can be measured in meaningful ways to the organization.  Without that, it is purely a waste in time.

So the question is how.  Measuring value can be a tricky task but it cannot be ignored and pushed out to be addressed “after the fact”.  Like any measurement, the first step is to verify you have a Baseline “value” for performance that should be defined and cross functionally agreed upon. It is also important that the way you calculate the measurement has been scrutinized and validated, so that it will not be questioned later by the “Doubting Thomas” members of your organization.  All of this should be done prior to taking action that is directly linked to the insights you gained from your Big Data initiative.  Finally, it is key that the ongoing use of the measurement of value is consistently applied each time it is used.

These are all standard value measurement considerations but they are just as important for sustaining your Big Data initiative as they are for any other business investment.

We would appreciate hearing your thoughts and comments.  All the best, Richard

Richard Sharpe

Richard Sharpe is CEO of Competitive Insights, LLC (CI), a founding officer of the American Logistics Aid Network(ALAN) and designated by DC Velocityas a Rainmaker in the industry. For the last 25 years, Richard has been passionate about driving business value through the adoption of process and technology innovations. His current focus is to support CI’s mission to enable companies to gain maximum value through specific, precise and actionable insights across the organization for smarter growth. CI delivers Enterprise Profit Insights (EPI) solutions that enable cross-functional users to increase and protect profitability. Prior to his current role, Richard was President of CAPS Logistics, the forerunner of supply chain optimization. Richard is a frequent speaker at national conferences and leading academic institutions. His current focus is to challenge executives to improve their company’s competitive position by turning enterprise wide data from a liability to an asset through the use of applied business analytics.