Simple enough: If you can’t identify and quantify an ROI from an investment, don’t invest.
That applies buying raw materials, physical machinery and plant, advertising and….big data processing.
Larisa Bedgood writes in Why 96% of Companies Fail With Marketing Data Insights:
At a time in our history when there is more data than ever before, the overwhelming majority of companies have yet to see the full potential of better data insights. PwC and Iron Mountain recently released a survey on how well companies are gaining value from information. The results showed a huge disconnect in the information that is available to companies and the actual insights being derived from it.
According to survey findings:
- Only 4% of businesses can extract full value from the information they hold
- 43% obtain very little benefit from their data
- 23% derive no benefit whatsoever
- 22% don’t apply any type of data analytics to the information they have
The potential of utilizing data can equate intro very big wins and even greater revenue. Take a look at this statistic based on research by McKinsey:
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Unlike most big data vendor literature, Larisa captures the #1 thing you should do before investing in big or small data management:
1. Establish an ROI
Establishing a strong return on investment (ROI) will help get new data projects off the ground. Begin by documenting any problems caused by incorrect data, including missed opportunities, and wasted marketing spend. This doesn’t have to be a time intensive project, but gather as much supporting documentation as possible to justify the investment. (emphasis added)
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An added advantage of establishing an ROI prior to investment is you will have the basis for judging the success of a data management project. Did the additional capabilities of data analysis/management in fact lead to the expected ROI?
To put it another way, a big data project may be “successful” in the sense that it was completed on time, on budget and it performs exactly as specified, but if it isn’t meeting your ROI projections, the project overall is a failure.
From a profit making business perspective, there is no other measure of success or failure than meeting or failing to meet an expected ROI goal.
Everyone else may be using X or Y technology, but if there is no ROI for you, why bother?
You can see my take on the PwC and Iron Mountain at: Avoiding Big Data: More Business Intelligence Than You Would Think.