Socrates said, “The only true wisdom is in knowing you know nothing.” Another great mind, Ed Morse (in his keynote address at this past year’s Coordinate Metrology Society Conference), said, “Data is only as good as what you can do with it.” If you were so inclined to put these two thoughts together, you could see the current dilemma regarding Big Data.
In the realm of sales, the concerns over Big Data, according to a post by Dominic Tomey, seemingly date back as far as the 1990s. He writes, “I lost count of the amount of times back in the days of being junior salesman that my bosses said to me, ‘You’re only as good as the data you put into your CRM (customer resource management system).’ The thing that amazes me is that the premise of what was being said in the 90s is still an issue today.”
Tomey cites reporting issues stemming from duplication of information, missing information, and poor governance of data input criteria that leave “data at risk from the onset.” According to Tomey, if they are lucky, sales professionals may have the opportunity once or twice a year to—either manually or through a third-party agency—cleanse their data. However, this battle against human error and maintaining good information is due to the lack of understanding and education on data quality tools.
But what about true Big Data, the kind harvested by the boatload, usually with the aid of automation and other technology?
In an article for the Harvard Business Review titled, “Good Data Won’t Guarantee Good Decisions,” authors Shvetank Shah, Andrew Horne, and Jaime Capellá offer analysis of what they term “global businesses’ entrance into a new era of decision making.”
According to the authors: “The ability to gather, store, access, and analyze data has grown exponentially over the past decade, and companies now spend tens of millions of dollars to manage the information streaming in from suppliers and customers. For all the breathless promises about the return on investment in Big Data, however, companies face a challenge. Investments in analytics can be useless, even harmful, unless employees can incorporate that data into complex decision making. Our research offers a succinct warning to managers. At this very moment, there’s an odds-on chance that someone in your organization is making a poor decision on the basis of information that was enormously expensive to collect.”
Why is it a good bet? Because only a small number of employees possess the skills to analyze data, companies spend more time on the technology than the information, reliable information is very difficult to find, and executives and managers are better at managing “talent, capital, and brand” than they are at managing information.
Their conclusion: “Companies that want to make better use of the data they gather should focus on two things: training workers to increase their data literacy and more efficiently incorporate information into decision making, and giving those workers the right tools.”
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Enjoy and thanks for reading!
