Big data is certainly all the rage. The Wall Street Journal recently ran a piece ondata scientists commanding up to $300,000 per year with very little experience. Clearly the era of embracing big data is here.
However, since the tools and best practices in this area are so novel, it’s important to revisit our assumptions about what big data can do for us – and, perhaps more importantly, what it can’t do. Here are three commonly held yetmistaken assumptions about what big data can do for you and your business.
Big Data Can’t Predict the Future
Big data – and all of its analysis tools, commentary, science experiments and visualizations – can’t tell you what will happen in the future. Why? The data you collect comes entirely from the past. We’ve yet to reach the point at which we can collect data points and values from the future.
We can analyze what happened in the past and try to draw trends between actions and decision points and their consequences, based on the data, and we might use that to guess that under similar circumstances, if a similar decision were made, similar outcomes would occur as a result. But we can’t predict the future.
Many executives and organizations attempt to glean the future out of a mass of data. This is a bad idea, because the future is always changing. You know how financial advisers always use the line, “Past performance does not guarantee future results?” This maxim applies to big data as well.
Instead of trying to predict the future, use big data to optimize and enhance what’s currently true. Look at something that’s happening now and constructively improve upon the outcomes for that current event. Use the data to find the right questions to ask. Don’t try to use big data as a crystal ball.
Big Data Can’t Replace Your Values – or Your Company’s
Big data is a poor substitute for values – those mores and standards by which you live your life and your company endeavors to operate. Your choices on substantive issues may be more crystallized, and it may be easier and clearer to sort out the advantages and disadvantages of various courses of action, but the data itself can’t help you interpret how certain decisions stack up against the standards you set for yourself and for your company.
Data can paint all sorts of pictures, both in the numbers themselves and through the aid of visualization software. Your staff can create many projected scenarios about any given issue, but those results are simply that – a projection. Your job as an executive, and as a CIO making these sorts of tools and staff available within your business, is to actually reconcile that data against your company’s values.
For instance, imagine you’re a car manufacturer. Your big data sources and tools tell you that certain vehicle models have a flaw that may cost a few cents to repair on vehicles yet to be manufactured, but would cost significantly more to repair in vehicles that have already been purchased by customers and are in production use. The data, and thus your data scientists on staff, might recommend fixing the issue on cars still on the assembly line but not bothering to fix the cars already out there in the world, simply because the data might have shown the cost exceeded the likelihood of damages across the board.
(Note that this scenario may sound familiar to you if you have been following theGeneral Motors ignition switch saga. However, this is only a hypothetical example, and further, there is no evidence big data played into the GM recall.)
Say your company has a value statement that quality is job 1 and safety is of paramount importance. Though the data suggests a recall isn’t worth it, you make the call as an executive to start the recall. You’re informed, but you’re not controlled by big data.
Above all, it’s vital to remember that sometimes the right answer appears to be the wrong one when viewed through a different lens. Make sure you use the right lens.