If you’ve never watched the dystopian 90s film Gattaca, go put it on your watch list. If you have, forgive my quick (inadequate) summary. The plot surrounds Vincent Freeman, a young man whose life is predetermined at birth due to an analysis of his genetic makeup to be “inadequate.” As the plot unravels, we see Vincent take ownership of his future as defies the societal determinism placed upon him. While the film is very philosophical in nature, it gives us picture of a world relying completely on prediction, instead of simply asking the people what they are capable of doing and then letting them determine the outcomes.
Image courtesy of Leon Fishman via Flickr
The Predictive vs. Human Data Problem
Businesses are starting to evaluate the use of data innovations for insight discovery, but what isn’t being discussed enough is what form of data to use:predictive or human data.
As we currently know it, predictive analytics is “an area of data mining that deals with extracting information from data and using it to predict trends and behavior patterns.” While Gattaca is obviously not a perfect example, businesses are, in a sense, currently trying to measure potential via predictive analytics. Essentially, analytics gurus gather information from a variety of sources in order to make predictions about the future. Businesses already use predictive analytics for movie recommendations, traffic management, dynamic ticket pricing, as well as predicting whether or not a employee canidate will meet expectations. Yet it’s not a crystal ball. Forbes noted that “predictive analytics can only tell a business what could happen in the future, not what will happen.”
As an industry, predictive analytics is estimated to be worth more than $32 billion by 2017. Gartner’s study in 2013 notes that 64 percent of organizations were investing or planning to invest in related big data technology. On top of that, as of July 1 of this year, the average predictive analytics salary has spiked to $112k. As the industry expands, that most likely will only continue to increase.
Graph accessed via Indeed
However, no matter how lucrative of a position it may be for the analyst, companies need to fork over a large amount of capital in order to add the analyst to the team or pay for a vendor. And while some may believe the benefits may be worth the cost, it doesn’t make sense for some business problems which can be tackled in a more streamlined, economical fashion.
On the other hand of the spectrum, we have the concept of leveraging “human data.” In essence, human data is the collective wisdom of an organization’s people, customers, and stakeholders. This sort of data is collected by realizing that everyone has a voice, and one of the best ways to discover and implement solutions to business problems is through simply asking the right people the right questions.
The funny part about using predictive analytics is that deciding certain numbers mean a certain thing is like complex juju in comparison simply asking the right people the right questions.
Using human data means business questions can be solved quickly and internally through asking questions such as:How fair do you believe the compensation program to be? What will our top products be in one, three, and five years? What skills and experience should we include on the job description? How do our customers respond to our sales team? What are team strengths that we’re not taking advantage of? Where do most bottlenecks occur within the product management team?
Instead of constantly trying to creative algorithms and collect data to predict what your company should do, simply talk to the people directly facing the problem. They often have a better understanding of the situation than what numbers could predict.
Is predictive analytics a bad thing? No, not at all. Many companies, such as Netflix and Redbox, leverage it effectively within their industries. But it can become a bad thing if we allow it to drown out the voices of the people. In many instances, leveraging human data is not only less costly but also more effective than the alternative. Like in Gattaca, people are the ultimate determinants of the future. So while predictive analytics can be a useful tool, we should never discount the powerful tool which creates our businesses and society:the people.
Before you wrap yourself around the axle of predictive, make sure you’re not missing the often better, richer insight from your own people. Use predictive analytics and big data on complex things no group of humans could know. Tap the human data of your own organization for confidence on the majority of decisions that matter.