Let’s discuss why data is important, and what a data-driven organization is. First and foremost, a data-driven organization is one that understands the importance of data. It possesses a culture of using data to make all business decisions. Note the word all. In a datadriven organization, no one comes to a meeting armed only with hunches or intuition. The person with the superior title or largest salary doesn’t win the discussion. Facts do. Numbers. Quantitative analyses. Stuff backed up by data.
Why become a data-driven company? Because it pays off. The MIT Center for Digital Business asked 330 companies about their data analytics and business decision-making processes. It found that the more companies characterized themselves as data-driven, the betterthey performed on objective measures of financial and operational success. Specifically, companies in the top third of their industries when it came to making data-driven decisions were, on average, five percent more productive and six percent more profitable than their competitors. This performance difference remained even after accounting for labor, capital, purchased services, and traditional IT investments. It was also statistically significant and reflected in increased stock market prices that could be objectively measured.
Another survey, by The Economist Intelligence Unit, showed a clear connection between how a company uses data, and its financial success. Only 11 percent of companies said that their organization makes “substantially” better use of data than their peers. Yet more than a third of this group fell into the category of “top performing companies.” The reverse also indicates the relationship between data and financial success. Of the 17 percent of companies that said they “lagged” their peers in taking advantage of data, not one was a top-performing business.
But how do you become a data-driven company? According to a Harvard Business Review article written by McKinsey executives, being a data-driven company requires simultaneously undertaking three interdependent initiatives:
Identify, combine, and manage multiple sources of data
You might already have all the data you need. Or you might need to be creative to find other sources for it. Either way, you need to eliminate silos of data while constantly seeking out new sources to inform your decision-making. And it’s critical to remember that when mining data for insights, demanding data from different and independent sources leads to much better decisions. Today, both the sources and the amount of data you can collect has increased by orders of magnitude. It’s a connected world, given all the transactions, interactions, and, increasingly, sensors that are generating data. And the fact is, if you combine multiple independent sources, you get better insight. The companies that do this are in much better shape, financially and operationally.
Build advanced analytics models for predicting and optimizing outcomes
The most effective approach is to identify a business opportunity and determine how the model can achieve it. In other words, you don’t start with the data—at least at first—but with a problem.
Transform the organization and culture of the company so that data actually produces better business decisions
Many big data initiatives fail because they aren’t in sync with a company’s day-to-day processes and decision-making habits. Data professionals must understand what decisions their business users make, and give users the tools they need to make those decisions.