Business intelligence and data analytics have become common tools in many companies. Executives use the uncovered information relationships and insights to fuel decision making. That includes such questions as where to locate a warehouse, what SKUs are most popular in given geographic region, or what profiles of job candidates correlate with the best long-term employee performance.
However, such uses of BI and data analytics include an inherent limitation. Management starts with a set of questions and then looks at data to find potential answers. That is a perfectly valid use. But there are other ways to use the technologies, like using analytics to uncover new insights.
As Jeff Frankel, vice president of business development and marketing at content management software company docSTAR, put it, start with what you think you know about the company. Identify issues that you currently find important and then train a data lens on them.
But that is a start. Two fundamental steps in addressing any potential business problem is first to avoid considering questions with pre-determined answers and then to stop assuming that you already know the important questions.
Asking a question with an answer in mind blinds you to potential better answers, or even to better understanding the question at hand. In the 1990s, for example, many manufacturing companies focused on outsourcing factory operations to other countries. They assumed that lower wages and less demanding safety and environmental regulations would decrease their costs of doing business and improve their competitiveness, or at least keep them at a par with rivals.
However, companies at the time often failed to take into account the cost of transportation, the additional inventory expense (because of the two-month sea journey, they added 60 days of inventory holding costs in the product that hadn’t arrived), the difficulty and expense in returning defective product, challenges in communications, and a loss of flexibility in quickly reacting to customer demand. It may be that outsourcing manufacturing made sense in some limited reckoning, but chances are good that companies lost at least as much as they gained, and possibly more.
Leaders often go astray, taking their companies with them, when they ask the wrong questions. Those are typically the ones they assume they should ask. In the case of outsourced manufacturing, the question was how to make the cost of good cheaper to be more competitive and raise margins.
Instead, the right question might have been how to lower the cost of getting the right high-quality products to the right people within time frames to satisfy both customer demand at the moment and changing market conditions. The question is far more complex, but lends itself to a more complex consideration, opening the door to the insights that BI and data analysis can provide.
Notice the trend now for manufacturers to begin to bring factory work back to the U.S. The total landed costs for products made in China have become too high. But then, so have the prices of bad PR and the inability to react quickly to customer needs.
As you use BI and analysis, try to move beyond looking at the preformed questions. Instead, find the insights that help lead to new ways of thinking about the business.
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