big data and leadership

People who work in retail sometimes joke that the manager of a store today is the cashier who didn’t quit yesterday. The ability to stay at a job may be sufficient to become a manager, but being further promoted to a leadership position requires the ability to make the hard decisions. It also requires the ability to communicate the rationale for making those hard decisions.

We think of leaders as visionary when they act on hunches or trust their intuition, especially when a hunch goes against what experts consider the best course of action. We value leaders who can draw on their experience to make forecasts or reform processes. With our romanticized perception of leadership, we tend to forget that hunches, intuition and expertise are ways of processing data. A hunch is often simply a person noticing a pattern that no one else notices. We call it a hunch because the person cannot document or even articulate how or why they notice such a pattern.

Big data gives everyone the ability to notice patterns that no one else notices. What we call big data is advanced software that uses algorithms to detect such patterns. The difference between big data and analytics is that big data programs can sift through multiple banks of data to detect such patterns. Big data makes it possible to sort through vast amounts of data, which would be impossible for one person or even a team to sort through in one lifetime.

So, if a manager needs to make a seemingly impossible forecast, or identify the cause of an intractable problem, he or she can use a program that can sort through records from payroll services, human resources statistics, production records, marketing and promotion results, and inventory records.

 Of course, the ability to detect meaningful patterns must start with a meaningful question. If a manager needs to schedule an event and reduce the start of it from a time frame of a 10 minute window to a one minute window, the software can search through multiple sources of data, in vast amounts, to determine past conditions and average them out more precisely than was possible in the past.

As an example, a phone room manager for a market research firm may need to schedule telephone interviewers on a project by project basis. To compensate for call offs and late arrivals, he overschedules hours by 10 per cent to ensure that each project is completed by deadline. However, doing this is not an efficient use of his time or his employer’s money.

By looking at records from past projects, the manager can learn the times of day, days of the week, and times of the year when people are more likely to answer the phone and participate in a survey. He can also look at records from payroll services to learn when employees are more likely to arrive late or call off a shift. This information allows him to schedule more precisely, saving money and finishing projects before deadline.

Vast amounts of data and the ability to analyze it cannot impart charisma to a manager or increase the level of trust employees feel, but it can give a manager the confidence that comes from being able to make a decision based on accurate information. Big data can provide the documentation necessary to convince others that a change is necessary or to identify the source of a problem. If a leader is someone who takes on the responsibility of making the hard decisions, then having accurate and precise information can help a manager make the hard decisions and know that they are the right decisions.

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