I had a discussion recently with someone who, for three decades, had been performing a statistical function at a large manufacturing company. He couldn’t understand why, in spite of excellent job performance reviews, his company had furloughed him indefinitely.
This person had excellent skills and was very good at data mining, analyzing data, and producing clear assumptions from this data. From his results his company had benefited enormously over the years so he was staggered by the news.
He asked, “Why did this happen to me?!” but the answer was relatively simple. He had failed to notice what was going on around him at his workplace and across the industry with no inclination to transform from statistician to consultant/leader. Even though many statisticians, especially with advanced degrees, are doing well, many have had to transform their roles so they become more flexible.
Bottom line, if you’re not changing with the times or the technology you’re likely becoming stagnant and no longer providing the value companies are expecting.
Statisticians, even though they’ve been around for more than half a century, are becoming an endangered species. At the onset of the statistician role there was essentially no computers, internet, websites, and no commercial statistical software available.
Statisticians focused on data analysis because there was no infrastructure in place for others to perform these tasks. Data analysis was considered a separate job function, removed from the process that created the data. Statisticians simply provided information extracted from the data source to others, such as business leaders, quality engineers, manufacturing engineers, and social scientists, who used the results to guide their decisions.
Over the last few years, a series of sweeping changes are rendering the traditional role of the statistician generally out-of-date. Many companies have statistical software loaded and available on the computers of employees.
In academia, statistics are part of most business, engineering, economics, and social science curricula. About a million U.S. college students will take a general introductory statistics course. This figure generally excludes the students targeted for engineering, business, and other disciplines.
Additionally, the private sector has been providing mass statistical training through programs such as Six Sigma. Focused functions like statisticians have been fading due to the advent of computers, internet, software and employee training where most anyone can analyze their own data to resolve issues.
As the demand for specialized data analysis to support decision-making erodes, statisticians must, like other quality professionals, adapt by expanding their role from data analyzers to consultants and eventually to a leadership role.
In the statistician’s traditional role, they essentially did data mining, performed analysis, and produced a report with assumptions. The more enlightened statisticians also designed experiments, taught statistical tools and consulted with others on their projects. However, in either case, especially with the earlier role, statisticians were seen to have narrow flexibility, expertise, and little accountability—so management generally considered them expendable, especially in an economic downturn.
In a new leadership role, statisticians must also determine appropriate tool sets for organizations, design training systems, work more closely with managers as advisors, volunteer for other roles to add to their skill set, lead cross-functional teams, develop a broad expertise, and take on greater accountability.
As an example, many companies have been transformed as a result of their commitment to aggressive ASQ Certified Quality/Reliability Engineer programs or to Six Sigma initiatives. Statistical tools are no longer the exclusive property of statisticians since virtually everyone has access to and uses them.
Statistical thinking has surpassed statistical methods in importance. It’s more important to know how to apply statistics to attack unstructured problems than to know how to perform a regression analysis or to design an experiment. Most companies still need statisticians, but not just to analyze data, because many can now do that mostly by and for themselves.
In this enlightened age, statisticians and non-statisticians realize tools don’t make improvements, leaders do. To become leaders, statisticians must first understand the basic change that has taken place in the way work is done and grasp how that change demands a clear understanding of the difference between managing work and leading people. They must understand what leaders do, and they must take up the task of learning how to do it themselves. They must be committed to the transformation or be left wondering “what did I do wrong?”