Insights from the Girard School of Business and the School of Science and Engineering

Change is a constant in every aspect of life, including running a business. Perfecting change management is a priority for organizations wanting to keep ahead of competitors. While the discussion typically centers on people and processes, it increasingly involves the use of data analytics to support changes in both. Or, at least, it will. While predictive data systems that focus on change management are still in development, business leaders recognize the need for a data-driven approach to change because of the success they’ve had using data elsewhere.

They also need the right people in the right jobs to oversee the collection and analysis of data. It’s the sort of job that earning a Master of Science in Data Science prepares graduates to take on. The shift to data-driven strategies in change management is a significant change. But are companies ready for it? Many experts think they are not, meaning the need for data scientists is is higher than ever.

Positioning Companies for Change

For companies that want to succeed in the future, now is the time to position themselves for success. But change management is notoriously hard. Data, which offers accurate information unclouded by emotions and free of guesswork, can offer companies the best way forward.

The issue is not in the collection of data – that part is now relatively easy given the advances in technology. Rather, the issue is in knowing what data to collect and then leverage what it reveals in a way that prepares a company for the future. That requires the kind of knowledge in predictive modeling offered through a data science master’s degree program.

In writing about the use of data science in change management, the Harvard Business Review reports that predictive models for change management are “still a ways off.” But HBR offers five “no-regrets steps” companies can make now for the future.

Use digital engagement tools. Real-time employee opinion tools are far more effective than annual employee surveys at determining what changes in an operation are working or not working.

Apply social media analytics. To gauge the sentiment of stakeholders such as customers, channel partners, suppliers and investors, HBR suggests monitoring social media channels where they are far more likely to offer their true opinions on changes your company has made.

Build a base of reference data on change projects. Much in the way companies collect data on even the smallest detail of operations, sales, inventory, etc., they can also collect data on projects involved with change. This may include data on the team members, the time it took to implement, the tactics used on the project, and the population engaged in the change. This can then be used to develop baselines for measuring the success of future projects.

Select change managers using data. Again, data can be collected and analyzed to determine which employees are the most effective at change. This includes matching change management jobs with people who have the right skill set as well as a leadership personality.

Build a Dashboard. Leadership teams within organizations can develop a dashboard that reflects their priorities, competitive position, and future plans. Dashboards provide insight into specific transformation investments. The data that makes up these indicators is available but the organization may not be collecting it.

What You’ll Learn in a Data Science Program

Clearly, someone is needed to manage the processes involved in the collection, analysis, and delivery of data involved in change management.  Graduates from a master’s program in data science learn the skills needed to take on these challenges. For example, the Merrimack College program focuses on teaching graduate students data science skills along with the “the business acumen needed to translate data sets into insights stakeholders can use to make business decisions.”

To understand the current needs of people in the business world, Merrimack has an industry advisory board that offers input on curriculum design. Students learn skills in machine learning, predictive modeling, data exploration, and data visualization, among many other areas.

Change management provides yet another career path for data scientists. Earning an online master’s degree in data science sets up graduates to take on leadership roles in this emerging, vital area of business.