Data science and change management

For successful data science and successful change management, a company needs to adopt a data science strategy that has been well thought out. This will help in the management of changes that data solutions inflict on an organization.

This is basically a data science challenge and one of the ways of handling this is by using data-driven change management techniques. Some of the ways of putting this into practice are detailed below;

  1. Use of digital engagement tools for change management.

For most companies, the old-fashioned opinion surveys being used have now been replaced with a generation of real-time opinion tools. In this case, you will be able to manage your data and be able to tell more often what your employees think. Moreover, there are simply instances wherein some companies surveys are done weekly with the use of a limited number of questions.

The questions are customized in such a way that managers can get feedback on whether a change is being received well throughout all locations. In addition to this, the effectiveness of delivering messages to employees is improved.

  • Figure this out:

It is important for a company to use a data-driven approach to experiment with different change management strategies in selected departments. Why is this? This is because when there are changes in the organization then you can use the data collected to measure the performance of managers. This gives real-time feedback. Communication and engagement get well received. What’s more?? You get to optimize your set goals in days rather in weeks!

2. Use of social media analytics to find out your investor’s opinion in change management.

Investors are key when it comes to change management. Furthermore, they are likely to comment on changes a company is making while giving potential in their response. This is what a manager should get to look out for. Be keen to look for a tool for social media analytics. A good example is SMAART which can well interpret sentiments.

3.  Taking reference data in change projects.

It is indeed alarming that most organizations do not have a standard set of measurements that are used across different change initiatives. Besides most companies dwell on having data on sales revised or manufacturing efficiency and inventory returns. They show little interest in performance tracking from changes in projects to know which ones have set goals met.

I believe different projects may have some unique features but there are definitely more similarities than differences in various projects. However, it is essential to know that with time the data will definitely grow hence it will be efficient to come up with predictive models that can make it accurate to manage this process.

It is important to be keenly aware of the tools that can be able to create good visualization and deliver good change management for your company. Work towards it. Won’t you?

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