Change management and the power of data


Alex Bigland change management, Data, Blog...

These days the art of successful change management is underpinned by data. Businesses that recognise this are the ones that will successfully transform over the next decade and forge ahead of their competitors.

Change management teams can learn from the success that industries like financial services have had from using predictive analytics engines or from investors embracing big data analytics to maximise the performance of their investments.

At present 70% of change management endeavours fail, but imagine the benefits to a company if this statistic was reversed. By harnessing predictive analytics and big data, change management teams could make this a reality and transform the organisations they work within more effectively and quickly, saving both money and time.

A deficit of data

At present, many change management programmes are variations of John Kotter’s eight-step model. Research in 2011 for the Journal of Management Development suggested that whilst the premise is reasonable, there is little data to support it, perhaps because it is so hard to effectively measure motivation and leadership.

Successful change management programmes and projects are often the result of experienced professionals who blend skillsets with practices to help an organisation achieve its targets. But the challenge remains that their efforts are not as easily quantifiable (beyond success) as other industries because without data it’s hard to determine the correlation between change efforts and results.

Approaching change management more scientifically could be the key to showing the cause and effect of transformation projects, using data that can be analysed, learned from and ultimately built on.

Tapping into the employee mindset

Understanding the employee mindset is crucial to successful change management. If employees aren’t on board with a particular transformation, it’s highly unlikely that the initiative will succeed.

Traditionally employee opinion surveys were used to gauge the employee mindset, but the rise of real-time employee opinion tools offers a fast and effective way of finding out what people are thinking. Tools such as IQ polls, focus groups like or smartphone apps all help measure insights and the results can help build a predictive change model.

Change management professionals can use these tools to assess mood and the effectiveness at any stage of a project by asking critical questions such as “are the reasons for change being communicated effectively?”, “are the project goals clear?”, “is the change being well received?”. The team then know quickly what’s working and what needs tweaking and can make the necessary adjustments within days as opposed to the weeks it used to take.

By collating the data, it can be channelled into a predictable model, helping target the actions that will encourage early and fast adoption of new behaviours, practices or processes by employees, not just for that particular project but in other projects and programmes going forward.

Using data to find change talent

It’s not only for the details of the project that data is useful, it is also a valuable tool for hiring the right people into a change team in the first place. Using predictive analytics for hiring staff into a project team could improve the outcome of the project. If each change manager and team member underwent psychometric testing and evaluation before being allocated their roles within a project, the data could be used by change overseers to allocate the individuals best suited to the individual needs of the project. A fully rounded team filled with the right expertise is far more likely to produce the right results.

So, through conscious data collection and analytics investment, change management teams can lay the foundations for successful project delivery as well as strengthening the business.

Whether you’re looking for talent for a change management project or are looking for your next role, speak to a Venquis team member today to explore your opportunities further.