In this fast paced, ever changing world, change has become the only constant. While businesses adapt to rapidly changing stakeholder needs and behavior, it is clear that new tools and techniques are needed to manage stakeholders and stay ahead of competition. One of the key drivers which has emerged with the Internet revolution is data. While areas like supply chain, marketing, consumer behavior have been quick to adapt and capitalize on the huge volumes of data being generated every second, one area which is behind the curve is organizational change management. In this blog, we will focus on some key tools and techniques which can be used to support change management initiatives in a scientific manner.
Use Digital Tools
Unlike the previous generations, millennials have grown up using digital tools and are well versed in this mode of communication. These are a far-cry from the age old techniques of annual opinion surveys and performance feedbacks. These tools are near real-time and provide instant data on the pulse of employees and what is going on in their minds. They also generate large volumes of data, which, if mined successfully, can determine the success (or failure) of any transformation project. A simple mobile app, gamification of Intranet sites, etc. are some simple and effective tools to generate and support data driven decisions, predictive models and change initiatives.
Social Media and Stakeholder Sentiment
With the increasing use of social media across all spheres of our professional and personal lives, it is clear that we are spending more time sharing our thoughts and ideas online than in person-to-person interactions. It is but logical for change management initiatives to tap into this pool of data to assess stakeholder sentiment and take corrective actions based on predictive analysis and trends. With the advancements in linguistic analysis of texts, we are now able to get indicators about stakeholder sentiment based on word choices, usage of articles and pronouns, etc. These tools can be further applied to anonymized company emails and chats to derive opinions and feedback about change readiness and the impact of organizational changes.
Building a project level database of change initiatives
Companies engage and implement in big and small change projects almost continuously. It is a known and adopted best practice of “lessons learned” as part of project closure activities. These present opportunities to classify and capture data from each and every project in a systematic manner about the teams involved, end user population involved, duration it took to implement the change, innovative and creative ideas used, etc. This project-related data on change management may not give immediate results but will pay rich dividends in the long run as the data volume grows and the company gets better at using this data in predictive models.
In conclusion, the end state of any change management initiative should be to move from a project specific phase / task to a business outcome driven activity. Ironically, to embark on this transformation journey, change management science and practitioners will need to re-engineer themselves to incorporate data in their DNA!!