You probably know that Mashey is a different kind of data analytics company: one that is focused on people. You can see that most clearly in our approach to change.
Change in a data analytics project can happen one of two ways: intentionally with clearly defined outcomes, or accidentally. When change happens accidentally, it's like Forrest Gump: you never know what you're going to get.
When data analytics is a key part of running your business, the change supporting new tools and processes can be as important as the tools and processes themselves. It's important to know how much change your new capabilities imply, how many people will be impacted by the initiative, and what sponsors you need to make the initiative wildly successful. The best way to make sure you have the best possible alignment among these factors is to prepare for change from the beginning.
In determining how much change the data analytics project requires, we begin with a change characteristics assessment. This assessment determines how much attention we need to devote to the change aspects of the initiative particularly key work processes. Small initiatives may not require much change at all. Large initiatives almost certainly require larger amounts of change. Understanding the scope of change implied by new tools allows you to better design for project success.
Once we have established how much change the initiative requires, we turn to the organizational attributes profile. This simple sketch of the organization gives a view of who is affected by the change and how much they will support or inhibit the new processes. This step is about winning hearts and minds and heading off points of resistance.
Based on the change characteristics profile and the organizational attributes profile, we then identify the change management team structure. Sometimes this is one person, and sometimes it is a larger group, depending on the size of the organization, the scope of the change, and the number of people affected. This role establishes who will be accountable for helping the organization to grow and develop.
With these components in place, we turn our attention to the most important aspect of change: sponsorship. Executive sponsorship is consistently rated as the one factor most closely associated with the success or failure of projects and initiatives. Our approach focuses on who will sponsor the project, what support they need, and a specific plan for enabling the sponsor(s) to be as persuasive and influential as possible on behalf of the change.
Finally, all these elements roll up into one change management strategy. This is a comprehensive view that shows the desired outcome, the actions we will take to achieve that outcome, and the benefits the organization will receive as a result. The change management strategy brings together change characteristics, organizational attributes, the change management team, and the role of the sponsor. All of these elements work in harmony to engineer the success of your new data analytics capabilities.
The first step in any successful data analytics initiative is to understand how people will use these new capabilities. For those initiatives that have significant impact on the organization, a change management strategy is a plan for success.