The Pace of Change: Speeding up Success or Failure for Change Management

The Pace of Change: Speeding up Success or Failure for Change Management

Speeding up Success or Failure for Change Management

Making change management more efficient is a difficult objective to accomplish, but through Talent Sphere Mapping, using organizational network analysis it is possible to make it so. Efficiency in affecting change can be a strategic driver for growth from the perspective of increasing success rates of change management projects, and thereby making change management more efficient, sounder, and more strategic.

For example, if we are able to detect, through the use of an organizational map, the focal points of communication and credibility within a clique, then we can use that to our advantage by using the natural cohesiveness of a tight-knit group to reduce the amount of intensive communication that organizational leadership must generally pursue, and we can tailor communication methods to the intended recipient-group of that communication. We would be reducing the time and resources required to successfully communicate and implement a given project, while increasing the potency and efficiency of communication tactics. This method can free up valuable time, resources, and break the cycle of failed change management communications plaguing the field, while increasing the organization’s natural susceptibility for change. One practical method of going this would be to first get the buy-in of the leaders of the cliques (top influencers) and in turn ensure the buy-in of the connected actors that they communicate with regularly.

One other method of ensuring the increased success rate of change projects is to change the speed at which buy-in is adopted by the employees of the organization. Organizational network analysis allows us to measure the shortest path in the organization from one node to another. It also allows us to use an averaging statistic named “cohesion” which gives us an overall look at the relative strength and numbers of connections in cliques. This cohesion statistic gives us insight into how fast opposition or support to a particular change initiative can move through an organization.

A strong culture in an organization could be descriptive of high a cohesion measure. To elaborate further, we can equate a culture as a river stream that carries within it sediments and material from one part of the river to another. High cohesion could mean that change would be adopted or defeated faster, but in either case they would be defeated or adopted with a reduced amount of time and effort invested by the change leaders, allowing them to either complete their change goals quickly and successfully, or move on to beginning a new series of activities and strategies after deeming the previous attempt a failure.

In the long term, if we assume that we can effectively move success or failure faster in change management then we can accomplish more in less time, and this frees up more time per time period (year, month, and week) to attempt more projects and results in more attempts at getting the change adopted.

To illustrate, let us assume that change projects’ success at ABC company is currently at 40%, and through efforts of cohesion increases we were able to decrease the time needed to establish a successful project or judge a project as a failure by 20%, and during one specific time period (say a year) the human resources team attempts 100 change projects in total. Then, through this increased cohesion they would be able to attempt 120 projects per year, yielding 48 successful projects instead of the previous 40, with the same resources as before. If new, more effective methods were established (after the first failure of the project), and the additional 8 projects were actually repeats of previously failed projects, then we have effectively increased the original success rate of change to 48%. This is a considerable increase, especially for large organizations.

Such an example exists in one company which had a 100 person network in one particular division and through connecting only 12 of the most connected individuals with subject matter experts that were formerly unconnected and on the periphery achieved a 25% increase in cohesion. Clearly, the return on investment in this scenario is substantial.

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