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Proactive Change Management

This post is from the Numerify blog and has not been updated since the original publish date.

Last Updated Apr 14, 2015 — AI-Powered Analytics expert

Proactive Change Management

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As promised in my first post, I present my first best-practice article. I started with Change Management process for my first article for the following reasons:

  • It's one of the most important yet least discussed IT processes
  • It has a direct impact on customer satisfaction and the relationship between IT and Business

The most concerning fact for today's IT Managers is value creation and sustenance by keeping up with changing business needs and yet ensuring service & process efficiency. Just meeting SLAs no longer delights customers - business users now look for value against the Total Cost of Ownership. It really is a challenging task for IT managers to welcome the frequent requests for change, and at the same time ensure uninterrupted service operation. A robust Change Management process becomes one of the key enablers in this regard, and the ITIL framework provides guidance here. However, implementing the defined process effectively is a challenging job, and Change Managers ought to have a proactive approach for this. They need to balance demand and resource allocation and run change operation efficiently enough to prevent any unwanted interruption to the business. What Does It Mean to Be Proactive in Managing Changes?

  1. Monitor and measure Change performance on a continuous basis
  2. Identify Change patterns
  3. Improve the Process to speed throughput while maintaining a high success rate
  4. Model Changes based on frequency and implementation time
  5. Assign resources per skill requirements while training junior staff

Adopting a simple 3 step methodology, as shown in the diagram below, helps manage changes proactively while increasing throughput.

Change-Process-Sangita

 

Analytics play an important role in enabling efficient implementation of the best practice mentioned above. The key analyses below will help achieve success – 1. Overrun Count by Assignment Group and Category > Identify Constraints Trend analysis of implementation overrun count by category and assignment group identifies the groups and categories causing most overruns, and allows drill-down analysis to identify the causes of the constraints. 2. Queue Length by Change Type vs Implementer's Skill level > Manage Constraints Once the change type and frequency pattern are known and standard changes are separately handled by a specific procedure, it becomes important to assign the right resources for the change type. Knowing the queue length of assignees by change type and comparing this with their experience level allows planning for resource augmentation. 3. Before & After Analysis of Change Volume & Fulfillment > Realize the Outcome An analysis on the process performance trend before and after implementing the best practice reveals the benefit. There should be a declining trend in the turnaround time of the changes, which are standardized for categories of changes where a resource augmentation has been carried out.

change-mgmt-best-practice

[Image credit: Pixabay.]

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