Adding Agility to the Change Management Process
“DevOps speeds up application development, provides for more feedback, and reduces design flaws,” writes TechBeacon. “But those gains come at a price: developers and IT operations personnel now struggle to keep pace with rapidly arriving system alterations.”
A desire to cut loose from the restraints of rigid hierarchy-based processes allows software platform businesses to produce more value faster. Traditional change management procedures, governed by ITIL principles, can significantly slow down their goals of constantly improving and updating products.
The annual DevOps Research & Assessment (DORA) report concluded that, “formal change management processes that require the approval of an external body such as a change advisory board (CAB) or a senior manager for significant changes have a negative impact on software delivery performance.” DORA respondents who had formal checkpoints in the approval process were 2.6 times more likely to be considered low performers.
This situation invites the question: how can IT Operations significantly reduce risks in production and add agility to processes without breaking things?
The answer is to give IT ops teams and CABs access to information that can allow rapid assessment and decision-making. They need self-service business analytics that informs them of both change risks as well as underlying risk factors. This capability can be further complemented through automation of tasks like low-level change approval or change risk remediation.
Removing Formal Gates and Approval “Checkpoints” Without Inviting Risk
ITIL CAB review processes are manually intensive, and they can also use highly subjective assessment techniques. The need for approval for each deployed change dramatically slows down business performance and hinders agility. Furthermore, it introduces multiple opportunities for subjective bias to influence risk assessments.
The challenge of implementing traditional CAB reviews is further complicated by the fact that “design, build, run” now happens continually and independently amongst every feature team. CABs — and change management processes in general — desperately need tools to make decision-making rapid without sacrificing their ability to catch and manage major risks.
A properly configured IT business analytics solution can satisfy these requirements. Not only can data sourced from key systems of record remove the subjectivity of human-guided change risk perception, but it can also automate the delivery of insights from that data.
“When you are able to have fast feedback, high levels of automation, and all the other things that contribute to high DevOps performance, you no longer need that [manual] approval in many, many cases,” observes Forrester’s Charles Betz.
Sourcing data directly from commonly used systems of record negates need for manual metric crunching. It can also lead to the creation of informative KPIs that score risks based on known risk factors. For instance, CABs and change approval teams can look at an expressive KPI, like a change risk score, which uses historical data and multiple metrics to gauge the risk of certain changes. They can then investigate the underlying risk factors or the change or the root causes of risk and react level of predicted risk appropriately.
Getting to the Point of Agile Change Management
A number of things need to happen for CABs and change managers to become more agile. They’ll require an IT business analytics solution with the following capabilities:
- A consolidated view of key information from relevant systems of record
- Dashboards to display analysis of this information in an actionable manner
- AI/ML models to automate the process of discovering risk factors, scoring risks, or indicating need for certain actions
The addition of these capabilities augments CABs, hastens the process of change approval, and adds agility without adding risk.
You can learn more about bringing agile transformation to change management by watching our recent webinar: “Make Innovative IT Change Management Process Smarter and Faster with Artificial Intelligence (AI)”
Top Five Challenges to Change Management in 2020
We are in the midst of a bold new transition in IT operations away from…
How to Make Decisions to Mitigate Change Risk (Part 4)
Once risks in the production environment are identified, an organization must be capable of making…
How IT Operations Can Anticipate Change-Related Risks (Part 3)
Using data generated from key systems of record and analyzed using a System of Intelligence,…