Agile change management processes reduce bottlenecks and speed up software releases, resulting in deploying more beneficial changes and happier customers.
With its emphasis on delivery value faster, agile product management should prioritize fast response times to customer feedback . In spite of this, many organizations continue to rely on cumbersome change management practices which can lead to bottlenecks in release delivery. When legacy practices like manual change review are allowed to impact lead and cycle times, they negatively impact both the product and the customer experience.
Though product managers rarely get involved in efforts like shortening change approval times, the reality is that accelerating change delivery is every bit as important as managing a backlog. Change approval teams, therefore, should reach backward towards product managers to hasten the process to get from user story to deployment, meeting each other in the middle by taking mutual ownership of change approval times.
Accelerating change approvals can be achieved through technology: data analytics and automation. Artificial intelligence and machine learning (AI/ML) analytics can model change risk, allowing teams to only dedicate time to changes that pose genuine risk threats. Automation can grant automatic approval to low-risk changes, especially those that fit a standard change model. This process results in more-frequent releases and happier customers. It also provides the opportunity to immediately begin working on deploying the beneficial changes in the next release.
Change management is a critical point for value delivery
The software delivery pipeline can dramatically slow down while releases wait on change approvals. Yet, many organizations remain cautious with their change approval policy, requiring manual change advisory board (CAB) approval in nearly all instances.
Slowdowns may also occur because change approval represents a handoff from development to operations. When organizations are heavily siloed between development and operations, a queue can form as new releases await deployment approval. In light of this relationship, it’s worth mentioning that slow change approvals can represent more than customers waiting on the next release; they can also indicate a lag in feedback development can use to inform their ongoing work.
The Scrum.org team highlights the detriment this feedback lag causes, and it encourages teams to consider conceptually seeking a short “time to learn” window — meaning quick feedback loops — over that of a short time to market. The difference is subtle, but it will be reflected within cultural practices. Once changes are released, the business can start learning about the effects of those changes based on the feedback loop from customers and users.
Change management teams do have an important role: they are gatekeepers there to ensure releases meet minimum standards for quality, performance, and security — summed up as overall value delivery. Teams can solve the problem of the handoff by incorporating two things:
- Implement process improvements needed to encourage ownership of change review cycle time from both sides of DevOps
- Invest in analytics technology to make risk management quicker and more informative
Agile product management should include change management in its purview
Agile product managers have a lot on their plate already. They should nevertheless still assume ownership of overall cycle time to ensure that needed changes reach the market in a timely manner.
To move beyond the lagging “order taker” role into a leading, proactive role, agile experts suggest looking for process improvement opportunities so that change management and product management can be fluid. Tim Creasey, Prosci’s Chief Innovation Officer, describes effective change management practices, including:
- Approach — The change management approach must align to Agile process phases and must be selective regarding which activities drive value.
- Resources — Change management resourcing needs vary across an Agile development effort and must be ready to pivot based on the employee impact of a given phase.
- Integration with Project Management — The change management and project teams must integrate earlier, with higher levels of communication and collaboration.
Map your processes, and identify places where change management could be improved. Nina Scarnici (PMP, Publicis Seattle) says that procedural matters can tend to overcomplicate processes, creating a bottleneck. “When that happens, the easiest way to make things right is to identify where you are wasting your time, streamline the work process and find opportunities to improve your workflow.”
Aim for smaller batch sizes. DevOpsGroup ran a thought experiment on changing deployment frequency from quarterly to monthly to daily. “The smaller the batch size, the easier it is to test, the easier it is to deploy, and the easier it is to roll it back if it fails — so we’d expect change failure rate to go down, lead time to go down, MTTR to go down, and availability to go up as a result of more frequent deployments and smaller batch sizes.”
Recognize that more-frequent deployments deliver more value in sum than the same changes on a less-frequent cycle. DevOpsGroup noted that “Given each deployment is an opportunity to learn what our customers actually want and need we’d also expect wasted effort to go down. Many teams spend time building features that the customer doesn’t really want and never use (some estimates are as high as 50% or more of delivered features add no value to the customer and hence are waste). By deploying more frequently, in smaller increments, we avoid batching up large chunks of work that ultimately deliver no value.”
Agile product management has a lot of priorities, including the need to incorporate customer feedback in upcoming feature planning, but product management should also hold change delivery times to a high standard. Put another way: improving change management is often low-hanging fruit for the acceleration of value delivery and the improvement of DevOps team continuity overall.
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