How do you evaluate different release management methodologies?

“Deliver/release at a speed that the market is ready to accept”. Anything beyond that has low or even negative ROI. Product, marketing, sales, support functions have a big stake in nailing down the release cadence. Organizational strategy too influences this decision. Technology supports the above decision with adequate automation and practices. I have had experience of reaching continuous delivery maturity and then settling down for lower release frequencies for business reasons. Focus on holistic optimization to avoid this trap.

There are a series of questions I ask when figuring out releases. 1. Is this required by law? If yes, what's the deadline, and repercussions if not on time. 2. Is this required by the company? If, yes - same deadline & repercussions question applies. 3. List all dependencies (by Story since I work in Scrum). 4. From remaining items, rank them from hardest to easiest, AND most important to least important. 5. Align work based on 1-4, with legal requirements being first, then business mandates, then most important & hardest to easiest, down to the least important & fastest. 6. Each Sprint, if everything from the top tier is hard, pull in 1-2 super fast items for some "quick wins" (it helps morale from my experience).

Frequency and scope are going to follow the velocity of the teams doing the work. If the teams can create deployable changes every 2 weeks, you should. However, there are always going to be times when you have to push outside of your schedule. What is sustainable and what does the business need?

Release frequency and scope are vital considerations in evaluating release management methodologies. Organizations need to assess how often software changes are required and the size/complexity of these changes. For frequent releases, methodologies like Continuous Delivery or DevOps are suitable, while Waterfall or ITIL may be preferable for less frequent, larger releases. Methodologies should also be assessed based on their ability to manage different release scopes effectively, considering factors like team collaboration and interdependencies.

Evaluating release management methodologies involves assessing various factors to find the best fit for your organization. Consider the complexity of your projects, choosing Agile or DevOps for complex tasks and Waterfall for simpler ones. Match the methodology to your release frequency needs—continuous delivery for frequent updates or traditional methods for periodic releases. Ensure it supports team structure, manages risk, and integrates quality assurance. Evaluate its capacity to handle customer feedback, its tooling and automation needs, and how well it scales with growth. Also, ensure it meets compliance requirements and aligns with your organization’s culture and values.

The release process has to, above all, be reusable and standardized. Even for agile and adaptive processess, you need a stable baseline from which to work. The details can and will change.

I agree with Jason. It is definitely a challenge to maintain standards while supporting Agile autonomy. Sometimes I feel like I have to sell the standards speech hard but use the old WIIFM trick. Any others that work well if getting head strong teams to agree on a standard practice?

When evaluating release process and workflow, consider planning, scheduling, approving, and executing releases. Assess the responsibilities of release managers, teams, and stakeholders. Evaluate tools supporting the process and communication with other teams. Address issue handling and feedback mechanisms. For standardized processes, ITIL or PRINCE2 are suitable, while Scrum or Kanban offer agile and adaptive approaches.

From an audit perspective, it's always good to have Unit & Functional testing done by the person who coded it. QA/regression testing should be done by someone else, as should code reviews. UAT should be done by a business partner and they should have final sign off. Once it's live, production testing should be done. If any issues are found, then discussions have to happen. There should ideally be a window for the release, in case any quick fixes are needed, but code that has been tested 4 times before going live shouldn't have many issues.

When evaluating release quality and performance, focus on ensuring releases meet customer standards. Measure impacts and verify releases pre- and post-deployment. Test and debug across environments and mitigate risks effectively. For quality assurance and testing emphasis, consider methodologies like Waterfall or V-model. For continuous improvement, DevOps or Lean methodologies are preferred.

While there are many frameworks and best practices out there, the choice of a release management methodology should be a reflection of what works best for the unique dynamics of the team and organization. It's about finding the balance between the release process and the organization's culture that supports it.

While Agile,Scrum,Lean & DevOps are great methadologies that promote release management best practices, one should consider a more pragmatic approach that aligns with the organizations' GTM goals, tech & resource capabilities supported by one or many of the above methadologies (whichever suits the organizational structure) to foster a culture of collaboration & empowerment.

I just use the Agile mindset. My team is fully empowered to control releases, and I lead the pushback if others disagree. Our Product Owner is really good about supporting us though, so it's hardly ever a fight, just a push.

For me this is the most important. A mindset of true collaboration and this culture on a team is what will get you through. Whether the release has been in the making for 2 weeks or 2 years, a culture and attitude of working together to form solutions to the challenges, constraints and mitigate risks will be the make or break of a release.

When assessing release culture and mindset, prioritize alignment with organizational vision. Foster collaboration, innovation, and learning among teams and stakeholders. Empower teams to make decisions and take ownership. Adapt to change and uncertainty effectively. For stability, consistency, and compliance, ITIL or COBIT are suitable. For agility, experimentation, and value focus, consider DevOps or Lean methodologies.

Knowing what a successful release looks like for the business or product owners is also something I consider. For example of speed to market is most important, then this can change how you cut up the work that will go into the pipeline for the team, how frequently you need to release/launch and so much more. Knowing what defines a release success is critical and helps shape so many aspects.

If you teach your team to behave as a solid unit, almost everything else happens organically. I'm usually able to assess a tean for a Sprint, and give a timeline for their growth. It's always a gap (2-3 years for example), but I have yet to be wrong. Approach everything with the mindset that whoever you're working with is a good person, who wants to succeed, and you'll reap the rewards.

In addition to prior considerations, scalability and adaptability are crucial. Methodologies must scale with organizational growth and adapt to evolving market demands. Cultural fit is vital; align methodologies with organizational values and working styles for successful implementation. Continuously evaluate and optimize methodologies to ensure alignment with organizational goals, soliciting stakeholder feedback for ongoing improvement.

I think first we need to assess how frequently your team aims to release software updates. Some methodologies, like continuous delivery or continuous deployment, focus on frequent and incremental releases, while others may follow a more traditional release schedule. More importantly assess your infrastructure and technology stack. Some release management methodologies, like DevOps, are closely aligned with specific technologies and infrastructure practices, such as containerization and automation Assess budget and resource constraints. Some methodologies may require significant upfront investment in tooling and training, while others may be more cost-effective but potentially less feature-rich.