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ALM is dead.
Okay, maybe not dead, dead...but it’s no longer able to stand on its own as the most evolved software practice in an organization. And honestly, with the advent of Agile methodologies and DevOps practices in recent years, it hasn’t been able to for a while.
Application lifecycle management has been a cornerstone of software development for the last decade or so. And for good reason - its introduction and adoption were critical in getting people to think beyond snippets of code to the broader end-to-end development, maintenance, and governance stages of an application’s life as a whole. However, in traditional ALM, each phase of the lifecycle is discrete - think: waterfall.
But, digital transformation isn’t about apps, and it’s most definitely not about siloed phases of development (especially when Agile frameworks are applied). Digital transformation is about continually optimizing value delivery to the customer.
DevOps has enabled digital transformation at a higher rate for many organizations. DevOps can be described as a set of practices that combines software development and IT operations, with central goals of shortening the development lifecycle and promoting continuous software delivery with high quality. In fact, a DevOps mindset - a mindset towards continuous improvement, innovation, and delivery with high quality - is crucial for organizations undergoing digital transformation. Practitioners of DevOps should be able to learn and continuously improve on their processes to optimize their system over time. In this way, DevOps has taken ALM to the next level by more closely integrating work phases and applying metrics that can facilitate data-driven decision making to continuously improve the end-to-end system. Although this can very much apply at an application level, DevOps has helped raise software development practices out of an app-centric, discrete step-wise view, and into a more integrated system of delivering work.
But, in an ironic alignment with what DevOps itself stands for, we’ve reached a time when even DevOps practices can be improved upon and applied in new ways.
The next step in software at scale? Value stream management - and large-scale digital transformations and operations cannot succeed without it.
Value stream management focuses on increasing the flow of value to the customer. It lives one step above DevOps, in that it looks at the software development process in terms of lean thinking and delivering value to the business - not just as pieces of work in an integrated system. This assigning of value to work is a key difference in the mindset as it’s no longer “just” about software delivery - every decision is made through the lens of “how does this contribute to value creation, and what impact does it have to the value stream as a whole?”
This systematic approach to measuring and improving flow has the end goal of decreasing time to market of valuable features by increasing throughput of the system. Ultimately, effective value stream management can lead to optimized business outcomes - in other words, ROI, as teams deliver more value, faster.
If we think about a general definition of value stream management - a practice that looks to increase the flow of value to the customer - it inherently includes two key aspects: value must flow, and we can improve said flow.
Flow evokes a certain fluidity - a connectivity between people, processes, and products in which there are no clear boundaries. Tools are seamlessly integrated. Work stages - such as testing - are automated where possible. People who contribute have clear lines of communication to those up and downstream, ensuring the handoff of work is smooth. Value stream management is all about ensuring this flow of value is uninterrupted.
Next, our definition tells us we should be able to improve our value flow. Improving the flow relies heavily on two activities: value stream mapping, and applying DevOps to our value stream.
In their book Value Stream Mapping, Karen Martin and Mike Osterling famously said, “If you can’t describe what you are doing as a value stream, you don’t know what you’re doing.” In order to increase flow, we need to know what’s working in our system and what isn’t...but until we have visibility into our value streams, all we can do is guess. Mapping your value stream is a practice that brings together relevant stakeholders from across the organization to define the sequence of activities and inputs that must happen to deliver value to the customer. By explicitly defining activities and inputs, you’ll be able to create a solid implementation plan that maximizes your available resources and ensures materials and time are used efficiently.
Once you have greater visibility into your processes and how work flows (or should flow!), implementing DevOps practices across the value stream will allow you to unlock process improvements more efficiently. Gartner notes that “DevOps practices improve the flow in the value stream through agile delivery methods, collaboration and automation. Continuous feedback is an important aspect of value streams, because it helps remove constraints and, thus, improves quality, reliability and safety.” While value stream mapping helps us understand what areas are best to target for improvement, DevOps practices are the true first step in optimizing a value stream.
It is nearly impossible to succeed in a large-scale digital transformation without value stream management. Tools like Copado’s Value Stream Maps not only help outline and define how value is delivered to the customer, but also help to track development metrics within and across stages of work. These metrics are - crucially - presented in a non-technical way to facilitate understanding across the business. By stripping back in-depth technical language while maintaining the underlying metadata, stakeholders gain the insight needed to drive discussions around things like priorities, budgets, trade-offs, and resource allocation to not only deliver value to the customer, but capture ROI for the company.
The fact is, every company has data. However, few have access or visibility into that data...and even fewer have the ability to see the data organized in such a way that leads to insightful decision-making. This is the critical gap organizations need to fill in order to maximize potential ROI from digital transformation based in DevOps practices. Data-driven development can only happen when that data is surfaced in a clear way, using metrics to optimize flow from idea to value realization. Performance data visibility enables and expedites data-driven decisions about future investments in the product, brings to light opportunities for business process re-engineering, and improves delivery velocity and quality while mitigating risk factors. Monitoring and analyzing how work is done is an essential part of an effective DevOps practice: DevOps ROI is directly rooted in visibility into your value stream.
The thing about living in an age of constant digital gains and change is change comes at you fast, and getting left behind is increasingly costly. Gartner notes: “by 2023, 70% of organizations will use value stream management to improve flow in the DevOps pipeline, leading to faster delivery of customer value.” 2023 is only two years away. If you wait any longer before jumping in and understanding how value stream management can benefit your business, you may just be part of that 30% that is behind the curve and inevitably left behind.
So while you may not feel “ready” for value stream management if you are just getting your feet wet with DevOps at scale, that’s really the crux of it all. Value stream management will actually take you farther than DevOps alone. It’s not something to start thinking about once you get everything in your organization figured out and organized - it is THE thing that will enable you to detangle the complex web of practices and dependencies in the first place.
It should be clear now that value stream management doesn’t replace or cancel out the need for DevOps practices in an organization...just like DevOps does not wholly replace ALM. Instead, each is a natural evolution of its predecessor, building on the principles of that which came before it. In many cases, the frameworks can even be enhanced by layering their different principles to realize maximum value.
Digital transformation is all about innovation, moving forward, and doing and working better in this new future. While application lifecycle management has given people permission to “think beyond the code” and think instead about the application’s broader lifecycle, ALM alone is not enough. Enter, DevOps. It has enabled massive process and standardization gains in companies globally, allowing them to continue learning and improving how they develop software. But, the two alone - and together! - are no longer enough for a company to thrive in an era where digital transformations are accelerating every day. Value stream management is the next step in software at scale - large-scale digital transformations and operations cannot succeed without it.
Copado is an end-to-end data-driven DevOps platform with integrated value stream management functionality. To learn more about gaining visibility into your value stream and how to best apply DevOps practices and tools to optimize value delivery to customers, schedule a demo today!
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