Why Value Streams Matter Now

2022 was the year the longest boom cycle in our industry started a sudden and sustained pullback. By 2023, we were about a decade into the data-enabled engineering revolution that kicked off in the early teens. Large technology companies had invested hundreds of millions of dollars into software R&D and tooling over the prior decade to measure and analyze developer productivity. Venture capitalists had invested billions of dollars into startups over the prior decade to democratize access to rich real-time data in engineering processes, giving CTOs and engineering managers analytical tools that those of us who came up in the ranks in prior decades could only dream of.

In 2023, we were a decade into the DevOps movement - which, more than anything that came before it, used data and research to connect engineering practices to organization outcomes and created practical tools for technology companies to improve operational efficiency. 

So, with money no longer free and CEOs under pressure to deliver “efficiently,” 2023 was the year that all this investment should have paid off. 

But CEOs lacked the tools to help them rise to the sudden challenge of rationally creating organizational efficiencies when it became a material business priority.  

The only tool they could reach for was the same one their predecessors had in the last bust cycle in the early 2000s: the mass layoff. 

The reason? 

Despite all the progress in improving developer productivity and optimizing engineering management with data, we’ve made little progress in connecting engineering work to business outcomes. 

This has been, and continues to be the status quo: engineering and business living in harmonious isolation. 

When faced with the question: “how are my investments in engineering contributing to the success of the company?” we still have very few reliable ways of answering it confidently and backing it up with data.

Mass layoffs are a symptom.

Value Streams are analytical constructs that can help us fix this.

What is a Value Stream? 

A value stream represents a stable category of customer needs that a company attempts to fulfill through economically viable products and services [1].

A value stream connects value propositions tied to customer needs to the network of people, processes, and technology that fulfills them, along with clear criteria to measure how effectively the products and services deliver on the value propositions and what it costs to do so. 

The stability of a category of needs over longer periods distinguishes a value stream from a project, which is more tactically focused on meeting specific needs across shorter timeframes. 

The critical thing to note is that since value streams always start with a need and end with its fulfillment, they are an ideal tool to understand and improve how value is delivered across all the internal silos in a company and allow one to focus improvements across a path of needs-fulfillment in a holistic manner.

Value streams allow us to analytically decompose and re-aggregate a company's existing structures of people, processes, and technologies along the dimension of customer need fulfillment. 

It gives us the tools to assess whether these existing structures are the ideal way to fulfill all the customer needs the company sets out to meet in an economically viable fashion. 

With our vastly improved ability to collect and analyze granular data to inform decisions, it is now possible for companies to do this type of analysis and improve operational efficiency continuously rather than waiting for the next crisis to strike before making it a priority. 

This crucial missing element will allow us to move beyond the rather myopic focus over the last decade on “developer productivity” or “engineering effectiveness” and move towards thinking about how engineering contributes to the overall health of specific value streams that impact the experiences that customers value. 

Value Stream Management is the emerging cross-functional discipline that systematically develops practices and analytical techniques to make this a reality. 

What is Value Stream Management

Value Stream Management is a set of practices for analyzing organizational through-lines focused on the fulfillment of customer needs, cutting across product, engineering, operations, sales, customer support, etc., as needed, to continually assess how and where processes, tools,  and most importantly, organizational behaviors need to change, to improve the customer experience continuously. 

Value Stream Management is the pathway to building upon our progress over the last decade in data-informed engineering and extending it to how the company delivers value. By giving us an analytical tool to connect engineering outputs to  business outcomes, it finally gives us a tool to view engineering work through  a business-facing lens. 

It is the missing link needed to create ongoing alignment between strategy and execution, and modern technology makes it practical for companies to map and manage value streams to do this in much tighter loops than before. 

But beyond technology, Value Stream Management takes work and openness to change. 

This is still the hardest challenge, but the means to do this are well within reach now. 

Done well, better discipline around managing value streams promises to make the gut-wrenching cycle of unmanaged growth followed by uninformed retrenchment, the hallmark of the technology industry in 2023, less necessary by the time we get here in the next business cycle. 

In the next post, we will delve deeper into what this means.   

Notes:

[1] The definition of value streams we use here is somewhat more general than the one that is derived from the definition of value streams that originated in the domain of Lean manufacturing.  It is closer in spirit to the notion of a “value chain” originally defined by Michael Porter, as a tool for reasoning about strategy. 

While derived from both concepts, it is important to recognize that neither one is a perfect fit for reasoning about the way we build and deliver modern digital products.

To the extent that we borrow useful ideas from the industrial production domain to apply in the digital realm, we need to adapt them to work in a world where products are being built and refined continuously in response to customer needs and market conditions. 

This is a topic that is much larger in scope than can be covered here, but we will highlight these differences in footnotes along the way so as not to distract from the overall theme of the discussion.

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