Value stream intelligence – SD Times

by Joseph K. Clark

The metrics are great. They give you insight into how your systems are running and help you see the results of what you’ve done. They allow you to derive value from your efforts. But what if you want to not merely play catch-up with what the metrics are telling you but instead wish to mitigate against how things will go? According to Adam Dahlgren, VP of product development at Allstacks, that is where value stream intelligence comes in. He calls VSI the evolution of value stream management.

Organizations (mostly) all believe they’re doing great work. But from a business-level view, many are still flying blind. He explains: “There are all these different value streams for marketing, sales, customer success, product developers, and the like. But they’re all hinged on each other. One of these value streams is developers building a feature that drives later and later. Well, the product marketing stream relies on and reacts to the developer stream’s change. And all they can do right now is react when I say, ‘Oh, it’s way crap; I gotta do something else.’ I’m scrambling, always playing catch-up.

 If, instead, we can give the developers and the product marketers in this example the ability to communicate with each other on an ongoing basis on how things are changing, now we’ve restored power to each of the orgs to say, well, based on what’s transpiring, how do you want to change your behavior? Now you’ve connected those values. So this developer value stream that maybe is running late has a cascading impact on the marketing value stream. … And that’s like the intelligence layer. It’s not just what has transpired; it’s given what’s happened. What are we going to do next?”


Dahlgren said the widely accepted DORA metrics provide organizations with snapshots of how they’re doing. Those metrics — deployment frequency (DF), mean lead time for changes (MLT), mean time to recover (MTTR), and change failure rate (CFR) — is considered the gold standard for organizations seeking the value that can be derived from moving quickly to add features and remove bugs from their software. But, Dahlgren pointed out, these metrics show you how you’re doing, not where you’re going. And, they’re limited in scope to the product and don’t give the wide-angle view businesses need. The DORA metrics, he said, “were a great starting point. But those DORA metrics are tiny snippets of what’s possible for the real business alignment and core value capture for these big companies. Together, they are helpful, but you can be nailing all four of your DORA metrics, building all the wrong stuff, and not knowing what’s happening.”

He gave an abstract example of a city dealing with traffic problems. “You’re looking at timings at traffic lights, and some engineer somewhere has decided that the yellow light needs to be three seconds on all these different traffic lights, but there’s one yellow light that’s four seconds. Okay, should we change that to three seconds if that’s out of the boundary? Did that accomplish anything? It got it into spec. But is there still traffic?” 

“But if you look at it another way, like, at this intersection, there’s a significant amount of traffic,” he continued. “We could fix the traffic at that one intersection. Well, it turns out that, you know, the left turn lane is just part of the left lane. And we need to create a dedicated left-turn lane to solve the problem. That’s management by exception. That’s the intelligence to say there’s something out of bounds here. It’s an unknown unknown. It’s not something you know to monitor, but you need to focus on it.” 

Dahlgren said that value stream intelligence could show you where you’ve been historically successful and how you deviate from those successful pathways that cause delays. “So when these things manifest again, whether you’re monitoring them or not, we will bring them to your attention. And all the value stream management stuff is your supporting documentation.”

He continued that this is important when things go out of bounds in a way we’re not familiar with. So, by looking at related data and seeing some things in combination, you can determine the next steps. “The four-second yellow light is beneficial because it gives people one extra second to sneak in that extra left turn, smoothing the traffic flow. And some smart engineer had just realized that and set it up. When we brought it back into spec [of three seconds], we didn’t realize it would have these cascading impacts [of slowing traffic]. That’s what we’re bringing to bear when you leverage this intelligence.”

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