Ecosystems Over Products
Ecosystems Over Products means building an interconnected system of analytics assets that reference and reinforce each other, instead of a pile of isolated dashboards and models that each stand alone.
A forest, not a tree farm. Individual products decay on their own. Ecosystems compound.
The island of misfit dashboards
A team manages dozens of dashboards, a stack of databases, and a handful of standalone ML models — each one built for a specific ask, each one living in its own bubble, none of them talking to any of the others. Every solution gets evaluated on its own merits in isolation, which means the team never asks the more valuable question: does this connect to anything, or does it just add one more island to a growing archipelago nobody can navigate. That disconnected debt is what actually caps how much value an analytics org can produce, long before headcount or budget does.
Products over projects, but not monoliths either
The fix isn't building one giant unified platform that tries to do everything — that just trades forty-seven disconnected small failures for one enormous fragile one. It's treating each solution as a product with an owner and a lifecycle, while relentlessly focusing on the connections between products as much as the products themselves. Draw the ecosystem you actually want: a core platform at the center, tier-one products connected directly to it, tier-two products building on tier-one. Revisit the drawing every quarter, on the same cadence as your other planning, and ask two questions every time — what connections did we build, and what bubbles should we erase.
Erasing bubbles is part of the job
Retiring a disconnected, low-value product is not an admission of failure — it's the ecosystem doing what a healthy one does, the same way a forest sheds a dead branch to put more light on everything still growing. A product that connects to nothing and has almost no users is not neutral; it's still consuming maintenance time that could go toward the parts of the ecosystem that are actually compounding in value. Teams that make this a quarterly habit tend to retire a meaningful chunk of their portfolio every year and feel their remaining work get more valuable, not less, because the surviving products now reinforce each other instead of competing for the same attention.
Where this shows up in the book
This is Chapter 13, where Sarah discovers ClassicMotors has quietly built dozens of disconnected analytics products with barely a quarter of them actually being used — and has to decide which bubbles to erase before she can draw a real ecosystem.
Read this in the book
Chapter 13: The Product Ecosystem →Where do you already do this — and where don’t you?
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