Highly Optimized Waste (el. knyga) (skaityta knyga) | Doug Dockery | knygos.lt

Aprašymas

Your teams are shipping. Your roadmap is full. Your dashboards are green. So why isn't the business getting better?

Highly Optimized Waste examines a costly problem in modern organizations: talented people efficiently building things that should never have been built.

For CEOs, CTOs, product leaders, and executives responsible for technology investment, Doug Dockery offers a practical way to connect strategy, decisions, delivery, and evidence. Drawing on his experience leading software and technology organizations, he shows how reasonable requests, competing priorities, and confident assumptions become expensive commitments-and how to interrupt that pattern.

At the heart of the book is the HOW operating loop: Signal, Decide, Shape, Commit, Build, Prove, Repeat. It connects the reason for an investment to the work being done, the capacity it consumes, the promises it creates, and the evidence that determines what happens next.

You'll learn how to:

- Find the underlying problem behind feature requests.

- Make priorities meaningful by naming what will be delayed, displaced, or declined.

- Treat capacity as capital and clarify who has authority to make consequential decisions.

- Shape a Bet Brief that preserves the problem, expected outcome, assumptions, and limits of an investment.

- Give customers and colleagues commitments they can trust.

- Keep intent attached to the work as teams build and circumstances change.

- Distinguish shipping from adoption, value, and validated results.

- Decide when to kill, fix, or scale an investment.

Dockery also examines what AI changes-and what it doesn't. Faster implementation can accelerate the cost of weak judgment. Leaders still need to decide which problems deserve attention, what evidence supports action, and when to change course.

With practical examples, book-specific figures, a diagnostic scorecard, and downloadable companion templates, Highly Optimized Waste helps leadership teams build a shared operating discipline around better decisions.

Because the goal is not simply to deliver more software. It is to make better investments-and know whether they worked.