liveBook · Manning

Stakeholder

As explained in Machine Learning System Design

A stakeholder is a person or group with an interest in, influence over, responsibility for, or authority regarding a project or system.

A stakeholder is anyone with interest, influence, responsibility, or authority over a project or system. In an ML project, that includes more than a boss or product manager: budget owners, approvers, executives, domain experts, and the individual contributors who handle the current process. section 2.2

Involve stakeholders while defining the problem, and look for different kinds of knowledge:

  • Interview executives for strategic goals and initiative context. section 2.2
  • Talk with individual contributors for tactical details, workarounds, and design constraints. section 2.2
  • Identify who controls budgets and who approves each system component. section 2.2
  • Share measured results with stakeholders using business metrics, not only model metrics. section 12.0

A discovery conversation

An executive may describe the initiative's goal, while an employee handling the current process reveals practical tricks that change the design. Recording both perspectives in the initial problem statement creates a foundation for the design document. section 2.2

How Machine Learning System Design covers it

How deep it goes
Maps strategic and tactical perspectives, budget ownership, and approval responsibility, but stops short of prescribing a formal stakeholder-management process.
Examples
Uses executives, product managers, budget owners, domain experts, and individual contributors as contrasting stakeholder perspectives.
What it assumes
Assumes a project or system under consideration and teaches stakeholder identification from the need to understand what people want and need.
What you can do after
Evaluate/understand whose goals, authority, approval, and operational knowledge must shape an ML project's definition and reporting.
How it connects
Connects stakeholders to problem definition, design documents, ML systems, online testing, offline testing, A/B tests, and business metrics.

Also explained in

Compare how 9 books explain stakeholder →

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Machine Learning System Design. The section links point to the parts of the book it draws on.