People: Teams and stakeholders
Learning goals
- In an invoice AI pilot, finance may prioritize avoiding incorrect payments while engineering prioritizes response time. Agree who decides exceptions and how quality and time are measured before acceptance.
Key points
- A shared direction explains whose outcomes matter, beyond a deliverables list. Translate conflicting departmental language into measurable outcomes and priorities. Revisit assumptions with the relevant decision makers when circumstances change.
- Identify whether disagreement concerns facts, relationships or decision procedures. Collaboration explores underlying interests for a joint solution. Urgent safety situations need protective action; ordinary disagreements should not automatically be delegated upward.
- Working agreements define observable collaboration and decision behavior. Psychological safety enables reporting concerns and mistakes without removing accountability or quality standards. Address violations through agreed behavior and observed impact.
- Match support to skill, experience and risk. Give experienced specialists clear outcomes and room to act; provide newcomers with staged practice and feedback. Removing impediments differs from doing all the team’s work.
- Separate outcome accountability, execution and decision authority. A responsibility matrix supports discussion but does not replace agreement. Compare skills and available capacity, then address gaps through development, allocation or external support.
- Stakeholders include operators, communities and partners affected by delivery, not just sponsor and users. Power, interest and impact change over time. Significant effects on low-power groups still require attention and appropriate engagement.
- Engagement is more than broadcasting updates. Give affected people suitable ways to influence decisions and follow through on commitments. Resistance can reflect losses or prior experience, so combine listening with evidence rather than assuming ignorance.
- Explore interests behind stated positions and compare feasible alternatives. Conflicting budget, timing and outcome expectations require authorized trade-offs. Assess impacts before making commitments rather than promising every request immediately.
- Expectations can change after initial agreement. Define testable acceptance conditions and compare demonstrations with real user experience. Conformance and customer value are related but distinct; new expectations need explicit change or priority decisions.
- Transfer decision context and experiential knowledge as well as documents. Make records findable, maintained and appropriately restricted. Knowledge sharing does not mean indiscriminate disclosure of confidential information.
- Mentoring develops perspective and judgment; coaching can help a learner find their own solution. Turnover requires transfer of relationships, authority, knowledge and open decisions. Confirm readiness with the incoming person rather than relying on introductions alone.
- Match recipient, purpose, urgency, channel, frequency and owner. Across time zones, combine asynchronous records with fair access to live discussion. Sending is not understanding; close the loop through feedback and decision readiness.
Workplace uses
- Workplace applicationIn an invoice AI pilot, finance may prioritize avoiding incorrect payments while engineering prioritizes response time. Agree who decides exceptions and how quality and time are measured before acceptance.
Learning topics mapped to ECO tasks (site curriculum)
- Shared direction and success criteria
- Diagnosing disagreements
- Working agreements and speaking up
- Situational leadership and coaching
- Roles, delegation and capability
- Discovering affected stakeholders
- Trust and meaningful involvement
- Reconciling expectations
- Customer feedback and acceptance
- Capturing reusable project knowledge
- Mentoring and continuity through turnover
- Distributed communication and reporting