Explore Tasks
Plan a data, AI or system-enabled change with measurable adoption outcomes
A sponsor receives an implementable change plan (impacts, readiness, adoption measures, risks) for a data, AI or system change.
1job does it
5jobs help with it
33skills it needs
- Change Lead
- Communications Lead
- Communications Manager
- Change Analyst
- Change Manager
- Head of Transformation
Does itHelps with it
- Reading and tracing unfamiliar code
- Reviewing human- and AI-generated code changes for correctness and risk
- Sampling and reviewing a team's work against standards
- Diagnosing misleading data visualisations
- Verifying reports and dashboards before and after release
- Verifying AI-assisted outputs against sources
- Disclosing AI contribution to professional work
- Testing competing explanations with discriminating evidence
- Independently checking analytical conclusions and claims
- Escalating unresolved risks with evidence and clear ownership
- Giving specific developmental feedback on data and AI work
- Judging the materiality of defects and deficiencies for the intended use
- Interpreting trends and seasonality
- Designing experiments
- Estimating and challenging causal effects
- Defining measurable outcomes and leading indicators
- Testing, implementing and sustaining measured improvements
- Evaluating learning transfer and performance outcomes
- Designing implementable change plans
- Evaluating whether people understood, adopted and sustained a change
- Diagnosing capability gaps from work evidence and planning development
- Measuring campaign outcomes with valid denominators
- Choosing an analytical method to fit the question and data
- Weighing conflicting evidence by design strength
- Verifying benefits realisation and attribution
- Applying research ethics and participant consent
- Identifying and quantifying decision downside and exposure
- Making accountable decisions under uncertainty
- Revising prior decisions when evidence changes
- Reasoning about systems, feedback and second-order effects
- Facilitating group decisions using disputed evidence
- Rating risks against appetite and choosing proportionate treatment
- Recognising and resolving ethical conflicts in data and AI work
Paths that teach the skills it needs
Skill Path
Data Literacy for Business Decisions
Judge whether a business claim from a table, KPI, chart or dashboard really holds up.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Leading Analytics and AI Change
Lead adoption, diagnose learning needs, coach and assure team capability.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Experimentation and Causal Impact Evaluation
Answer "did it work" with randomised experiments where possible and quasi-experimental methods where not.
- Modules
- 5 open
- Practice data
- Raket Parts