Roles Strategy & Transformation
Head of Transformation
Accountable for the transformation portfolio and its operating model, investment and realised change.
4tasks in this job
36skills it uses
6tools named
The skills this job leans on most
- 1Verifying benefits realisation and attributionNeeded in 4 of 4 tasks
- 2Prioritising work by evidenced value, cost, risk and confidenceNeeded in 3 of 4 tasks
- 3Planning delivery dependencies and the critical pathNeeded in 3 of 4 tasks
ToolsMicrosoft PowerPointWorkdayMicrosoft Power BIPlanviewMicrosoft ExcelQlik Sense
All 4 tasks, where people get stuck and all 36 skills
Tasks
- Plan a data, AI or system-enabled change with measurable adoption outcomes
- Prioritise and rebalance an investment portfolio against value, capacity and benefit evidence
- Track and verify benefits realisation against the business case
- Assess a project or programme at a stage gate and recommend proceed, hold or stop
Where people get stuck
All skills
- Planning delivery dependencies and the critical path
- Prioritising work by evidenced value, cost, risk and confidence
- Verifying benefits realisation and attribution
- Appraising options on a common incremental basis against a do-nothing baseline
- Assessing data source credibility and fitness for a question
- Building cohort and retention analyses with correct denominators
- Choosing an analytical method to fit the question and data
- Communicating quantified uncertainty
- Comparing options against explicit decision criteria
- Comparing periods consistently
- Defining measurable outcomes and leading indicators
- Designing and comparing decision scenarios
- Designing decision-oriented research with customers, users or employees
- Designing implementable change plans
- Diagnosing capability gaps from work evidence and planning development
- Eliciting the decision behind an analytical request
- Evaluating learning transfer and performance outcomes
- Identifying and quantifying decision downside and exposure
- Independently checking analytical conclusions and claims
- Interpreting customer feedback and qualitative evidence
- Interpreting trends and seasonality
- Judging whether a change exceeds normal variation
- Judging whether external evidence applies to the decision context
- Maintaining a risk register with owners, triggers and responses
- Making accountable decisions under uncertainty
- Mapping stakeholders' decisions, constraints and needs
- Measuring campaign outcomes with valid denominators
- Presenting and defending evidence-based recommendations to decision-makers
- Rating risks against appetite and choosing proportionate treatment
- Reading business metrics
- Recognising and resolving ethical conflicts in data and AI work
- Revising prior decisions when evidence changes
- Testing competing explanations with discriminating evidence
- Testing, implementing and sustaining measured improvements
- Variance analysis
- Writing evidence-led findings and auditable recommendations with their limits
Paths to start
Coming soonDelivering Data and AI Projects with EvidenceManaging Data and AI Products
6tasks in this job
56skills it uses
6tools named
The skills this job leans on most
- 1Verifying benefits realisation and attributionNeeded in 5 of 6 tasks
- 2Defining measurable outcomes and leading indicatorsNeeded in 4 of 6 tasks
- 3Prioritising work by evidenced value, cost, risk and confidenceNeeded in 3 of 6 tasks
- 4Planning delivery dependencies and the critical pathNeeded in 3 of 6 tasks
ToolsMicrosoft PowerPointWorkdayMicrosoft Power BIPlanviewMicrosoft ExcelQlik Sense
All 6 tasks, where people get stuck and all 56 skills
Tasks
- Plan a data, AI or system-enabled change with measurable adoption outcomes
- Prioritise and rebalance an investment portfolio against value, capacity and benefit evidence
- Prepare a periodic performance or risk report for a management or governance committee
- Track and verify benefits realisation against the business case
- Assess the combined change load on affected groups and recommend sequencing
- Assess a project or programme at a stage gate and recommend proceed, hold or stop
Where people get stuck
All skills
- Defining measurable outcomes and leading indicators
- Planning delivery dependencies and the critical path
- Prioritising work by evidenced value, cost, risk and confidence
- Verifying benefits realisation and attribution
- Appraising options on a common incremental basis against a do-nothing baseline
- Assessing data source credibility and fitness for a question
- Assessing the control and reliability of end-user calculation files
- Building cohort and retention analyses with correct denominators
- Building decision-focused reports and dashboards
- Choosing an analytical method to fit the question and data
- Communicating quantified uncertainty
- Communicating sensitive or unwelcome analytical findings
- Comparing options against explicit decision criteria
- Comparing periods consistently
- Constructing clear and honest charts
- Designing and comparing decision scenarios
- Designing decision-oriented research with customers, users or employees
- Designing implementable change plans
- Diagnosing capability gaps from work evidence and planning development
- Diagnosing misleading data visualisations
- Disclosing AI contribution to professional work
- Eliciting the decision behind an analytical request
- Escalating unresolved risks with evidence and clear ownership
- Estimating quantities and differences with intervals
- Evaluating and improving chart accessibility
- Evaluating learning transfer and performance outcomes
- Explaining technical work to accountable non-specialists
- Identifying and quantifying decision downside and exposure
- Independently checking analytical conclusions and claims
- Interpreting correlation without inferring cause
- Interpreting customer feedback and qualitative evidence
- Interpreting sustainability reporting standards and metric boundaries
- Interpreting trends and seasonality
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether a change exceeds normal variation
- Judging whether external evidence applies to the decision context
- Maintaining a risk register with owners, triggers and responses
- Making accountable decisions under uncertainty
- Mapping entity results and eliminating intercompany balances in consolidation
- Mapping stakeholders' decisions, constraints and needs
- Measuring campaign outcomes with valid denominators
- Monitoring and testing data control effectiveness
- Presenting and defending evidence-based recommendations to decision-makers
- Rating risks against appetite and choosing proportionate treatment
- Reading business metrics
- Reading charts and dashboards correctly, including their state
- Recognising and resolving ethical conflicts in data and AI work
- Recognising misleading numerical claims
- Reconciling finance subledgers and close records
- Revising prior decisions when evidence changes
- Selecting charts for evidence and decisions
- Testing competing explanations with discriminating evidence
- Testing, implementing and sustaining measured improvements
- Tracing data lineage upstream and downstream
- Variance analysis
- Writing evidence-led findings and auditable recommendations with their limits
Paths to start
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
Discovering Requirements and Defining Metrics
Turn stakeholder needs into verifiable requirements and governed metric definitions with owners, grain and acceptance tests.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonDelivering Data and AI Projects with EvidenceManaging Data and AI Products
6tasks in this job
58skills it uses
6tools named
The skills this job leans on most
- 1Verifying benefits realisation and attributionNeeded in 5 of 6 tasks
- 2Defining measurable outcomes and leading indicatorsNeeded in 4 of 6 tasks
- 3Prioritising work by evidenced value, cost, risk and confidenceNeeded in 3 of 6 tasks
- 4Planning delivery dependencies and the critical pathNeeded in 3 of 6 tasks
ToolsMicrosoft PowerPointWorkdayMicrosoft Power BIPlanviewMicrosoft ExcelQlik Sense
All 6 tasks, where people get stuck and all 58 skills
Tasks
- Plan a data, AI or system-enabled change with measurable adoption outcomes
- Prioritise and rebalance an investment portfolio against value, capacity and benefit evidence
- Prepare a periodic performance or risk report for a management or governance committee
- Track and verify benefits realisation against the business case
- Assess the combined change load on affected groups and recommend sequencing
- Assess a project or programme at a stage gate and recommend proceed, hold or stop
Where people get stuck
All skills
- Defining measurable outcomes and leading indicators
- Planning delivery dependencies and the critical path
- Prioritising work by evidenced value, cost, risk and confidence
- Verifying benefits realisation and attribution
- Appraising options on a common incremental basis against a do-nothing baseline
- Assessing data source credibility and fitness for a question
- Assessing the control and reliability of end-user calculation files
- Building cohort and retention analyses with correct denominators
- Building decision-focused reports and dashboards
- Choosing an analytical method to fit the question and data
- Communicating quantified uncertainty
- Communicating sensitive or unwelcome analytical findings
- Comparing options against explicit decision criteria
- Comparing periods consistently
- Constructing clear and honest charts
- Designing and comparing decision scenarios
- Designing decision-oriented research with customers, users or employees
- Designing implementable change plans
- Diagnosing capability gaps from work evidence and planning development
- Diagnosing misleading data visualisations
- Disclosing AI contribution to professional work
- Eliciting the decision behind an analytical request
- Escalating unresolved risks with evidence and clear ownership
- Estimating quantities and differences with intervals
- Evaluating and improving chart accessibility
- Evaluating learning transfer and performance outcomes
- Explaining technical work to accountable non-specialists
- Facilitating group decisions using disputed evidence
- Identifying and quantifying decision downside and exposure
- Independently checking analytical conclusions and claims
- Interpreting correlation without inferring cause
- Interpreting customer feedback and qualitative evidence
- Interpreting sustainability reporting standards and metric boundaries
- Interpreting trends and seasonality
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether a change exceeds normal variation
- Judging whether external evidence applies to the decision context
- Maintaining a risk register with owners, triggers and responses
- Making accountable decisions under uncertainty
- Mapping entity results and eliminating intercompany balances in consolidation
- Mapping stakeholders' decisions, constraints and needs
- Measuring campaign outcomes with valid denominators
- Monitoring and testing data control effectiveness
- Presenting and defending evidence-based recommendations to decision-makers
- Rating risks against appetite and choosing proportionate treatment
- Reading business metrics
- Reading charts and dashboards correctly, including their state
- Reasoning about systems, feedback and second-order effects
- Recognising and resolving ethical conflicts in data and AI work
- Recognising misleading numerical claims
- Reconciling finance subledgers and close records
- Revising prior decisions when evidence changes
- Selecting charts for evidence and decisions
- Testing competing explanations with discriminating evidence
- Testing, implementing and sustaining measured improvements
- Tracing data lineage upstream and downstream
- Variance analysis
- Writing evidence-led findings and auditable recommendations with their limits
Paths to start
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
Discovering Requirements and Defining Metrics
Turn stakeholder needs into verifiable requirements and governed metric definitions with owners, grain and acceptance tests.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonDelivering Data and AI Projects with EvidenceManaging Data and AI Products
About the role
Accountable for the transformation portfolio and its operating model, investment and realised change. Decides which data, technology and process initiatives proceed and reports realised benefits to executives. Manages programme and change managers and differs from the Head of Strategy in delivering change against a direction rather than setting it.
Also called Head of Change