Roles Strategy & Transformation
Strategy Manager
Manages a strategy team and is accountable for the quality of its analysis and business cases.
4tasks in this job
58skills it uses
5tools named
The skills this job leans on most
- 1Reasoning about systems, feedback and second-order effectsNeeded in 4 of 4 tasks
- 2Testing investment business cases under uncertaintyNeeded in 3 of 4 tasks
- 3Judging whether external evidence applies to the decision contextNeeded in 3 of 4 tasks
- 4Comparing options against explicit decision criteriaNeeded in 2 of 4 tasks
- 5Appraising options on a common incremental basis against a do-nothing baselineNeeded in 2 of 4 tasks
ToolsMicrosoft ExcelMicrosoft PowerPointMicrosoft Power BIAnaplanMicrosoft Purview
All 4 tasks, where people get stuck and all 58 skills
Tasks
- Evaluate strategic options with market and performance evidence
- Build a defensible business case
- Size a market and assess the competitive landscape
- Translate a strategic choice into measurable objectives and targets and track strategic KPIs through the planning cycle
Where people get stuck
- Calculating and verifying KPIs against their specification
- Designing and comparing decision scenarios
- Defining measurable outcomes and leading indicators
All skills
- Appraising options on a common incremental basis against a do-nothing baseline
- Comparing options against explicit decision criteria
- Judging whether external evidence applies to the decision context
- Reasoning about systems, feedback and second-order effects
- Testing investment business cases under uncertainty
- Analysing business drivers and contributions
- Analysing costs, allocation and margin drivers
- Analysing pay equity with raw and adjusted pay gaps
- Analysing working-capital drivers and cash conversion
- Assessing data source credibility and fitness for a question
- Assigning and operating data ownership and stewardship
- Building driver-based financial forecasts
- Communicating quantified uncertainty
- Comparing periods consistently
- Constructing a controlled cash-flow plan
- Defining measurable outcomes and leading indicators
- Designing and comparing decision scenarios
- Designing auditable decision models
- Designing semantic models for governed analytics
- Diagnosing forecast accuracy and bias and comparing methods fairly
- 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 and challenging causal effects
- Estimating market size by triangulating top-down and bottom-up methods
- Estimating quantities and differences with intervals
- Explaining how business events flow into accounting records
- Forecasting business trends and turning points for planning
- Giving specific developmental feedback on data and AI work
- Identifying and quantifying decision downside and exposure
- Identifying keys and testing referential integrity
- Independently checking analytical conclusions and claims
- Interpreting averages, weighted measures and mix effects
- Interpreting budgets and planning assumptions
- Interpreting trends and seasonality
- Interpreting workforce metrics and populations
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether a change exceeds normal variation
- Making accountable decisions under uncertainty
- Mapping competitor positions from external evidence
- Mapping stakeholders' decisions, constraints and needs
- Presenting and defending evidence-based recommendations to decision-makers
- Prioritising work by evidenced value, cost, risk and confidence
- Reading business metrics
- Reconciling conflicting reports
- Running sensitivity and break-even analysis on model assumptions
- Specifying BI measure semantics: additivity, aggregation and time
- Specifying decision-useful reports
- Structuring ambiguous professional problems
- Testing competing explanations with discriminating evidence
- Testing, implementing and sustaining measured improvements
- Variance analysis
- Verifying AI-assisted outputs against sources
- Verifying benefits realisation and attribution
- Verifying reports and dashboards before and after release
- Writing data quality rules
- 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
Strategic and Commercial Decisions: Options, Trade-offs and Priorities
Frame and decide commercial and strategic options, prioritise portfolios under capacity and review decisions afterwards.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonFinancial Modelling and Decision Support
4tasks in this job
65skills it uses
6tools named
The skills this job leans on most
- 1Testing investment business cases under uncertaintyNeeded in 3 of 4 tasks
- 2Judging whether external evidence applies to the decision contextNeeded in 3 of 4 tasks
- 3Designing and comparing decision scenariosNeeded in 2 of 4 tasks
- 4Defining measurable outcomes and leading indicatorsNeeded in 2 of 4 tasks
- 5Calculating and verifying KPIs against their specificationNeeded in 1 of 4 tasks
ToolsMicrosoft ExcelMicrosoft Power BIQlik SenseMicrosoft PowerPointAnaplanMicrosoft Purview
All 4 tasks, where people get stuck and all 65 skills
Tasks
- Evaluate strategic options with market and performance evidence
- Build a defensible business case
- Size a market and assess the competitive landscape
- Translate a strategic choice into measurable objectives and targets and track strategic KPIs through the planning cycle
Where people get stuck
- Prioritising work by evidenced value, cost, risk and confidence
- Planning delivery dependencies and the critical path
- Verifying benefits realisation and attribution
All skills
- Calculating and verifying KPIs against their specification
- Defining measurable outcomes and leading indicators
- Designing and comparing decision scenarios
- Judging whether external evidence applies to the decision context
- Testing investment business cases under uncertainty
- Analysing business drivers and contributions
- Analysing costs, allocation and margin drivers
- Analysing pay equity with raw and adjusted pay gaps
- Analysing working-capital drivers and cash conversion
- Appraising options on a common incremental basis against a do-nothing baseline
- Assessing data source credibility and fitness for a question
- Assigning and operating data ownership and stewardship
- Building driver-based financial forecasts
- Communicating quantified uncertainty
- Comparing options against explicit decision criteria
- Comparing periods consistently
- Constructing a controlled cash-flow plan
- Designing and versioning data contracts for consumers
- Designing auditable decision models
- Designing semantic models for governed analytics
- Diagnosing forecast accuracy and bias and comparing methods fairly
- 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
- Establishing and declaring data grain
- Estimating and challenging causal effects
- Estimating market size by triangulating top-down and bottom-up methods
- Estimating quantities and differences with intervals
- Explaining how business events flow into accounting records
- Forecasting business trends and turning points for planning
- Giving specific developmental feedback on data and AI work
- Governing shared data definitions
- Identifying and quantifying decision downside and exposure
- Identifying keys and testing referential integrity
- Independently checking analytical conclusions and claims
- Interpreting averages, weighted measures and mix effects
- Interpreting budgets and planning assumptions
- Interpreting trends and seasonality
- Interpreting workforce metrics and populations
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether a change exceeds normal variation
- Making accountable decisions under uncertainty
- Mapping competitor positions from external evidence
- Mapping stakeholders' decisions, constraints and needs
- Presenting and defending evidence-based recommendations to decision-makers
- Prioritising work by evidenced value, cost, risk and confidence
- Reading business metrics
- Reasoning about systems, feedback and second-order effects
- Reconciling conflicting reports
- Running sensitivity and break-even analysis on model assumptions
- Sampling and reviewing a team's work against standards
- Setting and reviewing reliability objectives and error budgets for data and AI services
- Specifying BI measure semantics: additivity, aggregation and time
- Specifying decision-useful reports
- Structuring ambiguous professional problems
- Testing competing explanations with discriminating evidence
- Testing, implementing and sustaining measured improvements
- Tracing data lineage upstream and downstream
- Variance analysis
- Verifying AI-assisted outputs against sources
- Verifying benefits realisation and attribution
- Verifying reports and dashboards before and after release
- Writing data quality rules
- 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
Strategic and Commercial Decisions: Options, Trade-offs and Priorities
Frame and decide commercial and strategic options, prioritise portfolios under capacity and review decisions afterwards.
- 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 soonFinancial Modelling and Decision Support
6tasks in this job
87skills it uses
6tools named
The skills this job leans on most
- 1Testing investment business cases under uncertaintyNeeded in 4 of 6 tasks
- 2Designing and comparing decision scenariosNeeded in 3 of 6 tasks
- 3Defining measurable outcomes and leading indicatorsNeeded in 3 of 6 tasks
- 4Prioritising work by evidenced value, cost, risk and confidenceNeeded in 3 of 6 tasks
- 5Calculating and verifying KPIs against their specificationNeeded in 1 of 6 tasks
ToolsMicrosoft Power BIQlik SenseMicrosoft PowerPointMicrosoft ExcelAnaplanMicrosoft Purview
All 6 tasks, where people get stuck and all 87 skills
Tasks
- Evaluate strategic options with market and performance evidence
- Build a defensible business case
- 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
- Size a market and assess the competitive landscape
- Translate a strategic choice into measurable objectives and targets and track strategic KPIs through the planning cycle
Where people get stuck
- Prioritising work by evidenced value, cost, risk and confidence
- Judging whether external evidence applies to the decision context
- Reasoning about systems, feedback and second-order effects
All skills
- Calculating and verifying KPIs against their specification
- Defining measurable outcomes and leading indicators
- Designing and comparing decision scenarios
- Prioritising work by evidenced value, cost, risk and confidence
- Testing investment business cases under uncertainty
- Analysing business drivers and contributions
- Analysing costs, allocation and margin drivers
- Analysing pay equity with raw and adjusted pay gaps
- Analysing working-capital drivers and cash conversion
- Appraising options on a common incremental basis against a do-nothing baseline
- Assessing data source credibility and fitness for a question
- Assigning and operating data ownership and stewardship
- Building cohort and retention analyses with correct denominators
- Building decision-focused reports and dashboards
- Building driver-based financial forecasts
- Communicating quantified uncertainty
- Communicating sensitive or unwelcome analytical findings
- Comparing options against explicit decision criteria
- Comparing periods consistently
- Constructing a controlled cash-flow plan
- Constructing clear and honest charts
- Designing and versioning data contracts for consumers
- Designing auditable decision models
- Designing decision-oriented research with customers, users or employees
- Designing experiments
- Designing semantic models for governed analytics
- Diagnosing forecast accuracy and bias and comparing methods fairly
- Diagnosing misleading data visualisations
- Diagnosing operational handoffs and flow
- Disclosing AI contribution to professional work
- Eliciting the decision behind an analytical request
- Escalating unresolved risks with evidence and clear ownership
- Establishing and declaring data grain
- Estimating and challenging causal effects
- Estimating market size by triangulating top-down and bottom-up methods
- Estimating quantities and differences with intervals
- Evaluating and improving chart accessibility
- Evaluating product outcomes and metric integrity
- Explaining how business events flow into accounting records
- Explaining technical work to accountable non-specialists
- Forecasting business trends and turning points for planning
- Giving specific developmental feedback on data and AI work
- Governing shared data definitions
- Identifying and quantifying decision downside and exposure
- Identifying keys and testing referential integrity
- Independently checking analytical conclusions and claims
- Interpreting averages, weighted measures and mix effects
- Interpreting budgets and planning assumptions
- Interpreting correlation without inferring cause
- Interpreting customer feedback and qualitative evidence
- Interpreting trends and seasonality
- Interpreting workforce metrics and populations
- 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
- Judging whether uncertainty changes the decision
- Maintaining a risk register with owners, triggers and responses
- Making accountable decisions under uncertainty
- Mapping competitor positions from external evidence
- Mapping stakeholders' decisions, constraints and needs
- Planning delivery dependencies and the critical path
- 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 conflicting reports
- Revising prior decisions when evidence changes
- Running sensitivity and break-even analysis on model assumptions
- Sampling and reviewing a team's work against standards
- Selecting charts for evidence and decisions
- Setting and reviewing reliability objectives and error budgets for data and AI services
- Specifying BI measure semantics: additivity, aggregation and time
- Specifying decision-useful reports
- Structuring ambiguous professional problems
- Testing competing explanations with discriminating evidence
- Testing, implementing and sustaining measured improvements
- Tracing data lineage upstream and downstream
- Variance analysis
- Verifying AI-assisted outputs against sources
- Verifying benefits realisation and attribution
- Verifying project progress against accepted outcomes
- Verifying reports and dashboards before and after release
- Writing data quality rules
- 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
Strategic and Commercial Decisions: Options, Trade-offs and Priorities
Frame and decide commercial and strategic options, prioritise portfolios under capacity and review decisions afterwards.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonFinancial Modelling and Decision SupportDelivering Data and AI Projects with Evidence
About the role
Manages a strategy team and is accountable for the quality of its analysis and business cases. Allocates strategy leads and analysts across workstreams and decides which recommendations go forward. Data judgement sits in deciding when evidence is too weak to support a recommendation.
Also called Corporate Strategy Manager