Demand Planning Manager
Accountable for the statistical demand forecast, its accuracy and the team of demand planners who produce it.
1task in this job
25skills it uses
7tools named
The skills this job leans on most
- 1Forecasting operational demand at interval and site grainNeeded in 1 of 1 tasks
- 2Forecasting business trends and turning points for planningNeeded in 1 of 1 tasks
- 3Diagnosing forecast accuracy and bias and comparing methods fairlyNeeded in 1 of 1 tasks
ToolsSAP Integrated Business Planning (IBP) and APORELEXBlue YonderKinaxis RapidResponseAnaplanMicrosoft ExcelMicrosoft PowerPoint
All 1 tasks, where people get stuck and all 25 skills
Tasks
Where people get stuck
- Forecasting business trends and turning points for planning
- Diagnosing forecast accuracy and bias and comparing methods fairly
All skills
- Diagnosing forecast accuracy and bias and comparing methods fairly
- Forecasting business trends and turning points for planning
- Forecasting operational demand at interval and site grain
- Analysing queue behaviour, capacity and service constraints
- Balancing territories and quotas from account potential
- Building driver-based financial forecasts
- Challenging probability-weighted sales forecasts
- Communicating quantified uncertainty
- Converting demand into capacity requirements
- Designing and comparing decision scenarios
- Diagnosing misleading data visualisations
- Diagnosing operational handoffs and flow
- Disclosing AI contribution to professional work
- Escalating unresolved risks with evidence and clear ownership
- Estimating quantities and differences with intervals
- Evaluating service performance and quality trade-offs
- Giving specific developmental feedback on data and AI work
- Independently checking analytical conclusions and claims
- Interpreting trends and seasonality
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether a change exceeds normal variation
- Reading business metrics
- Testing competing explanations with discriminating evidence
- Verifying AI-assisted outputs against sources
- Verifying reports and dashboards before and after release
Paths to start
Tool Path
Excel for Analysis and Decision Models
Build and check Excel workbooks others can trust.
- Modules
- 5 open
- Runs in
- Your browser
Skill Path
Forecasting and Scenario Planning
Build and challenge planning forecasts and scenarios.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonService Operations Analytics and Capacity Planning
4tasks in this job
63skills it uses
9tools named
The skills this job leans on most
- 1Forecasting operational demand at interval and site grainNeeded in 3 of 4 tasks
- 2Forecasting business trends and turning points for planningNeeded in 3 of 4 tasks
- 3Diagnosing forecast accuracy and bias and comparing methods fairlyNeeded in 3 of 4 tasks
ToolsAnaplanSAP Integrated Business Planning (IBP) and APORELEXBlue YonderKinaxis RapidResponseMicrosoft Excel+ 3 more
All 4 tasks, where people get stuck and all 63 skills
Tasks
- Build a scenario-based financial forecast
- Forecast demand statistically, test accuracy and agree the demand plan
- Assess forecast accuracy and bias and recommend which forecast methods to rely on
- Oversee an automated or AI system in operational use and correct, restrict or withdraw faulty outputs
Where people get stuck
All skills
- Diagnosing forecast accuracy and bias and comparing methods fairly
- Forecasting business trends and turning points for planning
- Forecasting operational demand at interval and site grain
- Analysing error patterns and failure modes in models and AI systems
- Analysing event sequences, states and durations
- Analysing queue behaviour, capacity and service constraints
- Assessing data source credibility and fitness for a question
- Assessing data-driven fairness and bias
- Assessing data-service continuity and recoverability
- Assessing privacy risk through data protection impact assessments
- Assessing supplier dependency, data-handling and exit risk
- Balancing territories and quotas from account potential
- Building driver-based financial forecasts
- Calculating and interpreting percentages, rates and ratios
- Challenging probability-weighted sales forecasts
- Choosing and justifying missing-data treatments
- Classifying AI uses against regulatory obligations
- Communicating quantified uncertainty
- Comparing groups
- Converting demand into capacity requirements
- Decomposing one's own tasks for AI assistance
- Describing distributions with summaries and plots
- Designing and comparing decision scenarios
- Designing and interpreting hypothesis tests
- Designing efficient and reproducible investigations
- Diagnosing incorrect query and calculation results
- 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
- Estimating quantities and differences with intervals
- Evaluating fitness and full cost of AI-assisted work
- Evaluating responsible AI use risks
- Evaluating service performance and quality trade-offs
- Exercising human oversight of automated and AI outputs
- Explaining control types, dependencies and compensating controls
- Explaining how business events flow into accounting records
- Exploring data to find patterns that survive validation
- Giving specific developmental feedback on data and AI work
- Independently checking analytical conclusions and claims
- Interpreting averages, weighted measures and mix effects
- Interpreting trends and seasonality
- Investigating anomalies
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether a change exceeds normal variation
- Judging whether and how to use AI for a task
- Making accountable decisions under uncertainty
- Monitoring model fitness and drift
- Profiling data
- Rating risks against appetite and choosing proportionate treatment
- Reading business metrics
- Reading charts and dashboards correctly, including their state
- Recognising and containing suspected personal data breaches
- Recognising cybersecurity threats to data work
- Recognising personal data and privacy duties
- Selecting charts for evidence and decisions
- Specifying AI transparency and explanation duties to affected people
- Standardising and cleaning data under agreed rules
- Testing competing explanations with discriminating evidence
- Verifying AI-assisted outputs against sources
- Verifying reports and dashboards before and after release
- Writing evidence-led findings and auditable recommendations with their limits
All tools
- Anaplan
- SAP Integrated Business Planning (IBP) and APO
- RELEX
- Blue Yonder
- Kinaxis RapidResponse
- Microsoft Excel
- Microsoft PowerPoint
- Python
- Microsoft Power BI
Paths to start
Tool Path
Excel for Analysis and Decision Models
Build and check Excel workbooks others can trust.
- Modules
- 5 open
- Runs in
- Your browser
Skill Path
Forecasting and Scenario Planning
Build and challenge planning forecasts and scenarios.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Responsible AI Governance and Assurance
Govern and assure AI across its lifecycle including third-party AI and redress.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonService Operations Analytics and Capacity Planning
4tasks in this job
63skills it uses
9tools named
The skills this job leans on most
- 1Forecasting operational demand at interval and site grainNeeded in 3 of 4 tasks
- 2Forecasting business trends and turning points for planningNeeded in 3 of 4 tasks
- 3Diagnosing forecast accuracy and bias and comparing methods fairlyNeeded in 3 of 4 tasks
- 4Designing and comparing decision scenariosNeeded in 2 of 4 tasks
ToolsAnaplanSAP Integrated Business Planning (IBP) and APORELEXBlue YonderKinaxis RapidResponseMicrosoft Excel+ 3 more
All 4 tasks, where people get stuck and all 63 skills
Tasks
- Build a scenario-based financial forecast
- Forecast demand statistically, test accuracy and agree the demand plan
- Assess forecast accuracy and bias and recommend which forecast methods to rely on
- Oversee an automated or AI system in operational use and correct, restrict or withdraw faulty outputs
Where people get stuck
- Designing and comparing decision scenarios
- Diagnosing forecast accuracy and bias and comparing methods fairly
All skills
- Designing and comparing decision scenarios
- Diagnosing forecast accuracy and bias and comparing methods fairly
- Forecasting business trends and turning points for planning
- Forecasting operational demand at interval and site grain
- Analysing error patterns and failure modes in models and AI systems
- Analysing event sequences, states and durations
- Analysing queue behaviour, capacity and service constraints
- Assessing data source credibility and fitness for a question
- Assessing data-driven fairness and bias
- Assessing data-service continuity and recoverability
- Assessing privacy risk through data protection impact assessments
- Assessing supplier dependency, data-handling and exit risk
- Balancing territories and quotas from account potential
- Building driver-based financial forecasts
- Calculating and interpreting percentages, rates and ratios
- Challenging probability-weighted sales forecasts
- Choosing and justifying missing-data treatments
- Classifying AI uses against regulatory obligations
- Communicating quantified uncertainty
- Comparing groups
- Converting demand into capacity requirements
- Decomposing one's own tasks for AI assistance
- Describing distributions with summaries and plots
- Designing and interpreting hypothesis tests
- Designing efficient and reproducible investigations
- Diagnosing incorrect query and calculation results
- 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
- Estimating quantities and differences with intervals
- Evaluating fitness and full cost of AI-assisted work
- Evaluating responsible AI use risks
- Evaluating service performance and quality trade-offs
- Exercising human oversight of automated and AI outputs
- Explaining control types, dependencies and compensating controls
- Explaining how business events flow into accounting records
- Exploring data to find patterns that survive validation
- Giving specific developmental feedback on data and AI work
- Independently checking analytical conclusions and claims
- Interpreting averages, weighted measures and mix effects
- Interpreting trends and seasonality
- Investigating anomalies
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether a change exceeds normal variation
- Judging whether and how to use AI for a task
- Making accountable decisions under uncertainty
- Monitoring model fitness and drift
- Profiling data
- Rating risks against appetite and choosing proportionate treatment
- Reading business metrics
- Reading charts and dashboards correctly, including their state
- Recognising and containing suspected personal data breaches
- Recognising cybersecurity threats to data work
- Recognising personal data and privacy duties
- Selecting charts for evidence and decisions
- Specifying AI transparency and explanation duties to affected people
- Standardising and cleaning data under agreed rules
- Testing competing explanations with discriminating evidence
- Verifying AI-assisted outputs against sources
- Verifying reports and dashboards before and after release
- Writing evidence-led findings and auditable recommendations with their limits
All tools
- Anaplan
- SAP Integrated Business Planning (IBP) and APO
- RELEX
- Blue Yonder
- Kinaxis RapidResponse
- Microsoft Excel
- Microsoft PowerPoint
- Python
- Microsoft Power BI
Paths to start
Tool Path
Excel for Analysis and Decision Models
Build and check Excel workbooks others can trust.
- Modules
- 5 open
- Runs in
- Your browser
Skill Path
Forecasting and Scenario Planning
Build and challenge planning forecasts and scenarios.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Responsible AI Governance and Assurance
Govern and assure AI across its lifecycle including third-party AI and redress.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonService Operations Analytics and Capacity Planning
About the role
Accountable for the statistical demand forecast, its accuracy and the team of demand planners who produce it. Decides forecast methods and overrides and represents the demand plan in sales and operations planning. Data judgement sits in testing forecasts against actuals and judging when market signals justify a change, where an Operations Manager runs a unit rather than a forecast.
Also called Demand Planning Lead (when the role manages a team), S&OP Manager