4tasks in this job
15skills it uses
5tools named
The skills this job leans on most
- 1Variance analysisNeeded in 3 of 4 tasks
- 2Analysing business drivers and contributionsNeeded in 3 of 4 tasks
- 3Designing and comparing decision scenariosNeeded in 3 of 4 tasks
- 4Interpreting budgets and planning assumptionsNeeded in 3 of 4 tasks
- 5Building driver-based financial forecastsNeeded in 3 of 4 tasks
ToolsMicrosoft Power BIMicrosoft ExcelMicrosoft 365 CopilotAnaplanJedoxPower QueryExcel VBA and macrosMicrosoft SQL Server (with SSMS)SAP BW and DatasphereSAP S/4HANAMicrosoft PowerPoint
All 4 tasks, where people get stuck and all 15 skills
Tasks
- Investigate variance of actuals against budget or forecast
- Build a scenario-based financial forecast
- Model cash needs and defend a liquidity action
- Prepare a periodic performance or risk report for a management or governance committee
Where people get stuck
All skills
- Analysing business drivers and contributions
- Building driver-based financial forecasts
- Designing and comparing decision scenarios
- Interpreting budgets and planning assumptions
- Variance analysis
- Analysing costs, allocation and margin drivers
- Communicating quantified uncertainty
- Constructing a controlled cash-flow plan
- Designing auditable decision models
- Explaining how business events flow into accounting records
- Forecasting business trends and turning points for planning
- Interpreting averages, weighted measures and mix effects
- Interpreting trends and seasonality
- Interpreting workforce metrics and populations
- Testing competing explanations with discriminating evidence
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
KPI, Variance and Performance Analysis
Explain performance against plan with variance decomposition and driver trees.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Forecasting and Scenario Planning
Build and challenge planning forecasts and scenarios.
- Modules
- 5 open
- Practice data
- Raket Parts
7tasks in this job
68skills it uses
11tools named
The skills this job leans on most
- 1Building driver-based financial forecastsNeeded in 4 of 7 tasks
- 2Variance analysisNeeded in 3 of 7 tasks
- 3Analysing business drivers and contributionsNeeded in 3 of 7 tasks
- 4Designing and comparing decision scenariosNeeded in 3 of 7 tasks
- 5Interpreting budgets and planning assumptionsNeeded in 3 of 7 tasks
ToolsMicrosoft Power BIMicrosoft ExcelMicrosoft 365 CopilotAnaplanJedoxPower Query+ 5 more
All 7 tasks, where people get stuck and all 68 skills
Tasks
- Investigate variance of actuals against budget or forecast
- Build a scenario-based financial forecast
- Answer a commissioned business question with reproducible query-based analysis
- Model cash needs and defend a liquidity action
- Prepare a periodic performance or risk report for a management or governance committee
- Automate a recurring reporting or data task with controls and a named owner
- Assess forecast accuracy and bias and recommend which forecast methods to rely on
Where people get stuck
All skills
- Analysing business drivers and contributions
- Building driver-based financial forecasts
- Designing and comparing decision scenarios
- Interpreting budgets and planning assumptions
- Variance analysis
- Analysing costs, allocation and margin drivers
- Analysing event sequences, states and durations
- 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
- Building data protection by design into data products and pipelines
- Building decision-focused reports and dashboards
- Calculating and interpreting percentages, rates and ratios
- Challenging probability-weighted sales forecasts
- Choosing an analytical method to fit the question and data
- Choosing and justifying missing-data treatments
- Combining tables safely: cardinality, fan-out and conservation of totals
- Communicating quantified uncertainty
- Comparing groups
- Comparing options against explicit decision criteria
- Constructing a controlled cash-flow plan
- Decomposing one's own tasks for AI assistance
- Defining the analysis population: filters, nulls, dates and time zones
- Describing distributions with summaries and plots
- Designing and interpreting hypothesis tests
- Designing auditable decision models
- Designing automated pipelines and processes that fail safely and recover
- Designing efficient and reproducible investigations
- Designing semantic models for governed analytics
- Diagnosing forecast accuracy and bias and comparing methods fairly
- Diagnosing incorrect query and calculation results
- Eliciting the decision behind an analytical request
- Establishing and declaring data grain
- Estimating quantities and differences with intervals
- Explaining how business events flow into accounting records
- Exploring data to find patterns that survive validation
- Fitting, checking and interpreting inferential regression models
- Forecasting business trends and turning points for planning
- Forecasting operational demand at interval and site grain
- Formulating answerable data questions
- Gating releases on evidence with rollback ready
- Identifying and quantifying decision downside and exposure
- Identifying keys and testing referential integrity
- Interpreting averages, weighted measures and mix effects
- Interpreting trends and seasonality
- Interpreting workforce metrics and populations
- Investigating anomalies
- Judging whether a change exceeds normal variation
- Judging whether external evidence applies to the decision context
- Making accountable decisions under uncertainty
- Monitoring data quality and freshness in production
- Preparing analysis-ready datasets reproducibly
- Presenting and defending evidence-based recommendations to decision-makers
- Prioritising work by evidenced value, cost, risk and confidence
- Profiling data
- Reading and tracing unfamiliar code
- Reading charts and dashboards correctly, including their state
- Reasoning about systems, feedback and second-order effects
- Selecting charts for evidence and decisions
- Standardising and cleaning data under agreed rules
- Testing changes to data services and business systems for business meaning and downstream impact
- Testing competing explanations with discriminating evidence
- Testing investment business cases under uncertainty
- Tracing data lineage upstream and downstream
- Training reproducible machine learning models
- Writing evidence-led findings and auditable recommendations with their limits
- Writing maintainable code for analytical and data work
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
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
KPI, Variance and Performance Analysis
Explain performance against plan with variance decomposition and driver trees.
- Modules
- 5 open
- Practice data
- Raket Parts
7tasks in this job
78skills it uses
10tools named
The skills this job leans on most
- 1Forecasting business trends and turning points for planningNeeded in 4 of 7 tasks
- 2Building driver-based financial forecastsNeeded in 4 of 7 tasks
- 3Diagnosing forecast accuracy and bias and comparing methods fairlyNeeded in 4 of 7 tasks
- 4Designing and comparing decision scenariosNeeded in 3 of 7 tasks
ToolsMicrosoft Dynamics 365 Finance and OperationsOracle NetSuiteMicrosoft ExcelAnaplanOracle Hyperion and Oracle EPM Cloud (Planning, HFM, FCCS, EPBCS)Microsoft PowerPoint+ 4 more
All 7 tasks, where people get stuck and all 78 skills
Tasks
- Investigate variance of actuals against budget or forecast
- Build a scenario-based financial forecast
- Model cash needs and defend a liquidity action
- Prepare a periodic performance or risk report for a management or governance committee
- Automate a recurring reporting or data task with controls and a named owner
- Assess forecast accuracy and bias and recommend which forecast methods to rely on
- Set and maintain working standards for a team's analytical, reporting and modelling work products
Where people get stuck
- Building driver-based financial forecasts
- Diagnosing forecast accuracy and bias and comparing methods fairly
All skills
- Building driver-based financial forecasts
- Designing and comparing decision scenarios
- Diagnosing forecast accuracy and bias and comparing methods fairly
- Forecasting business trends and turning points for planning
- Analysing business drivers and contributions
- Analysing costs, allocation and margin drivers
- Analysing event sequences, states and durations
- Analysing pay equity with raw and adjusted pay gaps
- Analysing working-capital drivers and cash conversion
- Applying data classification and handling rules
- Appraising options on a common incremental basis against a do-nothing baseline
- Assessing data source credibility and fitness for a question
- Building data protection by design into data products and pipelines
- Building decision-focused reports and dashboards
- Calculating and interpreting percentages, rates and ratios
- Challenging probability-weighted sales forecasts
- Choosing an analytical method to fit the question and data
- Choosing and justifying missing-data treatments
- Combining tables safely: cardinality, fan-out and conservation of totals
- Communicating quantified uncertainty
- Comparing groups
- Comparing options against explicit decision criteria
- Constructing a controlled cash-flow plan
- Decomposing one's own tasks for AI assistance
- Defining the analysis population: filters, nulls, dates and time zones
- Describing distributions with summaries and plots
- Designing and interpreting hypothesis tests
- Designing auditable decision models
- Designing automated pipelines and processes that fail safely and recover
- Designing efficient and reproducible investigations
- Designing semantic models for governed analytics
- Diagnosing incorrect query and calculation results
- 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 quantities and differences with intervals
- Explaining how business events flow into accounting records
- Exploring data to find patterns that survive validation
- Fitting, checking and interpreting inferential regression models
- Forecasting operational demand at interval and site grain
- Formulating answerable data questions
- Gating releases on evidence with rollback ready
- 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
- Investigating anomalies
- 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
- Making accountable decisions under uncertainty
- Monitoring data quality and freshness in production
- Preparing analysis-ready datasets reproducibly
- Presenting and defending evidence-based recommendations to decision-makers
- Prioritising work by evidenced value, cost, risk and confidence
- Profiling data
- Reading and tracing unfamiliar code
- Reading charts and dashboards correctly, including their state
- Reasoning about systems, feedback and second-order effects
- Sampling and reviewing a team's work against standards
- Selecting charts for evidence and decisions
- Standardising and cleaning data under agreed rules
- Testing changes to data services and business systems for business meaning and downstream impact
- Testing competing explanations with discriminating evidence
- Testing investment business cases under uncertainty
- Tracing data lineage upstream and downstream
- Training reproducible machine learning models
- Variance analysis
- Verifying AI-assisted outputs against sources
- Verifying reports and dashboards before and after release
- Writing evidence-led findings and auditable recommendations with their limits
- Writing maintainable code for analytical and data work
All tools
- Microsoft Dynamics 365 Finance and Operations
- Oracle NetSuite
- Microsoft Excel
- Anaplan
- Oracle Hyperion and Oracle EPM Cloud (Planning, HFM, FCCS, EPBCS)
- Microsoft PowerPoint
- Excel VBA and macros
- Power Query
- Microsoft Power BI
- Jedox
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
Exploratory Data Analysis and Pattern Discovery
Describe a distribution honestly and decide which unusual records need checking before anyone acts.
- Modules
- 5 open
- Practice data
- Raket Parts
Tool Path
Excel for Analysis and Decision Models
Build and check Excel workbooks others can trust.
- Modules
- 5 open
- Runs in
- Your browser
About the role
Accountable for forecasts, scenarios, forecast-to-actual variance and cash-need analysis that inform financial decisions. Decides which drivers and assumptions a forecast rests on and how uncertainty is shown. Differs from Management Accountant by looking forward rather than explaining actuals.
Also called Financial Analyst, Finance Analyst