3tasks in this job
35skills it uses
3tools named
The skills this job leans on most
- 1Writing evidence-led findings and auditable recommendations with their limitsNeeded in 1 of 3 tasks
- 2Presenting and defending evidence-based recommendations to decision-makersNeeded in 1 of 3 tasks
- 3Testing the completeness and accuracy of reports and data that controls rely onCore to this role
ToolsSAP S/4HANAMicrosoft PowerPointEcoVadisWorldfavorMicrosoft ExcelMicrosoft Power BISAP AribaCoupa
All 3 tasks, where people get stuck and all 35 skills
Tasks
- Review supplier performance against contract obligations and recommend renewal or remedy
- Prepare a periodic performance or risk report for a management or governance committee
- Assess supplier risk and maintain the supplier risk register
Where people get stuck
- Identifying and quantifying decision downside and exposure
- Evaluating supplier total cost and value
- Interpreting supplier contract duties, terms and exposure
All skills
- Writing evidence-led findings and auditable recommendations with their limits
- Assessing supplier dependency, data-handling and exit risk
- Assessing the control and reliability of end-user calculation files
- Building decision-focused reports and dashboards
- Communicating sensitive or unwelcome analytical findings
- Comparing options against explicit decision criteria
- Constructing clear and honest charts
- Diagnosing misleading data visualisations
- Disclosing AI contribution to professional work
- Escalating unresolved risks with evidence and clear ownership
- Estimating quantities and differences with intervals
- Evaluating and improving chart accessibility
- Evaluating supplier total cost and value
- 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 supplier contract duties, terms and exposure
- Interpreting sustainability reporting standards and metric boundaries
- Investigating procurement spend leakage and duplicate commitments
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether a change exceeds normal variation
- Making accountable decisions under uncertainty
- Mapping entity results and eliminating intercompany balances in consolidation
- Monitoring and testing data control effectiveness
- Rating risks against appetite and choosing proportionate treatment
- 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
- Tracing data lineage upstream and downstream
- Writing verifiable requirements and acceptance criteria
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
Evidence-based Briefing and Influence
Brief and influence accountable decision-makers with evidence, its limits and unwelcome findings, and check the message landed.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Business Data Controls and Reconciliation
Design, test and operate controls and reconciliations.
- Modules
- 5 open
- Practice data
- Raket Parts
5tasks in this job
54skills it uses
8tools named
The skills this job leans on most
- 1Rating risks against appetite and choosing proportionate treatmentNeeded in 4 of 5 tasks
- 2Evaluating supplier total cost and valueNeeded in 3 of 5 tasks
- 3Interpreting supplier contract duties, terms and exposureNeeded in 3 of 5 tasks
- 4Assessing supplier dependency, data-handling and exit riskNeeded in 3 of 5 tasks
- 5Identifying and quantifying decision downside and exposureNeeded in 2 of 5 tasks
ToolsSAP S/4HANAMicrosoft PowerPointEcoVadisWorldfavorMicrosoft ExcelMicrosoft Power BI+ 2 more
All 5 tasks, where people get stuck and all 54 skills
Tasks
- Review supplier performance against contract obligations and recommend renewal or remedy
- Prepare a periodic performance or risk report for a management or governance committee
- Assess supplier risk and maintain the supplier risk register
- Develop a category strategy from spend, market and supplier evidence
- Oversee an automated or AI system in operational use and correct, restrict or withdraw faulty outputs
Where people get stuck
- Setting and reviewing action thresholds for scores and model predictions
- Escalating unresolved risks with evidence and clear ownership
- Exercising human oversight of automated and AI outputs
All skills
- Assessing supplier dependency, data-handling and exit risk
- Evaluating supplier total cost and value
- Identifying and quantifying decision downside and exposure
- Interpreting supplier contract duties, terms and exposure
- Rating risks against appetite and choosing proportionate treatment
- Analysing error patterns and failure modes in models and AI systems
- Analysing supply markets and choosing a sourcing route
- Assessing data-driven fairness and bias
- Assessing data-service continuity and recoverability
- Assessing privacy risk through data protection impact assessments
- Assessing the control and reliability of end-user calculation files
- Building decision-focused reports and dashboards
- Classifying AI uses against regulatory obligations
- Classifying spend to a category taxonomy and maintaining a trusted baseline
- Communicating sensitive or unwelcome analytical findings
- Comparing options against explicit decision criteria
- Constructing clear and honest charts
- Designing and applying governed tender evaluation criteria
- Diagnosing misleading data visualisations
- Disclosing AI contribution to professional work
- Escalating unresolved risks with evidence and clear ownership
- Estimating quantities and differences with intervals
- Evaluating and improving chart accessibility
- Evaluating fitness and full cost of AI-assisted work
- Evaluating responsible AI use risks
- Exercising human oversight of automated and AI outputs
- Explaining control types, dependencies and compensating controls
- Explaining technical work to accountable non-specialists
- Independently checking analytical conclusions and claims
- Interpreting correlation without inferring cause
- Interpreting sustainability reporting standards and metric boundaries
- Investigating anomalies
- Investigating procurement spend leakage and duplicate commitments
- 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
- Mapping entity results and eliminating intercompany balances in consolidation
- Monitoring and testing data control effectiveness
- Monitoring model fitness and drift
- Reading charts and dashboards correctly, including their state
- Recognising and containing suspected personal data breaches
- Recognising and resolving ethical conflicts in data and AI work
- Recognising cybersecurity threats to data work
- Recognising misleading numerical claims
- Recognising personal data and privacy duties
- Reconciling finance subledgers and close records
- Revising prior decisions when evidence changes
- Selecting charts for evidence and decisions
- Specifying AI transparency and explanation duties to affected people
- Testing competing explanations with discriminating evidence
- Tracing data lineage upstream and downstream
- Writing evidence-led findings and auditable recommendations with their limits
- Writing verifiable requirements and acceptance criteria
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
Procurement, Spend and Supplier Analytics
Analyse spend, contract exposure and supplier value.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Business Data Controls and Reconciliation
Design, test and operate controls and reconciliations.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonFinancial Modelling and Decision Support
7tasks in this job
73skills it uses
7tools named
The skills this job leans on most
- 1Escalating unresolved risks with evidence and clear ownershipNeeded in 7 of 7 tasks
- 2Assessing supplier dependency, data-handling and exit riskNeeded in 4 of 7 tasks
- 3Identifying and quantifying decision downside and exposureNeeded in 3 of 7 tasks
- 4Evaluating supplier total cost and valueNeeded in 3 of 7 tasks
- 5Setting and reviewing action thresholds for scores and model predictionsCore to this role
ToolsSAP S/4HANAMicrosoft PowerPointMicrosoft Power BISAP AribaMicrosoft ExcelEcoVadis+ 1 more
All 7 tasks, where people get stuck and all 73 skills
Tasks
- Review supplier performance against contract obligations and recommend renewal or remedy
- Prepare a periodic performance or risk report for a management or governance committee
- Design and govern the operating model for data, analytics and AI work in a function
- Maintain a data and AI risk register and record risk treatment and acceptance
- Assess supplier risk and maintain the supplier risk register
- Develop a category strategy from spend, market and supplier evidence
- Oversee an automated or AI system in operational use and correct, restrict or withdraw faulty outputs
Where people get stuck
- Setting and reviewing action thresholds for scores and model predictions
- Identifying and quantifying decision downside and exposure
- Evaluating supplier total cost and value
All skills
- Assessing supplier dependency, data-handling and exit risk
- Escalating unresolved risks with evidence and clear ownership
- Evaluating supplier total cost and value
- Identifying and quantifying decision downside and exposure
- Analysing error patterns and failure modes in models and AI systems
- Analysing supply markets and choosing a sourcing route
- Applying data classification and handling rules
- Appraising options on a common incremental basis against a do-nothing baseline
- Assessing data-driven fairness and bias
- Assessing data-service continuity and recoverability
- Assessing privacy risk through data protection impact assessments
- Assessing the control and reliability of end-user calculation files
- Assigning and operating data ownership and stewardship
- Building decision-focused reports and dashboards
- Classifying AI uses against regulatory obligations
- Classifying spend to a category taxonomy and maintaining a trusted baseline
- Communicating quantified uncertainty
- Communicating sensitive or unwelcome analytical findings
- Comparing options against explicit decision criteria
- Constructing clear and honest charts
- Designing and applying governed tender evaluation criteria
- Designing and comparing decision scenarios
- Diagnosing misleading data visualisations
- Disclosing AI contribution to professional work
- Eliciting the decision behind an analytical request
- Enforcing and auditing data access
- Estimating quantities and differences with intervals
- Evaluating and improving chart accessibility
- Evaluating fitness and full cost of AI-assisted work
- Evaluating responsible AI use risks
- Exercising human oversight of automated and AI outputs
- Explaining control types, dependencies and compensating controls
- Explaining technical work to accountable non-specialists
- Facilitating group decisions using disputed evidence
- Giving specific developmental feedback on data and AI work
- Governing shared data definitions
- Identifying and prioritising critical data elements
- Independently checking analytical conclusions and claims
- Interpreting correlation without inferring cause
- Interpreting supplier contract duties, terms and exposure
- Interpreting sustainability reporting standards and metric boundaries
- Investigating anomalies
- Investigating procurement spend leakage and duplicate commitments
- 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
- Judging whether external evidence applies to the decision context
- Making accountable decisions under uncertainty
- Mapping entity results and eliminating intercompany balances in consolidation
- Mapping stakeholders' decisions, constraints and needs
- Monitoring and testing data control effectiveness
- Monitoring model fitness and drift
- Presenting and defending evidence-based recommendations to decision-makers
- Preserving incident evidence and timeline
- Rating risks against appetite and choosing proportionate treatment
- Reading charts and dashboards correctly, including their state
- Reasoning about systems, feedback and second-order effects
- Recognising and containing suspected personal data breaches
- Recognising and resolving ethical conflicts in data and AI work
- Recognising cybersecurity threats to data work
- Recognising misleading numerical claims
- Recognising personal data and privacy duties
- Recognising statutory incident reporting duties and deadlines
- Reconciling finance subledgers and close records
- Revising prior decisions when evidence changes
- Selecting charts for evidence and decisions
- Specifying AI transparency and explanation duties to affected people
- Testing competing explanations with discriminating evidence
- Tracing data lineage upstream and downstream
- 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 verifiable requirements and acceptance criteria
All tools
- SAP S/4HANA
- Microsoft PowerPoint
- Microsoft Power BI
- SAP Ariba
- Microsoft Excel
- EcoVadis
- Coupa
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
Procurement, Spend and Supplier Analytics
Analyse spend, contract exposure and supplier value.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonFinancial Modelling and Decision SupportMachine Learning: from Data to Validated Models and Decisions
About the role
Accountable for procurement's operating model, supplier risk, spend investment and contract performance across the organisation. Heads the procurement managers and decides which supplier risks the organisation accepts and how procurement is organised. Data and AI judgement sits in using spend and supplier data to set priorities and in governing automated buying tools.