Decision Intelligence for Corporate Functions: Analytics, Generative AI Briefing and Controls Course

Programme Summary

Decision intelligence for corporate functions is the subject of this two-week training course for heads of corporate support functions and senior managers, ending in a decision intelligence pack for one function. Support functions prepare the analysis and papers on which executives decide, yet evidence is gathered by hand, forecasts are rebuilt each cycle and generative tools are used without agreed checks. The programme moves from a decision inventory to evidence, analytics, forecasting, generative briefing, bias, controls and governance, applied to a function the participant selects. Mars Training Centre UK delivers this programme on decision intelligence for corporate functions to mixed-organisation cohorts.

The Business Case

Corporate functions shape decisions on budgets, people, suppliers and policy, but their papers are often late, uneven in quality and hard to trace back to evidence. Analytics and generative tools can shorten preparation, yet they add risks of invented facts, hidden bias and unclear accountability. Organisations that pair these tools with clear evidence rules, challenge routines and AI governance can brief executives faster and defend what was recommended and why.

• Paper Preparation Time: Falls as evidence, templates and briefing routines are reused across decisions.
• Decision Reversals: Fall as assumptions, scenarios and dissent are recorded before a choice is made.
• Audit Findings on AI Use: Fall as sign-off rules, logs and change control are defined and followed.

Principles and Evidence Base

• ISO/IEC 42001 AI Management System: Its approach to policy, roles and review structures the governance work in Sessions 8 and 9.
• Decision Quality Principles: Framing, alternatives, evidence and commitment to action guide the decision inventory in Session 1 and the challenge routines in Session 6.
• Forecast Accuracy Measurement: Tracking error against outcomes shapes the forecasting and scenario work in Session 4.
• Human Oversight of AI Output: Review of generated content before use frames the briefing checks in Session 5 and the sign-off rules in Session 8.

Intended Participants

• Heads of finance, people and procurement functions who answer to executives for the quality of their analysis.
• Senior managers who prepare decision papers, forecasts and board briefings.
• Legal and administration leaders who handle policy queries, records and case notes.
• Strategy and performance leads who own metrics and management reporting.
• Risk and internal control managers who test how AI-supported work is reviewed.

Typical settings include banks, utilities, manufacturers and government agencies.

Learning Outcomes

1. Participants will be able to construct a decision inventory that ranks corporate decisions by value, risk and evidence need.
2. Participants will be able to evaluate data sources and metrics for quality, definition and confidentiality.
3. Participants will be able to diagnose variances and trends and justify the cause behind them.
4. Participants will be able to prioritise scenarios and test forecasts against recorded assumptions.
5. Participants will be able to design a generative briefing routine with grounding, fidelity checks and human review.
6. Participants will be able to prepare a control and governance set that makes AI-supported decisions auditable.

Programme Structure

Day 1: Decision Intelligence for Corporate Functions: Foundations

Which corporate decisions repay analytical and generative support?

• Decision Inventory Sheet
• Decision Rights Map
• Evidence Quality Scale
• Use Case Screening Grid
• Support Function Value Chain

Day 2: Data and Evidence for Decisions

What evidence does a decision need, and where does it come from?

• Data Source Register
• Metric Definition Sheet
• Data Quality Scorecard
• Evidence Gap Log
• Confidentiality Classification Table

Day 3: Descriptive and Diagnostic Analytics

What happened in the numbers, and why did it happen?

• Variance Analysis Template
• Trend and Seasonality Check
• Root Cause Tree
• Dashboard Design Brief
• Insight Validation Checklist

Day 4: Forecasting and Scenario Analysis

How are future outcomes estimated, and how are those estimates tested?

• Baseline Forecast Model
• Scenario Planning Matrix
• Sensitivity Table
• Forecast Accuracy Review
• Assumption Register

Day 5: Generative AI Briefing Methods

How is a briefing drafted from evidence without inventing facts?

• Briefing Prompt Template
• Source Grounding Rules
• Summary Fidelity Check
• Hallucination Test Set
• Briefing Pack Layout

Day 6: Decision Quality and Bias

How do bias and over-trust distort AI-supported decisions, and how are they challenged?

• Decision Maker Bias Checklist
• Automation Reliance Review
• Pre-Mortem Exercise
• Red Team Challenge Session
• Dissent Recording Form

Day 7: Applications in Finance, People and Procurement

Where do these methods fit in everyday support function decisions?

• Budget Variance Briefing Case
• Workforce Planning Brief
• Supplier Choice Evidence Pack
• Policy Query Triage Case
• Case Note Summary Review

Day 8: Controls, Risk and Assurance

Which controls keep AI-supported decisions accountable and auditable?

• AI Use Control Matrix
• Human Sign-off Rules
• Decision Log Standard
• Prompt and Model Change Control
• Error Escalation Path

Day 9: Governance and Management Standards

How does an AI management standard shape policy, roles and review for AI-supported decisions?

• AI Policy Draft
• Role and Ownership Table
• Procurement Checklist
• Review Cycle Table
• Assurance Report Format

Day 10: Decision Intelligence Pack for One Function

Do the decision inventory, evidence rules, briefing routine and controls work as one routine for one function?

• Applying the Session 1 Decision Inventory Sheet
• Testing the Session 4 Scenario Planning Matrix
• Checking the Session 5 Summary Fidelity Check
• Reviewing the Session 8 Human Sign-off Rules
• Completing the Decision Intelligence Pack

Methodology

The programme uses a structured exercise method built on a shared case of a mid-sized group whose finance, people and procurement functions prepare monthly decision papers by hand. Participants build each artefact on the case, then on a function from their own organisation, with written facilitator feedback in every session and a peer challenge at the end of each week.

• Suggested activity: Rebuilding a decision paper from a source pack and testing every statement against its evidence.
• Suggested activity: Comparing a generated briefing with the source data and logging each unsupported claim.
• Suggested activity: Presenting a control matrix to a mock audit committee.

Capstone Output

Each participant completes a decision intelligence pack for one corporate function. It holds a decision inventory, an evidence and metric register, a forecast and scenario set, a briefing routine with fidelity checks, a control matrix and a governance outline. The pack is used at work to brief executives, start a controlled pilot in the function and set review dates for each tool.

Frequently Asked Questions

Is decision intelligence for corporate functions training suitable for managers without a data background?

Yes. Decision intelligence for corporate functions training uses cases and templates, assuming management experience in a support function but no earlier work building models or using generative tools.

Which standard does decision intelligence for corporate functions training rest on?

Decision intelligence for corporate functions training draws on ISO/IEC 42001, the AI management system standard, applied through the organisation's own governance of decisions and a nominated tool owner for the pack.

How is the pack from decision intelligence for corporate functions training used at work?

You use the decision intelligence pack to brief executives, start a controlled pilot in your function and set review dates for each tool.

How does decision intelligence for corporate functions training differ from general data analytics training?

Decision intelligence for corporate functions training centres on decisions, briefing and controls in support functions, while general data analytics training centres on techniques for working with datasets.