Module 1
Model Architecture, Assumptions and Value Drivers
- Decision framing and model purpose
- Inputs, calculations, outputs and control checks
- Revenue, cost and operational drivers
- Assumption documentation and version discipline
Decision Analytics Flagship
Financial Modelling and Decision Analytics
Build transparent financial and decision models that connect value drivers, cash flows, scenarios, risk and strategic alternatives.
Course overview
Use models to clarify decisions—not to disguise assumptions.
Financial Modelling and Decision Analytics develops disciplined modelling practice for business cases, investments, projects and strategic choices.
Participants structure assumptions, value drivers and cash flows; evaluate time value of money and investment measures; test scenarios and sensitivities; and incorporate uncertainty into decision analysis.
The course emphasises model transparency, auditability, decision logic and communication so stakeholders can understand what drives the result and where judgement remains necessary.
Learning outcomes
What participants will be able to do.
- Design a clear financial-model architecture with inputs, logic and outputs.
- Model revenues, costs, cash flows and value drivers.
- Apply discounting, NPV and related investment measures appropriately.
- Build scenarios and perform one-way and multi-variable sensitivity analysis.
- Use break-even and threshold analysis to clarify decision conditions.
- Incorporate risk-adjusted assumptions and simulation concepts.
- Compare strategic alternatives using structured decision criteria.
- Review model integrity and communicate findings to decision-makers.
Who should attend
Designed for professionals who use data, analysis or evidence to improve decisions.
- Finance business partners and FP&A professionals.
- Business and investment analysts.
- Project, programme and portfolio professionals.
- Commercial and strategy teams.
- Managers responsible for business cases and investment decisions.
Prerequisites
Professionally relevant and application-focused.
Participants should be comfortable with spreadsheets and basic financial concepts. Advanced accounting knowledge is not required.
Course structure
A five-Module journey from analytical understanding to workplace application.
The sequence may be delivered across five days or adapted to another approved format while preserving the learning outcomes and the five connected Modules.
Module 2
Cash Flows and Investment Evaluation
- Incremental cash-flow logic
- Time value of money and discounting
- Net present value and related measures
- Working capital, timing and terminal assumptions
Module 3
Scenario, Sensitivity and Break-Even Analysis
- Base, upside and downside scenarios
- One-way and two-way sensitivity analysis
- Break-even and threshold conditions
- Identifying critical value drivers
Module 4
Risk and Decision Analytics
- Risk-adjusted assumptions
- Probability-weighted outcomes
- Monte Carlo simulation concepts
- Decision trees, alternatives and trade-offs
Module 5
Model QA, Interpretation and Executive Communication
- Formula and logic checks
- Consistency, transparency and auditability
- Decision-focused charts and summaries
- Integrated business-case model and recommendation
Learning experience
Move from understanding to application, production and workplace value.
Understand
Connect concepts with business decisions
Clarify methods, assumptions, evidence requirements and the decision context before applying tools.
Apply
Work through realistic analytical cases
Use datasets, scenarios and decision questions to practise analytical judgement in context.
Produce
Create practical analytical outputs
Develop artefacts that can be adapted to reporting, modelling, governance or decision-support work.
Review
Challenge evidence and analytical choices
Use peer review, validation criteria and facilitated critique to improve analytical reasoning.
Transfer
Apply the learning at work
Identify how to adapt the methods to organisational data, decisions, systems and governance requirements.
Completion requirements
Demonstrate participation, application and professional judgement.
- Participate actively in case discussions, data exercises and analytical workshops.
- Complete the principal analytical or decision-support outputs assigned during the programme.
- Contribute to the integrated case, model, dashboard or application workshop.
- Complete knowledge checks and a workplace application or study plan.
Participant outputs
Leave with practical analytical artefacts.
- Financial-model architecture.
- Value-driver and assumption register.
- Cash-flow and investment evaluation.
- Scenario and sensitivity analysis.
- Risk/decision-analysis worksheet.
- Executive decision recommendation.
Delivery options
Select the learning format that fits your people and analytical environment.
Instructor-led
Live Classroom
Facilitated face-to-face learning with analytical cases, datasets, modelling tasks, discussion and immediate feedback.
Instructor-led
Live Virtual Classroom
Interactive online delivery using collaborative workspaces, data exercises, breakout analysis and guided model development.
Flexible
Blended Learning
A structured combination of preparation, live facilitation, applied assignments, analytical work and follow-up application.
Organisation-specific
Corporate and In-Company
Tailored delivery aligned with organisational datasets, measures, tools, governance, decisions and analytics maturity where appropriate.
Frequently asked questions
Course information and participation.
Is this an accounting course?
No. It focuses on decision-oriented modelling and investment logic rather than financial accounting or statutory reporting.
Will participants build a model?
Yes. The course uses a structured modelling case and produces a decision model with scenarios and analysis.
Does it cover Monte Carlo simulation?
The course introduces simulation concepts and their decision use; the depth and software used can be adapted to the cohort.
Can the course use our business-case template?
Yes. Corporate delivery can incorporate approved organisational modelling standards, templates and investment criteria.
Does completion provide professional certification?
The course develops financial-modelling and decision-analytics capability and may provide an INDENTRA course-completion record where applicable. It is not a third-party certification.
Take the next step
Build models that make value, risk and decision logic transparent.
Discuss a course or tailored modelling programme aligned with your organisation’s investment, project and strategic decision processes.