Certificate in Business Decision Models
- Structure a business decision by defining objectives, alternatives, constraints and uncertainties.
- Apply weighted scoring and multi-criteria analysis to compare options such as supplier or site selection.
- Build a decision tree and calculate expected monetary value for a decision under uncertainty.
- Formulate and solve a resource allocation problem using linear programming with Excel Solver.
- Run sensitivity and Monte Carlo analysis to test how input assumptions affect a recommendation.
- Present model results with stated assumptions and limitations to decision makers.
- Framing Decisions
- Decision types: strategic, tactical and operational
- Objectives, alternatives, constraints and uncertainties
- Common cognitive biases in managerial decisions
- Multi-Criteria Decision Models
- Weighted scoring and decision matrices
- Analytic Hierarchy Process (AHP) for pairwise comparison
- Handling qualitative criteria and stakeholder weights
- Decisions Under Risk and Uncertainty
- Payoff tables and maximin, maximax and regret criteria
- Decision trees and expected monetary value
- Value of perfect information
- Optimisation Models
- Linear programming formulation for resource allocation
- Solving with Excel Solver and reading sensitivity reports
- Applications in staffing, production mix and budget allocation
- Simulation and Sensitivity Analysis
- What-if and scenario analysis
- Monte Carlo simulation of uncertain inputs
- Tornado charts and break-even thresholds
- From Model to Recommendation
- Validating model logic and data quality
- Communicating assumptions, ranges and limitations
- Embedding decision models in approval processes
Get the Brochure
To receive a brochure with the full course content, please complete the following form with your correct details

Program Professional Framework
Certificate in Business Decision Models
Program Overview
Managers increasingly face decisions where intuition alone is not enough: capacity investments, supplier selection, pricing and resource allocation under budget limits. This program introduces practical quantitative decision models and shows when each applies, from weighted scoring and the Analytic Hierarchy Process to decision trees with expected value, linear programming for allocation, Monte Carlo simulation and sensitivity analysis. Participants build models in Excel, test assumptions, and translate outputs into clear recommendations that executive committees in Gulf public and private organizations can scrutinise and approve.
Learning Outcomes
- ✓Structure a business decision by defining objectives, alternatives, constraints and uncertainties.
- ✓Apply weighted scoring and multi-criteria analysis to compare options such as supplier or site selection.
- ✓Build a decision tree and calculate expected monetary value for a decision under uncertainty.
- ✓Formulate and solve a resource allocation problem using linear programming with Excel Solver.
- ✓Run sensitivity and Monte Carlo analysis to test how input assumptions affect a recommendation.
- ✓Present model results with stated assumptions and limitations to decision makers.
Target Audience
- Managers and section heads responsible for investment or resource decisions
- Business, financial and planning analysts
- Operations, supply chain and project planners
- Strategy and performance office staff
Detailed Program Modules
01Framing Decisions
- Decision types: strategic, tactical and operational
- Objectives, alternatives, constraints and uncertainties
- Common cognitive biases in managerial decisions
02Multi-Criteria Decision Models
- Weighted scoring and decision matrices
- Analytic Hierarchy Process (AHP) for pairwise comparison
- Handling qualitative criteria and stakeholder weights
03Decisions Under Risk and Uncertainty
- Payoff tables and maximin, maximax and regret criteria
- Decision trees and expected monetary value
- Value of perfect information
04Optimisation Models
- Linear programming formulation for resource allocation
- Solving with Excel Solver and reading sensitivity reports
- Applications in staffing, production mix and budget allocation
05Simulation and Sensitivity Analysis
- What-if and scenario analysis
- Monte Carlo simulation of uncertain inputs
- Tornado charts and break-even thresholds
06From Model to Recommendation
- Validating model logic and data quality
- Communicating assumptions, ranges and limitations
- Embedding decision models in approval processes
Training Methodology
Applied Project & Assessment
Applied Project
Participants select a real decision from their organization, such as fleet replacement, vendor selection or budget allocation across programs, build an Excel model combining at least two techniques covered, run sensitivity tests and present a recommendation memo to a simulated executive committee.
Assessment
Short diagnostic at the start, practical tasks linked to each learning outcome, and evaluation of the applied project against published criteria.


