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CourseAerospace, UAM, Drones & Space Applications open

Course in What-If Scenario Planning

Online course of 300 hours in what-if scenario planning, with 6 modules covering scenario building, system modelling, sensitivity analysis and Monte Carlo simulation, decision optimisation and plan monitoring, with an assigned technical tutor.

Duration3 months
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Run a real engineering trade-off from this programme. Move the sliders, watch the model react in real time and beat the challenge.

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Learning outcomes

What you will be able to do

01

Build coherent planning scenarios.

02

Model a system with its variables and constraints.

03

Carry out what-if and sensitivity analyses.

04

Formulate optimisation problems for decision-making.

05

Quantify uncertainty through simulation.

06

Set indicators for monitoring decisions.

07

Draw up a scenario-based plan for a real case.

Profile

Who it's for

  • Planning analysts who want to specialise in what-if scenario planning.
  • Operations research analysts who want to specialise in what-if scenario planning.
  • Strategy consultants who want to specialise in what-if scenario planning.
  • Operations planners who want to specialise in what-if scenario planning.
  • Risk analysts who want to specialise in what-if scenario planning.
  • Capacity planning managers who want to specialise in what-if scenario planning.
  • Engineering or science graduates looking to move into air transport.
Standards & tools

What you'll work with

  • ISO 31000 (risk management)
  • IEC 31010 (risk assessment techniques)
  • ISO 22301 (business continuity)
  • ISO 21500 (project management)
  • ISO 55000 (asset management)
  • ISO 9001 (quality management)
  • Advanced Excel (Solver)
  • Python (pandas, PuLP)
  • AnyLogic
  • Power BI
  • Gurobi
Syllabus

6 modules

  1. 1.1. Difference between a forecast and a scenario
  2. 1.2. Structural versus random uncertainty
  3. 1.3. Planning horizon and granularity
  4. 1.4. Critical variables and drivers of change
  5. 1.5. Building coherent scenarios
  6. 1.6. Base, optimistic and adverse scenarios
  7. 1.7. Common biases in planning
  8. 1.8. Governance of the scenario process
  9. 1.9. Communicating scenarios to management
  10. 1.10. Workshop: defining a scenario framework
  1. 2.1. Identifying decision variables
  2. 2.2. Cause-and-effect relationships and feedback loops
  3. 2.3. Well-structured spreadsheet models
  4. 2.4. Separating data, logic and results
  5. 2.5. Capacity and resource constraints
  6. 2.6. Fixed, variable and stepped costs
  7. 2.7. Validating the model with historical data
  8. 2.8. Model documentation and auditing
  9. 2.9. Version control
  10. 2.10. Laboratory: capacity model
  1. 3.1. One-variable analysis and tornado charts
  2. 3.2. Data tables and multiple scenarios
  3. 3.3. Break-even points and thresholds
  4. 3.4. Elasticities and lever variables
  5. 3.5. Monte Carlo simulation
  6. 3.6. Distributions and correlations
  7. 3.7. Interpreting percentiles
  8. 3.8. Risk of ruin and tails
  9. 3.9. Visual communication of uncertainty
  10. 3.10. Laboratory: simulating an annual plan
  1. 4.1. Formulating an optimisation problem
  2. 4.2. Objective functions and constraints
  3. 4.3. Applied linear programming
  4. 4.4. Resource allocation and product mix
  5. 4.5. Shift and capacity planning
  6. 4.6. Optimisation under uncertainty
  7. 4.7. Dual value analysis
  8. 4.8. Practical limits of optimisation
  9. 4.9. Available tools
  10. 4.10. Laboratory: optimal resource allocation
  1. 5.1. Decision criteria under uncertainty
  2. 5.2. Value of additional information
  3. 5.3. Real options and deferrable decisions
  4. 5.4. Leading indicators and triggers
  5. 5.5. Contingency plan by scenario
  6. 5.6. Periodic review and recalibration
  7. 5.7. Responsibilities and monitoring committee
  8. 5.8. Decision log and learning
  9. 5.9. Common mistakes when executing the plan
  10. 5.10. Workshop: table of triggers
  1. 6.1. Defining the case and key questions
  2. 6.2. Building the scenarios
  3. 6.3. Quantitative model and validation
  4. 6.4. Sensitivity analysis and simulation
  5. 6.5. Recommendation and contingency plan
  6. 6.6. Monitoring indicators
  7. 6.7. Presentation to management
  8. 6.8. Model documentation
  9. 6.9. Final report
  10. 6.10. Review with the tutor
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, so it can be combined with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is advanced Excel (Solver), Python (pandas, PuLP), AnyLogic, Power BI and Gurobi, in free, academic or evaluation versions. Testing is studied through real procedures for planning cases with real data and sensitivity analysis. Assessment is continuous by module, plus the final project.

Standards covered: ISO 31000, IEC 31010, ISO 22301, ISO 21500, ISO 55000, ISO 9001.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of ISO 31000, IEC 31010 and ISO 22301 applied to real cases.
Industry software:advanced Excel (Solver), Python (pandas, PuLP), AnyLogic, Power BI and Gurobi, in free, academic or evaluation versions.
Final project:a scenario-based plan for a real case, with quantitative model, sensitivity analysis, simulation, contingency plan and monitoring indicators, reviewed by your tutor.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Scenario framework
Define a scenario framework with key questions, critical variables and drivers of change.
Capacity model
Build and validate a well-structured capacity model with historical data.
Annual plan simulation
Run a Monte Carlo simulation of an annual plan and interpret its percentiles.
Optimal resource allocation
Solve an optimal resource allocation problem and build a table of triggers.
Final project
Present a complete scenario-based plan with recommendation, contingency plan and monitoring indicators to management.
Career opportunities

Where this takes you

Planning analystOperations research analystStrategy consultantOperations plannerRisk analystCapacity planning manager
Admissions & scholarships

Requirements

  • No previous qualification is required.
  • An internet connection and a computer capable of running the programme software.
  • English sufficient to read technical standards.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The course totals 300 hours over 3 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You will work with advanced Excel (Solver), Python (pandas, PuLP), AnyLogic, Power BI and Gurobi. Free, academic or evaluation versions are used, and your tutor indicates the free alternative where one exists.

A SEIUM Institute certificate, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.

Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.

No previous qualification is required. You need an internet connection, a computer capable of running the programme software, and English sufficient to read technical standards.

Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.

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