Management Decision Analysis Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends Department Managers, Programme and Project Managers and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 7 Nov 2026 Course code SD-EM-079

Before you join: Participants should have experience contributing to management discussions, business cases, operational planning, projects, budgets or improvement initiatives.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Management decisions often combine incomplete evidence, competing stakeholder priorities, financial consequences and uncertain future outcomes. Managers may need to recommend a capital investment, service redesign, supplier choice, policy change or risk response within a short approval window. Poorly framed decisions can produce unclear accountability, hidden assumptions, weak business cases and commitments that are difficult to reverse.

This course teaches a disciplined approach to analysing management decisions before resources are committed. Participants learn to frame the decision, define measurable objectives, identify alternatives, assess evidence quality and select proportionate analytical methods. The course covers decision matrices, multi-criteria decision analysis, financial evaluation, probability, decision trees, scenario planning, sensitivity analysis and common cognitive biases. Participants also learn how to document assumptions, challenge preferred options and communicate recommendations to executives and governance bodies.

Instructor-led sessions combine short briefings with realistic management cases from investment, operations, procurement, public services and programme delivery. Participants work with decision memos, scoring models, cash-flow calculations, risk scenarios and approval papers, then apply the methods to a current decision from their own role where appropriate. Each participant leaves with a reusable decision analysis toolkit, a structured decision charter and an approval-ready recommendation format. A certificate of completion is issued after the course.

The course is suited to managers and specialists who prepare recommendations, evaluate options, approve business cases or contribute evidence to significant operational and strategic decisions.

What you will be able to do

  • Frame management decisions using objectives, alternatives, constraints and decision rights
  • Construct weighted decision matrices with defensible criteria and scoring rules
  • Assess evidence quality using data checks, base rates and assumption registers
  • Evaluate investment options using cash flow, NPV, payback and break-even analysis
  • Model uncertainty using probability estimates, decision trees and sensitivity analysis
  • Apply multi-criteria decision analysis to choices with conflicting objectives
  • Challenge recommendations using bias controls, pre-mortems and structured dissent
  • Prepare decision memos that state evidence, trade-offs, risks and approval requirements

Benefits of attending

For you

  • Produce clearer recommendations for managers, boards and approval committees
  • Identify hidden assumptions before they become costly delivery problems
  • Select analysis methods proportionate to decision value and uncertainty
  • Defend recommendations when stakeholders disagree on priorities or evidence
  • Build a documented record of reasoning for future review and accountability

For your organisation

  • Improve consistency of business cases, investment proposals and operational approvals
  • Reduce decisions based on unsupported assumptions or dominant stakeholder views
  • Expose financial, delivery and risk trade-offs before resources are committed
  • Create clearer audit trails for material decisions and delegated authorities
  • Increase confidence in recommendations involving competing objectives and uncertainty

Course modules

10 modules over 5 days

Participants can define a decision clearly, establish authority and distinguish the decision from its surrounding problem.

  • Decision framing separates symptoms, choices, constraints, stakeholders and decision authority
  • Problem statements specify measurable objectives, boundaries, time horizon and ownership
  • Stakeholder mapping identifies approvers, advisers, affected parties and conflicting interests
  • Distinguish strategic, tactical, operational and programmed decisions by consequence and reversibility
  • Decision rights mapped through RACI for accountable escalation and approval routes
  • Value-focused thinking converts stated positions into fundamental and means objectives

Participants can define decision criteria and compare alternatives using transparent scoring rules.

  • SMART criteria define performance measures, thresholds, direction and acceptable trade-offs
  • Criteria trees separate objectives, attributes, measures and supporting subcriteria
  • Weighting methods compare swing weights, direct rating and pairwise judgments
  • Independence tests prevent double-counting correlated criteria within scorecards
  • Construct decision matrices with consistent scales, evidence sources and owners
  • Document assumptions and scoring rules before comparing alternatives

Participants can assess the reliability, relevance and limits of evidence used in management decisions.

  • Evidence hierarchies distinguish audited data, operational records, expert judgment and opinion
  • Data-quality checks assess completeness, accuracy, timeliness, consistency and lineage
  • Base-rate thinking counters conclusions drawn from vivid but unrepresentative cases
  • Separate leading indicators from lagging indicators when testing causal claims
  • Sensitivity registers record uncertain inputs, ranges, sources and update triggers
  • Visualise distributions with histograms, box plots and cumulative probability curves

Participants can interpret quantitative evidence and build simple forecasts for decision purposes.

  • Descriptive statistics summarise central tendency, dispersion, skewness and outliers
  • Correlation analysis identifies association without claiming causation or forecast validity
  • Regression outputs interpreted using coefficients, residuals, confidence intervals and fit
  • Forecast error measured through MAE, MAPE and root mean square error
  • Scenario forecasts distinguish baseline, upside, downside and stress-case assumptions
  • Spreadsheet model audits trace formulas, inputs, units, versions and controls

Participants can compare alternatives using relevant costs, cash flow and investment appraisal methods.

  • Incremental cash-flow analysis separates relevant costs, sunk costs and opportunity costs
  • Net present value compares alternatives using explicit discount rates and timing
  • Internal rate of return limitations examined for mutually exclusive investments
  • Payback and discounted payback expose liquidity timing and recovery periods
  • Break-even analysis tests volume, price, fixed-cost and contribution assumptions
  • Cost-benefit analysis records monetised effects, non-monetised impacts and distributional consequences

Participants can model uncertain outcomes and judge the financial and operational implications of risk.

  • Probability assessments use frequency data, calibration questions and structured expert judgment
  • Expected monetary value combines outcome probabilities, payoffs and decision choices
  • Decision trees represent sequential choices, chance events, branches and terminal values
  • Bayes' theorem updates prior probabilities after diagnostic evidence arrives
  • Monte Carlo simulation estimates outcome ranges from uncertain input distributions
  • Risk appetite statements set escalation thresholds for material downside exposure

Participants can evaluate options systematically when financial, operational, social and risk criteria conflict.

  • Multi-criteria decision analysis combines weighted evidence across competing objectives
  • Analytic Hierarchy Process structures criteria, pairwise comparisons and consistency ratios
  • Weighted-sum models test rankings under alternative weights and scores
  • Outranking methods compare options where compensation between criteria is limited
  • Dominated alternatives removed before detailed scoring and stakeholder review
  • Rank-reversal checks identify unstable recommendations after option-set changes

Participants can identify cognitive biases and introduce practical controls that improve decision quality.

  • Recognise anchoring, confirmation bias, availability bias and escalation of commitment
  • Pre-mortem analysis surfaces failure modes before approval and resource commitment
  • Red-team review challenges evidence, assumptions, incentives and preferred options
  • Reference-class forecasting compares proposals against outcomes from similar initiatives
  • Structured dissent records minority views, unresolved risks and decision conditions
  • Decision journals capture forecasts, rationale, confidence levels and later outcomes

Participants can prepare traceable recommendations that support timely executive review and approval.

  • Decision memos present recommendation, alternatives, evidence, uncertainties and required approval
  • Executive summaries distinguish decision request from background and supporting analysis
  • Assumption logs assign owners, validation dates, status and decision impact
  • Audit trails connect source data, calculations, revisions, approvals and exceptions
  • Stage-gate governance specifies evidence requirements, authority limits and escalation triggers
  • Recommendation narratives explain trade-offs without disguising uncertainty or dissent

Participants can plan a proportionate analysis for a live management decision and prepare next actions.

  • Select a live management decision with material cost, risk or service implications
  • Frame objectives, alternatives and constraints using the course decision charter
  • Build an evidence plan covering data, experts, assumptions and validation
  • Choose proportionate analysis methods based on stakes, uncertainty and reversibility
  • Prepare an approval-ready recommendation with sensitivity findings and implementation conditions
  • Create a 90-day action plan for validation, decisions and review

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Decision framing charter
  2. Weighted decision matrix template
  3. Evidence quality checklist
  4. Investment appraisal model
  5. Decision tree and sensitivity worksheet
  6. Executive decision memo template

Who should attend

  • Department Managers — need defensible methods for operational, staffing and investment choices
  • Programme and Project Managers — assess options, risks and change requests before approval
  • Business Analysts — structure evidence and recommendations for management decisions
  • Finance Managers — evaluate financial consequences and assumptions behind proposals
  • Procurement Managers — compare suppliers and sourcing options against weighted criteria
  • Policy and Strategy Officers — prepare evidence-based recommendations under competing priorities

Skills and tools covered

Decision framingEvidence assessmentFinancial evaluationUncertainty modellingMulti-criteria analysisExecutive recommendation writing

Tools and standards

RACI matrix, Analytic Hierarchy Process (AHP), Monte Carlo simulation, Bayes' theorem

How the course runs

Training methodology

The course uses short instructor briefings to introduce each method, followed by guided case analysis, group discussion and spreadsheet-based calculations. Participants assess realistic decisions involving investment, procurement, service performance and programme risk. Simulations show how changing assumptions, probabilities and criteria weights affect recommendations. Facilitated peer review tests evidence quality, bias controls and decision communication. Application planning helps participants select a live workplace decision and identify the analysis, stakeholders and approvals required after the course.

Requirements and prerequisites

Participants should have experience contributing to management discussions, business cases, operational planning, projects, budgets or improvement initiatives. They should be comfortable reading tables, interpreting percentages and using basic spreadsheet formulas such as sums, averages and percentages. Familiarity with organisational approval processes is helpful but not essential. No prior training in statistics, finance, economics, decision science or specialist software is required. The course explains the quantitative methods used and focuses on selecting and interpreting analyses rather than advanced mathematical derivations.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

You should be comfortable with basic business numbers, percentages and simple spreadsheets. Prior study in finance, statistics or economics is not required, because the course explains the methods used and focuses on management application.

Bring a laptop if possible, as participants may work with decision matrices and spreadsheet calculations. You may also bring a non-confidential example of a current decision, proposal or business case from your role.

The course is designed for managers, analysts, project leaders, finance staff, procurement professionals and policy officers who prepare or review recommendations. It is especially useful where decisions involve competing objectives, uncertain outcomes or significant resource commitments.

This course concentrates on the analytical discipline behind management decisions. It teaches specific methods for evaluating evidence, financial consequences, uncertainty, criteria trade-offs and recommendation quality rather than general leadership behaviours.

Participants can use the decision charter, evidence checklist, weighted matrix and memo template for current proposals. The methods are suitable for investment choices, supplier selection, service changes, risk responses and project decisions.

Training runs from 08:30 to 16:30 each day, with about 6.5 contact hours daily. The five days move from decision framing and evidence assessment through quantitative analysis, uncertainty, governance and application planning.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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