Project Feasibility Studies and Investment Decision-Making Course

Course Introduction

Project feasibility studies provide the analytical foundation for determining whether a proposed project is viable, strategically justified, financially sustainable, technically achievable, commercially practical, and capable of delivering its intended outcomes. This advanced course provides a comprehensive framework for assessing investment opportunities before major commitments are made, enabling participants to evaluate uncertainty, alternatives, risks, costs, benefits, implementation requirements, and long-term value through disciplined and evidence-based feasibility analysis.

The course examines the full lifecycle of feasibility assessment, from initial opportunity identification and strategic alignment through technical, market, operational, financial, economic, environmental, legal, organizational, and commercial evaluation. Participants will learn how to structure feasibility studies, define decision criteria, establish assumptions, collect and validate evidence, develop alternatives, estimate costs and benefits, evaluate implementation constraints, and formulate investment recommendations that are credible to executives, investors, boards, lenders, regulators, and other stakeholders.

A central focus is placed on investment decision-making under uncertainty. Participants will explore discounted cash flow analysis, net present value, internal rate of return, payback, benefit-cost analysis, whole-life costing, sensitivity analysis, scenario planning, probabilistic modelling, Monte Carlo simulation, risk-adjusted appraisal, and real-options thinking. The course emphasizes how decision-makers can distinguish between uncertainty that should be accepted, uncertainty that requires mitigation, and uncertainty that may justify delaying, redesigning, restructuring, or rejecting an investment.

Technical and operational feasibility are addressed alongside financial analysis to prevent investment decisions from being driven solely by attractive financial projections. Participants will assess technology maturity, engineering requirements, infrastructure availability, resource capacity, supply chain conditions, implementation capability, operating models, regulatory requirements, organizational readiness, environmental considerations, and stakeholder acceptance. Particular attention is given to dependencies and constraints that can undermine an otherwise compelling investment proposition.

The programme incorporates emerging technologies and analytical capabilities that are reshaping feasibility studies. Participants will examine AI-assisted feasibility analysis, predictive analytics, machine learning, generative AI, intelligent scenario modelling, automated market analysis, digital twins, geospatial intelligence, real-time data, and AI-supported investment screening. The course also addresses responsible use of AI, including data quality, model validation, explainability, human oversight, cybersecurity, bias, confidentiality, model drift, and governance of AI-supported investment recommendations.

Through practical feasibility frameworks, investment appraisal exercises, alternative evaluation, quantitative analysis, case studies, scenario simulations, and executive decision-making exercises, participants will develop the capability to produce and challenge high-quality feasibility studies. The course ultimately enables organizations to improve investment discipline, reduce avoidable decision errors, identify value-creating opportunities, recognize unacceptable exposures early, and allocate capital toward projects with the strongest combination of strategic value, feasibility, resilience, affordability, and sustainable long-term outcomes.

Duration

10 Days

Who Should Attend

• Project managers responsible for assessing new projects, initiatives, investments, and development opportunities before authorization.

• Project directors and programme managers involved in investment screening, project selection, feasibility assessment, and strategic decision-making.

• Investment and capital planning professionals evaluating project viability, financial returns, affordability, and funding requirements.

• Finance professionals responsible for financial modelling, investment appraisal, economic analysis, cash-flow projections, and capital allocation.

• Business case and feasibility specialists developing, reviewing, challenging, and assuring investment proposals.

• Strategy and corporate planning professionals evaluating strategic opportunities, transformation initiatives, market entry, and long-term investment options.

• PMO professionals establishing feasibility, stage-gate, investment governance, portfolio prioritization, and project selection frameworks.

• Cost engineers and project controls professionals contributing estimates, forecasts, contingency, schedules, productivity assumptions, and investment scenarios.

• Risk managers assessing uncertainty, investment risks, scenario exposure, resilience, and risk-adjusted project viability.

• Engineering and technical managers evaluating technical feasibility, technology alternatives, infrastructure requirements, design maturity, and implementation constraints.

• Commercial and procurement professionals assessing market conditions, delivery models, contracting strategies, supplier capability, and commercial feasibility.

• Operations and asset management professionals evaluating operating models, lifecycle requirements, maintainability, capacity, and long-term operational viability.

• Sustainability, environmental, and ESG professionals assessing environmental impacts, climate resilience, regulatory requirements, social outcomes, and sustainability considerations.

• Assurance, audit, governance, and investment review professionals challenging feasibility assumptions, evidence, analysis, recommendations, and decision quality.

• Senior executives and professionals seeking advanced capability in feasibility studies, investment appraisal, project selection, risk-adjusted decision-making, and strategic capital allocation.

Course Objectives

• Develop advanced capability to structure, conduct, evaluate, and challenge comprehensive project feasibility studies covering strategic, technical, commercial, financial, economic, operational, environmental, and organizational dimensions.

• Apply systematic feasibility methodologies to determine whether proposed projects are achievable, affordable, sustainable, strategically aligned, and capable of delivering their intended benefits.

• Identify and evaluate alternative investment options using transparent criteria covering value, risk, cost, benefits, technical feasibility, implementation complexity, resilience, and long-term strategic contribution.

• Develop robust financial and economic models incorporating capital expenditure, operating costs, revenues, savings, benefits, cash flows, financing requirements, lifecycle costs, and investment assumptions.

• Apply advanced investment appraisal techniques including NPV, IRR, payback, benefit-cost analysis, discounted cash flow, whole-life economics, and risk-adjusted financial evaluation.

• Assess market demand, competitive conditions, customer requirements, economic trends, supply capacity, pricing assumptions, market risks, and external factors that may affect project viability.

• Evaluate technical and operational feasibility by examining technology maturity, engineering requirements, infrastructure, resources, operating models, capability, maintainability, and implementation readiness.

• Apply quantitative risk analysis, sensitivity analysis, scenario modelling, probability distributions, Monte Carlo simulation, and confidence analysis to evaluate investment resilience under uncertainty.

• Identify optimism bias, unsupported assumptions, incomplete evidence, unrealistic forecasts, hidden dependencies, execution constraints, and other factors that can undermine feasibility conclusions.

• Use artificial intelligence, predictive analytics, machine learning, generative AI, digital twins, and automation to strengthen feasibility assessment, forecasting, alternative analysis, and investment decision intelligence.

• Establish robust feasibility governance, assurance, evidence validation, stage-gate review, decision rights, approval criteria, and post-investment learning mechanisms that improve investment discipline.

• Develop practical investment recommendations that clearly communicate feasibility findings, strategic value, risks, uncertainties, alternatives, affordability, implementation requirements, and decision consequences to senior stakeholders.

Comprehensive Course Outline

Module 1: Foundations of Project Feasibility and Investment Decision-Making

• Principles, purpose, scope, lifecycle, and strategic importance of feasibility studies in project development, capital investment, and organizational decision-making.

• Relationship between opportunity identification, strategic alignment, feasibility assessment, business case development, investment approval, project execution, and benefits realization.

• Key dimensions of feasibility covering strategic, market, technical, operational, commercial, financial, economic, legal, environmental, organizational, and social considerations.

• Common feasibility failures including premature commitment, confirmation bias, inadequate evidence, unrealistic forecasts, incomplete alternatives, underestimated risks, and weak decision governance.

Module 2: Strategic Opportunity Identification and Investment Rationale

• Techniques for identifying investment opportunities arising from market demand, strategic priorities, operational problems, regulatory requirements, technology change, asset needs, and organizational transformation.

• Development of clear investment objectives, strategic outcomes, value drivers, critical success factors, decision criteria, and consequences of action versus inaction.

• Assessment of alignment between proposed investments, corporate strategy, portfolio priorities, organizational capabilities, sustainability objectives, and long-term value creation.

• Development of compelling investment rationales supported by evidence, strategic analysis, stakeholder requirements, market intelligence, and clearly defined problems or opportunities.

Module 3: Feasibility Study Framework, Scope and Evidence Requirements

• Development of structured feasibility study methodologies covering study objectives, scope, workstreams, assumptions, deliverables, evidence requirements, review gates, and decision outputs.

• Establishment of information requirements covering market data, technical studies, estimates, schedules, operating assumptions, financial data, risk information, environmental considerations, and stakeholder inputs.

• Techniques for assessing evidence quality, source reliability, data completeness, assumption maturity, information gaps, and limitations affecting feasibility conclusions.

• Development of feasibility study governance including roles, responsibilities, independent challenge, decision rights, review processes, approval criteria, and auditability.

Module 4: Market, Demand and Commercial Feasibility

• Assessment of market size, customer demand, competitive dynamics, pricing, market growth, supply conditions, customer behavior, and external economic influences.

• Development of demand forecasts using historical data, market research, economic indicators, scenario analysis, predictive analytics, and sensitivity testing.

• Evaluation of commercial models, revenue structures, customer propositions, supplier markets, procurement strategies, competitive positioning, and contractual considerations.

• Identification of market and commercial risks including demand volatility, price uncertainty, competitor response, supply constraints, regulatory change, and market disruption.

Module 5: Technical and Engineering Feasibility

• Assessment of technology options, engineering concepts, design maturity, infrastructure requirements, technical standards, asset requirements, and implementation complexity.

• Evaluation of technology readiness, scalability, reliability, maintainability, interoperability, cybersecurity, technical dependencies, and future upgrade requirements.

• Development of technical alternatives and option comparisons considering performance, lifecycle cost, implementation risk, operational requirements, and strategic flexibility.

• Identification of technical constraints, design uncertainties, specialist resource requirements, long-lead components, interfaces, regulatory approvals, and engineering risks affecting investment viability.

Module 6: Operational, Organizational and Resource Feasibility

• Assessment of operating models, organizational structures, workforce requirements, skills, facilities, processes, systems, maintenance arrangements, and operational capability.

• Evaluation of organizational readiness, change impacts, leadership capability, workforce capacity, culture, training requirements, and adoption challenges.

• Development of resource and capability plans covering people, equipment, technology, facilities, suppliers, specialist skills, and operational support requirements.

• Assessment of operational resilience, business continuity, maintainability, service capacity, performance requirements, and long-term sustainability of the proposed investment.

Module 7: Cost Estimation, Affordability and Lifecycle Economics

• Development of feasibility-level capital and operating cost estimates covering direct costs, indirect costs, contingencies, financing, implementation, maintenance, renewal, and lifecycle expenditure.

• Integration of cost assumptions with project scope, schedule, procurement strategy, resource requirements, technical alternatives, and operating scenarios.

• Application of whole-life costing to compare options with different acquisition, operating, maintenance, replacement, energy, disposal, and residual-value profiles.

• Assessment of affordability, funding requirements, cash-flow timing, budget constraints, financial capacity, and the consequences of cost uncertainty for investment decisions.

Module 8: Advanced Investment Appraisal and Economic Evaluation

• Application of net present value, internal rate of return, payback period, profitability measures, discounted cash flow, benefit-cost ratios, and equivalent economic measures.

• Evaluation of financial and economic benefits including revenues, cost savings, productivity improvements, capacity gains, risk reduction, service improvements, and strategic value.

• Application of cost-benefit analysis where wider economic, environmental, social, or public-value outcomes are important to investment decisions.

• Interpretation and comparison of appraisal results while recognizing limitations associated with discount rates, timing, non-financial value, uncertain assumptions, and long-term impacts.

Module 9: Risk, Uncertainty and Feasibility Resilience

• Identification of risks affecting market demand, technical performance, costs, schedules, benefits, financing, regulation, implementation capability, supply chains, and long-term operations.

• Distinction between risk, uncertainty, assumptions, ambiguity, contingency, management reserve, and structural factors that influence investment outcomes.

• Application of risk-adjusted appraisal, sensitivity analysis, scenario testing, probability distributions, and Monte Carlo simulation to quantify investment exposure.

• Development of resilience strategies including risk mitigation, option flexibility, phased investment, contingency planning, alternative suppliers, technology choices, and decision triggers.

Module 10: AI, Predictive Analytics and Intelligent Feasibility Assessment

• Application of machine learning and predictive analytics to demand forecasting, cost estimation, schedule assessment, market analysis, operational modelling, and investment outcome prediction.

• Use of generative AI for feasibility study research, evidence synthesis, assumption analysis, option generation, scenario narratives, and preparation of decision-support documentation.

• Application of AI agents and intelligent automation to collect evidence, monitor assumptions, compare alternatives, identify inconsistencies, and support recurring feasibility reviews.

• Responsible AI governance covering data quality, explainability, model validation, human oversight, model drift, cybersecurity, confidentiality, bias, accountability, and auditability.

Module 11: Digital Feasibility, Data Integration and Digital Twins

• Integration of feasibility models with project management information systems, enterprise data platforms, financial systems, GIS, BIM, engineering systems, and business intelligence environments.

• Use of digital engineering, geospatial data, digital twins, asset information, real-time operational data, and simulation to improve technical and operational feasibility assessments.

• Development of integrated data models linking scope, cost, schedule, resources, risks, benefits, market assumptions, operational performance, and investment outcomes.

• Application of interactive dashboards, scenario engines, automated analytics, predictive models, and digital decision environments to improve feasibility transparency and responsiveness.

Module 12: Environmental, Social, Regulatory and Sustainability Feasibility

• Assessment of environmental impacts, regulatory obligations, permitting requirements, climate exposure, resource consumption, emissions, biodiversity, and environmental constraints.

• Evaluation of social outcomes, community impacts, stakeholder acceptance, workforce considerations, accessibility, social value, and potential sources of opposition or support.

• Integration of sustainability, climate resilience, circular economy principles, energy efficiency, resource efficiency, and long-term environmental performance into investment evaluation.

• Identification of regulatory, environmental, social, and sustainability risks that may affect cost, schedule, approvals, operating performance, reputation, or long-term project viability.

Module 13: Option Analysis, Scenario Planning and Strategic Flexibility

• Development and evaluation of strategic, technical, commercial, financing, procurement, phasing, technology, and implementation alternatives within feasibility studies.

• Application of multi-criteria decision analysis to compare options using financial, strategic, technical, operational, environmental, social, risk, and resilience criteria.

• Development of scenario models covering changing demand, costs, financing conditions, technology performance, regulatory environments, implementation schedules, and market conditions.

• Application of real-options thinking to evaluate flexibility, staged investment, deferral, expansion, abandonment, technology switching, and other responses to uncertainty.

Module 14: Investment Governance, Assurance and Stage-Gate Decisions

• Establishment of feasibility governance structures defining approval authorities, decision rights, evidence standards, stage gates, escalation requirements, and investment thresholds.

• Application of independent technical, financial, commercial, risk, market, environmental, and operational assurance to validate feasibility study conclusions.

• Development of challenge processes that test assumptions, evidence, alternatives, forecasts, risks, benefits, affordability, and implementation readiness before investment approval.

• Management of feasibility updates, decision records, approval conditions, changes in assumptions, revalidation triggers, audit trails, and governance requirements throughout project development.

Module 15: Executive Investment Recommendations and Decision Intelligence

• Development of executive-ready feasibility reports that communicate investment rationale, alternatives, financial outcomes, risks, uncertainty, affordability, implementation requirements, and recommendations.

• Design of decision dashboards showing key value drivers, investment metrics, sensitivity results, risk exposure, confidence levels, scenario outcomes, and critical assumptions.

• Techniques for communicating complex analytical findings and uncertainty clearly to boards, investment committees, executives, investors, lenders, regulators, and other decision-makers.

• Facilitation of investment challenge sessions and decision workshops that encourage evidence-based debate, transparent trade-offs, structured challenge, and disciplined investment conclusions.

Module 16: Future-Ready Feasibility and Investment Decision Transformation

• Development of an organizational framework for improving feasibility maturity through standardized methodologies, data quality, analytical capability, governance, benchmarking, and investment learning.

• Implementation roadmaps covering people, processes, technology, financial modelling, AI capabilities, data architecture, assurance, change management, and investment governance.

• Emerging approaches including autonomous feasibility screening, AI-powered investment intelligence, predictive benefits modelling, digital twins, real-time market intelligence, and intelligent portfolio optimization.

• Establishment of continuous investment learning systems using post-investment reviews, actual-versus-forecast analysis, benefits realization, benchmarking, predictive insights, and lessons learned to improve future feasibility and investment decisions.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.

Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment:

Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.