Program Overview
This program empowers business, finance, and operations professionals to translate digital transformation initiatives — such as digital twins, IoT-enabled smart factories, and predictive maintenance systems — into measurable business and financial outcomes. Participants will learn how to assess ROI, NPV, and risk profiles of Industry 4.0 projects, develop digital investment scorecards, and integrate CapEx-to-Outcome mapping in their decision-making. Combining financial modeling, real-world case studies, and simulation-based business case exercises, the workshop helps leaders bridge the gap between technology innovation and enterprise value creation, ensuring investments drive both strategic competitiveness and sustainable returns.
Features
- Evaluate digital twin and smart manufacturing initiatives using advanced financial metrics (NPV, IRR, EVA)
- Translate digital transformation outcomes into tangible business and P&L impacts
- Build investment cases and risk-adjusted ROI models for Industry 4.0 projects
- Design governance and funding frameworks to maximize digital transformation ROI
Target audiences
- Finance Managers
- FP&A Teams
- Capital Budgeting & Investment Analysts
- CFOs
Curriculum
- 6 Sections
- 34 Lessons
- 1 Day
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- Understanding Digital Twin & Smart Manufacturing Economics6
- 1.1Digital Twin vs. Digital Thread vs. Cyber-Physical System
- 1.2Smart Factory ROI levers – OEE, MTTR, energy savings, throughput
- 1.3CapEx vs. OpEx investments in Industry 4.0 technologies
- 1.4Total Economic Impact (TEI) & Value-at-Risk in digital projects
- 1.5Cost-to-Value Pyramid for automation maturity
- 1.6Exercise: Identify current digital twin initiatives in participants’ organizations and map them against ROI maturity stages
- Capital Budgeting & Valuation of Smart Manufacturing Projects7
- 2.1NPV, IRR, and Payback Period for digital projects
- 2.2EVA (Economic Value Added) and Real Options valuation
- 2.3Risk-adjusted discount rates for technology uncertainty
- 2.4Risk-adjusted discount rates for technology uncertainty
- 2.5CAPEX-to-Outcome Mapping: From Sensors to Predictive Maintenance
- 2.6Example Sharing: Rolls-Royce and Siemens – Digital twin ROI through engine uptime monetization
- 2.7Exercise: Build a mini ROI model for a smart manufacturing line using provided cost and savings data
- Data-Driven Value Creation & Monetization Models7
- 3.1Data as a financial asset – valuation and depreciation of data sets
- 3.2Productivity, yield, and predictive maintenance benefits in financial terms
- 3.3Subscription, as-a-service, and platform-based business models
- 3.4Linking operational KPIs to P&L impact (OEE – EBITDA – Cash flow)
- 3.5Measuring intangible returns – customer uptime, ESG compliance, digital resilience
- 3.6Example: GE Predix and Honeywell Forge – converting digital insight into recurring revenue
- 3.7Exercise: Link performance KPIs to balance sheet & income statement metrics
- Financial Governance of Digital Transformation Portfolios6
- 4.1Portfolio prioritization: strategic fit vs. financial feasibility
- 4.2Funding structures – JV, pay-per-use, outcome-based financing
- 4.3Digital CapEx accounting under IFRS / Ind AS frameworks
- 4.4Internal governance: ROI gates, stage-gate approval models
- 4.5ESG-linked financing and green CapEx for Industry 4.0 initiatives
- 4.6Exercise: Design a CapEx approval scorecard combining financial and strategic KPIs
- Risk, Resilience & Scenario-Based Planning6
- 5.1Risk heatmap for digital twin programs – cyber, integration, obsolescence
- 5.2Scenario planning using Monte Carlo / sensitivity modeling
- 5.3Total Cost of Ownership (TCO) for digital assets
- 5.4Digital amortization and lifecycle cost tracking
- 5.5Case Study: ABB – managing ROI volatility through hybrid financing and modular rollouts
- 5.6Exercise: Develop a risk-adjusted ROI plan for a digital twin pilot
- Building a Digital Investment Roadmap2
Instructor
