Innovation Decision Orchestration via Integrated Modeling & Simulation
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Innovation Decision Orchestration via Integrated Modeling & Simulation

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An integrated methodology for organizational decision making via stakeholder scoping, NPV modeling, Monte Carlo simulation, and Real Options Analysis (ROA). This integrated decision-making process ...

An integrated methodology for organizational decision making via stakeholder scoping, NPV modeling, Monte Carlo simulation, and Real Options Analysis (ROA). This integrated decision-making process offers: (a) a simulation framework for strategic decision making, integrating Net Present Value (NPV), Monte Carlo, and Real Options Analysis (ROA); and (b) a robust model validation process which minimizes organizational overhead, utilizing organizational Social Network Analysis (SNA). Continuously and iteratively refined, the model is an organizational artifact, bringing together diverse experts and stakeholders into a unified, structured conversation.

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Innovation Decision Orchestration via Integrated Modeling & Simulation Document Transcript

  • 1. Innovation Decision Orchestration via Integrated Modeling & Simulation www.sark7.com Integrated financial modeling & simulation for structuring, managing, OVERVIEW and validating high-risk / high-reward innovation decision makingThe proposed integrated process offers: (a) a simulation framework for finance-based, strategic decision making, integratingNet Present Value (NPV), Monte Carlo, and Real Options Analysis (ROA); and (b) a structured, robust model validation processwhich minimizes organizational overhead, utilizing organizational Social Network Analysis (SNA).Keywords: strategic decision making, innovation management, management of uncertainty, portfolio analysis, IP, R&D management,validation, Net Present Value (NPV), Monte Carlo simulation, Real Options Analysis (ROA), Social Network Analysis (SNA) Mapping organizational structure to 1 SCOPE business objectives and model artifacts A. Organizational Assessment: Social Network Analysis (SNA) allows for a rapid, robust mapping of organizational stakeholders to key model components. Traditional organizational charts often neglect key experts & hidden stakeholders. Mapping formal roles, rights (ownership, change, approval, review), and interactions to key data and decision processes promotes transparency, rigor, and organizational consensus / commitment regarding decision outcomes. B. Elicitation of Objectives: Identification of business needs, requirements, opportunities, challenges, risk tolerance, data Providing insight into risks / opportunities 2 MODEL via integrating probability & scenarios Static Net Present Value (NPV) Revenue streams NPV Model Decision Tree Opportunities Monte Carlo analysis presents a highly linear [structure] [probabilities] [decision] [scenarioes] and selective view of a prospect, OPEX costs often overlooking key oppor- tunities and risks. This model CAPEX outlay framework extends traditional Net Financing Present Value (NPV) analysis via integrated Monte Carlo (probability) and Real Options Analysis (scenarios) to facilitate robust analytical Financial model: uncertainties/ ranges, discussions of risks and opportunities in order to drive decision-making. Continuously and iteratively objectives, revenues, CAPEX/OPEX, market prices, currency rates, etc... refined, the model is an organizational artifact, bringing together diverse experts and stakeholders into Scenario model: commercialization/ a unified, structured conversation. Economy and transparency are key: the model must be as simple as revenue strategies, financing scenarios, possible with a clear audit path concerning key assumptions. market boundaries, key risks, etc… 3 OPTIMIZE 1 5 SCENARIOESIntegrated simulation allows for formal A number of strategies for commercializ-volatility, sensitivity, and optimization ation are attached to the model, eitheranalysis. Gaining insight into systemic via simulation or linked decision trees.dynamics, particular areas can be 2 NPV analysis allows strategies to betargeted for efficiency / exploitation. refined: structured finance, hybridStructured scenarios can be tailored to 6 models (i.e. licensing, risk sharing),optimize profits and reduce costs. scale, timing optimization, tax, etc. 5 3 4 ITERATE 6 SIMULATEImplicit perceptions & assumptions Utilizing ranges (min, max, average)are made explicit and verified 4 collected from data and experts, keycontinuously throughout the develop- variables are simulated in unison to varyment and refinement of the model. By possible outcomes: capital and operatingformally linking organizational structure costs, revenue streams, technical factors,and roles to the model, the stakeholder net- 7 economic variables, etc. Results show expectedwork continuously refines and validates the model. ranges & sensitivities via NPV outcomes. Establishing concordance between model, 7 VALIDATE x organizational assumptions & outcomesIntegrated financial models are inherently complex and thus sensitive to initial assumptions. Robust validation is required to ensure bothquality and organizational acceptance. The use of SNA promotes a tight connection between model artifacts / outcomes to organizationalstructures / roles. The integrated validation and valorization process centralizes and structures organizational conversations concerningstrategic risks and opportunities. The analysis thus provides not only structured financial insight, but also a collective organizationalunderstanding of the often unstated assumptions regarding the practical “real” circumstances surrounding the opportunity under evaluation.