decision-analysis

What Is Decision Analysis? Decision Analysis In A Nutshell

Stanford University Professor Ronald A. Howard first defined decision analysis as a profession in 1964. Over the ensuing decades, Howard has supervised many doctoral theses on the subject across topics including nuclear waste disposal, investment planning, hurricane seeding, and research strategy. Decision analysis (DA) is a systematic, visual, and quantitative decision-making approach where all aspects of a decision are evaluated before making an optimal choice.

Understanding decision analysis

Fundamentally, decision analysis enables organizations to evaluate or model the potential outcomes of various decisions so they can choose the one with the most favorable outcome. The tool assesses all relevant information and incorporates aspects of training, economics, psychology, and various management techniques.

Another part of decision analysis requires the business to examine uncertainty around a decision. Uncertainty is measured by probability. In other words, what are the chances the outcome will occur? From this point, the organization can make a decision based on the value and likelihood of success of a decision. Alternatively, it can base the decision on the likelihood of failure and its corresponding impact. 

Decision analysis is extremely valuable in the project planning stage and during periodic reviews of project progress by senior management. Since most projects are characterized by decisions made with high uncertainty, decision analysis has multiple applications. For one, the analysis helps project teams obtain accurate activity duration estimates. Decision analysis also assists in risk analysis, “what-if” analysis, and subproject terminating in a research and development context. 

How does decision analysis work?

The decision analysis process can be explained in the following steps.

1 – Identify the problem 

What is the problem to be solved or the decision to be made? 

Once this has been determined, a list of possible options should be devised. For instance, a non-profit that receives a large endowment may have several ways they can put the money to good use. 

2 – Research options 

Each choice or option must then be researched, with any relevant data set aside to develop a decision model later in the process. Data may be quantitative or qualitative, depending on the context. 

It is important to consider each outcome in terms of its costs, risks, benefits, and probability of success or failure. 

3 – Create a framework

To allow the business to properly assess its options, an evaluation framework must be created. 

One way to achieve this is by using key performance indicators (KPIs) to measure and indicate progress. For example, a business looking to expand may stipulate that each potential new market causes a minimum increase in monthly sales volume.

Like the research from the previous step, KPI data may be qualitative or quantitative.

4 – Develop a decision model

Now it is time to combine the framework with a decision model. One of the most popular decision analysis models is the decision tree, where each choice has branches representing different outcomes. 

Influence diagrams can also be used when there is a high amount of uncertainty around a decision or goal.

5 – Calculate the expected value

The expected value (EV) is the weighted average of all potential decision outcomes. To calculate the expected value, multiply the probability of each outcome occurring by the resulting value – sometimes referred to as the expected payoff. Then, sum the expected values for each decision.

For example, consider a large architectural firm that designs stadiums. During a public tender process, the firm submits two designs which the city council must evaluate for viability. For the sake of this article, we will call them Design A and Design B.

The city council determines that Design A, once completed, has a 55% chance of a $350 million valuation and a 25% chance of a $275 million valuation. The expected value of Design A is (0.55 x 350,000,000) + (0.25 x $275,000,000) = $261.25 million

On the other hand, Design B has a 20% chance of being valued at $400 million and a 60% chance of being valued at $290 million. The expected value of Design B is (0.20 x 400,000,000) + (0.60 x 290,000,000) = $254 million. 

In this instance, the council should choose Design A.

Case Studies

  • Pharmaceutical Company: New drug development versus other R&D projects.
    • Identify the problem: Whether to invest in the development of a new drug or allocate resources to other R&D projects.
    • Research options: Analyze the success rate of similar drugs, potential market size, regulatory challenges, and the competitive landscape.
    • Create a framework: Use KPIs like potential ROI, time-to-market, and success rate of clinical trials.
    • Develop a decision model: Use a decision tree to map out each phase of drug development and the probabilities of success/failure at each stage.
    • Calculate the expected value: Estimate potential revenues from the new drug against the costs and risks, and compare with the expected returns from other R&D projects.
  • Oil and Gas Exploration: To drill or not to drill.
    • Identify the problem: Assess the potential profitability of drilling in a new location.
    • Research options: Investigate geological data, historical successes in similar terrains, and current oil market conditions.
    • Create a framework: KPIs might include estimated oil reserves, drilling costs, potential environmental impact, and breakeven oil price.
    • Develop a decision model: A decision tree that weighs the cost of drilling, potential oil yield, and market prices.
    • Calculate the expected value: Factor in the potential revenues from oil sales against drilling and operational costs.
  • Venture Capital Investment: To invest in a particular startup or not.
    • Identify the problem: Determine if the startup presents a lucrative investment opportunity.
    • Research options: Assess the startup’s business model, market potential, competition, and team competency.
    • Create a framework: KPIs can include projected ROI, market share potential, and scalability.
    • Develop a decision model: Use a decision tree to model potential growth trajectories and associated risks.
    • Calculate the expected value: Weigh potential returns against the investment amount and associated risks.
  • Supply Chain Management: Selecting a supplier based on cost versus reliability.
    • Identify the problem: Decide between a cheaper supplier with a less reliable track record or a slightly more expensive but trusted supplier.
    • Research options: Examine past performance, reviews, and testimonials of the suppliers.
    • Create a framework: KPIs might encompass delivery timelines, defect rates, and communication efficiency.
    • Develop a decision model: Decision tree comparing potential disruptions or benefits from each supplier.
    • Calculate the expected value: Factor in potential costs from supply chain disruptions against savings from the cheaper supplier.
  • Environmental Policy: Renovate an old water treatment plant or build a new one.
    • Identify the problem: Determine the most efficient and sustainable water treatment solution for the city.
    • Research options: Compare the costs, efficiency, and environmental impact of renovation versus new construction.
    • Create a framework: KPIs could include water treatment capacity, operational costs, and environmental compliance levels.
    • Develop a decision model: Decision tree analyzing the long-term benefits and costs of both options.
    • Calculate the expected value: Evaluate the long-term savings and benefits against initial costs.
  • Real Estate Developer: Build a residential complex or a commercial complex on a newly acquired land.
    • Identify the problem: Decide the best utilization of the newly acquired land for maximum profit and sustainability.
    • Research options: Assess the local demand for housing versus commercial spaces, potential rent or sale prices, and local infrastructure.
    • Create a framework: KPIs might include potential ROI, occupancy rates, and maintenance costs.
    • Develop a decision model: Decision tree considering construction costs, potential revenue, and long-term market trends.
    • Calculate the expected value: Compare potential profits from both residential and commercial complexes against construction and maintenance costs.
  • Tech Company: Launch a new software product or improve an existing one.
    • Identify the problem: Determine where to allocate resources for product development.
    • Research options: Analyze market demand for new features, competition, and feedback on the current product.
    • Create a framework: KPIs can include user adoption rates, customer retention, and potential market share.
    • Develop a decision model: Decision tree weighing the costs of new development versus enhancement and potential market reception.
    • Calculate the expected value: Contrast potential sales and subscription revenues against development and marketing costs.
  • Agricultural Producer: Invest in organic farming or continue with traditional methods.
    • Identify the problem: Determine the farming method that will yield maximum profit and sustainability.
    • Research options: Study market demand for organic produce, cost implications, and potential yield differences.
    • Create a framework: KPIs might encompass crop yield per acre, market prices, and long-term soil health.
    • Develop a decision model: Decision tree comparing the short-term and long-term costs and benefits of both farming methods.
    • Calculate the expected value: Evaluate potential premium prices for organic produce against increased costs and potential yield variations.
  • Automobile Manufacturer: Introduce electric vehicles (EVs) or improve fuel efficiency in traditional vehicles.
    • Identify the problem: Decide on the product direction in light of changing environmental regulations and market demands.
    • Research options: Analyze market trends for EVs, technological advancements, and potential government incentives.
    • Create a framework: KPIs can include sales volume, profit margins, and brand perception.
    • Develop a decision model: Decision tree weighing the R&D costs, production costs, and potential market share of both options.
    • Calculate the expected value: Compare potential profits from EVs and improved traditional vehicles against development and production costs.
  • Tourism Board: Invest in promoting local tourism or attract international tourists.
    • Identify the problem: Determine where marketing efforts and investments will yield maximum tourist influx and revenue.
    • Research options: Assess the current state of local versus international tourism, accessibility, and attractions.
    • Create a framework: KPIs might include tourist footfall, average spend per tourist, and hotel occupancy rates.
    • Develop a decision model: Decision tree analyzing the potential reach and effectiveness of local versus international marketing campaigns.
    • Calculate the expected value: Weigh potential revenues from increased tourism against marketing and infrastructure investment costs.

Key takeaways:

  • Decision analysis is a systematic, visual, and quantitative decision-making approach where all aspects of a decision are evaluated before making an optimal choice.
  • Decision analysis is used in the project planning stage and during periodic reviews of project progress by senior management. The approach is especially suited to project management where there is often uncertainty around decision outcomes.
  • Decision analysis occurs via five steps: identify the problem, research options, create a framework, develop a decision model, and calculate the expected value. At the heart of this process are the decision tree framework and the calculation of expected value.

Key Highlights

  • Understanding Decision Analysis: Decision analysis is a systematic, visual, and quantitative approach to decision-making that evaluates all aspects of a decision before making an optimal choice. It involves assessing relevant information, considering uncertainty, and incorporating various disciplines like training, economics, psychology, and management techniques.
  • Application of Decision Analysis: Decision analysis is valuable in project planning and project progress reviews, especially for projects with high uncertainty. It helps obtain accurate activity duration estimates, conduct risk analysis, perform “what-if” analysis, and make decisions in a research and development context.
  • The Decision Analysis Process:
    1. Identify the Problem: Define the decision or problem to be solved and generate a list of possible options.
    2. Research Options: Gather relevant data for each option, considering costs, risks, benefits, and probability of success or failure.
    3. Create a Framework: Develop an evaluation framework using key performance indicators (KPIs) to measure progress and assess options.
    4. Develop a Decision Model: Use decision trees or influence diagrams to create decision models that represent different outcomes for each choice.
    5. Calculate the Expected Value: Calculate the weighted average of all potential decision outcomes to determine the expected value (EV) for each option. Select the option with the highest expected value.
  • Decision Analysis Example: For instance, a large architectural firm submitting stadium designs for a public tender has Design A with a 55% chance of a $350 million valuation and a 25% chance of a $275 million valuation. The expected value of Design A is $261.25 million. Design B, with a 20% chance of $400 million and a 60% chance of $290 million, has an expected value of $254 million. Based on expected values, the city council should choose Design A.

Connected Analysis Frameworks

Failure Mode And Effects Analysis

failure-mode-and-effects-analysis
A failure mode and effects analysis (FMEA) is a structured approach to identifying design failures in a product or process. Developed in the 1950s, the failure mode and effects analysis is one the earliest methodologies of its kind. It enables organizations to anticipate a range of potential failures during the design stage.

Agile Business Analysis

agile-business-analysis
Agile Business Analysis (AgileBA) is certification in the form of guidance and training for business analysts seeking to work in agile environments. To support this shift, AgileBA also helps the business analyst relate Agile projects to a wider organizational mission or strategy. To ensure that analysts have the necessary skills and expertise, AgileBA certification was developed.

Business Valuation

valuation
Business valuations involve a formal analysis of the key operational aspects of a business. A business valuation is an analysis used to determine the economic value of a business or company unit. It’s important to note that valuations are one part science and one part art. Analysts use professional judgment to consider the financial performance of a business with respect to local, national, or global economic conditions. They will also consider the total value of assets and liabilities, in addition to patented or proprietary technology.

Paired Comparison Analysis

paired-comparison-analysis
A paired comparison analysis is used to rate or rank options where evaluation criteria are subjective by nature. The analysis is particularly useful when there is a lack of clear priorities or objective data to base decisions on. A paired comparison analysis evaluates a range of options by comparing them against each other.

Monte Carlo Analysis

monte-carlo-analysis
The Monte Carlo analysis is a quantitative risk management technique. The Monte Carlo analysis was developed by nuclear scientist Stanislaw Ulam in 1940 as work progressed on the atom bomb. The analysis first considers the impact of certain risks on project management such as time or budgetary constraints. Then, a computerized mathematical output gives businesses a range of possible outcomes and their probability of occurrence.

Cost-Benefit Analysis

cost-benefit-analysis
A cost-benefit analysis is a process a business can use to analyze decisions according to the costs associated with making that decision. For a cost analysis to be effective it’s important to articulate the project in the simplest terms possible, identify the costs, determine the benefits of project implementation, assess the alternatives.

CATWOE Analysis

catwoe-analysis
The CATWOE analysis is a problem-solving strategy that asks businesses to look at an issue from six different perspectives. The CATWOE analysis is an in-depth and holistic approach to problem-solving because it enables businesses to consider all perspectives. This often forces management out of habitual ways of thinking that would otherwise hinder growth and profitability. Most importantly, the CATWOE analysis allows businesses to combine multiple perspectives into a single, unifying solution.

VTDF Framework

competitor-analysis
It’s possible to identify the key players that overlap with a company’s business model with a competitor analysis. This overlapping can be analyzed in terms of key customers, technologies, distribution, and financial models. When all those elements are analyzed, it is possible to map all the facets of competition for a tech business model to understand better where a business stands in the marketplace and its possible future developments.

Pareto Analysis

pareto-principle-pareto-analysis
The Pareto Analysis is a statistical analysis used in business decision making that identifies a certain number of input factors that have the greatest impact on income. It is based on the similarly named Pareto Principle, which states that 80% of the effect of something can be attributed to just 20% of the drivers.

Comparable Analysis

comparable-company-analysis
A comparable company analysis is a process that enables the identification of similar organizations to be used as a comparison to understand the business and financial performance of the target company. To find comparables you can look at two key profiles: the business and financial profile. From the comparable company analysis it is possible to understand the competitive landscape of the target organization.

SWOT Analysis

swot-analysis
A SWOT Analysis is a framework used for evaluating the business’s Strengths, Weaknesses, Opportunities, and Threats. It can aid in identifying the problematic areas of your business so that you can maximize your opportunities. It will also alert you to the challenges your organization might face in the future.

PESTEL Analysis

pestel-analysis
The PESTEL analysis is a framework that can help marketers assess whether macro-economic factors are affecting an organization. This is a critical step that helps organizations identify potential threats and weaknesses that can be used in other frameworks such as SWOT or to gain a broader and better understanding of the overall marketing environment.

Business Analysis

business-analysis
Business analysis is a research discipline that helps driving change within an organization by identifying the key elements and processes that drive value. Business analysis can also be used in Identifying new business opportunities or how to take advantage of existing business opportunities to grow your business in the marketplace.

Financial Structure

financial-structure
In corporate finance, the financial structure is how corporations finance their assets (usually either through debt or equity). For the sake of reverse engineering businesses, we want to look at three critical elements to determine the model used to sustain its assets: cost structure, profitability, and cash flow generation.

Financial Modeling

financial-modeling
Financial modeling involves the analysis of accounting, finance, and business data to predict future financial performance. Financial modeling is often used in valuation, which consists of estimating the value in dollar terms of a company based on several parameters. Some of the most common financial models comprise discounted cash flows, the M&A model, and the CCA model.

Value Investing

value-investing
Value investing is an investment philosophy that looks at companies’ fundamentals, to discover those companies whose intrinsic value is higher than what the market is currently pricing, in short value investing tries to evaluate a business by starting by its fundamentals.

Buffet Indicator

buffet-indicator
The Buffet Indicator is a measure of the total value of all publicly-traded stocks in a country divided by that country’s GDP. It’s a measure and ratio to evaluate whether a market is undervalued or overvalued. It’s one of Warren Buffet’s favorite measures as a warning that financial markets might be overvalued and riskier.

Financial Analysis

financial-accounting
Financial accounting is a subdiscipline within accounting that helps organizations provide reporting related to three critical areas of a business: its assets and liabilities (balance sheet), its revenues and expenses (income statement), and its cash flows (cash flow statement). Together those areas can be used for internal and external purposes.

Post-Mortem Analysis

post-mortem-analysis
Post-mortem analyses review projects from start to finish to determine process improvements and ensure that inefficiencies are not repeated in the future. In the Project Management Book of Knowledge (PMBOK), this process is referred to as “lessons learned”.

Retrospective Analysis

retrospective-analysis
Retrospective analyses are held after a project to determine what worked well and what did not. They are also conducted at the end of an iteration in Agile project management. Agile practitioners call these meetings retrospectives or retros. They are an effective way to check the pulse of a project team, reflect on the work performed to date, and reach a consensus on how to tackle the next sprint cycle.

Root Cause Analysis

root-cause-analysis
In essence, a root cause analysis involves the identification of problem root causes to devise the most effective solutions. Note that the root cause is an underlying factor that sets the problem in motion or causes a particular situation such as non-conformance.

Blindspot Analysis

blindspot-analysis

Break-even Analysis

break-even-analysis
A break-even analysis is commonly used to determine the point at which a new product or service will become profitable. The analysis is a financial calculation that tells the business how many products it must sell to cover its production costs.  A break-even analysis is a small business accounting process that tells the business what it needs to do to break even or recoup its initial investment. 

Decision Analysis

decision-analysis
Stanford University Professor Ronald A. Howard first defined decision analysis as a profession in 1964. Over the ensuing decades, Howard has supervised many doctoral theses on the subject across topics including nuclear waste disposal, investment planning, hurricane seeding, and research strategy. Decision analysis (DA) is a systematic, visual, and quantitative decision-making approach where all aspects of a decision are evaluated before making an optimal choice.

DESTEP Analysis

destep-analysis
A DESTEP analysis is a framework used by businesses to understand their external environment and the issues which may impact them. The DESTEP analysis is an extension of the popular PEST analysis created by Harvard Business School professor Francis J. Aguilar. The DESTEP analysis groups external factors into six categories: demographic, economic, socio-cultural, technological, ecological, and political.

STEEP Analysis

steep-analysis
The STEEP analysis is a tool used to map the external factors that impact an organization. STEEP stands for the five key areas on which the analysis focuses: socio-cultural, technological, economic, environmental/ecological, and political. Usually, the STEEP analysis is complementary or alternative to other methods such as SWOT or PESTEL analyses.

STEEPLE Analysis

steeple-analysis
The STEEPLE analysis is a variation of the STEEP analysis. Where the step analysis comprises socio-cultural, technological, economic, environmental/ecological, and political factors as the base of the analysis. The STEEPLE analysis adds other two factors such as Legal and Ethical.

Activity-Based Management

activity-based-management-abm
Activity-based management (ABM) is a framework for determining the profitability of every aspect of a business. The end goal is to maximize organizational strengths while minimizing or eliminating weaknesses. Activity-based management can be described in the following steps: identification and analysis, evaluation and identification of areas of improvement.

PMESII-PT Analysis

pmesii-pt
PMESII-PT is a tool that helps users organize large amounts of operations information. PMESII-PT is an environmental scanning and monitoring technique, like the SWOT, PESTLE, and QUEST analysis. Developed by the United States Army, used as a way to execute a more complex strategy in foreign countries with a complex and uncertain context to map.

SPACE Analysis

space-analysis
The SPACE (Strategic Position and Action Evaluation) analysis was developed by strategy academics Alan Rowe, Richard Mason, Karl Dickel, Richard Mann, and Robert Mockler. The particular focus of this framework is strategy formation as it relates to the competitive position of an organization. The SPACE analysis is a technique used in strategic management and planning. 

Lotus Diagram

lotus-diagram
A lotus diagram is a creative tool for ideation and brainstorming. The diagram identifies the key concepts from a broad topic for simple analysis or prioritization.

Functional Decomposition

functional-decomposition
Functional decomposition is an analysis method where complex processes are examined by dividing them into their constituent parts. According to the Business Analysis Body of Knowledge (BABOK), functional decomposition “helps manage complexity and reduce uncertainty by breaking down processes, systems, functional areas, or deliverables into their simpler constituent parts and allowing each part to be analyzed independently.”

Multi-Criteria Analysis

multi-criteria-analysis
The multi-criteria analysis provides a systematic approach for ranking adaptation options against multiple decision criteria. These criteria are weighted to reflect their importance relative to other criteria. A multi-criteria analysis (MCA) is a decision-making framework suited to solving problems with many alternative courses of action.

Stakeholder Analysis

stakeholder-analysis
A stakeholder analysis is a process where the participation, interest, and influence level of key project stakeholders is identified. A stakeholder analysis is used to leverage the support of key personnel and purposefully align project teams with wider organizational goals. The analysis can also be used to resolve potential sources of conflict before project commencement.

Strategic Analysis

strategic-analysis
Strategic analysis is a process to understand the organization’s environment and competitive landscape to formulate informed business decisions, to plan for the organizational structure and long-term direction. Strategic planning is also useful to experiment with business model design and assess the fit with the long-term vision of the business.

Related Strategy Concepts: Go-To-Market StrategyMarketing StrategyBusiness ModelsTech Business ModelsJobs-To-Be DoneDesign ThinkingLean Startup CanvasValue ChainValue Proposition CanvasBalanced ScorecardBusiness Model CanvasSWOT AnalysisGrowth HackingBundlingUnbundlingBootstrappingVenture CapitalPorter’s Five ForcesPorter’s Generic StrategiesPorter’s Five ForcesPESTEL AnalysisSWOTPorter’s Diamond ModelAnsoffTechnology Adoption CurveTOWSSOARBalanced ScorecardOKRAgile MethodologyValue PropositionVTDF FrameworkBCG MatrixGE McKinsey MatrixKotter’s 8-Step Change Model.

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