In this blog post, we will examine the latest decision support innovations brought to the DoD and intelligence community by Innovative Decisions, Inc. (IDI) and explore the reasons it chose to build its Decision Support solution on an Enterprise NoSQL database.
Obstacles to Effective Decision Support
An art and a science, decision support is comprised of both social and technical processes designed to derive value for decision makers. Unfortunately, providing effective decision support is not without its challenges. First, the processes are often manual and not always grounded in consistent methodologies. Second, current decision support processes are not based on factual information – but rather on derivative metrics that do not allow decision-making based on ground truths. In fact, most decisions are driven only by small subsets of the total information available to agencies, resulting in delays and increased risks. But, in the deluge of information we create and consume every day, without a consistent methodology to follow, it’s overwhelming to analyze alternatives, risks, and all possible courses of action. This is where IDI comes in.
Leveraging Analytics to Support Better Decisions
One of the leading decision analysis firms in the country, IDI is an analytics and management consulting company that serves business and government clients with innovative applications for decision and risk analysis, operations research, and systems engineering. IDI further supports national defense, security, and financial agency clients with projects focused on resource allocation, alternatives of analysis (AoA), intelligence tasking, future forecasting, and requirements development. IDI strives to bring people together to organize and process technical information as well as share individual areas of expertise in support of high-stakes decisions.
IDI benefits from the expertise of over a dozen PhDs with deep quantitative analytics experience and several highly-regarded, authoritative books to their credit, including:
- Handbook of Decision Analysis
- Trade-off Analytics: Creating and Exploring the System Tradespace
- The Engineering Design of Systems: Models and Methods
- Decision Making in Systems Engineering and Management
- Rapid, Low Cost Modeling and Simulation: Integrating Bayesian Networks and Neural Networks as an Alternative to an Equation-Based Approach
- Decision Synthesis: The Principles and Practice of Decision Analysis
Second, we always strive to facilitate inclusive decisions by bringing together diverse stakeholders, perspectives, and information. When a group of decision makers are deciding a path forward, for example, in budgeting for the coming year, they bring their own priorities and expertise to the process. Inclusive decision processes incorporate more stakeholders than just the decision makers who ‘own the budget.’ By bringing in stakeholders early, it increases the likelihood of success when decisions are implemented.”
Why IDI Built Its Solution on MarkLogic
When asked why IDI selected MarkLogic’s multi-model database for its solution, Mark Fedeli explains the decision this way: “One of the major challenges of decision-making is information management. We can architect a winning decision process, but without the right qualitative and quantitative information, the decision support process will tend to reinforce what people already think or assume. MarkLogic has unique enterprise capabilities as a database, search engine, and application server that enable us to apply our core methodology rigorously while ingesting a wide array of data sources and tagging the information for analysts to keep the data in context.
More specifically, we chose MarkLogic because our strategy team had conducted a thorough market survey of decision support systems (DSS) for a Department of Defense (DoD) customer. A decision support system typically is a closed analytics environment that is purpose-built for specific types of decisions. Our DoD, intelligence community, and homeland security customers are not working in a closed environment. Innovation, adaptive adversaries, and accelerating mission change outside the organization’s control will impact risk and uncertainty levels. A closed DSS cannot support those decisions effectively.
Similarly, traditional business intelligence (BI) applications fall short of the requirements of our decision support customers because BI analyzes past events and tends to focus on descriptive analytics. Our customers need predictive and prescriptive analytics that look ahead to various future scenarios and model the risks of allocating resources or implementing a new technology in each of those scenarios. The social side of decision support is imaginative and creative, which traditional BI was not built to readily support.
We chose MarkLogic because neither a closed DSS nor a descriptive BI application can support the depth of risk analysis, scenario modeling, and quantitative multi-objective decision analysis that we do for our clients. The technical aspects of our analysis require both structured and unstructured information from various data sources to be used to compare alternative courses of action and quantify for our customers the probable promises and perils of these alternatives. The social aspects of our analysis require flexibility of visualization, so that we can display information for decision makers in adaptive ways that help them to clearly understand their options and how those options may change over time. This temporal aspect of decision-making is critical, and MarkLogic brought unmatched temporal data management features that blew us away when we tested them.”
Empowering Leaders to Act With Confidence
IDI’s decision support solution is an execution framework that implements decision analysis methods and mathematics for organizations facing complex tradeoffs across multiple viable options. It is not a panacea, but it is a powerful step forward, offering technical capabilities that IDI’s consulting experts use to help customers make informed decisions. Critical elements of decision support are automated and applied at scale within MarkLogic’s Enterprise NoSQL database, enabling IDI to tailor solutions to the decision at hand. This application allows analysts, experts, and decision makers to break down a decision’s complexity and adapt it to change over time – empowering leaders to act with confidence when making strategic investments of money, time, and credibility.
A powerful combination of risk analysis and decision support, below is a graphical overview of a cyber risk decision support model IDI has developed for a U.S. government agency:
For more information, please see our solutions and resources for Government.