Advancing Aviation Safety and Efficiency through Innovative Technology

Oakleaf Group Analytics Execution Framework Process

Oakleaf Group brings to our clients our proprietary Analytics Execution Framework, developed over the last decade to optimize analytic business processes at financial institutions and regulators. The execution framework ties together all necessary components to execute analytic processes in an efficient and controlled manner.

 Oakleaf Group’s Analytics Execution Framework emphasizes innovation at every stage. Our team continuously identifies ways to further improve upon our customers’ solutions, processes, tools and technologies by developing new tools, formulating new designs and providing reusable knowledge.

Oakleaf Group Analytics Execution Framework™

Project Management Methods for Analytics-Based Business Processes

Use Cases: Set, manage and mature large-scale quantitative and analytic business processes

Financial Modeling ♦ Stressing Testing ♦ Econometrics-based Pricing & Valuation Studies ♦ Forecasting ♦ Monte Carlo Simulations ♦ Model Development ♦ Research Studies ♦ Statistical Analyses ♦ Financial Risk & Risk Scenario Analyses ♦ Financial Research Supporting Policy Formulation

Oakleaf layers-over the traditional project lifecycle with the five areas below, reflecting best practices for designing, executing, controlling and maturing analytic processes on large complex data sets.

Initiation & Planning

Execution, Monitoring, Control & Close-out

Mission-focused Outcome Orientation

• Project Value Expectations

• Data Asset & Inventory

• Future State Vision

• Outcome/Baseline Planning

• Decision Needs Prioritization

• Knowledge Transfer Plan


• Implemented Analytics Value & Improved Decision-Support Capabilities

• Value of Outcomes Reporting

• Value of Current & Future (Desired) Outcomes

• Decision Needs Mapped to Analytics Roadmap

• Continuous Knowledge Management

• Data Reliability & Fitness Improvements

Business and IT-Aligned Development Methodology

Discover IT Department Requirements & Standards;

• SDLC & Agile/Dev Ops Standards

• Info Sec, Business Continuity, Data Privacy

Discover Business Area’s: Quantitative, Analytic, and Forecasting Business Processes


• Alignment of Enterprise IT & Data Management with Analytics Environment

• Conduct Agile/ Dev Ops-based Sprints for Process Improvement of Analytic Environment

• Continuous Business & IT Communication

Innovation Mandate at Every Stage

• Model Performance Expectations

• Analytics Prototyping

• Project Analysis

• Capture Process

• Identification of Immediate & “Quick Hit” Opportunities

• Continuous Improvement Recommendations (ad hoc and monthly reports)

• Innovation and Execution Reporting

• Prototype

• “So What?” Deck

• Scenario Analysis Design, Scenario testing and Attribution Analysis

Big Data Sets

• Evaluate Client’s Big Data Analytic Tools and Data Sets

• Quantitative and Big Data Tools Selection & Utilization (R, SAS, Python, Hadoop, AWS, etc.)

• Data Sensitivity Analysis

• Analytics Tool Peer Review

• Source Data Management

• Standardization and Management of Analytic Support Data Sets

Optimize Client’s Analytics Environment

• Assessment of Analytics & Data-dependent Decision-Support Needs

• Analytics Capabilities & Resources Assessment

• Analytics Optimization Roadmap

• Analytic Tools & Environment Maturity & Gap Assessment

• Analytics Maturity & Environment Improvement Plan


• Analytics Program Risks Management

• Resources and Skills Assessment

• Resource Development Planning

• Implemented Analytics Improvements

• Capture Lessons Learned

• Leverage Designs & Processes for Client’s Re-use

• Development Feedback

• Analytics Maturity Action Plan & Innovation Roadmaps

Performance-Tested Process

Oakleaf Group’s Analytics Execution Framework evolution since 2007

  • Initial version used at Fannie Mae and FDIC to automate and control execution of multiple models using SAS and shell scripting. Created single-click, lights-out execution of complex models to shorten execution times from days to hours.
  • Subsequent investments to add compliance with IT SDLC standards to deploy to production environments
  • In 2010 Oakleaf Group deployed the Process to commercial banks and added support for R.  Version 2 of the process created. Created an operational risk modeling framework with scenario analysis and attribution analysis.
  • In 2013 Oakleaf Group deployed the process for asset managers pursuing litigation. Created a structured finance model library.  2014: Added support for Python.  Build Monte Carlo module.  Support litigation generating over $100 million in recoveries for clients.
  • In 2017, Oakleaf Group has a mature process for analytics execution to bring to DERA.