Fortune 50 Global Financial Services Company.
Establish a risk benchmarking methodology to model risk consistently and objectively across their application portfolio, raise the general awareness of risk throughout the entire organization, and leverage the model to drive funding conversations and improved decision making.
- Performed a statistical model evaluating over 400 enterprise applications containing almost 8 million data elements from operational metrics and technological environment conditions
- Identified applications having higher relative risk and needing further review utilizing an objective assessment method and establishing a portfolio benchmark
- Developed detailed modeling process diagrams and instructions allowing for Knowledge Transfer (KT) and model mentoring with internal Subject Matter Experts (SME)
The ability to objectively identify application risk across a portfolio is a challenge. Funding for application risk mitigation and upgrades must be allocated in a fashion providing the largest return for the organization. Too often varied personalities, personal agendas, and incomplete application knowledge contributes to misplaced system funding decisions, placing the stability and profitability of a company at risk. Using an objective and structured methodology that leverages multiple data inputs to quantify risk can mitigate funding misdirection, improve internal associate and customer satisfaction, and optimize application investment.
The goal of the project was to evaluate and utilize an existing statistical risk assessment modeling tool developed in another line of business. Initially, a discovery analysis was performed to determine if the tool can be used with the available information. A detailed proof of concept was then conducted by gathering, transforming, and importing extensive amounts of operational and system environment metrics. The model was executed and the results were discussed with senior management and key application stakeholders. The entire transformation process, model calculations and model execution was fully documented. This documentation was used to explain the model to stakeholders and conduct knowledge transfer to the internal staff assigned to perform future risk assessments. Modeling results objectively identified applications needing further review. The project also included the facilitation of over 100 meetings with varied staff members throughout the organization. The analysis was able to identify application risks supporting 11 business units impacting 54,000 internal associates and 90 million clients in 60 countries.
The Major Oak Difference:
Major Oak’s team, led by a former CIO, brought expertise in IT strategy, technology management, and statistical model building. Our unique combination of skills and executive facilitation experience, allowed for the successful analysis and documentation of a complex statistical model. The results of the model provided an objective analysis that benchmarked the relative risk of each application across their entire portfolio and helped direct application investments.