Customized Procurement Data Analytics Strategies
Using decades of contract oversight and anti-fraud experience, we work in partnership with our clients to design and implement the most effective tailored procurement integrity data analytical and predictive model searches and approaches. Every organization wants its procurement data and analytics
to produce different information allowing them to achieve a business objective. Some want their analytics to help them be more effective in their oversight, others look to enhance their contract management, some need help in anomaly detection, and others want it all. No one strategy works and taking a “cookie-cutter-approach” only wastes limited financial resources. Even though there is no one way to do effective and efficient data analytics there are a few things to remember:
§ Know the Data - Knowing the data is not just understanding what data your organization is collecting, but also its availability, reliability, format (i.e. structured with predetermined data sets or free flowing textual or both), and how the data can be analyzed to identify indicators of specific risk of misconduct or improper payments.
§ Know the Risk - Along with knowing the data, you need to know the traditional techniques used that puts your contracts at risk to corruption, fraud, abuse, or can cause improper payments.
§ Know which Approach - You have to know how to design a tailored “analytical approach” that will indicate the specific contract risk which may have or has occurred in your specific organization. This is one of the most difficult aspects of data analytics of procurement data. Designing an effective analytical approach requires a strong understanding of the indicators (i.e. red flags) for each of the risks, such as misconduct and improper payments, along with a deep knowledge of how to structure searches to identify them.
It is no longer a question of how can data analytics enhance procurement integrity and identify improper payments, rather it’s how can we maximize the various techniques.