Analytical Engine

(There is no dictionary definition of P2P process, but often P2P is defined as a generic term used to encompass the payment for goods and services: The basic process of raising a purchase order, receiving the goods and paying the invoice is often put under P2P process .)

In a recently finished engagement with a manufacturing major, we leveraged Diamond’s procurement analytics solution to help the client identify dollar leakages and potential saving opportunities across their P2P process. This engagement had all the challenges associated with a large manufacturing setup viz. inbound and outbound from plants located across various locations, multiple vendors supplying the same raw material, a complex distribution and lack of unified IT systems. The list below can give you a feel of some the issues we identified –
1) Price variation/anomalies:
a. Procurement organization paying different price for the same raw material within the same time frame across different vendors
b. Price changes for certain non-contract items being anomalously higher (even in an increased demand scenario, where the organization might have had a chance to negotiate better prices)
2) Contract Adherence:
a. Shippers invoicing higher than the negotiated rates in purchase orders
b. Vendors charging prices which are not consistent with contract-negotiated prices
3) Freight Charge Variations:a. Different freight charges being charged for the same kind of delivery across supplies
b. Freight charges being consistently higher than industry standards
c. Variation in the freight charges for equal shipments from the same vendor Payment
4) Payment & Order Schedule:a. Payments made significantly prior to the negotiated deadlines leading to loss of revenue
b. Sub optimal volume discounts because of fragmented orders

Organizations are investing a lot of money and effort in IT solutions, designing data warehouse(s), and data collection methodology. These efforts, though, aimed at streamlining decision making processes, continue to exist in silos and are not creating the desired impact for the business. To help our client tackle this challenge, some of the things we tried to focus on, as part of the engagement were –

• Master Data Management: Integrating different data sources (General Ledger, Purchase Orders, Invoice, Vendor information etc.) and incorporating process information to come up with the final form of an analysis data mart
• Basic Data Profiling: Performing basic data validation, enriching/ cleansing and classifying required data, instead of building highly complex spend analyzers around existing solutions; The essence of all analytics done by a team should be the business benefit that can be derived, and not intellectual gratification
• Variance Reports: Leveraging the analysis data mart to create variance reports that help identify the variation in price/freights for a certain procured material
• Dashboards/Segmentation of the invoices : Developing a segmentation tool that helps identify where the money is invested/spent; Having a sense of where the dollars are going always helps businesses prioritize their spend rightly
• Payment segmentation: Identifying anomalies between the POs and Invoices, and keeping track of vendor issues such as reject rate/ quality, etc. can help renegotiate contracts, create appropriate procurement and penalty mechanisms for ongoing cost reduction
As can be seen, a significant part of our approach was about getting the basics right, and instituting basic analytics processes in place. Before moving on to advanced statistical concepts/techniques, we demonstrated the value of analytics through simplified dashboard and analytics reports,and showcased a potential saving of multimillion dollar to the client