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Data Driven Strategies in Procurement

Data Driven Strategies in Procurement. Tom Roberts Jason Stanton Director Systemwide Program Analyst Contract Services & Procurement Office of the Chancellor. Data to Management Information. What is data Data can be any level of information detail from our systems (or elsewhere)

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Data Driven Strategies in Procurement

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  1. Data Driven Strategiesin Procurement Tom Roberts Jason Stanton Director Systemwide Program Analyst Contract Services & Procurement Office of the Chancellor

  2. Data to Management Information • What is data • Data can be any level of information detail from our systems (or elsewhere) • What is management information? • Management information is gleaned from data and used to make decisions. Business Intelligence (BI) • There is a place in business for both

  3. Mining Data • Choices in data to use • Raw data • Cleansed data • Enriched data • Choices of accessing data • PeopleSoft financial system • Downloading into applications then manipulating it • Data Warehouse • Spreadsheets or databases • Oracle (or other) tools • Hire a third party

  4. CSU Hired a Third Party • Spikes Cavell • Spend analytics company specializing in public sector • We now have: • Three years of data (refreshed every four months) • All campuses / business units • Over 100 user accounts systemwide • Can see our data and data from other institutions

  5. What Does Spikes Do? Appending of supplemental attributes from Spikes Cavell and licensed 3rd party reference datasets to each of the core trade vendor records. Accurate extraction of raw financial data from PeopleSoft and US Bank. Data standardization, removal of duplicates and identification of errors. Aggregation of all of the spend and related data into a single, unified and consistent master database. Identification and redaction of payments made to individuals or where security might be compromised. Classificationof vendor and purchase card datainto NAICS, NIGP, and vCode categories DATA 2 5 3 1 4 6 COLLATE COLLECT ENRICH REDACT CLEANSE CLASSIFY

  6. Raw Data A/P Voucher Level Transaction Table

  7. PeopleSoft Open PO Report • Sample of a few lines from the PeopleSoft report

  8. Commodity Codes Project • Recommend an approach to change the use of the current NIGP commodity codes from three to five digits to achieve a more granular reporting of expenditures with in the CSU.

  9. CSU Current Use of Codes • Started out 12 years ago with 270 NIGP codes • Now over 1,000 codes across all campuses • Created by campuses for their individual needs 88200 96185 DEFAULT 96256 15027 42500BT 84066C 42554N 95403 LAMPS TRVL

  10. Commodity Codes Project • Recommend an approach to change the use of the current NIGP commodity codes from three to five digits to achieve a more granular reporting of expenditures with in the CSU. • Findings • The CSU does not use commodity codes in a uniform manner across campuses • Large jump from 270 select codes to the full five digit NIGP series • UNSPSC or NIGP are both used in online catalogues

  11. CSU Data by the Numbers • 2012/13 Fiscal Year Transaction Count • 1,028,000 AP voucher lines (313,000 vouchers) • 242,000 pCardtransactions • 91 tables

  12. High Level View of Data Transaction Volume In Dollars pCard $127m pCard 242,000 Non-pCard 313,000 Non-pCard $1.3b 95% Accuracy Target

  13. Low Level Data Rolled Up

  14. Low Level Data Charted • Spikes Chart here – Whole Slide • Invoice Distribution by Range of Invoice Values (Summary) all campuses – non p-card filter

  15. Low Level Data Drilled • Spikes chart here -Whole Slide • Invoice Distribution by Range of Invoice Values (Low End) non-pcard

  16. Conclusions? • Spikes chart here -Whole Slide • Invoice Distribution by Range of Invoice Values (Low End) non-pcard

  17. Progressive Value-add to the CSU over Three Years • Year One(the learning year) • Perfected data collection methodologies • Custom face-to-face visits/demos/training for many campuses and groups (FOA, PSSOA) • CSP Data Analyst serves as first response to end user support. • Spend Analytics used in several CO projects

  18. Progressive Value-add to the CSU over Three Years • Year Two(guiding campuses to savings, creating awareness) • Delivered 23 campus-tailored Savings Opportunity Assessments and tutorials in: • Invoice Consolidation (reduce invoice volume) • Category Rationalization (reduce vendors in highly populated commodity or service categories) • Compliance with Contracted Vendors (confirming campus is purchasing from vendors under contract)

  19. Invoice Consolidation • From 2011/12 to 2012/13 – Reduction of AP invoices in almost all campuses (2% systemwide, over 5,300 invoices) • During the same period – overall increase of 1% in total spend • Increase of 2% in pCard usage • According to RPMG Research Corp, each invoice can cost up to $71 from receipt to payment. Overall value-add would then exceed $376,000 (2010 Purchasing Card Benchmark Survey)

  20. Progressive Value-add to the CSU over Three Years • Year Threein progress (“spend under management”) • Development of project program to define how much CSU total spend is being managed (under contract). • This is a necessary metric in measuring strategic sourcing and contract compliance success. • Campuses will be presented with a specific action plan to bring greater spend under contract • Joint development (at no cost to CSU) of custom dashboard views of spend for executive review.

  21. Spend Under Management • 849 contracts uploaded to the Spikes Observatory from: • CSU systemwide contracts • UC contracts • DGS contracts • E&I contracts • One-stop place to search for available contracts • Ability to track monthly spend with contracted vendors

  22. Spend Under Management

  23. Spend Under Management Monthly spend with contracted vendors

  24. Example ofCampus Use of Data:San Luis ObispoDru Zachmeyer, Director

  25. San Luis Obispo

  26. San Luis Obispo

  27. San Luis Obispo

  28. San Luis Obispo

  29. San Luis Obispo

  30. San Luis Obispo

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