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Procurement Analytics: Swipe Mapping Your Data Journey Across the Source-to-Pay

Unleash the power of Procurement Analytics to optimize your Source-to-Pay (S2P) cycle. Our comprehensive solution enables you to map your data journey seamlessly, empowering you to uncover actionable insights, streamline processes, and drive strategic decision-making for maximum procurement efficiency and cost savings.

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Procurement Analytics: Swipe Mapping Your Data Journey Across the Source-to-Pay

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  1. ProcurementAnalytics s Mapping your data journey across Source to Pay(S2P) cycle Swipe

  2. Payments Spend Analysis Category Strategy Invoice Management Good Receipt Service Confirmation Strategy Execution DATA Purchase Order Management Supplier Management Purchase Requisition Contracts Management Swipe

  3. The cycle of Procurement Analytics Act on the derived insights to capture incremental Capture good quality relevant data at source 5 1 Interpret the collated data to derive meaningful insights Store the data in a standardized Data Lake or Data Warehouse 4 2 3 Build analytics use cases out of available data estate Swipe

  4. In week 1 we spoke about different data sources in Source to Contract journey and complexity of incorporating those for our analytics Spend Analysis Category Strategy Strategy Execution Supplier Management Contract Management Low Medium High Swipe

  5. In week 2, we addressed the complexity of extracting the data from source, standardizing, connecting it to each other, linking all data sources together and pushing into a centralized Data warehouse Swipe

  6. Payments Spend Analysis Category Strategy Invoice Management Good Receipt Service Confirmation Strategy Execution Purchase Order Management Supplier Management Purchase Requisition Contracts Management Swipe

  7. This week, lets talk about how to Build Analytics uses cases using the robust Data Estate we just created Build Analytics use cases out of available data estate 3 Swipe

  8. Comprehensive analytics may be conducted by merging the different available data sources in a structured fashion Data received from the procurement transaction systems Data received from the procurement transaction systems Data extracted from available data and documents using OCR, AI and machine learning models Data pulled from 3rd party sources (tealbook, eco vadis, TINCHECK, IBAN etc.) Swipe

  9. Common Analytics use cases across STC process cycle Spend Analytics Spend by Category, Business Unit and Region Spend under contracts Spend with qualified suppliers Spend by buying channel Spend with P Card Spend with Preferred Suppliers Spend with Low performing suppliers Spend with suppliers with Sustainability certificates Spend with Diverse suppliers Swipe

  10. below are some examples on how to build Spend Analytics data sets Invoice Paid data P CARD Level 2 Data Spend by Category, Business Unit and Region Travel and Expense data Category Names/ID Supplier provided line-item data Vendor Master BU Names/ID Geography Names/ID Invoice Paid data P CARD Level 2 Data Spend under contracts Travel and Expense data Contracts meta-Data Invoice Paid data P CARD Level 2 Data Spend with suppliers with Sustainability certificates Travel and Expense data Vendor Master 3rd Party Sustainability data Invoice Paid data P CARD Level 2 Data Spend by buying channel Travel and Expense data Vendor Master Buying channel planning Supplier provided line-item data Invoice Paid data P CARD Level 2 Data Spend with Diverse suppliers Travel and Expense data Vendor Master 3rd Party Diversity data Swipe

  11. Common Analytics use cases across STC process cycle Category Management Sourcing Event Analytics Tail Spend Management Savings Delivery or Cost Avoidance Sourcing technology Diverse Suppliers Sourcing cycle time Supplier Engagement Sourcing Channel Effectiveness Swipe

  12. below are some examples on how to build Category Strateg? & Execution data sets RFX/Auction Event meta-Data Award Information Sourcing Event Analytics Vendor Master Category Names/ID BU Names/ID Geography Names/ID Invoice Paid data P CARD Level 2 Data Tail Spend Management Travel and Expense data Buying channel planning Supplier provided line-item data Vendor Master RFX/Auction Event meta-Data Award Information Savings Delivery or Cost Avoidance Vendor Master Negotiated prices Supplier provided line-item data Invoice Paid data RFX/Auction Event meta-Data Award Information Sourcing technology Vendor Master Swipe

  13. Common Analytics use cases across STC process cycle Supplier Management Supplier Landscape Supplier Performance Supplier Risk Management Single/Sole source spend Duplicate Suppliers New Supplier Introduction Supplier Enablement Sustainable suppliers Swipe

  14. below are some examples on how to build Supplier Management data sets Vendor Master RFX/Auction Event meta-Data Supplier Landscape Invoice Paid data P CARD Level 2 Data Travel and Expense data Invoice Paid data P CARD Level 2 Data Supplier Performance Travel and Expense data Performance survey data Travel and Expense data Vendor Master Single/Sole source strategy Negotiated prices Receipt and Service confirmation Data PO Line level Data Contracts line level data Invoice Paid data Supplier Risk Management Travel and Expense data Vendor Master Performance survey data 3RD Party Risk data (Environmental/financial/PEP/ OFAC/Geo Political etc.) RFX/Auction Event meta-Data Award Information Single/Sole source spend Vendor Master Contracts meta data Invoice Paid data RFX/Auction Event meta-Data Sustainable suppliers Award Information Vendor Master 3rd Party sustainability data Swipe

  15. Common Analytics use cases across STC process cycle Contract Management Contract Analytics Financial Commitments Contract Compliance Contracts Technology Contract Utilization Contracting cycle time Obligation Management Contract risk Analysis Swipe

  16. below are some examples on how to build Contract Management data sets Contracts meta-Data Vendor Master Contract Analytics Category Names/ID Category Names/ID BU Names/ID Geography Names/ID Contracts meta-Data OCR Data from Contracts Financial Commitments Machine Learning services Contracts meta-Data OCR Data from Contracts Contract Compliance Machine Learning services Invoice Paid data Travel and Expense data Supplier provided line-item data Contracts meta-Data Contracts Technology Manual data collected from Contract analysts/Legal Contracts meta-Data OCR Data from Contracts Contract risk Analysis Machine Learning services Invoice Paid data Travel and Expense data Supplier provided line-item data 3RD Party Risk data (Environmental/financial/PEP/ OFAC/GeoPolitical etc.) Swipe

  17. Once the Analytics use case has been structured correctly multiple useful insights and subsequent action may be derived from it Swipe

  18. How many RFPs have been released that did not include any Diverse supplier? Is there a specific category where the Diverse supplier inclusion is particularly low? What is the rate of business award to Diverse suppliers, when invited? Are we including the right diverse suppliers in the mix? Which other potential Diverse suppliers could be invited for the next iteration of the RFP? What is the average % price gap between Diverse supplier and awarded supplier, if diverse supplier was not awarded? Is there a significant capability gap between Diverse suppliers and non diverse suppliers? Which Diverse suppliers can be incubated and grown as potential suppliers in future? Swipe

  19. More information on extracting the right insights in the next edition of our STC Analytics Series

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