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Data Science in Sourcing Gartner BI 2016
- 1. 1 Analytics Accelerator What questions do you have? 1 How Data Science and Spend Analytics Found $100 Million+ in Savings
- 2. Tamr works with analytical teams at all stages of maturity improving business process decisions. 2
- 3. Andy Palmer Co-Founder & CEO Previously: Co-Founder & CEO, Vertica CIO Infinity Pharmaceuticals Global Head of Software and Data Novartis Institute for Biomedical Research Dr. Michael Stonebraker Co-Founder & CTO Previously: Co-Founder & CTO, Vertica Founder, Ingres Architect, Postgres 2015 ACM A.M. Turing Award Jerry Held Chairman Previously: CTO Tandem, VP Engineering Oracle Founded in 2013 By Enterprise Database Software Veterans
- 4. The Contract is Changing Right Now Outcomes and Behavior Transformation Business Automation and Process Enablement IT
- 5. Reporting and Descriptive Data and Enablement From Basic Reporting To Data Services Flexibility
- 6. The Challenge: Overwhelming Amount of Messy Data 6 ERP Sources Source-to-pay Sharepoint Supplier spreadsheets Concur Market intelligence Sources
- 7. Customer Case Study: Large, Diversified Manufacturing Teams ● Corporate IT, Analytics COE ● Sourcing Council, Functional Teams Desired Outcomes ● Designate Best Contract Terms ● Renegotiate Pricing in the Long-tail ● Assess Supplier Risk Challenge ● Hundreds of P&L’s and ERP’s ● No accurate supplier master list and sparse classification
- 8. Slew of Additional Cases for Tamr-Created Data Asset Inventory rationalization: reduce the number of duplicate items being held in inventory to reduce overall inventory levels SKU rationalization: consolidate spend with the lowest cost suppliers of comparable items Payment terms optimization: identify payment term discrepancies across business units and supplier subsidiaries Contract Compliance: identify invoices that violate specific contractual terms Travel spend optimization: improve policies and compliance with a granular understanding of how employees spend on travel M&A integration: identify cross-BU leverage points to drive down costs enterprise-wide
- 9. Machine learning and expert sourcing are used to prep the data needed for rapid, repeatable insight 9 Data in its native formats is ingested and validated by Tamr Tamr’s machine-learning algorithms clean & classify ~60% of the data Algorithms adjust by asking domain experts for high-impact feedback and can reach ~95% classification Is “Husky #.25 J Blt” a bolt? YES NO Automate Extend
- 10. Tamr automates data prep to enable analytics teams to quickly identify opportunities 10 Contracts Existing EDW External Benchmarks MDM Systems Purchase Orders Parent-Child Suppliers Sources Flexibility Direct Spend Granular Categories Best Contract Terms Supplier Risk
- 11. Customer Case Study: Large, Diversified Manufacturing Solution ● Pulled data from a variety of spend data sources and integrated / cleansed the data ● Accurately classified parts and suppliers through automation + expert sourcing ● Enabled Tableau Dashboards and Advanced Analytics Benefits ● Scaled to $40B in spend across hundreds of ERP and other Sources ● Identified $100M in contract opportunities ● Driving long-tail category views of spend
- 12. This enables organizations to think holistically about how they can improve their business Past: laundry lists of open-ended problems across functions Today: prioritized recommendations
- 13. 13 Analytics Accelerator What questions do you have? 13 Q&A Booth 114
Editor's Notes
- Questions / Qualification: Need: Why did you take this call? What isn’t the business able to accomplish now? What would solving this problem enable the enterprise to do? Why is this important? How are you currently doing this? What is the implication of doing it this way? What activities does this bottleneck for your org? What would success look like? Authority: Describe your role in the organization and in solving this problem Who else are you working with in solving this problem? What are their roles? Budget / Time: Is this for a current project? Future budgeted project?
- I’ll make this better but is this generally what you are thinking? YES
- Reduce travel spend
- Questions / Qualification: Need: Why did you take this call? What isn’t the business able to accomplish now? What would solving this problem enable the enterprise to do? Why is this important? How are you currently doing this? What is the implication of doing it this way? What activities does this bottleneck for your org? What would success look like? Authority: Describe your role in the organization and in solving this problem Who else are you working with in solving this problem? What are their roles? Budget / Time: Is this for a current project? Future budgeted project?