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Tomkins Spend Visibility Project Kick-off Meeting

Tomkins Spend Visibility Project Kick-off Meeting. May 17, 2010. Keith Luers, C.P.M. SV Project Mgr. Agenda. Introductions Spend Visibility Overview Project Scope Project Overview Roles Timeline Project Phases Data Acquisition Overview Enrichment Overview

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Tomkins Spend Visibility Project Kick-off Meeting

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  1. Tomkins Spend Visibility Project Kick-off Meeting May 17, 2010 Keith Luers, C.P.M. SV Project Mgr

  2. Agenda • Introductions • Spend Visibility Overview • Project Scope • Project Overview • Roles • Timeline • Project Phases • Data Acquisition Overview • Enrichment Overview • Designated Support Contacts • Next Steps

  3. Ariba Data Enrichment Ariba Analysis Processing Engines, Supplier DB, Knowledge Base Reporting UI Spend Visibility Overview • Software and Solution • Ariba Analysis Software • Hosted • Configurable database with reporting UI • Ariba Data Enrichment Software • Hosted • Processing engine • Supplier database • Knowledge (rules/content) databases

  4. Ariba Data Enrichment Ariba Analysis Processing Engines, Supplier DB, Knowledge Base Reporting UI Spend Visibility Overview • Software and Solution • Ariba Analysis Software • Hosted or installed • Configurable database with reporting UI • Spend Visibility • Fully hosted Analysis and ADE • Project Management services provided to enable data collection and validation • Data Enrichment services provided to classify transactions and enrich supplier information • Standard data schema enables robust OOTB reports • Web deployed Analysis user interface • Ariba Data Enrichment Software • Hosted or installed • Processing engine • Supplier database • Knowledge (rules/content) databases

  5. Implement Contract & Execute Identify Opportunity Develop Strategy Source & Negotiate Invoice& Pay Monitor &Manage Spend Visibility Enables Best In Class Sourcing • Visibility should be the launching pad for all sourcing and procurement activities • Provides high level view of corporate spend for strategic planning • Enables supplier evaluation for spend and parent/child leverage opportunities • Fuels the drive for opportunity visibility • Allows to answer key questions like - What we spend our money on and who we spend it with - across multiple source systems and company sites, etc

  6. Agenda • Introductions • Spend Visibility Overview • Project Scope • Project Overview • Roles • Timeline • Project Phases • Data Acquisition Overview • Enrichment Overview • Designated Support Contacts • Next Steps

  7. Project Scope • Number of Source Systems: 17 • Estimated Annual Spend: $2B • Number of Users: 200 Max • Initial Deployment: 12 months historical data (2 phases) • Refresh Cycles: Quarterly • Refresh Data: 3 months worth of data

  8. Project Scope • Service Level Agreement: • Ariba certified commodity classification on a minimum of 90% of customer spend • 95% accuracy of Ariba classifications when supported by data • 90% accuracy of Ariba classifications when data does not support 95% accuracy • Supplier enrichment for a minimum of 90% of customer spend • 95% accuracy of parentage for Supplier Records with name and address information – minimum of country and city • 90% accuracy of parentage for Supplier Records when no country or city information provided • Implementation of customer “Custom Taxonomy” of up to six levels

  9. Agenda • Introductions • Spend Visibility Overview • Project Scope • Project Overview • Roles • Timeline • Project Phases • Data Acquisition Overview • Enrichment Overview • Designated Support Contacts • Next Steps

  10. Project Overview: Roles • Ariba • SV Project Manager – Daily responsibility for execution of hosted Spend Visibility program • ADES Manager and Team – Responsible for data enrichment process • Tomkins Gates • Customer SV Champion – Overall responsibility for success of Spend Visibility program • Customer SV Project Manager – Daily responsibility for execution of Spend Visibility Manager (may be Champion) • Business Owner(s) – Individuals who understand client business data from a user prospective, facilitates the validation spend based on extracted data (Typically one representative from each business unit) • IT Owner(s) – Individual(s) within the client organization who own responsibility for data extraction and transformation if required

  11. Client Ariba PM ADES Project Overview: Timeline (Typical) Refinement 1 – 2 Weeks Deployment 1 Week Collect and Validate Data 4 - 8 Weeks Data Enrichment 5 – 9 Weeks • Extract data • Approve Spend • Load final data, QA, publish • Train customer on SV Analysis • Train Client on Data Schema • Initiate Analysis site deployment • Receive, validate, and load data Review question sheets and provide feedback Review refinement drop in AA and provide feedback • Enrichment Assessment • Set timeline Perform Enrichment Automated + Manual Apply Feedback

  12. Project Phase: Data Collection & Validation • Goal: • To collect customer’s spend data in the most complete and form fitting way possible. • Activities: • Conduct the KickOff Meeting • Train the customer on the data schema • Proactively work with client on issues/questions to ensure spend data is collected in the right format • Use the visibility tool to validate data which has been submitted. • Extract data • Approve spend • Train Client on Data Schema • Initiate Analysis site deployment • Receive, validate, and load data • Enrichment Assessment • Set timeline

  13. Project Phase: Data Enrichment • Goal: • To classify and enrich customer’s spend providing easy segmentation and thus visibility into spending patterns. • Activities: • - Coordinate enrichment and timeline with the ADE Manager • Present project plan and timeline to customer • Educate customer on Ariba Analysis Tool and Enrichment Process • Load and Validate Enrichment results into the Ariba Analysis Tool Review question sheets and provide feedback Perform Enrichment Automated + Manual

  14. Project Phase: Refinement ** Note will only do after 2nd cycle • Goal: • Educate the customer on building reports and the refinement feedback form • Crete report templates • Collect and apply feedback • Combination of manual feedback and automatic through Analysis tool Review refinement drop in AA and provide feedback Apply Feedback

  15. Project Phase: Deployment • Goal: • To publish the approved data on the customer’s instance and enable them to use their site • Activities: • - Load final data • QA final data • Push final data to Presentation • Train customer on Analysis • Customer satisfaction survey • Load final data, QA, publish • Train customer on SV Analysis

  16. Tomkins Gates Specific Project Plan

  17. Agenda • Introductions • Spend Visibility Overview • Project Scope • Project Overview • Roles • Timeline • Project Phases • Data Acquisition Overview • Enrichment Overview • Designated Support Contacts • Next Steps

  18. Data Acquisition Overview • The Ariba Data Acquisition Schema • A roadmap for the customer to create files in the proper format • Helps the customer to define which data they want to include for upload • Provides technical “do’s” and “don’ts” for the IT owner to follow in data extraction • Defines the various tables and fields, and the requirements for their successful creation • Is the primary and final reference for all matters relating to data extraction and file creation.

  19. Data Acquisition Overview • Where does the data come from? • Spend Data refers to the accounts payable data or any other supporting data including but not limited to purchase order data, purchasing card data, and third party payable data which the client provides to Ariba for processing during the Spend Visibility project. This data may include transactional data and data identifying client suppliers from any accounts payable systems. • A Source System generally refers to a standalone software installation where actual payment transaction data is available (typically AP systems). • The creation of a complete data set for a given Source System may include feeds from multiple feeds a number of systems to augment the AP data.

  20. Data Acquisition Overview Example of Related Systems Invoice (payment) information found in an AP system describes the transaction but does not contain a lot of related detail 1 invoice system = 1 SV Source System Supporting supplier detail may be found in a vendor master system 1 vendor master ≠ 1 SV Source System PO and item master detail may be found in an MRP system 1 MRP system ≠ 1 SV Source System Three separate source systems = 1 SV Source System

  21. Data Acquisition Overview Example of Independent Source Systems Oracle = 1 SV Source System SAP = 1 SV Source System To capture all the spend, transactions from both Oracle AP and SAP AP are required = 2 SV Source Systems

  22. Data Acquisition Overview Questions • The following questions need to be answered prior to an extract being generated • What constitutes an Accounts Payable (AP) Spend Event? • Invoice entered for eventual payment • Invoice receipt • Invoice payment • PO receipt • Other? • What types of transactions/spend should be included/excluded? • Invoice supported by PO • Invoice without supporting PO • P-Card • Expenses • Check Requests • Wire Transfers • Intra/Inter-Company • Payroll (should probably be excluded from extract) • Other Transaction Types

  23. Data Acquisition Overview Questions • Which ERP date field should be used to determine transactions that are in scope/out of scope? • Which timeframe should the extract include? 12 months per contract • How should taxes be handled? • Is it necessary to flag direct vs. indirect spend? • Is it necessary to flag Internal vs. External Suppliers? • Are there specific requirements for enrichment we should be aware of upfront?

  24. Data Acquisition Overview – Next Steps • A formal Data Acquisition Schema training will be right after this overview session • The following team members should be present: • Ariba Project Manager • Customer Project Manager • Business Analysts or Business Users • IT Resources (person(s) performing extracts)

  25. Agenda • Introductions • Spend Visibility Overview • Project Scope • Project Overview • Roles • Timeline • Project Phases • Data Acquisition Overview • Enrichment Overview • Designated Support Contacts • Next Steps

  26. Data Enrichment Overview • The Ariba Data Enrichment (ADE) team will focus on two areas for enrichment: • Supplier - Provide parentage and enriched supplier information. • Invoice - Classify to a commodity code based on descriptive and ‘hint’ fields available in the customer-provided data.

  27. Data Enrichment Overview • The following fields will be used to assign supplier parentage during the supplier enrichment: • Name • Address • City • State • Zip Code • Country

  28. Data Enrichment Overview Supplier Enrichment Example Outcome Spend with the Palmer House Hilton was $4,456, but total spend with Hilton Hotels Corporation as a parent is $577k Enriched Supplier Parent Enriched Supplier Supplier Provided

  29. Data Enrichment Overview • Supplier Level Hierarchy in Analysis • Level 1 (highest): Active Supplier / Low Activity Supplier • Shows enriched supplier parent for top 75% of spend or line items. The remaining 25% is grouped in one value as Low Activity Suppliers • Level 2: Supplier Parent (enriched) • Parent of raw supplier as enriched • For the active suppliers, this will be the same as Active Supplier • Level 3: Supplier (enriched) • Supplier name after it has been Enriched • Level 4: ERP Supplier • Raw supplier as imported from source system (ERP) • Basis for supplier dimension

  30. Data Enrichment Overview • The following hint fields will be used to help perform classification during the invoice enrichment: • Invoice & PO Descriptions • Part Descriptions • Suppliers • ERP Commodity Descriptions • GL Accounts • Invoice Flex Fields (1-3)

  31. Data Enrichment Overview Invoice Classification Example Customer Provided Information Ariba Classifications This example shows how the ADE classification process looks at multiple sources of information to make a classification to UNSPSC

  32. Data Enrichment Overview • Invoice Enrichment • Ariba Analysis allows users to report on invoice commodity classifications using the following fields • UNSPSC – United Nations Standard Products and Services Code • ACT – Ariba Classification Taxonomy

  33. Data Enrichment Overview • UNSPSC • Level 1: Segment • Example: 44 – Office Equipment, Accessories and Supplies • Level 2: Family • Example: 44 12 – Office Supplies • Level 3: Class • Example: 44 12 19 – Ink and Lead Refills • Level 4: Commodity • Example: 44 12 19 03 – Pen Refills

  34. Data Enrichment Overview • ACT • Foundation is UNSPSC • New codes are being constantly added from 3 different sources: • Newer version UNSPSC table when it is available. • Leverage other industry taxonomies as benchmarking (e.g. Wand, eClass, NATO etc) • SV customers' specific needs (e.g. Ingredients-Fruits-Fresh Fruits-Fresh Oranges) • Offers six level - allows more detailed classification results than UNSPSC

  35. Data Enrichment Overview • ACT • Level 1, Example: Chemicals including Bio Chemicals and Gas Materials • Level 2, Example: Compounds and Mixtures • Level 3, Example: Inorganic Compounds • Level 4, Example: Inorganic Acids • Level 5, Example: Nitric Acid • Level 6, Example: Pure Nitric Acid

  36. Source Data Hints Expense Description Part Description other hints Supplier Name Invoice Description GL Account Commodity Description Supplier Address Supplier Engine Rationalization Engine Business Rule Engine • Text Reading • Learned Models • Custom Mapping • Custom Rules • 39M+ Supplier Database • Matching & Parentage • Enrichment: Industry (SIC and NAICS), Revenue Enriched Spend Data Inference Engine • Weighted Triangulation Data Enrichment Overview • Data Enrichment Classification Methodology

  37. Agenda • Introductions • Spend Visibility Overview • Project Scope • Project Overview • Roles • Timeline • Project Phases • Data Acquisition Overview • Enrichment Overview • Designated Support Contacts • Next Steps

  38. Designated Support Contacts • Designated Support Contact (DSC)* • Allows the user to submit administrative requests including: • Master data updates, site customizations, legal agreement changes, and enhancement requests. • Acts as liaison for end-user requested changes • Interfaces with Ariba regarding end-user issue trends • DSCs automatically receive the following types of notifications: • Scheduled/unscheduled downtime • Security information/bulletins • Information on new product releases, new features and service pack availability • Full access on Connect.ariba.com *Designated Support Contact access is available for up to 3 contacts per solution. If you have any questions, please contact supportservices@ariba.com.

  39. Becoming a Designated Support Contact • Register on Connect • Navigate to https://connect.ariba.com • Click the “New User” link • Complete the brief registration form • After you set up your account, you will receive an email from Connect Support when your account is activated. Please respond to the email from Connect Support and request DSC access. • If you have any issues logging in or creating the account on Connect, send an email to connect_support@ariba.com.

  40. Agenda • Introductions • Spend Visibility Overview • Project Scope • Project Overview • Roles • Timeline • Project Phases • Data Acquisition Overview • Enrichment Overview • Designated Support Contacts • Next Steps

  41. Next Steps • Data schema training • Receive/review extracted data • Begin uploading and validating data • Validate and approve spend • Enrichment Process • Automated Process • Manual Process • Refinement drop and feedback • Deployment • Survey

  42. Instance Set-Up (Hosted Site) • URL Convention • http://tomkins.sourcing.ariba.com/ • Currencies • USD Default • Up to 5 additional • Unit of Measure • Metric (gram, kilometer) • US (pound, mile) • Source Systems • Quantity - 17 • Names – see supplied list to fill out

  43. Communications Plan • Weekly Status Call (best days/times?) • Weekly Project Status Report & Project Plan

  44. Support and Escalation • Project Manager – Keith Luers,C.P.M. • Data Issues / Day to day project support • Analysis support and training • kluers@ariba.com • 719 260 6333 • Spend Visibility Support • https://connect.ariba.com • Analysis site via a webform • 1-866-218-2155

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