Data Governance challenges in a major Energy Company


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IRM Data Governance Conference February 2009, London. Presentation given on the Data Governance challenges being faced by BP and the approaches to address them.

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  • Slide Update: This slide is reviewed on an annual basis. Next update – April 2009. Speaker’s Notes: The information on this slide is taken from the Sustainability Report World Map featured on and will not be updated until the next Sustainability Report is published in April 2009. This slide is part of a set of seven slides that show where BP operates around the world. A simple option would be to use this slide only. However if you would prefer to link to more detail on a specific region then click on the Region buttons whilst in slide show. If you wish to incorporate these slides as part of your own slide pack you will need to adjust the links to your new slide numbers. To do this : 1)Right click on the button ( showing the region name) 2) Select Action Settings option 3) Go to Mouse Click 4) Select the Hyperlink option 5) Choose Slide option from the drop down menu 6) Preview and select the correct slide.
  • Most companies have silos of information. Why? People are busy and information sharing is seen as an “extra effort” WIIFM: There is no incentive to share information To remove those silos and encourage information sharing, remember: Reward drives behaviour. Make info sharing a carrot, not a stick Make it EASY for people Listen!! What do they want? Why aren’t they sharing now? Start Small, “Pick your Battles” wisely, and Communicate Find the ONE key pain that will have visibility Small, incremental, initial successes go a long towards long-term buy-in. i.e. “Don’t boil the ocean” Communicate successes back to the users Make the users an active part of the process Remember, we’re in the Blog era now! Users don’t want to be passive readers, but active participants. Allow users to update their own information (with the appropriate security and lifecycle controls in place) Make it easy Integrate governance into their daily workflow Automation and integration are key, for example: automatic updates to the metadata repository upon data model check-in. email notification when data definitions have changed
  • Data Governance challenges in a major Energy Company

    1. 1. Data Governance Challenges at BP IRM Data Governance Europe Conference London, February 2009 Chris Bradley Ken Dunn
    2. 2. Agenda <ul><li>What is Data Governance? </li></ul><ul><li>BP Roles and Approaches </li></ul><ul><li>BP Challenges & Case Studies </li></ul><ul><li>Making Data Governance Happen </li></ul>Data Governance 2.0
    3. 3. 1. What is Data Governance?
    4. 4. The Traditional View of Data Governance <ul><li>Things take a looong time. </li></ul>Data Governance 2.0 It’s not hip. It’s outdated. They’re so strict, they’re zealots about this stuff. It gets in my way 3NF It’s overly academic. I can’t understand it.
    5. 5. A Common Definition... <ul><li>Set of Standards, Policies, and Guidelines centred around Managing Corporate Data </li></ul><ul><li>Goals </li></ul><ul><ul><li>To enhance Data Quality </li></ul></ul><ul><ul><li>Promote the Reuse of core assets </li></ul></ul><ul><ul><li>Better service Executive Management and their decisions </li></ul></ul><ul><ul><li>To Communicate affectively to diverse stakeholders </li></ul></ul><ul><ul><li>To provide Accountability of data </li></ul></ul><ul><li>Tools, Modelling and Metadata help, but aren't the answer </li></ul><ul><ul><li>Need a defined program </li></ul></ul><ul><ul><li>Need principles to dictate ownership and accountability </li></ul></ul><ul><ul><li>Need to get to the source of the problem </li></ul></ul>
    6. 6. History: Data Management growth drives Data Governance Data Governance 2.0 Database development Database operation 1950-1970 Data requirements analysis Data modelling 1970-1990 Enterprise data management coordination Enterprise data integration Enterprise data stewardship Enterprise data use 1990-2000 Data quality Security & Compliance SOA Aligning with the Business 2000-beyond <ul><li>vs. the “new” view of Information </li></ul><ul><ul><li>Web 2.0 </li></ul></ul><ul><ul><li>Blogs </li></ul></ul><ul><ul><li>Mashups </li></ul></ul><ul><ul><li>Anyone can create data! </li></ul></ul>
    7. 7. So, what needs to change? <ul><li>Be relevant for the new technologies </li></ul><ul><li>Make information available in a format users understand. </li></ul><ul><ul><li>Don’t show a business user a data model! </li></ul></ul><ul><li>Make it real-time. </li></ul><ul><ul><li>Information should updated instantaneously. </li></ul></ul><ul><li>Allow users to give feedback. </li></ul><ul><ul><li>You’ll achieve common definitions quicker that way. </li></ul></ul><ul><li>But!...Remember the principles of data management </li></ul>Data Governance 2.0
    8. 8. What needs to stay the same? <ul><li>Modelling rigour </li></ul><ul><ul><li>Logical and Physical Data models </li></ul></ul><ul><ul><li>3rd normal form </li></ul></ul><ul><ul><li>Consistent definitions </li></ul></ul><ul><li>Standards & Governance </li></ul><ul><li>Ownership </li></ul><ul><li>Object reuse via a common repository </li></ul>Data Governance 2.0
    9. 9. DG Considerations: SOA <ul><li>Definition of data & consequently calls to / results from services is vital. </li></ul><ul><li>Straight through processing can exacerbate the issue </li></ul><ul><li>How traditional data principles still apply </li></ul><ul><ul><li>Standard Definitions: </li></ul></ul><ul><ul><ul><li>What does the data mean? which definition of X (e.g. “cost of goods”)? </li></ul></ul></ul><ul><ul><ul><li>Need to utilise the logical model and ERP models definitions </li></ul></ul></ul><ul><ul><li>Structured Models </li></ul></ul><ul><ul><ul><li>Logical model drives XML formats </li></ul></ul></ul>Data Governance 2.0
    10. 10. DG Considerations: Data integration & lineage <ul><li>Mashups & portals = easy assembly of data … … but is it correct? </li></ul><ul><li>Still need the basics: </li></ul><ul><ul><li>SOX lineage requirements </li></ul></ul><ul><ul><li>Repository based Data migration design = Consistency </li></ul></ul><ul><ul><li>Legacy data take on </li></ul></ul><ul><ul><li>Source to target mapping </li></ul></ul><ul><ul><li>Reverse engineer & generate ETL </li></ul></ul><ul><ul><li>Impact analysis </li></ul></ul>Data Governance 2.0
    11. 11. DG Considerations: ERP & packaged systems <ul><li>“ We don’t need a data model – the package has it all” </li></ul><ul><li>But, does it … </li></ul><ul><ul><li>Meet your business requirements? </li></ul></ul><ul><ul><ul><li>Data Model will aid configuration / fit for purpose evaluation </li></ul></ul></ul><ul><ul><li>Have identical data structures & meanings as your legacy systems? </li></ul></ul><ul><ul><ul><li>Data model will aid Data Integration, Legacy Data take on and Master Data integration. </li></ul></ul></ul>Data Governance 2.0
    12. 12. DG Considerations: XML messages <ul><li>XML becoming all pervasive …. </li></ul><ul><ul><li>Integration layers </li></ul></ul><ul><ul><li>“ Standard” XML schemas </li></ul></ul><ul><ul><li>Off the shelf web services (WSDL) </li></ul></ul><ul><li>But, who is analysing the metadata & meaning? </li></ul><ul><ul><li>Can utilise a logical data model for XML messages </li></ul></ul><ul><ul><li>But, XML message model = Hierarchic view of data model </li></ul></ul><ul><ul><li>Sub-models break up model into XML message chunk </li></ul></ul><ul><ul><li>Generate & customise XSD from sub-model </li></ul></ul><ul><ul><li>Import WSDL to capture metadata about data in the service </li></ul></ul><ul><li>Benefit = Accuracy, impact analysis, consistency </li></ul>Data Governance 2.0 ---- ---- ---- ---- ---- ---- ---- ---- ----
    13. 13. 2. BP Roles and Approaches
    14. 14. BP Overview <ul><li>BP is one of the world's largest energy companies, providing its customers with fuel for transportation, energy for heat and light, retail services and petrochemicals products for everyday items </li></ul><ul><ul><li>Turnover: $284 billion (year 2007) </li></ul></ul><ul><ul><li>Number of employees: 97,600 (at Dec 2007) </li></ul></ul><ul><ul><li>Service stations: 24,100 </li></ul></ul><ul><ul><li>Exploration: Active in 29 countries </li></ul></ul><ul><ul><li>Refineries: Interest in 17 </li></ul></ul>The data above is taken from the 2007 Annual Report and Accounts
    15. 15. Our global presence
    16. 16. BP Corporate Culture <ul><li>The company is a diverse federated organisation of “strategic performance units” – culture encourages local decision making within a corporate framework </li></ul><ul><li>Current position: </li></ul><ul><ul><ul><li>Data architecture planning, modelling & governance undertaken to different degrees in different Segments & Functions </li></ul></ul></ul><ul><ul><ul><li>Variety of tools & techniques used but the majority of data models are stored in an ER/Studio corporate repository </li></ul></ul></ul><ul><ul><ul><li>Projects encounter common cross business data concepts, but largely create their own models & definitions </li></ul></ul></ul>
    17. 17. Business Roles Three tier governance model <ul><li>Determine business process to manage information subject areas </li></ul><ul><li>Mandate stewardship and quality activity </li></ul><ul><li>Primacy over entire subject area </li></ul><ul><li>Maintain high-level corporate information model </li></ul><ul><li>Define the overall process and framework </li></ul><ul><li>Allocate accountability for individual information subject areas </li></ul><ul><li>Ongoing subject area maintenance </li></ul><ul><li>Compliance with policies and procedures </li></ul>Information Director Owners Stewards
    18. 18. Establish Local Accountabilities Local Information Director Local Specification Owners [local data] Data Steward(s) Data Quality Steward(s) Collaborating Specification Owners [Data common across many localities] + Collaborating Information Director(s) + IT & Business Implementation re-using common data
    19. 19. Principles, Asset Types and Governance Master Data MI/BI Data Transaction Unstructured Information Asset Types Unique definitions Recognised ownership Life-Cycle Management Information Principles Information Director Consumer Business Owner Steward Information Governance Business & Technical Accessible repositories
    20. 20. Role of the Data Architect <ul><li>Be Visible about the program: </li></ul><ul><ul><li>Identify key decision-makers in your organization and update them on your project and its value to the organization </li></ul></ul><ul><ul><li>Focus on the most important data that is crucial to the business first! Publish that and get buy in before moving on. (e.g. start small with a core set of data) </li></ul></ul><ul><ul><li>Monitor the progress of your project and show its value: </li></ul></ul><ul><ul><li>Define deliverables, goals and key performance indicators (KPIs) </li></ul></ul><ul><li>Start small—focus on core data that is highly visible in the organization. </li></ul><ul><li>Track and Promote progress that is made </li></ul><ul><li>Measure Metrics where possible </li></ul><ul><ul><li>“ Hard data” is easy (# data elements, #end users, money saved, etc.) </li></ul></ul><ul><ul><li>“ Softer data” is important as well (data quality, improved decision-making, etc.) Anecdotal examples help with business/executive users </li></ul></ul><ul><ul><li>“ Did you realize we were using the wrong calculation for Total Revenue?” (based on data definitions) </li></ul></ul>Part of YOUR job IS Marketing! How to gain Traction, Budget and Executive buy-in:
    21. 21. 3. BP Challenges & Case Studies
    22. 22. Case Study 1: Vendor Master Data <ul><li>Ownership: Central Procurement and Supply Chain Management function. </li></ul><ul><li>Business Objectives: Establish a unique identifies for every vendor doing business with BP and ensure it is associated with all company wide spend with that vendor </li></ul><ul><li>Primary Benefit: Drive down duplicate payments, assist in contract negotiations and aid purchasing decisions </li></ul><ul><li>Strategy: Single centrally maintained integrated vendor master file, enriched by D&B company information </li></ul><ul><li>Governance Model: Mandated use of D&B numbers on vendor records. Offer of a Vendor record maintenance service. </li></ul><ul><li>Issues: time and cost to retro-fit solution </li></ul>
    23. 23. Case Study 2: Plant Maintenance Data <ul><li>Owner: Plant Manager </li></ul><ul><li>Business Objective: ensure that data is accurate and meets legislative, safety and business requirements </li></ul><ul><li>Governance Model: Central Safety group specified policies and minimum requirements. Accountability for adherence at local level </li></ul><ul><li>Benefits: clear accountability close to workplace </li></ul><ul><li>Issues: different plant managers may do things different ways. No easy way to ensure commonality across plants. </li></ul>
    24. 24. Case Study 3: Business Data Management Program <ul><li>Owner: Business Unit Leader </li></ul><ul><li>Business Objective: increase the quality, management and usability of the key business data </li></ul><ul><li>Governance Model: Industry standard data model used to delegate ownership (from business unit leader) </li></ul><ul><li>Benefit: Business Unit can determine business value and priorities </li></ul><ul><li>Issues: Need to be aware of function activities (e.g. vendor) and other policies (e.g. plant maintenance). Different business units may duplicate activity </li></ul>
    25. 25. Conclusions <ul><li>“ One size does NOT fit all” – need to have a flexible approach to governance that allow model to gain maximum business benefit </li></ul><ul><li>Governance can drive massive benefit through reuse of common models (including standard industry models) and use of consistent definitions </li></ul><ul><li>Matrix approach is needed as different parts of the business and data types will need to be driven from different directions </li></ul><ul><li>Central organization is required to drive governance adoption, implement corporate repositories and establish corporate standards </li></ul>
    26. 26. Working within Corporate Cultures <ul><li>Most companies have silos of information. Why? </li></ul><ul><li>To remove those silos and encourage information sharing, remember: </li></ul><ul><ul><li>Start Small, “pick your battles” wisely, and communicate </li></ul></ul><ul><ul><li>Make the users an active part of the process </li></ul></ul><ul><ul><li>Make it easy </li></ul></ul>
    27. 27. 4. Making Data Governance Happen
    28. 28. Model-Driven Data Governance Repository & Model-Driven Multiple Audiences: Multiple Levels of “Data” Objects: 3NF Subject Area Business Entity Logical Entity Physical Table Implemented Table / DDL Is Mapped To Is Mapped To Is Mapped To Is Mapped To
    29. 29. Establish a Corporate Repository
    30. 30. Establishing a Community of Interest <ul><li>Purpose </li></ul><ul><ul><li>Share best practices inside company </li></ul></ul><ul><ul><li>Exchange ideas across projects </li></ul></ul><ul><ul><li>Represent company on vendor user forum </li></ul></ul><ul><li>Charter </li></ul><ul><ul><li>ALL internal data management users </li></ul></ul><ul><ul><li>Invited consultants & contractors </li></ul></ul><ul><li>Subjects </li></ul><ul><ul><li>Standards & guidelines </li></ul></ul><ul><ul><li>Training & education </li></ul></ul><ul><ul><li>“ Best practices” </li></ul></ul>Part of OUR job IS Marketing!
    31. 31. Measure Data Management Maturity Level 1 - Initial Level 2 - Repeatable Data Principles Delivering broad Quality & Re-use Ideal, Obtaining Optimal Value from Data As-Is To-Be As-Is As-Is As-Is To-Be To-Be To-Be Aspiration Obtaining Limited Benefits Operating in “Fire Fighting” Mode Undesirable Level 4 - Managed Level 5 - Optimised Level 3 - Defined Data Ownership Model does not exist. Data Owners, if any, evolve on their own during project rollouts (i.e. self appointed data owners). Data Ownership Model does not exist. Owners commissioned in the short-term for specific projects & initiatives. Ownership tends to be in form of “Data Teams” or “Super Users” that manage “all” data. Defined Data Ownership Model exists. Ownership Model is loosely applied to key data entities. Data Ownership Model is implemented for the key data entities. Governance process regularly reviews this model and its application, updating and improving as needed. Data Ownership Model has been extended such that the majority of data entities are now governed in a consistent manner. Data definitions unknown and/or inconsistent across the business(s). Key data defined in the short-term for specific projects & initiatives. Definitions are not leveraged from project to project and change often. Key data definitions exist to those who know where to look. Multiple sets of definitions exist because no rationalization/standardization occurs. Single set of data definitions exist for the key data entities. Definitions are published to a central location that is accessible to other programs, projects and users in secure manner. Data definitions extended beyond just “key” data entities. Common data definitions used throughout the businesses & functions. Data repository(s) does not exist. Disparate set of data repositories exist as a result of specific projects & initiatives. Little or no synch/communication across these tools. Multiple data repositories that synchronize and/or communicate via bespoke interfaces. A single integrated data repository houses the “record of reference” (single version of the truth). Other systems access the RoR from the central integrated repository. Central data repository is optimized via standard data collection & distribution mechanisms. Data accessible to other programs, projects and users in secure manner. Complete lack of procedures or controls for key data operations of create, read, update & delete. No warehouse and/or archiving processes in place. Short term procedures or controls for key data operations of create, read, update & delete. Ltd warehouse & archiving driven only by space constraints. Limited procedures or controls for key data operations of create, read, update & delete. Warehouse/archiving defined only for key data entities. Defined & consistent set of procedures & ctrls for key data operations of create, read, update & delete. Key data is proactively monitored so that arch’ing/warehousing occurs at optimal times. Defined & consistent set of procedures & ctrls extend beyond just key data. End-to-end automated “create to archive/warehouse” processes optimize the life-cycle mgmt. of all data. Recognized Ownership Unique Definitions Accessible Repositories Lifecycle Management
    32. 32. Maturity @ your company Data Governance Visibility Technology Trigger Peak of inflated expectations Trough of disillusionment Slope of enlightenment Plateau of productivity Typical Gartner “hype cycle” Avoid the abyss via investment in “sustain” activities Current position Beware this is not “fire & forget”
    33. 33. Summary 1 <ul><li>Understand roles and motivations and work within the organization </li></ul><ul><ul><li>Federated governance model </li></ul></ul><ul><ul><li>Avoid silo mentality </li></ul></ul><ul><ul><li>Communicate </li></ul></ul><ul><ul><li>Obtain buy in by starting small & document success </li></ul></ul><ul><ul><li>Make it easy to get hold of </li></ul></ul><ul><ul><li>Market, market, market! </li></ul></ul><ul><li>Follow up with a robust architecture </li></ul><ul><ul><li>Common repository </li></ul></ul><ul><ul><li>Models appropriate for the audience </li></ul></ul><ul><ul><li>Defined stewardship </li></ul></ul><ul><ul><li>Unique definitions </li></ul></ul><ul><ul><li>“ Repurpose” data for various audiences: via the web, Excel, DDL, XML, etc. It’s the data that’s important, not the format. </li></ul></ul>
    34. 34. Summary 2 <ul><li>Data Governance and Modeling need to get out of the “old school” </li></ul><ul><li>Use new technologies to reach users </li></ul><ul><li>Approach users in their language </li></ul><ul><li>Don’t forget the fundamentals </li></ul>Data Governance 2.0
    35. 35. Questions? Chris Bradley Business Consulting Manager [email_address] +44 7501 224230 Ken Dunn Head of Information Architecture [email_address] +1 630 836 7805 Contact details