Enterprise Master Data Architecture: Design Decisions and Options

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The enterprise-wide management of master data is a prerequisite for companies to meet strategic business
requirements such as compliance to regulatory requirements, integrated customer management, and global business process integration. Among others, this demands systematic design of the enterprise master data architecture. The current state-of-the-art, however, does not provide sufficient guidance for practitioners as it does not specify concrete design decisions they have to make and to the design options of which they can choose with regard to the master data architecture. This paper aims at contributing to this gap. It reports on the findings of three case studies and uses morphological analysis to structure design decisions and options for the management of an enterprise master data architecture.

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Enterprise Master Data Architecture: Design Decisions and Options

  1. 1. 15th International Conference on Information Quality, 2010ENTERPRISE MASTER DATA ARCHITECTURE:ENTERPRISE MASTER DATA ARCHITECTURE:DESIGN DECISIONS AND OPTIONSBoris OttoUniversity of St. GallenAlexander SchmidtUniversity of St. GallenInstitute of Information Managementboris.otto@unisg.chExecutive Summary/Abstract: The enterprise wide management of master data is aInstitute of Information Managementalexander.schmidt@unisg.chExecutive Summary/Abstract: The enterprise-wide management of master data is aprerequisite for companies to meet strategic business requirements such as compliance toregulatory requirements, integrated customer management, and global business processintegration. Among others, this demands systematic design of the enterprise master dataarchitecture. The current state-of-the-art, however, does not provide sufficient guidance forpractitioners as it does not specify concrete design decisions they have to make and to thedesign options of which they can choose with regard to the master data architecture. This paperaims at contributing to this gap It reports on the findings of three case studies and usesaims at contributing to this gap. It reports on the findings of three case studies and usesmorphological analysis to structure design decisions and options for the management of anenterprise master data architecture.
  2. 2. 15th International Conference on Information Quality, 2010Agendag• Motivation• Research Question• Related Work• Case Studies• Design Decisions and Options• Conclusion and Outlook
  3. 3. 15th International Conference on Information Quality, 2010Motivation• Enterprise master data is key for strategic business requirements– Compliance to regulations– 360 degree view on customers– Enterprise-wide spend analysis• Active management of enterprise master data requires enterprisemaster data architecture (EMDA) managementmaster data architecture (EMDA) management• A gap exists in both research and practice regarding the relateddesign decisions and optionsdesign decisions and options
  4. 4. 15th International Conference on Information Quality, 2010Research Question and Approach• Research Question:– What are design decisions companies have to make in the design ofenterprise master data architectures and which design options exist?R h A h• Research Approach:– Exploratory case studyMultiple cases analyzed at DB Netz Deutsche Telekom and SBB Cargo– Multiple cases analyzed at DB Netz, Deutsche Telekom, and SBB Cargo– Data collection followed the BECS principles, i.e. the method forBusiness Engineering Case Study researchg g y– Morphological analysis is applied after step-wise case studies
  5. 5. 15th International Conference on Information Quality, 2010Related Work: Master Data Managementg• Master data includes material and product data, supplier andcustomer data, but also employee, organizational and asset data.• MDM is an application-independent process for the description,hi d t f “ b i d t bj t ”ownership and management of “core business data objects”.Master data must be unambiguously understood, created, maintained, andused across the enterprise
  6. 6. 15th International Conference on Information Quality, 2010Related Work: Enterprise Master Data Architecture (EMDA)( )EMDAConceptual Application ArchitecturepMaster Data Modelppfor Master DataApplication Systems Data Flows
  7. 7. 15th International Conference on Information Quality, 2010Related Work: Existing Architecture FrameworksgZachman TOGAF EAP FEAF EAC DAMAZachman TOGAF EAP FEAF EAC DAMAEnterprise master dataarchitecture focusarchitecture focusCoverage of all enterprisemaster data architecturecomponentscomponentsReference to master dataDesign decisionsDesign optionsLegend:does fulfillcriteriadoes fulfill does not fulfillLegend: criteriacompletelycriteria partly criteria at all
  8. 8. 15th International Conference on Information Quality, 2010Case Study OverviewyDB Netz SBB Cargo Deutsche TelekomgSIC code 40 (RailroadTransportation)47 (TransportationService)48(Communications)Markets served Central Europe Central Europe InternationalMarkets served Central Europe Central Europe InternationalBusinessrequirementsCompliance reporting,process harmonizationNew business models,cash-flow reportingMerger of twobusiness unitsOrganizational Enterprise wide Enterprise wide Business unitOrganizationalscopeEnterprise-wide Enterprise-wide Business unitMaster data classes Infrastructure master data All All
  9. 9. 15th International Conference on Information Quality, 2010Case Study at DB Netz: Strategic Business Requirementsy gTunnel Railway Track#1: Inventory of RailwayInfrastructure#2: Unambiguous understandingin end-to-end businessprocesses
  10. 10. 15th International Conference on Information Quality, 2010Case Study at DB Netz: Issuesy• What is a common definition of the business objects “tunnel” and “station track”? Master data object definition Master data object definition• Which of the business object’s attributes must be used in a standardized way across differentprocesses, and which need not? Master data validity, master data object definition Master data validity, master data object definition• Which of the business object’s attributes are currently stored, altered, and distributed in whichapplication systems? Metadata management• How do data flows between application systems look like? Master data application topology and distribution• Who is responsible for which data?p Master data ownership• What data is created, used, changed in which activity of the business process? Master data lifecycle, master data operations• Should data describing station tracks be stored in a central system or in several, distributedsystems? Master data application topology
  11. 11. 15th International Conference on Information Quality, 2010Case Study at SBB Cargo: Strategic Business Requirementsy g g• In the past:– Cooperation between railways– Everyone is in chare, no-one isresponsible– Interface and quality problems• Today:– Seamless single-source freightSeamless, single-source freightresponsibility– Uniform business processesCoordinated timetables and– Coordinated timetables andsequences– One contact for the customerC titiDB CargoSBB CargoTrenitalia CargoDB SchenkerBLS CargoSBB CargoTX Logistik– Competition TX LogistikTrenitalia Cargo
  12. 12. 15th International Conference on Information Quality, 2010Case Study at SBB Cargo: Fields of Actiony g• Determine common uniform definitions and structures for the company’s master data objects Master data object definition conceptual master data model Master data object definition, conceptual master data model• Create unique identifiers for each master data class for unambiguous identification Master data validity• Establish a central organizational unit responsible for carrying out changes on master data objects• Establish a central organizational unit responsible for carrying out changes on master data objects Master data operations, master data ownership• Determine the “leading system” for each master data class and optimize architecture ofapplications administrating master dataapplications administrating master data Master data application topology• Create a Master Data Map depicting assignment of master data objects to applications and thedata flows between them Master data application topology and distribution• Design and implement tool-supported MDM processes Master data lifecycle, master data operations
  13. 13. 15th International Conference on Information Quality, 2010Case Study at Deutsche Telekom: Strategic Requirementy gCorporate CenterStrategic Business Units Shared ServicesFacility ManagementCreated 2007through merger offormerly separatebusiness units T-Online and T-ComBroadband/Fixed LineMobileBusinessCustomersDeTeFleet ServicesViventoOnline and T-ComViventoOthers
  14. 14. 15th International Conference on Information Quality, 2010Case Study at Deutsche Telekom: Lacking Transparencyy g y• Origin and distribution of master data objects on its current application architecture Master data application topology and distribution Master data application topology and distribution• Semantics of master data objects leading to ambiguous understandings and inconsistent usage Master data definitions, metadata management• Business requirements on enterprise wide data quality of certain master data objects• Business requirements on enterprise-wide data quality of certain master data objects Master data validity
  15. 15. 15th International Conference on Information Quality, 2010EMDA Design Decisions and OptionsgDesign Decision Design OptionsMaster Data Ownership Defined enterprise-wide Defined locallySpecificMaster Data Validity Enterprise-wideSpecificbusiness unitSingle business processMaster DataLif lCreation Centrally standardized Hybrid Local designUpdate Centrally standardized Hybrid Local designLifecyclep y y gDeactivation Centrally standardized Hybrid Local designMaster Data OperationsCentralized execution (e.g. by a centralorganizational unit)Local execution (e. g. by owner)Conceptual Master Data ModelEnterprise-wide,unambiguousPer business unit Per project Not definedMaster Data Object DefinitionEnterprise-wide,unambiguousPer business unit Per project Not definedunambiguousMetadata Management Owned and defined enterprise-wide Not actively managedMaster Data Application TopologyCentralsystemLeading systemConsolidationHubRepositoryyMaster Data Distribution Push PullMaster Data Processing Batch Real-timeEMDAEMDA
  16. 16. 15th International Conference on Information Quality, 2010Conclusion and Outlook• Paper contribution:– Investigation of an area in which little research is available– Guidance to practitioners in designing EMDA• Limitations:– Validity and generalizability restricted due to low number of casesinvestigatedinvestigated• Future research directions:Investigate an extended sample to validate findings– Investigate an extended sample to validate findings– Identification of “architecture patterns”– Relationship between EMDA design and data quality on one hand asRelationship between EMDA design and data quality on one hand aswell as cost and cycle time of business processes on the other
  17. 17. 15th International Conference on Information Quality, 2010Thank you for your attention.y y

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