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Competence Center Corporate Data Quality (CC CDQ): Overview Presentation Dr. Boris Otto St. Gallen, February 2008 cdq.iwi.unisg.ch
Table of Content ,[object Object],[object Object],[object Object],[object Object],[object Object]
Business drivers for corporate data quality are spread across the entire enterprise Corporate Management/ Business Intelligence Compliance Process Integration along the Value Chain Customer-centric Business Models ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Strategic Purchasing ,[object Object],[object Object]
Corporate Data Quality Management (CDQM) is about responding to the following questions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
A framework for Corporate Data Quality Management (CDQM) addresses strategic, organizational, and system aspect Strategy Organization Systems CDQ Controlling Applications for CDQ Information Architecture for CDQ CDQ Organization CDQ Operations Strategy for CDQ local global Business Networking Maturity & Transition
The project consortium consists of companies working on the same topics being confronted with comparable challenges CH D Berlin Köln Hamburg München Frankfurt Zürich ETA S.A Grenchen IWI-HSG St. Gallen Daimler AG Stuttgart IBM Deutschland GmbH Stuttgart Bayer CropScience AG Monheim/Rh. ZF Friedrichshafen AG Friedrichshafen DB Netz AG Frankfurt a. M. Deutsche Telekom AG Darmstadt E.ON AG München
The array of project results addresses a variety of questions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Result example: Baseline Assessment for CDQM in the consortium according to CMM-I Implementation of a CDQ strategy Measurement and control of CDQ CDQ organisation and standards setting Execution of CDQM processes Provision of systems support for CDQ  Partner A Partner B Partner C Partner D 1  – Initial 2  – Managed 3  – Defined 4  – Quantitatively Managed 5  – Optimizing  Partner E 1 2 3 4 5
Result example: Data Governance at a national infrastructure provider in Europe Key: Z - Zustimmung, E - Entscheidung, F - Federführung, M - Mitwirkung, D - Durchführung. VR - Vorstandsressort, GF - Geschäftsfeld, DM - Datenmanagement, GE - Geschäftseinheit, FDM - Fachlicher Datenmanager. NB: Illustration in German in accordance with bilaterla project language. Rolle / Beteiligter VR Vorstand GF DM Board GF Daten-manager DM Fach-daten-steward Oper. Daten-manager GE-FDM GE-FDM GE-FDM Aufgabe   Bereich 1 Bereich 2 Bereich n Entwickelung DM-Strategie Z Z E F M M M M M Aufbau DM-Führungssystem Z Z E F F M M M M Entwicklung Data-Governance-Modell Z Z E F F M M M M Entwurf Datenproduktions- und Datenbereitstellungs-prozesse Z   E F D D D D D Aufbau DM-Datenkatalog     E F F M D D D Entwickeln DM-Datenmodell Z   E F F M M M M Fachliche Vorgaben für die Anwendungsentwicklung Z   Z E M F M M M
Case study: KPIs for CDQM in the retail industry Source:  Schemm, J.; Otto, B.: Stammdatenmanagement bei der Karstadt Warenhaus GmbH, Institut für Wirtschaftsinformatik, Universität St. Gallen, St. Gallen, 2007. NB: Illustration in German in accordance with original paper language. Kennzahl Bezugsgrösse Berechnungsvorschrift Ebene Periodizität Formatwechsel Wert (Absolutwert der Formatwechsel) / Verbrauch * 100 Filiale, Abteilung Monatlich Pseudo-Bepo Wert (Wert Pseudo-Bepo) /  Wert Bepo Gesamt * 100 Filiale, Abteilung Monatlich Minusbestand Anzahl (Anzahl Bepo ohne Bestand) / (Anzahl Bepo Gesamt) * 100 Filiale, Abteilung Monatlich Inventurbestand ohne Bestellpositionen Wert (Inventurbestand ohne Bepo) / Inventurbestand * 100 Filiale, Abteilung Jährlich EK-Differenzen Anzahl (Anzahl fehlerhafte Repo) /  (Anzahl Repo Gesamt) * 100 Abteilung Monatlich Rechnungen ohne Auftrag Anzahl (Anzahl Rechnungen ohne Auftrag) / (Anzahl Rechnungen Gesamt) * 100 Filiale, Abteilung Monatlich Fehlerlisten Anzahl (Absolutwert der Menge mit Fehlern) / (Absolutwert der Gesamtmenge) * 100 Filiale, Abteilung Monatlich Stapf-Korrekturen Wert Wert der nachträglichen Ergebniskorrekturen Filiale, Abteilung Monatlich
Result example: Benefit tree for CDQM Human Resource Management Inbound Logistics Procurement Operations Outbound Logistics Marketing & Sales Service Technological Development Firm Infrastructure Profit Profit Support Activities Primary Activities
A common understanding on the company-wide information objects is key to successful CDQM Information Objects Information Object Information Object Information Object Information Object Information Object Business Objects Attribute Attribute Attribute Attribute Attribute Attribute Attribute Data Objects Process Layer (conceptual) System Layer (physical) Integration LAyer (logical) Process A Process B Plate Büromaterial Vertriebs GmbH Hilligenwarf 5 28865 Lilienthal
The first cycle of the CC CDQ ends in October 2008 - a second cycle is planned to run until 2010 23.11.06 (Frankfurt): Kick-off Workshop 01./02.02.07 (Darmstadt): Baseline Assessment and Data Governance  24./25.02.07 (Esslingen): Theoretical Foundations, Business Data Dictionary, Scorecarding 25./26.06.07 (Basel): Business Alignment and Business Case 20./21.09.07 (Leverkusen/Monheim): Data Governance 15./16.11.07 (Berlin): Business Value &Meta Data Management 16./17.01.08 (St. Gallen): Data Architecture & OCM 02./03.04.08 (nn): Data Management Processes 18./19.06.08 (nn): Change Management for CDQ 03./04.09.08 (nn): System Support and Architecture for CDQ 29./30.10.08 (nn): Final Workshop Key: completed still to come. OCM - Organizational Change Management. CC CDQ2 2006 2007 2008 11 12 01 02 03 04 05 06 07 08 09 10 11 12 01 02 03 04 05 06 07 09 09 10
The CDQ network keeps growing… CC CDQ Guest Speeches CDQ Market Survey Scientific Community Case Studies Practical Community Awareness
The standard CC CDQ participation packages covers research results, bilateral support and workshop participation 6 to 8 working reports Approx. 35 person days p.a. 5 to 6 workshops p.a.
The CC CDQ team at the chair of Prof. Dr. Hubert Österle Head of CC CDQ Scientic coordination and head of the institute Scientific researchers and PhD students Dr. Boris Otto Prof. Dr. Hubert Österle Kai Hüner Alexander Schmidt Tobias Vogel Kristin Wende
Selected feedback from participants of the 6 th  CC CDQ workshop „ Wir möchten uns bei Ihnen und Ihrem Team für die Möglichkeit zur Präsentation bedanken! Es war ein sehr spannender Workshop mit vielen interessanten Teilnehmern und neuen Erkenntnissen! Ein schönes Rahmenprogramm und die tolle Organisation haben das Event perfekt abgerundet!“   --- Wiebke Hedlefs, Deutsche Börse AG „ Professional organization in all means of the 2 days“ „ Participant are all professional in DQ“ „ Good mixture of companies all working in the same area as we do“ “ Content is not technical but business oriented, very pragmatic” „ I strongly recommend o join the group.“ --- Karsten Muthreich, Nestle S.A. „ Gratulation zu einem gelungenen Workshop an das ganze Team“ --- Albert Hatz, Robert Bosch GmbH
The CC CDQ objectives combine research excellence with practical application  ,[object Object],[object Object],[object Object],[object Object],[object Object]
Your contact for further information ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Competence Center Corporate Data Quality

  • 1. Competence Center Corporate Data Quality (CC CDQ): Overview Presentation Dr. Boris Otto St. Gallen, February 2008 cdq.iwi.unisg.ch
  • 2.
  • 3.
  • 4.
  • 5. A framework for Corporate Data Quality Management (CDQM) addresses strategic, organizational, and system aspect Strategy Organization Systems CDQ Controlling Applications for CDQ Information Architecture for CDQ CDQ Organization CDQ Operations Strategy for CDQ local global Business Networking Maturity & Transition
  • 6. The project consortium consists of companies working on the same topics being confronted with comparable challenges CH D Berlin Köln Hamburg München Frankfurt Zürich ETA S.A Grenchen IWI-HSG St. Gallen Daimler AG Stuttgart IBM Deutschland GmbH Stuttgart Bayer CropScience AG Monheim/Rh. ZF Friedrichshafen AG Friedrichshafen DB Netz AG Frankfurt a. M. Deutsche Telekom AG Darmstadt E.ON AG München
  • 7.
  • 8. Result example: Baseline Assessment for CDQM in the consortium according to CMM-I Implementation of a CDQ strategy Measurement and control of CDQ CDQ organisation and standards setting Execution of CDQM processes Provision of systems support for CDQ Partner A Partner B Partner C Partner D 1 – Initial 2 – Managed 3 – Defined 4 – Quantitatively Managed 5 – Optimizing Partner E 1 2 3 4 5
  • 9. Result example: Data Governance at a national infrastructure provider in Europe Key: Z - Zustimmung, E - Entscheidung, F - Federführung, M - Mitwirkung, D - Durchführung. VR - Vorstandsressort, GF - Geschäftsfeld, DM - Datenmanagement, GE - Geschäftseinheit, FDM - Fachlicher Datenmanager. NB: Illustration in German in accordance with bilaterla project language. Rolle / Beteiligter VR Vorstand GF DM Board GF Daten-manager DM Fach-daten-steward Oper. Daten-manager GE-FDM GE-FDM GE-FDM Aufgabe   Bereich 1 Bereich 2 Bereich n Entwickelung DM-Strategie Z Z E F M M M M M Aufbau DM-Führungssystem Z Z E F F M M M M Entwicklung Data-Governance-Modell Z Z E F F M M M M Entwurf Datenproduktions- und Datenbereitstellungs-prozesse Z   E F D D D D D Aufbau DM-Datenkatalog     E F F M D D D Entwickeln DM-Datenmodell Z   E F F M M M M Fachliche Vorgaben für die Anwendungsentwicklung Z   Z E M F M M M
  • 10. Case study: KPIs for CDQM in the retail industry Source: Schemm, J.; Otto, B.: Stammdatenmanagement bei der Karstadt Warenhaus GmbH, Institut für Wirtschaftsinformatik, Universität St. Gallen, St. Gallen, 2007. NB: Illustration in German in accordance with original paper language. Kennzahl Bezugsgrösse Berechnungsvorschrift Ebene Periodizität Formatwechsel Wert (Absolutwert der Formatwechsel) / Verbrauch * 100 Filiale, Abteilung Monatlich Pseudo-Bepo Wert (Wert Pseudo-Bepo) / Wert Bepo Gesamt * 100 Filiale, Abteilung Monatlich Minusbestand Anzahl (Anzahl Bepo ohne Bestand) / (Anzahl Bepo Gesamt) * 100 Filiale, Abteilung Monatlich Inventurbestand ohne Bestellpositionen Wert (Inventurbestand ohne Bepo) / Inventurbestand * 100 Filiale, Abteilung Jährlich EK-Differenzen Anzahl (Anzahl fehlerhafte Repo) / (Anzahl Repo Gesamt) * 100 Abteilung Monatlich Rechnungen ohne Auftrag Anzahl (Anzahl Rechnungen ohne Auftrag) / (Anzahl Rechnungen Gesamt) * 100 Filiale, Abteilung Monatlich Fehlerlisten Anzahl (Absolutwert der Menge mit Fehlern) / (Absolutwert der Gesamtmenge) * 100 Filiale, Abteilung Monatlich Stapf-Korrekturen Wert Wert der nachträglichen Ergebniskorrekturen Filiale, Abteilung Monatlich
  • 11. Result example: Benefit tree for CDQM Human Resource Management Inbound Logistics Procurement Operations Outbound Logistics Marketing & Sales Service Technological Development Firm Infrastructure Profit Profit Support Activities Primary Activities
  • 12. A common understanding on the company-wide information objects is key to successful CDQM Information Objects Information Object Information Object Information Object Information Object Information Object Business Objects Attribute Attribute Attribute Attribute Attribute Attribute Attribute Data Objects Process Layer (conceptual) System Layer (physical) Integration LAyer (logical) Process A Process B Plate Büromaterial Vertriebs GmbH Hilligenwarf 5 28865 Lilienthal
  • 13. The first cycle of the CC CDQ ends in October 2008 - a second cycle is planned to run until 2010 23.11.06 (Frankfurt): Kick-off Workshop 01./02.02.07 (Darmstadt): Baseline Assessment and Data Governance 24./25.02.07 (Esslingen): Theoretical Foundations, Business Data Dictionary, Scorecarding 25./26.06.07 (Basel): Business Alignment and Business Case 20./21.09.07 (Leverkusen/Monheim): Data Governance 15./16.11.07 (Berlin): Business Value &Meta Data Management 16./17.01.08 (St. Gallen): Data Architecture & OCM 02./03.04.08 (nn): Data Management Processes 18./19.06.08 (nn): Change Management for CDQ 03./04.09.08 (nn): System Support and Architecture for CDQ 29./30.10.08 (nn): Final Workshop Key: completed still to come. OCM - Organizational Change Management. CC CDQ2 2006 2007 2008 11 12 01 02 03 04 05 06 07 08 09 10 11 12 01 02 03 04 05 06 07 09 09 10
  • 14. The CDQ network keeps growing… CC CDQ Guest Speeches CDQ Market Survey Scientific Community Case Studies Practical Community Awareness
  • 15. The standard CC CDQ participation packages covers research results, bilateral support and workshop participation 6 to 8 working reports Approx. 35 person days p.a. 5 to 6 workshops p.a.
  • 16. The CC CDQ team at the chair of Prof. Dr. Hubert Österle Head of CC CDQ Scientic coordination and head of the institute Scientific researchers and PhD students Dr. Boris Otto Prof. Dr. Hubert Österle Kai Hüner Alexander Schmidt Tobias Vogel Kristin Wende
  • 17. Selected feedback from participants of the 6 th CC CDQ workshop „ Wir möchten uns bei Ihnen und Ihrem Team für die Möglichkeit zur Präsentation bedanken! Es war ein sehr spannender Workshop mit vielen interessanten Teilnehmern und neuen Erkenntnissen! Ein schönes Rahmenprogramm und die tolle Organisation haben das Event perfekt abgerundet!“ --- Wiebke Hedlefs, Deutsche Börse AG „ Professional organization in all means of the 2 days“ „ Participant are all professional in DQ“ „ Good mixture of companies all working in the same area as we do“ “ Content is not technical but business oriented, very pragmatic” „ I strongly recommend o join the group.“ --- Karsten Muthreich, Nestle S.A. „ Gratulation zu einem gelungenen Workshop an das ganze Team“ --- Albert Hatz, Robert Bosch GmbH
  • 18.
  • 19.