Westernacher Consulting

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1 Westernacher Consulting Innovating Business & IT Since 1969 Our Data Quality Management Methodology January Westernacher I All rights reserved. I

2 Do you know how much poor data quality is costing your business? Background If you look at any business function in your company, you re going to find some direct cost there attributed to poor data quality (Gartner) Data quality problems cost US business over $ 600 billion a year (The Data Warehouse Institute) 63% of businesses unaware of cost of poor data quality (Chartered Quality Institute) 42% (of businesses) unaware of the quality of their data (Chartered Quality Institute) Organisational Impact Poor data quality manifests itself in numerous ways Direct costs data correction, postal services Indirect costs opportunity costs, decision-making errors, data management costs Projects built on a foundation of poor data quality are unlikely to add value Is your data quality under control Do you know the quality of your data? Do you know the cost of your data quality? Do you have a successful Data Quality Management process in place? 1

3 Data Quality Management is key to optimising the overall data environment Data Quality Management Establish Standards Organise for Success Profile and Assess Resolve and Monitor DATA ARCHITECTURE DATA AND INFORMATION STRATEGY DATA QUALITY MANAGEMENT INFORMATION DELIVERY Data and Information Strategy Data Delivery Strategy Data Architecture Strategy Data Quality Strategy Integrate with Business & IT Strategy Information Delivery Business Intelligence Data Integration Data Visualisation Warehouses, Stores & Staging GOVERNANCE FRAMEWORK Data Architecture Enterprise Data Model Metadata Management & Taxonomies Master Data Model Data Standards, Principles & Policies Governance Framework Change Management & Approval Data Architecture Reviews Setting & Monitoring KPI s Service Level Agreements Data Quality management is a continuous improvement process and not a once-off exercise 2

4 Our Data Quality Management Methodology adopts a pragmatic approach to establishing your DQ framework and remediating root causes 3

5 A key theme of our methodology is embedding the measurement of success Accuracy values are correct Validity data has been validated and exceptions managed Consistency multiple sources of same data and formats are aligned Timeliness data is available at the right time Availability data is available in the right place, to the right people Auditability target to source traceability and auditability of changes Completeness no missing or incomplete data Currency the data is up to date Uniqueness no duplication of data fields in the data model Key performance indicators transform Data Quality management from theory into practice Number of customers without a VAT registration number Number of customers without a valid industry code KPI s are defined and monitored in the DQ Dashboard Monthly cost of returned post and telephone calls to incorrect numbers Number of transactions without a valid intercompany code 4

6 Our methodology will ensure that you have both the tools and mechanisms to monitor on-going Data Quality improvements in your organisation 5

7 Our Data Quality Management methodology is built on our experience and success across numerous industries and organisations Capability backed by Experience Information architecture strategy for a 20 billion USD globally operating retailer ( ) Finance & Regulatory data standards for a global Investment Bank (2010) Information architecture for globally operating Telco (product and pricing data management) ( ) Data architecture strategy for a 4 billion Utility operating in the UK and the US ( ) Data architecture strategy for a global Investment Bank (2009) Information architecture, process design, system design, build and global rollout for a global media company ( ) Participation in the global GL rollout ( ) and ongoing support for Finance Information Architecture for a global Investment Bank ( ) Partnership with university of StGallen Institute for Corporate Data Quality (research and survey partnership regarding data management) 6

8 Westernacher delivers a unique combination of industry and data domain expertise in addition to technology know-how We help resolve data quality issues for the following industries Discrete Industries Financial Services Life Sciences and FMCG Utilities Retail We understand the importance of data domains in the context of your business needs Master Data: Material, Vendor, Customer, Location, Chart of Accounts, Employee, Organization, broad Financial Data (Currency, Calendar) etc. Transactional: Trade, Purchase Order, Work Order, Sales Order etc. We understand critical data challenges for leading vendor ERP platforms SAP Oracle Microsoft Custom developments We deploy wide set of data quality tools Data Integration Platforms (e.g. Informatica and DataStage) Master Data Management Tools (e.g. SAP MDM, Oracle MDM Suite, IBM InfoSphere) Dashboards (e.g. QlikView, SAP Business Objects) Custom solutions (e.g. Semantic Wikis for Data Glossary and Data Dictionary maintenance) 7

9 40 Years, serving Clients worldwide with over 200 Professionals and 10 Locations in 7 Countries Founded in: 1969 Consultants: > 200 Locations: 10 Offices in 7 Countries Number of Partners: > % owned by Westernacher Partners Boston Brussels Heidelberg London Shanghai Sopot Vienna Berlin, Bonn, Stuttgart 8

10 Contact details Craig Schultz Westernacher & Partner Consulting Limited 72 New Bond Street London, W1S 1RR, UK Roger Brooks Westernacher & Partner Consulting Limited 72 New Bond Street London, W1S 1RR, UK Mobile: Phone: Fax: Mobile: Phone: Fax:

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