An Effective Approach to Master Management THOMAS RAVN PRACTICE DIRECTOR TRA@PLATON.NET March 4 th 2010, Reykjavik WWW.PLATON.NET
Agenda Introduction to MDM The aspects of an effective MDM program How do we get started with MDM? Platon 2
Key Concepts and Definitions Master Management (MDM) is the structured management of Master in terms of definitions, governance, architecture, technology and processes Information Management is the discipline of managing and leveraging information in a company as a strategic asset Information Management Governance MDM Quality Management is the discipline of ensuring high quality data in enterprise systems DQM Governance is the crossfunctional discipline of managing, improving, monitoring, maintaining, and protecting data Platon 3
Definition of Master Master is the data used to monitor and control our business processes Master is the static data that is referenced from transactional data that represents events Master is used across the organization and business processes Common Master entities (objects) include Customer, Product, Supplier, Employee and Chart of Accounts Master is often classified into: Basis Master (Customers, products, suppliers, employees, chart of accounts, etc.) Master hierarchies (Product hierarchies, customer hierarchies, etc.) Reference Master (Country codes, currency codes, customer type, payment terms, language codes, etc.) Platon 4
Components of an effective MDM approach Formalize business ownership, stewardship and decision making around data. Ensure that Master is taken into account each and every time a an IT system is changed. IT Change control Roles & Responsibilities Common definitions To be able to share data you need to share definitions and business rules. Definitions require management, rigor and documentation. Control in which systems Master is entered and how it is synchronized across systems. Master Architecture and Technology MDM Quality Management Effective Master processes Capturing Master data efficiently is essential to manage the quality of data. maintenance processes must be properly aligned with other business processes. Measure and monitor the quality of data Platon 5
Roles and Responsibilities The key elements of data governance are accountability, responsibility, business ownership of data, data definitions and robust data maintenance processes. The roles of data governance along with the policies and processes for management of data is commonly referred to as a data governance model. All organizations already perform many elements of data governance what s missing is the enterprise focus, across systems and across business units. Roles & Responsibilities Common Definitions Effective MD Processes Quality Mgt Architecture and Technology IT Change Control Platon 6
Governance The roles in the Governance model fall in three different groups that are likely to placed in different parts of the organization: 1. Central Governance Support Team. The roles that support the execution of the data governance work across data entities is placed centrally. 2. Roles for business data ownership the roles that own the data, the definitions and the business rules. These roles are entity specific and are placed in various parts of the business (the people that make the rules). 3. Roles in the data maintenance organization that perform operational day to day maintenance of data (the people that follow the rules). Platon 7
Best Practice Governance Organization The driver and integrator of the Governance work. In many organizations known as MDM Manager The owner of the Governance model Governance Policy Owner 5% Business owner of a shared data entity. Executive Entity Owner 5% Right hand of entity owner. Works in detail with definitions requirements and processes Governance Manager Assistant Entity Owner 50-100% Facilitates data governance work Governance Coordinator Enterprise Information Modeler The keeper of the Enterprise Information Model Steward Global function area A Steward Global Function area B 25% Governance role Escalation path Referral % Governance workload Central Governance Support Team Platon Quality Analyst Supports with ad hoc data cleansing and data analysis etc. Expert on data maintenance and data requirements within a functional area. 8? End User Manager Custodian Maintainer (Master) entity x (e.g. Customer) (Master) entity y (e.g. Product) Functional Business Teams? End User Manager Custodian Maintainer 10-100% 10-20%
Common Definitions Common definitions are essential to: Share and integrate data across systems Reuse data definitions across projects Manage the quality of data Do effective Business Intelligence Roles & Responsibilities Common Definitions Effective MD Processes Quality is the degree to which data meets the defined standards Quality Mgt Architecture and Technology IT Change Control Platon 9
Defining Good standards For every entity define: For every field define: Definition and keys Business description Hierarchies entry format and conventions Classification(s) Definition owner Life cycle Stakeholders Business Owner(s) Consider what a user needs to know to produce high quality data Platon 10
Effective Master Processes Ensure proper alignment with other business processes Sometimes completely new processes with automated workflows Goes hand in hand with design of maintenance organization and Master architecture Consider quality of data in design of processes Consider cross-system processes Roles & Responsibilities Common Definitions Effective MD Processes Quality Mgt Architecture and Technology IT Change Control Platon 11
Quality Management Like most other things, data quality can only be managed properly if it is measured and monitored A data quality monitoring concept is necessary to ensure that you identify Trends in data quality quality issues before they impact critical business processes Areas where process improvements are needed Roles & Responsibilities Common Definitions Effective MD Processes Quality Mgt Architecture and Technology IT Change Control Platon 12
Quality Management Do we have all required data? Are all data values within the valid domain for the field? Does data reflect the real world objects or a trusted source? Are data available at the time needed? Timeliness Quality Accuracy Are business rules on field and table relationships met? Are shared data elements synchronized correct across the system landscape? Platon 13
Master Architecture and Technology A Master architecture defines where Master is entered, stored and synchronized between IT systems. Best practice architectural principles: A particular piece of master data is only maintained in one system (System of Entry) A particular piece of master data is only sourced from one system (System of Record) Master Management systems (Master Repositories) Not every company needs one May be a compromise if no other system is a natural master Roles & Responsibilities Common Definitions Effective MD Processes Quality Mgt Architecture and Technology IT Change Control Platon 14
Master Architecture and Technology Designing a Master architecture is about: Ensuring cross-system master data consistency Providing a single version of master data Enabling of a more centralized control of data Reducing uncontrolled data redundancy Lowering data management costs Supporting efficient business processes Roles & Responsibilities Common Definitions Effective MD Processes Quality Mgt Architecture and Technology IT Change Control Platon 15
MDM and Business Intelligence High quality Master is a necessity to reap the full benefit of a Warehouse and Business Intelligence solutions. Reporting across systems and business units requires consistently defined and used Master. The traditional way of solving this is by building complicated transformation logic and business rules into the ETL-flow, which decreases transparency and makes it difficult to compare numbers between operational systems and BI reports. The data warehouse may be too late in the information supply chain to consolidate Master. Platon 16
The Information Supply Chain Traditional Approach Transforming data from multiple systems into a single version of the truth Operational Systems Marts BI Solutions XXXXXX 9999999 9999999 ABCDE FGHIJK ETL EDW XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX Heterogeneous systems with overlapping data One harmonized version of the truth? Platon 17
IT Change Control Amongst the top sources of current MDM challenges are IT development and support processes without an enterprise focus on: Cross system alignment of data usage Synchronization Optimal data maintenance processes Ensuring data quality through validations ownership Roles & Responsibilities Common Definitions Effective MD Processes Quality Mgt Architecture and Technology IT Change Control Platon 18
So, how do we start? Do we need a complete MDM Strategy first? Can we start with data definitions? Which data entity (customer, supplier, product, etc. should we look at first? How do we establish a strong business case? Platon 19
Components of an effective MDM approach Formalize business ownership, stewardship and decision making around data. Ensure that Master is taken into account each and every time a an IT system is changed. IT Change control Roles & Responsibilities Common definitions To be able to share data you need to share definitions and business rules. Definitions require management, rigor and documentation. Control in which systems Master is entered and how it is synchronized across systems. Master Architecture and Technology MDM Quality Management Effective Master processes Capturing Master data efficiently is essential to manage the quality of data. maintenance processes must be properly aligned with other business processes. Measure and monitor the quality of data Platon 20
Benefits of Master Management Business Objectives Increase Agility Reduce Cost Ensure Compliance Optimize Revenue Requirements Business Processes & Business Models Supply chain collaboration TQM Increase customer satisfaction ABC Procurement CRM Excellence BSC SRM Increase CLV Reduce Churn Optimize Processes Support Master Management Roles & Responsibilities Effective master data processes Common definitions quality management Master architecture and technology IT change control Platon 21
Benefits of Master Management Business Objectives Business Processes & Business Models Master Management Platon 22
An Effective Approach to MDM Contact me: Thomas Ravn Practice Director E: tra@platon.net M: +1 646-400-2862 PLATON US INC. 5 PENN PLAZA, 23 rd Floor NEW YORK NY 10001 www.platon.net Platon s contact in Iceland: Sigurður Jónsson Principal Consultant E: sjo@platon.is M: +354 895-8605 PLATON Upplýsingastýring ehf. Kringlan 1 104 Reykjavík www.platon.net Platon 23