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Who Should Be Involved In Your Mdm Program

Introduction to SAP Master Data Governance from a Business Perspective

Now that you understand the what and why, lets talk about the who and really, there are a several different ways to think about who to involve in an MDM program. First, lets take a high-level look at three core roles:

  • Data Governance: Individuals who drive the definition, requirements and solution. These users help administrators know what to create and data stewards know what to manage and how to manage it. Data governance users dictate to data stewards how data should be managed, including the processes for doing so, and then hold the data stewards accountable to following those requirements. Data governance users also dictate to administrators what to create during the implementation of the MDM solution, especially from a data matching and quality perspective.Data governance users also need to maintain a feedback loop from the MDM software to ensure everything is working as expected. This feedback covers the measurement perspective of the MDM program and might include information like:
  • How long does it take to onboard a new customer?
  • Is that process getting faster or slower?
  • How is the company doing compared to its SLA?
  • If there are any areas that are slipping, why is that happening?
  • How well is the data matching working?
  • How many business rules are failing from a data quality perspective?
  • Administrators: Individuals in IT who are responsible for setting up and configuring the solution.
  • Other MDM roles can include and vary by organization/project type:

    Presentation On Theme: Sap Master Data Governance Presentation Transcript:

    1 SAP Master Data GovernanceDavid Pugh Solution Specialist SAP D& T16th October 2015

    2 DisclaimerThis presentation outlines our general product direction and should not be relied on in making a purchase decision. This presentation is not subject to your license agreement or any other agreement with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or to develop or release any functionality mentioned in this presentation. This presentation and SAP’s strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. SAP assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally or grossly negligent.

    6 SAP Master Data Governance Easy to use, but fully integrated into your business logicHTML-based user interfacesMDG UIs are accessed via the SAP NW Business Client or any portalFully aware of the business contextFields are provided with value help look-upsValidation against the complete underlying business logictaking your companys configuration into account

    The Advantages Of Sap Mdg

    SAP Master Data Governance out-of-the-box applications

    • One trusted, “single version of the truth” of all system master data.

    • Approval workflows for all your master data creation and change requests.

    • Central creation and maintenance of master data across all SAP and non-SAP systems.

    • Compliance around master data management.

    • Audit trails when creating and modifying master data.

    • Improvement of data quality.

    Onbehalf of Business Excellence Wavin EMEA, we take this opportunity to acknowledge your hard work, we sincerely thank you for your utmost dedication and support throughout our SAP MDG deployment.

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    Introduction To Master Data Management

  • 1. Introduction to MDMWilliam El KaimOct. 2016 – V 2.0
  • 2. This Presentation is part of theEnterprise Architecture Digital Codexhttp://www.eacodex.com/Copyright © William El Kaim 2016 2
  • 3. PlanIntroduction to Data Governance Introduction to Data Quality Introduction to MDM MDM Delivery Model MDM Architecture Master Data Value MDM project Mgt. ConclusionCopyright © William El Kaim 2016 3
  • 4. The Data Management Context Large Global Organizations with a multitude of business processes andsystems to process transactions are often faced with the challenge of nothaving a Single Source of Truth for their Master Data. Systems Architecture and Data Architecture objectives appear to be divergent andtactical rather than cohesive and strategic Data is an enterprise asset used to make strategic business decisions Very often accuracy, completeness, accessibility and security of data prevents effectivebusiness decision making 80% of data in Transactions is Master and Reference Data! Organizations are naturally endowed with isolated pools of data that are notoptimally leveraged for the sum of the parts to result in the wholeCopyright © William El Kaim 2016 4
  • 10. Data Governance Framework ExampleCopyright © William El Kaim 2016 11Source: SAS
  • 13. Plan Introduction to Data GovernanceIntroduction to Data Quality Introduction to MDM MDM Delivery Model MDM Architecture Master Data Value MDM project Mgt. ConclusionCopyright © William El Kaim 2016 14
  • What Is Master Data Management

    Sap Master Data Governance Roadmap

    Master Data Management is the technology, tools and processes that ensure master data is coordinated across the enterprise. MDM provides a unified master data service that provides accurate, consistent and complete master data across the enterprise and to business partners.

    There are a couple things worth noting in this definition:

  • MDM is not just a technological problem. In many cases, fundamental changes to business process will be required to maintain clean master data and some of the most difficult MDM issues are more political than technical.
  • MDM includes both creating and maintaining master data. Investing a lot of time, money and effort in creating a clean, consistent set of master data is a wasted effort unless the solution includes tools and processes to keep the master data clean and consistent as it gets updated and expands over time.
  • Depending on the technology used, MDM may cover a single domain or multiple domains. The benefits of multi-domain MDM include a consistent data stewardship experience, a minimized technology footprint, the ability to share reference data across domains, a lower total cost of ownership and a higher return on investment.

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    The Benefits Of Creating A Common Master Data List

    While creating a clean master list can be a daunting challenge, there are many positive benefits to the bottom line that come from having a common master list, including:

    • A single, consolidated bill, which saves money and improves customer satisfaction
    • No concerns about sending the same marketing literature to a customer from multiple customer lists, which wastes money and irritates the customer
    • A cohesive view of customers across the organization, that way users know before they turn a customer account over to a collection agency whether or not that customer owes money to other parts of the organization or, more importantly, if that customer is another divisions biggest source of business
    • A consolidated view of items to eliminate wasted money and shelf space as well as the risk of artificial shortages that come from stocking the same item under different part numbers

    Finally, the movement toward SOA and SaaS make MDM a critical issue.

    For example:

    If you create a single customer service that communicates through well-defined XML messages, you may think you have defined a single view of your customers. But if the same customer is stored in five databases with three different addresses and four different phone numbers, what will your customer service return?

    Similarly, if you decide to subscribe to a CRM service provided through SaaS, the service provider will need a list of customers for its database. Which list will you send?

    How Should You Merge Your Data

    Most merge tools merge one set of input into the master list, so the best procedure is to start the list with the data in which you have the most confidence and then merge the other sources in one at a time. If you have a lot of data and a lot of problems with it, this process can take a long time.

    PRO TIP: You might want to start with the data from which you expect to get the most benefit once its consolidated and then run a pilot project with that data to ensure your processes work and that you are seeing the business benefits you expect.

    From there, you can start adding other sources as time and resources permit. This approach means your project will take longer and possibly cost more, but the risk is lower. This approach also lets you start with a few organizations and add more as the project demonstrates success instead of trying to get everybody on board from the start.

    Another factor to consider when merging your source data into the master list is privacy. When customers become part of the customer master, their information might be visible to any of the applications that have access to the customer master. If the customer data was obtained under a privacy policy that limited its use to a particular application, you might not be able to merge it into the customer master.

    Because of implications around privacy, you might want to add a lawyer to your MDM planning team.

    The next section provides some options on how to do just that.

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    A Few Thoughts On Versioning And Auditing

    No matter how you manage your master data, its important to be able to understand how the data got to the current state.

    For example:

    If a customer record was consolidated from two different merged records, you might need to know what the original records looked like in case a data steward determines that the records were merged by mistake and should really be two different customers. The version management should include a simple interface for displaying versions and reverting all or part of a change to a previous version.

    The normal branching of versions and grouping of changes that source control systems use can also be very useful for maintaining different derivation changes and reverting groups of changes to a previous branch. Data stewardship and compliance requirements will often include a way to determine who made each change and when it was made.

    To support these requirements, an MDM software should include a facility for auditing changes to the master data. In addition to keeping an audit log, the MDM software should include a simple way to find the particular change for which you are looking. An MDM software can audit thousands of changes a day, so search and reporting facilities for the audit log are important.

    Advantages Of Sap Master Data Governance

    Master Data Governance (MDG) SAP Tutorial || SAP MDG (SAP Master Data Governance) || SAPTube

    Master data governance is a discipline that is implemented across organisations via an ongoing and evolving program made up of technologies , subject matter experts and a focused project to enforce MDG. An MDG program is more than just the implementation of the technology. The greatest challenges will not be technical, but data governance-related. The creation of an appropriate, well-functioning data governance mechanism is essential for the success of an MDG program. It needs to ensure strong alignment with the organisations business vision and demonstrate on-going value through a set of metrics.

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    Sap Master Data Governance Training Course Overview

    SAP master data governance is an integrated data governance application with strong governance abilities for creation, maintenance, and replication of master data. This SAP Master Data Governance training course provides you with the technical and business information you need to use SAP Master Data Governance to ensure ongoing master data quality.

    In this SAP Master Data Governance training course, delegates will learn MDG for domain business partner, supplier, customer, process analytics, modelling, MDG exchange, and MDG data transfers. Our experienced instructors will give advanced knowledge related to SAP and MDG, as well as the necessary knowledge to extend and modify the solution.

    • Delegate pack consisting of course notes and exercises

    Master Data Management Steering Committee

    Its recommended that management-level representation from the MDM stakeholders form a Steering Committee to facilitate cross-functional decision-making. Here are a few characteristics of an effective Steering Committee:

    • Be sized appropriately Big enough to represent the priority stakeholders, but small enough to quickly analyze key information and make decisions.
    • Focused on fast decision-making
    • Become a vehicle for removing organizational barriers and not simply a regular meeting for listening to reporting from the Project Team members
    • Not be a substitute for hands-on Sponsorship

    Once the stakeholders are identified, the MDM Project Charter should include formation of a Steering Committee. Based on running hundreds or MDM projects, Profisee recommends the following roles participate in the Steering Committee. Note that there may be more than one team member per role, or some roles may not be applicable or a companys organizational structure.

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    A Single Source Of Truth

    Efficient data management is the need of the hour, making MDM software one of the best ways to overcome the challenges of manual data management, redundant data, and data discrepancies in master data. You can break free from cumbersome spreadsheets and complex data structures with this software. It streamlines all the processes related to the master data management of your company.

    The above-listed benefits of Master Data Management are just the tip of the iceberg. To-Increases data management solutions can help you reap these benefits effectively.

    What Is Master Data

    Data Modeling in SAP Master Data Governance for Financials

    Most software systems have lists of data that are shared and used by several of the applications that make up the system.

    For example: A typical ERP system will have at the very least Customer Master, Item Master and Account Master data lists. This master data is often one of the key assets of a company. In fact, its not unusual for a company to be acquired primarily for access to its Customer Master data.

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    The 6 Disciplines Of A Strong Mdm Program

    Given that MDM is not just a technological problem, meaning you cant just install a piece of technology and have everything sorted out, what does a strong MDM program entail?

    Before you get started with a master data management program, your MDM strategy should be built around these 6 disciplines:

  • Governance: Directives that manage the organizational bodies, policies, principles and qualities to promote access to accurate and certified master data. Essentially, this is the process through which a cross-functional team defines the various aspects of the MDM program.
  • Measurement: How are you doing based on your stated goals? Measurement should look at data quality and continuous improvement.
  • Organization: Getting the right people in place throughout the MDM program, including master data owners, data stewards and those participating in governance.
  • Policy: The requirements, policies and standards to which the MDM program should adhere.
  • Process: Defined processes across the data lifecycle used to manage master data.
  • Technology: The master data hub and any enabling technology.
  • Item Added To Your Cart

    SAP Master Data Governance, cloud edition

    This product allows organizations to perform master data governance on core attributes of selected master data on the SAP BTP.

    Key capabilities include central governance, consolidation, and data quality management on core attributes of business partner data.

    Sold in Blocks of 5,000 Objects with minimum of 20 blocks. Objects are all unique master data objects stored or managed in the Cloud Service.SAP Master Data Governance, cloud edition trialTry out the free trialExperience for yourself how you can easily get started with or expand your current master data management initiative in the cloud.

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    Why Is Master Data So Important

    Inadequate master data costs companies a fortune every year. Frustrated users, incorrect system operation and incorrect reporting are the result.

    Today’s managers require correct data to support their decisions. Nearly 70% of managers experience errors or shortcomings in the data they use. The figures speak for themselves, there is still a long way to go. Quality in master data is a matter for all departments within an organization. Solid and correct master data can be seen as a competitive advantage.

    If you experience the following needs:

    • Full monitoring and integration of your master data across the enterprise

    • Reduction of problems and identification of incorrect master data

    • Improve the accuracy and reliability of master data analysis

    • Gain more insight into your master data quality.

    Then SAP Master Data Governace might be a suitable tool for you. SAP MDG is a solid master data management SAP Add-on that can meet all these requirements.

    Cleaning And Standardizing Master Data

    SAP Master Data Governance, cloud edition: A Guided Tour | SAP Community Call

    Before you can start cleaning and normalizing your data, you must understand the data model for the master data. As part of the modeling process, you should have defined the contents of each attribute and defined a mapping from each source system to the master data model. Now, you can use this information to define the transformations necessary to clean your source data.

    Cleaning the data and transforming it into the master data model is very similar to the Extract, Transform and Load processes used to populate a data warehouse. If you already have ETL tools and transformation defined, it might be easier just to modify these as required for the master data instead of learning a new tool. Here are some typical data cleansing functions:

    • Normalize data formats: Make all the phone numbers look the same, transform addresses and so on to a common format.
    • Replace missing values: Insert defaults, look up ZIP codes from the address, look up the Dun & Bradstreet Number.
    • Standardize values: Convert all measurements to metric, convert prices to a common currency, change part numbers to an industry standard.
    • Map attributes: Parse the first name and last name out of a contact name field, move Part# and partno to the PartNumber field.

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    Benefits Of Master Data Management

    In this digital era, data is one of the most significant assets for any business. The increasing volume of data in the past few years has made it difficult for companies to manage data efficiently. As companies aim to utilize their data optimally, master data management has become their prime focus.

    Master data is the powerhouse of the most valuable information that a company owns. It is used by its departments across the organization to get their work done.

    Given just how critical data is, Master Data Management is a vital function for any business irrespective of its size and reach.

    This process deals with the end-to-end process of the data journey in the organization. It involves data collection from the relevant sources, application of business rules to establish a single data source, data validation, data transmission to the concerned parties, and data reconciliation.

    An MDM solution helps various departments and applications of a company navigate through the master data. It consolidates the complete data offering into a single source, which provides an integrated data application to diverse business functions across the organization.

    Here are a few benefits of Master Data Management:

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