SAP Customers Talk MDM: Part Two - SentrySafe

General Information About the Blog Series

In this SCN blog series, we'd like to let you hear directly the customer's voice when it comes to mastering master data in the enterprise. The blogs include video statements from SAP MDM customers plus additional info on the MDM initiatives.

The Customer's Voice: SentrySafe

Part Two features Sentry Group, a privately held manufacturer of fireproof files and safes. The company uses SAP NetWeaver Master Data Management to get a single view of their product data.

Click the image to start the video and listen to Gregg Griebel, ERP Program Manager at Sentry Group.

More Information on SentrySafe's MDM Initiative

Type of MDM Initiative
Consolidation of Product Data to provide one single source of truth
Aggregate and consolidate product information from various sources into central MDM repository. Feed SAP ERP back-end with consolidated product information required for streamlined transactional processing.

Stay tuned for the next session.

Regards,

SAP Inside Track 2011: EIM sessions

SAP Inside Track 2011 Midwest is jointly held in two locations: St. Louis and Chicago. I'll be speaking at the Chicago meeting. Hey, did I mention that it's FREE?

Of course, my topic is Information Governance. I'm calling the session "Faster and Cheaper Information Governance. Seriously." If implementing information governance sounds like a 5-year plan involving more meetings than you can stand, then this is the session for you. Whether you are just getting started in your governance initiatives, or whether your company is struggling to reach *success* with governance, we can help. In this session, we’ll discuss common pitfalls of information programs. Most of our time, however, will be spent on how to start small to ensure future success. In this session, you'll learn these skills: - identify good target projects - shape lean teams to accomplish the work - identify which technologies will accelerate your project - prove the value of the initiative to your organization.

The stellar SAP Mentor Gingler Gatling will also be there. That alone is worth a trip. She wrote the book on workflow, you know. :-) Ginger has three sessions, spanning workflow, data migration, and EIM in support of workflow.

Understanding SAP Business Workflow and how it fits in with SAP's BPM Strategy: Sharpen your knowledge of SAP Business Workflow, what it can and can’t do, and how it fits into your SAP architecture. Find out how other companies are leveraging workflows to improve and streamline processes, and the business drivers that make SAP Business Workflow a critical piece of the SAP infrastructure.

Comprehensive Guide to Data Migration: This session takes a deep dive into SAP BusinessObjects Data Services and offers best practices for using both the integration and data quality management capabilities provided in SAP BusinessObjects Data Services.  Get step-by-step instruction for getting started with SAP BusinessObjects Data Services, such as leveraging the pre-delivered migration content it provides and understanding the various connectivity options. Walk though a demonstration of SAP BusinessObjects Data Services migration content for SAP ERP and SAP CRM data migrations, showing the connectivity to SAP configuration tables for data validation and how to map common structures such as customer basic data.   Explore the jobs, workflows, and transformation capabilities within SAP BusinessObjects Data Services, and learn how to ensure SAP application configuration is referenced for data validation.  Discover the data quality major capabilities that can ensure your data migration project enables data management and data governance.   Learn the pitfalls to avoid when using SAP BusinessObjects Data Services for data migration, such as not taking into consideration the customizations – such as Z tables – within your target SAP systems. Take home links to the data migration content within SAP BusinessObjects Data Services.

Enterpirse Information Management and how it relates to business processing: This session will provide a  'what is Enterprise Information Management" and then discuss what this means for the SAP Business Suite, business processing, and business process experts.  The goal of this session is to provide insight into Enterprise Information Management including what it is, why it’s important to business, how it fits into SAP’s strategy and where you can go to get more information.

Tammy Powlas will also be there. Join us at the SAP Inside Track 2011 Midwest meeting.

A bucket of smart ideas - Master Data Governanace Framework for Enterprises

In May of 2011 SAP Master Data Governance Solution aka Embedded MDM solution became generally available. Some brief information about the value proposition of this framework for your organisation can be read here.

Before I dive into describing some of the features of MDG which I find really useful let me describe the need that this solution majorly targets.

Need of an embedded MDM (embedded on ECC system) solution : Managing a solution built on the same/similar system where master data resides is highly desirable from application architecture point of view. It reduces the complexity of the solution to be built and thus also helps reduce long term maintenance cost. It also reduces the footprint of the application largely. Also reusage of the components (out of the box validations) etc helps to create uniformity on what the user experiences while creating data conventionally and via MDG change request framework. This also helps manage the change management activies easily for example end user training etc.

Now some of the smart features in MDG application framework which can help you design an optimum Master Data Governance Solution according to me are :-

1. Change request based processes : Having uniform user experience for differenet data domains such as suppliers, material etc. This framework also exposes historical data changes in the form of change documents (both from the change request and outside of change requests).

2. Flexible processes : The processes (change requests for create / update etc) can be designed on a generic out of the box business workflow. In broader terms this workflow solution has two components - 1. business workflow and 2. BRFPlus application. These two tied up together create a very basic but effective BPM environment where via quick and easy to do configuration, a process can be easily setup / modified to meet business requirements. This again helps expedite application building and also reduces process maintenance turn around times.

3. Data model & related UI views and validations : The MDG solutions need a data model which mirrors the relational model of the master data in question for creation of change request UI, staging area (explained below) and to create validations (both out of the box or custom). The smart thing here is that the application inherits the validations related to master data directly into the change requests as well gives the end user option to code validations via BADI's or though BRFPlus rule sets.The framework also has the capability where data duplication can be prevented via configuration.

4. Staging Area : The work in progress data is not stored in the master data tables but a temporary database until completly approved by the concerned user. This helps control availability of data in transactions.

5. Smart UI :  The UI for the embedded MDM solution is primarily ABAP WebDynpro based and can easily configured using FPM configurations. The resuting views can be same as the conventional master data maintenance transactions (SAP GUI) or can be modified as per business requirements.

6. Integration with Enterprise Search : Easy information search options.

7. EHP5 added functionaity like BCV (Business Context Viewer) : The BCV can be used as a side bar addon on the NetWeaver Business Console (NWBC) for integrating master data key elements to other relevant data and view it in different avaliable options. For example Data relevant to a given material can be obtained from PLM system or CRM sysem etc. So with this information integrations becomes seamless and thus representation of data is better.

8. Deployement Options :  Can be standalone on one system (ECC 6.0 and EHP5) or can be on top of an existing ECC 6.0 system by updating it with EHP5. The MDG system can also integrate with other non SAP systems to create one enterprise solution. More about this can be read here.

With these features, SAP has given the customerrs an option to create solutions which are robust, which donot compromise on data quality aspects but at the same time are flexible and have low cost of development and maintenance.

One SAP for Data Quality: Building an Operational Data Management Organization

Lessons from SAP

Launch of CDM

Customer Data Management (CDM) came into sharp focus at SAP as the data management topic was launched as a board sponsored program in 2008.  To support the CDM program a cross line of business leadership team was established and a multi-year business case and plan was developed.  CDM’s overall purpose was to address highest priority customer master data issues.  Improvement opportunities existed from both short and long term perspectives.   The team set about to fix the immediate issues such as getting the “basics” in place.  In addition, long term solutions included the design and build of an operational customer data management solution.   The successful program spanned a year with staff of 6 full time resources supported by an extended team of subject matter experts from the business and IT.

CDM program scope and focus

Very quickly the CDM team realized that to be successful scope definition and control was required as well as a sharp focus on the most important customer master data issues.  It was apparent that customer data had not received attention over the years. Without governance and quality management many data challenges existed.  The CDM team explored the issues in detail, from an outside in perspective, and found that 20% of the master data elements were delivering the most value to SAP.  That input was used to narrow the scope and evolved into a guiding principle to “get those right”.  To address the longer term root cause information governance issues, master data accountability and standard definitions were included in scope.  

CDM approach overview

Given the CDM scope and the broad nature of the requirements, the program methodology reflected a phased rollout of global data standards which were tested via a pilot and then rolled out to a broader audience. 

Country pilots of global data standards and ownership model (for the most critical elements of customer master data) was successful in delivering business benefits, particularly in the sales and marketing areas.  Data quality reporting and cleansing services leveraged SAP’s EIM suite and clearly demonstrated that the global CDM approach would successfully operate within a regional model.  

The pilots also served to validate the design of the future state data organization and transition plan which reflected a phased rollout to other areas and lines of business within SAP.  For example, the CDM program leadership evolved to form a Global Data Council, consisting of the newly appointed data leads within each line of business many of whom were directly involved in the pilot launch.  

Part of the operational plan also included ongoing data cleansing and resolving the priority customer master data issues.  That scope ran parallel to the establishment of the data management organization which was being established.  The tactical data quality cleansing enabled the program to stay on track and deliver business benefits in the shorter term while building the foundation for longer term data management solutions. 

The successful pilots and data quality improvements enabled the longer term CDM vision to move forward.  Upon program closure in Q1 2010, the team executed a smooth 4 month transition to the operational  “run” state.

SAP's current CDM organization

Fast forward to today as the transition is complete with Maria now leading  SAP’s  operational global data management team.  Maria wears “two hats”, leading both the global data management across the lines of business as well as detailed management within the global field organization.  She is responsible for driving both the global master data strategy and the sales line of business data strategy.   There’s also a close collaboration with the business process owners and a continuation of the data standards and governance established by the CDM program.

Cross LOB governance model

The global data management organization extends to all lines of business (LOB) which have identified data leads who are tasked with driving tactical and strategic data programs.  The LOBs are also responsible for delivering business process engineering and ensuring information governance and accountability is enforced throughout their organization. 

To support the cross-LOB collaboration a Global Data Council was established as a vehicle for the business leads, along with IT and others, to work together to address common data issues and foster cross-LOB alignment.  For example, the Council handles strategic functions such as defining information governance requirements, as well as having direct responsibility for business rollout/adoption.  The council also prioritizes and manages the IT portfolio for the data tool and technology changes , providing one business voice to IT for master customer data related IT projects 

The Council is supported by a cross-LOB Executive Data Steering Committee which provides oversight and decision support.  Executive engagement is a critical success factor for the master data management approach as their attention to the topic results in budget and resource allocation to the data programs.  

Regional data centerswill support process execution

One additional operational component established this year is the development of a Regional Data Management Center model.  Each region now has a team of skilled data resources who focus on delivering improvements to core master data such as enriching customer records, creating master data and updating account assignments.  The regional centers currently support marketing and sales data requirements but will soon expand to support other LOBs such as Finance and Customer Support.

These centers not only provide data services but they are also engaged in driving quality process improvements via best practices and tools.  The DMCs have the master data knowledge and are best positioned to best deliver best practice solutions.  For example, business partner creation processes can be developed and tested by the global data team and once proven can then be enabled via the regional data operations team.   The Global data management team, under Maria, provides the DMCs with common global tools, processes, resources.  They have established global KPIs by which to measure the DMC’s effectiveness.  

2011 areas of improvement

SAP’s global data quality program is measured on both specific KPIs such as reducing duplicates but also process improvements such as reduced data creation time.   KPIs are tracked with data quality reports which use EIM tools such as SAP BusinessObjects Explorer and Dashboard Design (formerly Xcelsius).  These online reports measure both regional and global data improvements and are tailored for the specific audience (e.g. executives vs. data managers) with drill down capabilities. 

Process improvements contribute to overall data management business case in a significant way, particularly in areas that impact the bottom line such as days sales outstanding.  These metrics are tracked by the global data team and are reporting to the executives through dashboards and scorecards. 

Tracking of these improvements is formalized into data quality readouts to the Executive Data Steering committee.  We are now also tracking specific line of business contributions via a holistic scorecard that monitors each line of business’ support of the data portfolio and helps provide a complete picture of all contributions to master data quality.  

Data management technology vision

Technology and tools are critical enablers of SAP’s data strategy and will allow us to more quickly scale and address additional master data requirements.  The vision or roadmap centers on a partnership with IT to deliver solutions that align with best in class technology capabilities.  For example, the roadmap reflects the use of tools to centralized workflow and business rules for easier management and control.  Data models and management tools will help us diagnose and automate changes as needed for more active governance.   Analytics and dashboard tools are required for transparency to all of the processes.  Thus, there’s a significant amount of funding allocated to a multiyear portfolio of IT projects to deliver Information management tools required by the business and prioritized by the Global Data Council.   We use SAP technology from the EIM product portfolio, as well as the SAP business suite.  SAP uses  SAP !! We  partner with the product develop team to provide our feedback  on future and current products .

EIM success factors

While information governance programs are tailored to a company’s Information Maturity,  company pain points  and culture,  there are many common success factors.  First, the company has to be ready for a top’s down enterprise governance approach where all functions participate, collaborate and play a part.  Business sponsorship is also key- the higher in the organization the better as roadblocks will be encountered that will need to be resolved . Funding is another  EIM success factors.  Perhaps even more important is having the right visibility on the required data capabilities along with business sponsorship and readiness for successful change management.   Data tool delivery goes hand in hand with having an organization in place to best leverage the automation with the right people and skills.

What does great data management look like?

Through the journey from focused program to creating a data management business capability , we have defined a few key practices for “great” data management at SAP.  It’s not just about creating roles and building work teams but data management must become an integral part of the organization with cross business decision making forums who will actively engage in driving accountability. The organization must ensure  the data programs enable business goals and don’t exist just for the sake of creating “good” data.  Great data management is embedded as a core part of the business and IT process so that whenever data is created, changed or updated and information governance is clearly defined and easy to follow.  This requires engagement from business leaders and IT leaders with simple language and clear accountability. Data quality is not just an organization practice but extends to trusted sources of data as those sources should adhere to the same standards.  These lessons learned have helped shape SAP’s data management organization; our priorities reflect a desire to achieve high levels of data confidence across the company.

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