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Guest blog: Attempting to address too many data domains at the same time

This is the second in a 3-part guest blog series by Nitin Joshi, a Principal in SAP’s Business Transformation Services consulting group. Nitin’s series will focus on Overcoming Roadblocks to Enterprise Data Management. This second post tackles scoping an initial project.

In the first blog, we looked at how to overcome the roadblock of a clearly defined business benefit case for EDM. In this blog we are going to look at the best practices on how to proceed once the business case is clear and is bought into by the senior management.

When I was helping a customer prepare a roadmap and internal justification for a global vendor master data management initiative I was asked by a customer executive – “But what about Customer, Product, Employee and Cost Center? When can we deliver those?” This IT executive was acting in the best interest of his company; he was convinced that the organization’s data issues need to be solved and was eager to address all the master data domains as soon as possible. However what the executive was missing was the fact that each data domain has its own nuances and needs its own commitments and investments to ensure that the data quality within that data domain stays high. The customer executive had made an assumption and had formed expectations based on that assumption that other major master data domains such as customer, product, chart of accounts would get delivered in about the same timeframe as vendor and with only incremental investments in cost.

I see this quite often that the leadership grossly underestimates the effort needed to successfully deliver an EDM program even for a single data domain. Many executives in IT and business both understand the importance of business processes and business intelligence. What they often miss is how master data enables these processes and the decision making analysis. As you try to deliver tangible business value from EDM programs you realize that before improving efficiencies in operational business processes and improving quality & efficiency of business decision making you first need to establish a foundational data infrastructure. One of the first orders of business in order to establish this data infrastructure is to define your important data objects in a consistent way. As you try to tackle the problem of having consistent data definitions you realize that master data is shared across business units, across processes, across systems, across functions, across geographical regions and even outside the boundaries of the organization with your customers, suppliers and governmental agencies.

For example in a CPG company, the supply chain function is interested in knowing the customer’s locations that the company ships to so that they can do the demand and supply planning by those locations; finance department wants to know who the legal entity is that they are dealing with so that they can do the credit check and fraud protection as well as determine where the invoice will be sent and where the payment will be received from; marketing wants to understand who the retailers and end consumers are and what their needs, preferences and buying patterns are so that they can run trade promotion programs most effectively; associates working in the export department deal only with the international customers and are aware of the nuances that exist in the foreign countries relating to tax, legal and compliance matters; contract manufacturing business unit deals with those indirect customers that receive the goods that you manufacture on behalf of another brand owner; there are business partners that provide packaging services to you and you need to ship your products to them; plants and companies within your business enterprise often ship products to each other and are set up as internal customers to facilitate intercompany billing processes; business executives want to understand who their biggest business partners are so that they can strengthen their relationships with those customers. As you can see the complexity of defining a customer is significant for this CPG company as there are external and internal customers; direct and indirect customers; distributors, retailers and consumers; domestic and international customers; co-packaging partners; customer hierarchies with headquarters, subsidiaries and branch offices; and finally relationships among all of these customer entities that need to be managed when managing customer master data.

Once the data definition part is under control you have just begun your journey to your desired end state of governing the customer master. You will need to understand the data requirements and map out which entities and data elements of the customer master are consumed by which business processes and analytical applications and by which systems; which systems will serve as the System of Entry, System of Record and System of Reference for the customer master data; standardize the entities and data elements with their definitions, unique identifiers, data types, lengths, formats and lists of valid values; design maintenance processes of search, create, change and mark for delete; define data quality reports and quality metrics with targets; identify and assign data stewards; select tools for data repository, user interface, workflow, business rules management; implement tools to serve as the enterprise wide repository of customer master and to automate & orchestrate the create/change/mark for delete process workflows; build interfaces among systems where customer data originates and where it is consumed; manage resistance to change and finally train the users on the new way of doing business of managing the customer master. Conquering one master data domain is a significant effort as it spans multiple departments and involves diverse stakeholders. The effort of standardizing, architecting and implementing technology solution further adds to the complexity of EDM deployment.

How to overcome this roadblock?

As stated previously, EDM strategy and case for change needs to align clearly with the business objectives. Focus should be on delivering tangible business value, not on doing a data project. If you find that you have data quality issues pretty much across the board, you need to prioritize. Best practice is to conquer one data domain (such as Customer, Product or Vendor) at a time. Although there are common themes that apply across master data domains, each data domain has its own unique challenges. An independent thinking and problem solving is needed for each domain. Although it might be the desired end state, it is neither prudent nor practical to think that all domains should be managed at the same level of maturity at the same time initially. The journey to get to the desired end state is often a marathon, not a sprint.

Experience shows that EDM projects that try to do too much at the same time (especially in those companies whose EDM maturity level is low) ultimately run into such issues as not delivering business value for a long time, running over budget with diminished interest from executives to keep sponsoring the program. Doing an EDM roadmap at the time of doing the strategy will clearly help overcome this roadblock. Executives need to be educated on what is involved in running an EDM program successfully along the dimensions of people, process, information and technology.

About the author

Nitin JoshiNitin Joshi is a Principal in SAP’s Business Transformation Services consulting group. He helps customers develop Information Strategy, Roadmap and Architecture with a focus on addressing business aspects of information management. Nitin has 18 years of IT and 15 years of SAP experience. He can be reached at his SAP email address –

Nitin Joshi
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