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Guest blog: Overcoming the business case roadblock

This is the first 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 first post tackles business cases.

Master data management, information governance and enterprise data management (EDM) are no longer emerging concepts. In fact data quality problems date as far back as the advent of computing itself. Several industry analysts have written about these enterprise capabilities extensively. Gartner started a new annual conference in 2007 that is dedicated just to master data management. Several large enterprises have recognized the need for EDM and have launched some type of information governance and data quality initiatives. However, in spite of all this attention to data, as I continue to deliver consulting services in the area of EDM, I experience that several misconceptions and misunderstandings still loom large in organizations across different industries and of all sizes. These misunderstandings create powerful and formidable roadblocks that prevent you from launching EDM programs or realizing tangible business value from EDM programs that are already launched. In this series of blogs I will attempt to describe some of the most common roadblocks for EDM, explain what some of the causes that create those roadblocks are and offer some high level approaches that can help overcome those roadblocks.

These blogs can benefit anyone who is getting started on EDM but they are written primarily for those EDM advocates that know that their organization needs to improve the quality of their data but struggle to articulate the business value of EDM and to get enough attention of the senior management in sponsoring the EDM program. These individuals could be in business or IT. If they are in business their responsibilities lie in a business process area that is typically downstream, e.g. accounts receivable personnel that are downstream in the Order to Cash process area. These individuals deal with the data quality issues on a daily basis; they receive calls from other people in the organization or externally from customers when something is wrong about a business transaction. They often spend a lot of time searching for the right master data record, backing out posted transactions and correcting some kind of a data problem before posting new transactions. These people talk to their managers about these issues and the inefficiencies caused by them. With the help of their managers they might have tried to put together some kind of a business case or justification to solve these problems but they have not been successful in selling it to their senior management so far. These advocates of EDM struggle to articulate the business value of EDM in a way that their senior management can relate to. They are also usually frustrated because the senior management neither grasps the complexity of solving master data problems nor understands the commitment EDM requires to deliver tangible business value successfully.

In this first blog of the series we will look at overcoming the roadblock of establishing a clear business benefit case in order to secure an executive sponsor for the EDM program.

Lack of a clearly defined business case for data management – EDM initiatives are not a low hanging fruit. These initiatives tend to be strategic in nature that deal with your core and foundational assets such as Customers, Products, Suppliers and Employees. They require significant organizational effort and investments in terms of people, process, information and technology. The success of EDM lies in bringing about a cultural change in the organization in which people across different functions, regions and grade levels whether they are producers or consumers of data become aware of the importance of data quality and commit themselves to become better custodians and stewards of data. This cultural change and the commitment needed for investments is not possible without a strong executive sponsor (VP or above). These executives are ultimately responsible for the financial performance of the organization and want to make sound investments that will yield tangible business results. For these executives to support EDM program and prioritize it above other competing corporate initiatives, they need to understand the business value that EDM will deliver. This means that we need to prepare a clearly defined business benefit case in a business oriented language that the executives can understand and relate to. In order to do articulate the business case, we first need to be clear ourselves on the linkage between data and the business value it can deliver and ultimately the improved business performance that it can enable. Let us delve a little deeper into uncovering and understanding this linkage first.

If you take a look at how master data gets used in your company you will realize that it drives two primary use cases – business processes and business intelligence. Master data flows like a lifeline through your business transactions, e.g. a sales order consists of customer, product or service, price and delivering plant. There is also other data on the sales order that controls how and when the goods and services will be delivered, what will be the delivery charge and who will pay it, how the taxes will be calculated and paid etc. The design of SAP’s ERP system (ECC) is such that it treats the customers and products as master data, pricing as conditional master data and plants as configuration or reference data. Once these sales transactions accumulate in your transactional processing system (OLTP) they are fed into a data warehouse for analysis to understand which customers bought products or services from you, who are your biggest customers, which are your most profitable customer segments, which products sold the most, which are your most profitable products, which products are profitable in which regions, what is the cost of manufacturing those products etc. Your executives are interested in doing this analysis so they can make sound fact based decisions for future investments and improved business performance. What we have just done is established a link between the business analysis at the top to the master data and reference data at the bottom with business transactions in between them.

In order to establish a business case for EDM then we need to find out what your executives’ business priorities are and tie those with the master data that supports them. Once we understand where to focus for data improvements we are better able to articulate the business value of EDM to the executives in a language that they will understand and we are even starting to chart a roadmap by identifying where to begin on the EDM journey. Let us illustrate this further with an example. If you find out that one of the top priorities of the CFO of your organization is to improve Days Sales Outstanding (DSO), you know that the DSO can be negatively impacted due to the inefficiencies in the sales, delivery and billing processes. Customer, product and pricing data gets used heavily in these processes. You might discover that inconsistencies in pricing data might be preventing customers from paying your invoices on time, for example, it is not uncommon to see that the price on the contract does not match the price on the invoice and the customer won’t pay the invoice due to the difference in price. There might be differences in the material that was on the quotation versus the material that was actually shipped due to the preferences and availability of that material at the shipping plant. It might be taking you a long time to get the invoice out to the customer once the goods or services are delivered. Investigate if there is a data problem behind these delays and inefficiencies. Techniques such as fish bone diagrams or the 5-Why technique can be used to identify data root causes that are negatively impacting the DSO. Do not assume that solving data problems alone will help you conquer the DSO problem; for example, you will need to improve the processes along with the improvements in data to realize all the business benefits of data improvements. Conversely improving processes alone is not enough either, as bad data often prevents realization of real business value from process improvement initiatives. Once you have zeroed in on the specific people, process, information and technology improvements that will improve the DSO, you need to estimate the commitment needed in terms of resources, timeline and cost. Founded in fact based data analysis such a business case that clearly lays out the costs and benefits over a period of time will no doubt win the vote of your CFO.

How to overcome this roadblock?

Start with the business strategies, goals, objectives and priorities of your executives. Understand which KPI’s are involved in tracking the improvements in business performance. Determine the business processes and master data that when improved will deliver the improvements in business performance. Analyze data and create data health assessment reports to establish a baseline of the current state. Articulate why an EDM program that comprehensively addresses the issues across such dimensions as people, process, information and technology is needed to solve not only the current problems in data quality but also to keep the data quality high on a sustainable basis.

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 –

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  • Thanks for providing!  I would love to know more about the graphic that you provided showing Master Data, Reference Data, etc.?  Do you have the original or is this the first time you illustrated this concept?  Thanks in advance,


    • Hey, Matt. Unfortunately, Nitin is no longer with SAP, so I can't provide an updated graphic from him. Lately, we've been using our data strategy master class to advise on the topic: