Mastering Master Data – How to Succeed with Master Data

Originally published June 26, 2007

In my previous articles, I’ve discussed how master and reference data are business problems first and foremost and how IT contributes to problems with master data. Now it’s time to focus on how to succeed with master data.

Success with master data is a challenging proposition. Thinking strategically, master data is at the heart of critical initiatives in many businesses today. Whether your company is committed to being customer-centric, product-focused or operationally excellent, master data is essential for success, and the degree of success will depend on how your company manages master data and its necessary responsibilities.

Because master data is a business problem first and foremost, business objectives and issues must be addressed on an enterprise, not line of business, basis. For customer master data, who is responsible for customer satisfaction and what data do they need? For product master data, who decides what products and services are offered by the company and who is responsible for ensuring that pricing is consistent across all distribution channels? These questions are typical, and their answers cross organizational boundaries and must be addressed to achieve business objectives successfully.

The first requirement for success with master data is that it must tie to a strategic business initiative. Let’s look at a few strategic initiatives occurring in business today and see what they tell us about master data:

Becoming Customer-Centric

Many businesses understand that customers need to be understood as individuals and households rather than simply transaction-based entities. These businesses are looking at the overall value of customers: their lifetime value to the company; the nature of their business relationship, whether it’s based on service, price or other factors; and the profitability of the customer.

Customer-centric companies recognize the importance of consolidating, integrating and confirming data on their customers, and often this is where they start. However, it is critical, if the company truly wants to become customer-centric, that essential business questions be addressed. If your company knows a customer has a high lifetime value and is worth keeping, which organization unit is responsible for keeping the customer satisfied with your company’s products and services? Generally, the answer is no one business unit.

This is the first challenge to becoming customer-centric: recognizing that a series of fragmented customer interactions delivered by separate customer service, account, product or billing business units does not ensure customer satisfaction. Businesses where customers churn are beginning to tackle this challenge in order to keep their high-value customers.

The best practice in this case is to establish a customer retention unit to monitor customer interactions with the business and take appropriate actions. By looking at all of a customer’s interactions with the business, patterns that indicate a customer may be considering severing his or her relationship with the company can be detected. An example of the need for this is a global financial services company. How will a branch service representative know that the customer across the desk is an important customer traveling internationally and, by not knowing, what treatment will the customer receive? How will this treatment affect the customer’s loyalty to the company?

Scenarios such as this help define the content of customer master data: all of a customer’s accounts, interactions and other data required to understand the importance of the customer to the company need to be available everywhere a customer can interact with the company.

Also, establishing a customer retention unit requires rethinking account and customer service responsibilities. Customer master data needs to include the data needed to detect behavioral patterns so that the need for a customer retention intervention can be determined. This separate business unit can intervene and act on the customer’s behalf to resolve any issues and answer any questions. Where this has been done, churn has been successfully reduced.

It is important to note that being customer-centric does not mean treating all customers the same. Being customer-centric means that you know who your high-value customers are and who your unprofitable customers are, and you treat each accordingly.

Becoming Product-Centric

Many businesses desire to differentiate themselves on the quality and innovation of their product offerings. However, in large companies, product offerings originate in different departments and business units. This results in a line-of-business approach to products with little thought given to a company’s overall product strategy. Product-centric companies recognize that a focus on product management is critical for success, particularly focusing on product profitability, product differentiation, and product appeal to customer demographics.

These companies recognize the importance of looking at products as critical factors in driving market success. This requires looking at how well a product is doing in the market (is its market share increasing faster than the competition’s market share, is the rate of growth consistent, growing, or declining, and so forth); product quality, especially if quality can be affected by suppliers; and product profitability.

This represents challenges to the business as well. Assessing product mix, profitability and market share require application of a consistent methodology and criteria not usually found in companies with multiple lines of business. Further, assessing quality and root causes of quality problems usually crosses organizational boundaries.

The best practice, in this case, is to establish a product management unit. This unit evaluates products, markets, product performance and product plans. A product management unit presents challenges to the business organization, especially around product evaluations, plans and investment decisions.

Product master data that supports product management therefore needs to include all products offered by the company; the cost and revenue factors for each product; its quality measurements, its market data – including market data for competitors and their products; and data on customers’ needs, problems and demographics for market analysis and product development.

Becoming Operationally Excellent

Many businesses are focused on improving business operations intending to become operationally excellent. This requires a focus on business processes, performance and effectiveness. Operationally excellent companies recognize that a focus on operations, especially performance metrics, is critical for success.

The business challenge here is to look beyond organizational structure as the sole means to assess operational performance. Business processes, which often cross organizational boundaries, need to be considered. Individual business “pain points,” such as increasing inventory turns, optimizing service staff, and any identifiable instance that can affect the bottom line also need to be included.

This is different than becoming customer- or product-centric. Here the business is looked at in organizational and abstract ways, such as by work location, business process, organization structure, and so forth. There is no business unit responsible for operational excellence – this is a responsibility of executive management. The challenge is for individual managers to be assigned accountability for improving a performance metric or an identified “pain point.”

The best practice in this case is to establish a strategic performance management unit. This unit tracks strategic business goals and the metrics that affect or measure them. This requires defining and understanding business operations from the perspectives of the organizational structure and the flow of work through business processes.

Master data in this context consists of reference data (see the definitions of master and reference data in my article entitled Mastering Master Data), business processes, metrics, key performance indicators (KPIs), and the underlying data that supports them. Industry benchmarks are also required in order to determine operational superiority objectively. These are familiar to data warehousing, business intelligence, and executive scorecard/dashboard professionals.

Students of business literature will recognize these categories as areas of strategic emphasis written about, I believe, by Michael Treacy, an internationally recognized expert on corporate strategy and business process transformation. While a company may set its strategic focus on one of these areas, every company is struggling with customer value and retention, product profitability and management, and operational excellence. Therefore, an effective master data strategy needs to address all three.

What do these strategic initiatives show us about master data? First, they challenge the business to address new organizational challenges and structures to be effective. Second, all require data that does not exist in existing transaction systems, including customer demographic data for determining lifetime (potential) value, market and competitive data for products, and industry benchmarks for performance comparisons.

There are operational and IT implications in how master data is implemented. How will master data be established? How will it fit in with existing and future application systems? How will this affect decision making about application systems and business functionality? These questions also cross existing organizational boundaries and must be addressed for the success of the business. There are important IT factors that are essential for the success of a master data solution, including:

  • Technologies used for master data must conform to a rigorous architecture. Too many IT organizations focus on technology issues such as whether a master data repository solution should be federated, distributed or a single data store. Also, there are specialized needs for customer master data and for product master data, and it seems as if different technologies and solutions may be required to satisfy their unique problems. Generally, these issues are driven by capabilities of products promoted by vendors as master data solutions. Products and vendors are essential for success with master data, but their selection and use must be driven by a rigorous master data architecture.

  • Master data must be maintained in a single master data environment, even though there are significant differences in the domains, characteristics and uses of customer, product and reference data. Product master data, for example, must serve pricing, distribution channels and catalogs, warranty and return processes, and profitability analysis and planning while customer data serves customer service, billings and receivables, and order taking. Because these have such diverse differences, they are often implemented as separate solutions.

    However, the control issues of managing access to and use of master data, the audit and compliance issues of ensuring the correctness of master data, and the security issues of data encryption are best served by maintaining all master data, in spite of its diversity, in a single master data environment. Using master data in transaction applications, data warehouses and enterprise reporting should be facilitated by a set of SOA-compliant data delivery services constructed to address these issues.

  • Master data must have a consistent set of policies and practices. The master data solution can only be effective if it is administered consistently across data domains and their application. This requires a consistent set of policies and practices, particularly monitoring master data content, quality and usage for overall management and control.

  • Master data requires effective governance. Clearly, management and control of master data requires an effective governance and decision-making process. This must go beyond data quality and address the role and structure of master data in the company’s business, information and application architectures. Governance is critical for effective IT support of the business. For more on this topic, see my paper, “A Manager’s Guide to Successful Governance.”

While master data is a responsibility of the business, how IT implements and manages it will determine its success.

Establishing an effective master data solution requires planning, activating and controlling steps. Here then is how to succeed with master data:

Planning for Master Data

  1. Identify ways in which centralized master data will be used to improve the business and set business improvement targets. This is the first step toward developing a master data solution. Without this, master data will become a temporary IT technical fix.

  2. Establish the customer retention, product management and strategic performance management business units and name the executive sponsor of each. This builds on the business focus by chartering the business unit that will use master data for new capabilities and naming the senior executive who will be responsible for their implementation and results.

  3. Define the mission, goals, objectives and measurements for the new business units. This formalizes the unit’s purpose and expected results and makes master data critical for meeting business objectives.

  4. Establish master data management governance, policies and practices. This provides the specification for master data governance and management.

  5. Architect the master data environment. This establishes the technical foundation for the master data solution.


    Activating Master Data

  6. Establish one master data repository for all master data. This requires consolidating and integrating data from applications and other systems to contain a single repository of master data. An information architecture is essential for developing an effective master data solution.

  7. Ensure that master data aligns with the “real world.” This is a different level of integrity than for a data warehouse, where data is expected to match its source system of record. Here, customer master data is expected to be true for the real-world customer. This is another reason why the business is responsible for master data.

  8. Ensure that the master data repository is the one, official source for master data that is always correct and up to date at any given instant on any given day. This is the most rigorous technical standard for master data. If this condition is not met, then the master data solution is a never-ending data integration effort that will require reconciliation and transaction correction processes to keep master data correct.

  9. Establish data delivery services for all master data. Making master data accessible to applications and systems that need it will require data delivery services for the master data repository. This is important for integrating master data into applications.

  10. Establish external sources of data as required. As noted, external data will be required to maximize the value of your master data. Plan for it and include it from the beginning of your master data solution.

    Controlling Master Data

  11. Monitor master data quality and correctness. This is necessary because the real world is likely to change faster than your master data. External data sources can be used to confirm or correct aspects of your master data. In any case, this is essential for the long-term usefulness of your master data.

  12. Ensure that IT applications integrate properly with master data. Without ensuring that applications are adhering to the use of data delivery services for master data and that the application ability to add, change or delete master data values remains disabled, master data inconsistencies will creep back into the applications and systems environment and create uncertainties about the usefulness of your master data.

  13. Make adjustments as required to eliminate problems and improve effectiveness. New business uses for master data will develop, occasional problems will be found, new data will be required and other demands will be made. Adjustments should be made as needed to keep your master data usable and useful.

None of this is easy, as seen in the business and IT challenges discussed, and master data solutions are just now coming into focus in many companies. Master data is a discipline and a journey, not simply a project or a task. It requires determining how to use master data for the benefit of the business, addressing data quality and integration issues, decision processes for application integration with master data, and measuring effectiveness. Master data will continue to be an ongoing business element and, if these guidelines are followed, can be an asset to any business.

  • Richard SkriletzRichard Skriletz

    Richard is a manager and management consultant with more than 35 years experience working in large corporate and start-up environments. His professional focus is on the strategic application of information technology to improving operational performance, managing organizational and technical change, and optimizing business effectiveness. Richard is a Global Managing Principal with RCG Global Services and CEO of InfoNovus Technologies. He can be reached via email at Richard.Skriletz@rcggs.com.

    Editor's Note: You will find more articles and resources, and Richard's blog in his BeyeNETWORK Expert Channel. Be sure to visit today!

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