The real value of corporate data lies not in the data itself but the value it has in speeding day-to-day business transactions and in the insights that can be pulled from it.
Consider the role that data plays in the extended retail industry, the ecosystem of manufacturers, wholesalers, logistics companies and other service providers that take a product from inception to a store shelf near you. This extended supply chain is far more efficient if the key players share information on the market, the products and the customer. The first step requires sharing or synchronizing master data, which consists of the key information that describes a company's products, vendors and customers. The standardized definition of the item at the consumable level allows for all parties to be working from the same page at all times. By doing so, members of a synchronized ecosystem can operate the supply chain at maximum efficiency. Manufacturers know what to ship and how much, and can get clear insights into consumer demand. Retailers know what to expect at the receiving dock and can accurately guide their suppliers on inventory replenishment. Doing this eliminates the invoice discrepancies common in the retail world as well as reduces inventory buffers, shortens lead times and minimizes out-of-stock situations.
An optimized supply chain is just one of the goals that drive companies seeking to create a real-time enterprise and ecosystem in which employees and partners have a consistent view of data across multiple applications and platforms - both inside and outside the four walls of the organization. By making clean, consistent information available where and when it's most needed, companies can continually improve processes and performance, and they can anticipate and seize new business opportunities.
For this to happen, however, the left hand has to know what the right hand is doing as far as IT systems go. Both of them have to communicate in the same language. Historically, companies have struggled with this because data and processes are encoded and identified in different ways across different applications. Moreover, those applications and business processes are often controlled by different business groups within the IT organization. Getting many disparate groups to commit to one standardized master data set can trigger some knotty political issues. When master data initiatives are extended up and down the supply chain, the issue becomes exponentially more complex.
This lack of consistency in master data has driven interest in master data management (MDM). The goal of MDM is to provide consistent, accurate, complete and timely master information across the ecosystem.
How important is the master data movement? To return to the retail example, the drawbacks of disharmonized data are many: trading partners cannot efficiently collaborate on promotion planning or item replenishment, and invoice reconciliation increases, creating write-offs and draining sales force productivity.
Ironically, although the need to solve the challenge is urgent, the problem itself is not new. After all, companies have been trying to do this in one form or another since the inception of computing. From cleansing the data that flows into data warehouses to efforts such as enterprise application integration, companies have long sought to achieve the benefits of synchronized master data.
The question is, how can companies implement MDM that actually solves the problem rather than creating yet another siloed solution? While doing so, how can organizations get the biggest bang for their buck? Experience dictates that for MDM to work, it cannot be an IT-only initiative. Successful MDM projects must include complete participation from the business side with attention to tangible business benefits.
The first need for MDM stems from the requirement of synchronizing business processes across the organization. One common corporate goal is to build a single view of corporate data, which would allow business leaders to truly maximize the value of information assets. In order to succeed, however, the wide range of systems, processes and people across the corporation need reliable and timely access to accurate master data, the lack of which causes breakdowns in business processes and disconnected business decisions.
Another driver lies with the service-oriented architecture (SOA) and business process management (BPM) initiatives that are being widely adopted by IT organizations to rapidly deploy new value-added services to support business goals. Much of the hype and attention in SOA deployments has gone into Web service creation and deployment and management standards and technologies. However, if data is inconsistent across applications, it is difficult, if not prohibitive, to build composite applications or execute business processes that cut across multiple systems and departments. For example, a composite application in a large multichannel financial service institution that calculates a customer's net value and service levels will only work if that customer is described in a consistent manner across retail banking, brokerage, mortgage and credit card systems. MDM practically becomes a prerequisite for SOA initiatives in organizations.
Many new business initiatives raise the stakes further. Organizations continually strive to gain competitive advantage by becoming more responsive and more real time. With many of these initiatives lacking the proper foundation of accurate master data, they risk moving bad data faster and creating more chaos. For example, retail and manufacturing firms are striving to meet mandates associated with collaborative planning, forecasting and replenishment, global data synchronization and radio frequency identification to enhance their operations. As data continues to be further embedded in business processes and transactions, access to accurate information becomes an imperative.
Finally, the ever-increasing array of global, federal and local regulations that govern how companies manage their information assets only magnifies the need to create and use clean, consistent data.
With such far-reaching bottom-line consequences, MDM will not succeed as a purely IT initiative, as the term MDM might imply. Such a bias carries over to many MDM vendors as well. Their solutions rely on IT departments to cleanse and aggregate data - a practice that is often sporadic and dependent on budgetary whim. Such a strategy also ignores an important fact: information is a constantly evolving organism. Any data cleansing or data integration exercise is soon obsolete because new data is constantly being introduced and existing data is being modified. MDM is not just a data problem; it is a process problem, requiring the right technology, processes, governance and discipline.
Lack of communication between IT and the business makes it hard to connect the dots between data integrity symptoms and the root problem. The business may complain that the IT billing system is faulty based on the number of complaints fielded by the customer service department. The real culprit might not be the billing system, but instead the data inconsistencies that exist between billing and order fulfillment. If CIOs want MDM to succeed, the initiative needs to be a joint effort between IT and the business users who work with the data every day - and eventually "live and die" by it. The users need to work closely with IT in diagnosing and addressing the master data challenges.
Managing information works best when it is built into "natural" everyday business activities and results as a consequence of those activities. To do this, it's vital that the business stakeholders of the data take the responsibility of managing it. For example, a person in the logistics department is most concerned with product dimension data. IT should give that person the tools to help him do his job better by maintaining that dimension information accurately and sharing it with other stakeholders.
To keep business users involved, companies must find ways to make MDM technology more about business than technology. CIOs must look for MDM solutions that adapt to the way the business works rather than asking the business to adapt to how the software is built. Having been burned by rigid ERP systems that dictate their own proprietary business processes, such as how to add a new vendor, regardless of how your company conducts business, business users are not interested in changing to fit technology. Moreover, when the business needs to change a process or introduce a new service, the last thing they want to hear is that it is not possible or will take six months of development - by which time any market window of opportunity would have closed. Process change management that requires IT intervention through custom development and coding usually leads to short-lived solutions that can quickly frustrate business users.
MDM solutions must reflect and automate the inherent business processes of data management, be easy to modify and use for a nontechnical person, and be easy to train people on. Finally, MDM solutions must be able to provide data views that fit individual needs. For example, the way a banker looks at client data is different than how a trader looks at the same data - which, in turn, differs from the data needs of a financial analyst. In order to make business users productive and happy, MDM technology must provide interfaces that cater to their specific functional needs.
Business users must be made equal partners in any MDM initiative. The value of an MDM solution is not in the initial cleansing and integration, but in the enforcement of ongoing information governance and management - introducing, updating and synchronizing information. This requires change on the part of users, and change is usually met with resistance. Thus, for this type of transformation to be successful, it must have the support and enthusiastic embrace of its biggest stakeholders - the natural users of the data. Only then can MDM become a part of the organization's DNA rather than yet another enterprise application that struggles for adoption.
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