Factors like the rising popularity of social media, cloud computing and "big data" management will each have a...
significant -- if not immediately obvious -- impact on organizations' master data management (MDM) programs, according to Stamford, Conn.-based IT research firm Gartner Inc.
Speaking at the Gartner MDM Summit last week in Los Angeles, Gartner research vice presidents Andrew White and John Radcliffe gave their take on the connections between MDM and big data, social media and cloud computing. They also discussed the biggest challenges facing MDM practitioners today and had several pieces of advice for companies that want to improve their overall MDM strategy.
What is MDM?
Gartner Research Inc. defines master data management (MDM) as a technology-enabled discipline in which the business and IT sides of an enterprise work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of shared master data sets. Gartner reports that the top drivers behind MDM investment include a desire among organizations for more accurate reporting and analytics, increased operational efficiency and improved customer service.
"We think MDM is a central point for information management and right now there are three forces that we see converging on information management," White told the conference attendees. "You guys are in exactly the right spot in exactly the right time to both make a difference to your company and to add significant value."
Gartner connects dots between MDM and major industry trends
A growing number of companies are using technologies like the open source Apache Hadoop distributed file system along with traditional relational databases and data warehouses to derive valuable business insights from so-called big data sets, according to the analysts.
Big data, which comes in many forms, might include Web logs, location-based global positioning system information and machine-generated sensor data. Big data is often described as being unstructured or semi-structured. Organizations typically use Hadoop to distill big data sets down to smaller data sets that can then be fed into relational databases or data warehouses for further analysis. Big data management, Radcliffe said, is all about creating structure out of the unstructured.
Radcliffe said organizations' MDM programs will ultimately serve to help "govern the relationships" between the internal data that organizations have been collecting and nurturing over the years -- like customer, product and supplier master profiles -- and the big data that is flowing in from external sources.
Big data also comes in the form of social network data. According to Radcliffe, an increasing number of organizations are looking to social networks like Facebook and Twitter to learn more about their customers and how they feel about particular products, brands or services.
It's impossible to use MDM tools and techniques to govern the external creation and dissemination of social network data. But one thing organizations can do, Radcliffe said, is link internal customer master files to external social network profiles in an effort to learn more about those customers and how to woo them.
"MDM is not trying to govern the data that is in the [social networking] environment," Radcliffe explained. "It's more about identification and linking and bringing those two worlds together."
The connection between MDM and cloud computing is a little more direct. Radcliffe said a growing number of application vendors now offer -- or plan to offer -- some cloud-based MDM and data governance-related capabilities.
The analyst said many organizations are still concerned about security risks that could arise as a result of storing master data within a public cloud. He also predicted that organizations' internal MDM programs will eventually serve as a central point for managing information in hybrid environments that are made up of both cloud and on-premises applications.
"Cloud is coming for MDM," Radcliffe said. "But it's not there today."
Be specific when building a business case for MDM
Two of the biggest challenges facing MDM programs today are hardly new, according to Gartner. Organizations continue to face great difficulty when it comes to building the business case for MDM. Organizations face perhaps even greater difficulty in translating the business case for MDM into metrics, which can be used to gauge progress after the program is implemented.
The key to building a solid business case, and eventually arriving at actionable metrics, is showing data -- or master data -- as it relates to a business process or business goal, said Gartner MDM Summit attendee John Ferraioli, the senior vice president of enterprise data management at Utopia, Inc., a Mundelein, Ill.-based consulting firm.
For example, a business goal might be reducing the number of outstanding invoices that have not been paid by customers. One way to tie that goal into an MDM program is to look at the accuracy of the master data contained within the outstanding invoices.
"If you look at an invoice and it has the wrong tax ID or you ship the wrong product through supply chain inefficiencies, the customers are not going to pay that invoice in a timely manner," Ferraioli said.
The same principle holds true for inventory management. Ferraioli said many organizations will spend too much on inventory because they do not have their master data houses in order.
"Look at your inventory and tell me if you're buying the same functionally equivalent product called eight different things," he said. "Is it a ball bearing or is it a bearing ball?"
By getting the enterprise to agree on the correct terminology for specific products, Ferraioli said organizations can greatly reduce the costs associated with carrying inventory.
"You cannot achieve strategic sourcing and spend optimization if you don't have a complete view of the materials and your vendors," he said.
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Gartner's White ended the conference session by going over some actions that should be taken and some that should not be taken when embarking on an MDM program.
Some of the best MDM practices he mentioned include obtaining executive sponsorship, tying the benefits of MDM to real world business goals, getting buy-in and participation from business stakeholders, and focusing strongly on change management and data governance.
Things to avoid include a lack of shared vision and commitment and weak or disjointed metrics. Organizations should also start small, expand gradually and avoid trying to achieve enterprise- wide MDM all at once.
"Executive sponsorship is very important," White said. "We're not going to get very far with the amount of change we need in the business processes if we don't have executive support."