White Paper. What is Enterprise MDM and Why You Need It
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1 White Paper What is Enterprise MDM and Why You Need It Reduce risks associated with disparate management of information assets and unleash the unrealized potential of your data Darryl D Williams, PMP, CSM Head of Global MDM and Platform Solutions
2 Having a progressive enterprise information management (EIM) strategy in place is well accepted as a cornerstone of commercial viability and success in the digital age. That strategy can be focused or broad-based, depending on the organization s culture and the quality of its leadership. EIM strategy often incorporates some or all of the following capabilities: Collaboration and content management Data management and governance Information technology implementation, delivery, and support Technology infrastructure and software/digital enablement In the past, these strategies have had varying levels of coordination and integration within modern enterprises. In recent years, as they have become more integrated into operations, Master Data Management (MDM) has become a critical and foundational component of a company s overall commercial strategy. Simply Put MDM, simply put, is where the company s critical data lives. It is the connective tissue throughout the corporate body. In health care, that includes everything from patient data to provider data detailing the treatments, procedures, modalities, products, and processes which govern and describe interactions and outcomes. Effective MDM has become an essential component to EIM because few organizations can continue to tolerate the unrealized potential and incalculable risk associated with the disparate management of information assets. Even so, many organizations are unprepared or unwilling to display the discipline required to form and execute an effective MDM strategy. Fortunately MDM platforms have matured to the point where modern enterprises have choices on how to integrate MDM capabilities into their EIM framework. For instance, in today s corporate strategic plans, an organization would be wise to employ agile, IT-based solutions, particularly in areas such as customer MDM where the benefits and opportunities are so great. Effective MDM has become an essential component to EIM because few organizations can continue to tolerate the unrealized potential and incalculable risk associated with the disparate management of information assets. First, let s get grounded with MDM terms. So what is Master Data? There are many definitions, most of which make the concept as clear as mud. This paper will add yet another perspective, but also provide a basic explanation along with some basic recommendations. Clearing Up the Mud For starters, Master Data is common. That is to say, it occurs and appears multiple times and in multiple places throughout an organization s systems and processes. It includes people, places, and things. That s right, Master Data is about the nouns of business. For example, one might define the nouns of business as follows: 2
3 People and Groups: Customers/consumers, producers, providers, departments, and the relationships among them are all master data entities or sub-entities Places: Regions, geographies, locations, zones, and alignments all address where things exist or happen Things: Products, components, services, and assets are those items that an entity delivers or performs On their face, these data nouns appear straightforward. But these nouns appear in different shapes and sizes and are governed by local, regional and global categories. We call these structures. For example, places could be territories that include postal code. Territories can roll up to form districts, and the districts can expand into regions, and so on. These structures are typically viewed as hierarchies, and fit into the category of Master Data as well. TRUST & QUALITY Business Revelance data information master data reference data Frequency of Change Territories can roll up to form districts, and the districts can expand into regions, and so on. These structures are typically viewed as hierarchies, and fit into the category of Master Data as well. FIGURE 1: BUSINESS RELEVANCE The progressive evolution of critical enterprise information assets That s it, pretty simple so far, right? But next is a part of the Master Data definition that gets little airtime. Data exists and is constructed on a continuum. In the figure above, the progression of data from small defined units to larger, integrated package is depicted. For starters, data is atomic. That is to say, it is the smallest complete unit of definition. By itself, each unit has very little meaning. For example, 7, main, Joseph, and Ready for Pickup are all examples of data, yet independently none conveys any sense of information: 7, what? Joseph who? What is ready for pickup? However, when these atomic units are brought together within a structure, they begin to convey meaning. If the aforementioned atomic data elements are arranged in a table as described below, they begin to provide basic insight. Assume the subject area is orders. A table called Orders might take on the following structure with the associated data elements arranged in columns and rows: 3
4 Table Name: Orders Column Name Value Order Type Quantity 7 Customer First Name Order Status One can consider this instance of an order to be information on orders. There may be context missing that requires additional information to make this instance more meaningful. Note below how the additional attributes (columns) and additional instances (rows) that convey more meaning about orders. TABLE NAME ORDERS Column Name Order Type Quantity Customer First Customer Last Name Name Order Status Product Order Date Row 1 Main 7 Joseph Jarman Ready for Widget 1/1/2014 Row 2 Custom 6 Steve Perez On hold Tool 1/2/2014 Row 3 Custom 1 Jennifer Harris Ready for Widget 1/4/2014 Row 4 Main 4 Patrice Jones Ready for Widget 1/4/2014 Row 5 Custom 2 Joseph Jarman Picked-up Widget 1/5/2014 Row 6 Adjusted 5 William Smith Delivered Widget 1/6/2014 Main Joseph Ready for pick-up Master Data is imperfect. If it were highly accurate by nature, it would be reference data and so would be highly defined and available in the marketplace as a commodity. Even though additional data is needed to make this more meaningful (quantity of what? pick-up from where?), we are starting to assemble detailed information about the Orders subject area. Data Equals Knowledge We are aware that this information is knowledge. But if we dissect the information into components, we will find that we have a fact or event (an occurrence of something meaningful to us) and dimensions (the attributes that describe the fact). If we build out Row 1 or Orders, we could have the following fact: Joseph Jarman ordered 7 Widgets on Jan 1, 2014, that are ready for pickup. Joseph Jarman is a customer and Widget is a product. These descriptive components of the Order fact are dimensions that are common (occur and appear multiple times) and include people and a thing, two of the types of nouns of business, and thus fit in the category of two common types of Master Data: Customer and Product. Here are a couple of other pertinent things to be aware of in the realm of MDM: Master Data is imperfect. If it were highly accurate by nature, it would be reference data and so would be highly defined and available in the marketplace as a commodity. For those organizations which have a high tolerance for marginally accurate data, Master Data is treated as a commodity and for them is essentially reference data. 4
5 Master Data is imperfect. As a result, it assumes the 80/20 rule of reliability. We assume that 80 percent of an enterprise s Master Data is near reference data grade. The discipline of MDM focuses on improving the quality of the remaining 20 percent. The discipline is in using MDM to drive higher data quality in the 20 percent, all while informing and maintaining the integrity of the 80 percent of data we believe is high quality. Both sides feed each other in the quest for higher quality data. C Address Attributes ID Type Number Street Name City State Postal Code Phone Number C Identifier P Profile C Affiliation Attributes ID Type Number Effective Date Expiration Date Granting Authority Phone Number Attributes ID Type Name Prefix Suffix Date of Birth or Founding Credential Attributes ID Form Profile ID To Profile ID Type FIGURE 2: BASE PARENT AND CHILD OBJECTS IN A BASIC CUSTOMER MDM RELATIONAL MODEL Now on to the specific-customer MDM. In the health care industry, especially in the life sciences arena, we typically refer to the influencers and providers of healthcare services as customers, and the consumers of healthcare as patients. Both are included in the People and Groups category of the nouns of business and tend to share a similar structure to the descriptive information about them. In the example below, the parent object Profile could represent People and Groups (HCPs and HCOs) and the child objects require links back to the parent object (i.e. identifiers, addresses, and affiliations, in order to be relevant to the business, must be linked back to an HCP or HCO). The P in the upper left corner of the entity type descriptor represents a parent object and the C represents a child object. In other words, a child object is dependent on the existence of a parent object, but not vice versa. 5
6 Organizations Types Hospitals Group Practices Pharmacies Clinics Long Term Care Facilities Delivery Networks Group Purchasing Organizations Individuals Types Medical Doctors Registered Nurses Dentists Executives Office Staff patients Employees Affiliations Types By Employment By Influence on Decision-making By Ownership By Referral By Network By Plan Participation These are the core customer MDM entities in the life sciences market segment, but an agile MDM approach to information management can deftly and swiftly expand to broader healthcare vertical relevance. Figure 3: Relationships between entities in an industry, If we decompose the parent objects into entity types (Organizations and Individuals), the example below shows that an Affiliation could link: An Organization to an Individual An Organization to an Organization An Individual to an Individual business, or subject area These are the core customer MDM entities in the life sciences market segment, but an agile MDM approach to information management can deftly and swiftly expand to broader healthcare vertical relevance. For example, patients can be added to the Profile object and implemented leveraging the Individual entity type and patient advocacy groups could be implemented leveraging the Organization entity type. 6
7 Knowledge Equals Intelligence A well-structured MDM approach can quickly and easily incorporate these new entities, as well as others, if the core entities already are properly structured to provide the information-management platform. The impacts of these and other platform-enabled capabilities are improved business performance, business model flexibility, and reduced risk, the precepts upon which commercial MDM agility are based. So, now with a solid grounding on what MDM is in general, and customer MDM in particular, let s examine how your organization might benefit from agile MDM. Here are four key factors that could identify where the benefits might come from in your organization: 1. Quality: Remember the MDM 80/20 rule. If most of an organization s MDM governance and effort is around remediating 20 percent of the information volume, risk to the performance of the business can be mitigated by lessening the impact of resource utilization and poor decision making based on incomplete and inaccurate data. Do you really want to build a target list containing MDs that have been kicked out of the Medicare program for prescribing drugs for off-label use? History shows that these rollouts often have taken longer (sometimes 2 to 3 times longer) than preliminary estimates and predictions specified. 2. Timing: Traditional operational models have relied on information that is anywhere from 7 to 60 days old. How long will it take your organization to learn how to take action on information that is hours fresh and not weeks or months old? 3. Adaptability: Legacy channels and methods of face-to-face detailing products and services are being replaced by mobile and digital capabilities that are more conducive to the way in which health care influencers can consume and act on relevant information. How quickly can your organization model and implement new approaches to marketing and sales effectiveness? 4. Cost: Today s enterprise may be quite content with having a complete on-premises solution for operating and managing its MDM assets. But do you really want to be in the business of buying and maintaining data storage and application servers with all the backup, redundancy, failover, patching and upgrading that comes along with IT stewardship, especially when new IT commercial capabilities emerge in weeks instead of months and years? Another major and often overlooked cost consideration is the time required for MDM implementation. History shows that these rollouts often have taken longer (sometimes 2 to 3 times longer) than preliminary estimates and predictions specified. This is not necessarily the fault of the MDM developers, but rather due to unrealistic expectations set by buyers and suppliers alike, often with an overly simplistic view of the true scope of even the simplest MDM model. 7
8 Here are some considerations for assessing preparedness for agile MDM: Internal resources (Business, IT, Governance, and Quality to name a few) will play a large role in any MDM program; however, limit internal team resources to truly value-added activities; partner with your supplier to let go of the heavy lifting of EIM and embrace the true challenges and opportunities your business faces. Implement using smaller, iterative deployments of key functionality that enable the business to reap the benefits as early in the program as possible. What Now? It takes true MDM experts to understand the change management that is necessary to make even the smallest MDM implementation successful and sustainable. Whether or not your enterprise is ready for agile MDM, MDM is ready for you. It is a mature discipline that has gone through transformative change in the last two years. What it really comes down to is that MDM is a valuable business asset, but only when the insights that it enables are accessible, accurate, and actionable. For More Information Call or visit About Health Market Science Health Market Science (HMS), a LexisNexis company, helps businesses and government entities solve complex business challenges centered on health care provider information. Using our patented big data and analytics platform, current, as well as deep domain expertise, HMS develops agile solutions so our clients can improve compliance with federal, state and international regulations, reduce operational costs and maximize market opportunities in real time. Our data assets include a comprehensive provider database of health care practitioners (HCPs,) health care organizations (HCOs,) and their affiliations, as well as the largest medical claims warehouse in the industry. About LexisNexis Risk Solutions LexisNexis Risk Solutions ( is a leader in providing essential information that helps customers across industries and government predict, assess and manage risk. Combining cutting-edge technology, unique data and advanced analytics, Risk Solutions provides products and services that address evolving client needs in the risk sector while upholding the highest standards of security and privacy. LexisNexis Risk Solutions is part of Reed Elsevier, a leading global provider of professional information solutions across a number of sectors. Our health care solutions assist payers, providers and integrators with ensuring appropriate access to health care data and programs, enhancing disease management contact ratios, improving operational processes, and proactively combating fraud, waste and abuse across the continuum. Due to the nature of the origin of public record information, the public records and commercially available data sources used in reports may contain errors. Source data is sometimes reported or entered inaccurately, processed poorly or incorrectly, and is generally not free from defect. This product or service aggregates and reports data, as provided by the public records and commercially available data sources, and is not the source of the data, nor is it a comprehensive compilation of the data. Before relying on any data, it should be independently verified. LexisNexis and the Knowledge Burst logo are registered trademarks of Reed Elsevier Properties Inc., used under license. Other products and services may be trademarks or registered trademarks of their respective companies. Copyright 2015 LexisNexis. All rights reserved. NXR EN-US This document is for educational purposes only and does not guarantee the functionality or features of LexisNexis products identified. LexisNexis does not warrant this document is complete or error-free. If written by a third party, the opinions may not represent the opinions of LexisNexis.
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