MDM The Cornerstone of Customer Centricity

Transcription

1 MDM The Cornerstone of Customer Centricity It is no secret that outstanding customer strategies produce positive business outcomes resulting in strong loyalty and higher revenues. However, the art of achieving a high degree of customer centricity within an organization has been a challenge in all aspects organizational, processes and systems. Organizations have long strived to capture data from multiple systems (ERP, CRM, Legacy, Web, Selling, Service Tools, etc.) and churn data into another set of systems (Data Warehouses and Data Marts) to gain a 360-degree view of customers and, maybe, even predict their behavior. This paper outlines the key drivers and presents a case for organizations to consider MDM in their solution stack to attain the elusive 360-degree customer view on their journey toward customer centricity.

2 Customer 360-degree View A Problem As customers across businesses become more demanding, any organization must understand their requirements and predict their purchase behavior to ensure customer delight and grow profits. Presenting customers with a clear and uniform message and a consistent and positive experience across product lines are integral to promoting customer satisfaction and loyalty. Initiatives promising the all-important 360-degree view of the customer, thus ensuring consistency in experience, have spanned numerous system implementations, typically the Customer Relationship Management (CRM) and Business Warehouse projects. However, very few of the implementations have truly been successful in delivering the desired holistic view. Some of the typical challenges that these initiatives face in delivering a unified view of the customer are: 1. Incomplete customer information owing to lack of data This includes the missing data attributes along with the lack of relationships and hierarchies (Household, Family, etc.) 2. Incorrect customer information due to multiple systems capturing the same information differently 3. Multiple customer records since multiple systems duplicate records resulting in more than one record 4. Inability to capture and display historical interactions appropriately owing to a lack of one consolidated record Incomplete Customer Information Incorrect Customer Information Challenges for 360-Degree Customer View Multiple Customer Records Inability to Display Historical Interactions Figure 1: 360-degree View Issues Most organizations have already implemented CRM and Enterprise Resource Planning (ERP) systems in some form or shape either standard commercial off-the-shelf (COTS) packages or custom applications. While some organizations have implemented more than one CRM system, numerous large-scale organizations have multiple, nonintegrated CRM and ERP systems creating a brilliant strategy when it comes to local execution. However, these numerous systems lead to systemic gaps across the organization on a global level which, in turn, leads to global inefficiencies and gaps for global strategic execution. Disparate systems cause significant problems as organizations strive to integrate their IT set-up to attain the Holy Grail of customer-centricity a single view of the customer. As customer data passes through the complex enterprise, it may get locked up, duplicated, or worse, misrepresented and misinterpreted, obscuring the facts and compromising information. The increasing demand for cleaner, complete and current customer data coupled with regulatory compliances has all heightened awareness of the risks of using poor quality and stale customer data. 2 Infosys

3 How Can MDM Help? MDM is a deliberate initiative comprising of a set of methodologies, strategies, disciplines, and technologies that enable organizations to acquire, cleanse, enrich, consolidate, federate, and govern data across many disparate systems. As a customer-centric business initiative, it offers a compelling business case for improving customer data quality by delivering access to a single reference that represents the Golden Record or Best Version of Truth (BVT) for a customer which can be achieved with an efficient Master Data Management (MDM) system. MDM offers a central repository to manage businesscritical customer data on an ongoing basis. It ensures synchronization with Business Intelligence and operational systems by integrating customer data in real time and empowering data stewards with capabilities to accurately govern customer data across the enterprise. The single reference helps the business gain critical organization-wide insight and helps users improve efficiencies, reduce costs, and enhance decision-making. Some of the key benefits that organizations can gain by using MDM include: Enhanced Analytics New Opportunities Data issue Figure 2: Key Benefits of MDM 1. Identifying and resolving key customer data issues and optimizing the manual effort required to manage and use customer data across the enterprise 2. Identifying new opportunities to interact with customers and recognize new customer segments 3. Enhancing business intelligence, reporting and analytic capabilities Customer Centricity and MDM With organizations across industry verticals making significant investments in achieving customer centricity, it is necessary to recognize how MDM solutions can benefit organizations and help manage customer data effectively. In an era where data is mastered in multiple systems, it is imperative to recognize the boundaries of each type of application. MDM as a philosophy can help realize the goal of customer centricity with these multiple systems. MDM is a developing philosophy backed with various tools to achieve the BVT concept. MDM tools are more commonly integrated with Data Cleansing tools for standardization and noise filtration in order to minimize data quality issues being faced by the users. MDM tools either have in-built address standardization tools or have adapters to integrate with various other address standardization tools. The next section covers our view point on what kind of MDM architecture and solution can achieve better customer centricity given the multiple applications in an organization s IT ecosystem. Infosys 3

4 MDM Architecture The type of MDM architecture to be applied in an implementation depends on the objective of the organization s MDM initiative. The key solution components for an MDM architecture are: 1. User Interfacing Application These can be the CRM applications, customer-facing web applications, etc. 2. Data Consuming/Managing Application ERP applications 3. Data Providers: Experian, D&B, etc. 4. MDM HUB Authoritative source of information 5. Data Cleansing Tools For data cleansing and standardization 6. Address Cleansing Tools For address standardization 7. Integration Layer To ripple out the effect of data creation/manipulation to other systems in real time or near-real time The types of MDM architecture are: Co-existence Style Architecture: Most organizations want the BVT to be calculated correctly from various sources for their master data customers, partners, suppliers, etc. They input all the data into the MDM and run through the MDM engine, applying the appropriate level of trust, data cleansing and standardization, address standardization, and consolidating the duplicate records achieving the co-existence style of architecture. Data standardization and cleansing happens after the data has already persisted in the source systems. Transaction Style Architecture: This is the typical Search-Before-Create architecture. The user interface needs to have a link into the MDM system to search for the data record being created. In case duplicate or near-duplicate records are entered, it warns users using the Data Cleansing Tools upfront. This facilitates users to make effective decisions, thus helping them manage their data more effectively. This requires an MDM system and Data Cleansing and Standardization tools to be available 24/7 and makes the MDM systems, along with their Data Quality and Data Cleansing tools, critical to the operational processes of Web and CRM either selling or service. This style of architecture is often referred to as the Transaction Style of architecture for MDM where the HUB becomes the source of authoritative information for the organization. In a typical organization, systems are used by multiple business groups and data operations are performed by people across these multiple business groups. These users view data pertaining to their department(s) as primary and other data inputs as optional and nice-to-have. Thus, they often lack perspective on the importance of their data operations for downstream systems and the impact it creates for organization as a whole. The key to achieving a robust and strategic data strategy is to limit the data operation mistakes (user errors or otherwise) at the source. It is imperative to operationalize the philosophy of robust search-before-create data in all front-end systems. Of course, there needs to be a cost-benefit analysis of doing it. The data governance organization also needs to be empowered with executive support in order to meet the objective of Right-First-Time (RFT) for data management operations. 4 Infosys

5 Customer World Wide Web or other Customer Facing App Data Cleanse & Standardization Enterprise Application CRM MDM HUB Address Standardization 3 rd Party Data Providers (D&B, Experian etc.) Figure 3: Co-existence Architecture Customer Enterprise Application World Wide Web or other Customer Facing App Integration Layer CRM Data Cleanse & Standardization Address Standardization 3 rd Party Data Providers (D&B, Experian etc.) Data Operations MDM HUB Sales Figure 4: Transactional Architecture Infosys 5

6 Key Benefits Some of the key benefits of a customer domain MDM system with respect to customer centricity are: Sales & Marketing Identification of creative products and services Identification of new customer segments Cross-Sell of products and services Data analysis of Customers and identification of new trends Compliance Do-Not-Track Initative Reduce Legal cost Increase customer satisfaction Operations Preference Management Extended Customer View Support Process Improvement Data Governance Initatives Figure 5: Key benefits of a customer domain MDM Sales and Marketing In a customer-centric business, customer insight, along with relevant customer segmentation in accordance with the organization s products and services, becomes the basis for all decisions. In order to attain this customer insight, it is imperative to have a single view of the customer and her preferences and attitudes as they relate to the organization s products and services. This has a direct correlation to cross-selling and up-selling opportunities. The analysis of the Golden Record of customers and their attributes from various sources can open untapped opportunities for organizations. These opportunities can arise from any of the following: 1. Identification of creative products and services 2. Identification of new customer segments Family/Household/Friends, etc. 3. Cross-sell of products and services 4. Suggestive selling of products and services 5. Data analysis of customers and identification of new trends Compliance In this age of online data collection of customers via web portals, walk-ins and other means, Do-Not-Track initiatives become very important from a legal and compliance perspective. As the same data moves from one system to another within the organization, the interpretation of the data can change. This often can lead to compliance issues with Do-Not-Track initiatives (such as Do-Not-Call, Do-Not- , etc.). Maintenance of master data for the Do-Not-Track initiative within the Customer Golden Repository helps reduce compliance slips for the organization with regards their end-customers. This also helps lower compliance costs for the organization 6 Infosys

7 Operations MDM can help in the day-to-day operations of an organization in various ways, such as: Preferences: In today s competitive market, the customer channel must be personalized to ensure that the target customer segment enjoys a distinctive experience. MDM can be used as a master repository to maintain and disseminate the personalization preference(s) of customers. In instances where there are multiple CRM applications within the organization, the case for maintenance of preferences of the customer, against their Golden Record in the HUB, is stronger. Extended Customer View: The HUB can be used to provide an extended customer view along with the 360-degree view, enabling the organization to view previously untapped customer relationships such as family, friends, household, employee, etc. Data Governance: The MDM HUB is a central component in strengthening the organization s data governance practices. It empowers the data champions within the organization with best-of-breed tools and helps improve data quality across the organization. Support Processes: Accessing correct and complete customer data along with their associated transactions is of vital importance in resolving support incidents. This enables quicker turnaround of issues for customers and helps achieve customer delight during the process. The identification of the hierarchies of customer data (Household, Family, Friends, etc.) can help in crosssell and up-sell during customer service calls as well making support calls an alternate revenue stream for the organization. Conclusion Organizations need to take a holistic customer data management perspective. The right MDM model can help the business across a range of activities from reporting, cross-selling and up-selling to decision-making and compliance. The chances of an MDM initiative enabling customer centricity increase significantly if organizations: 1. Consider MDM as an integral part of their customer management program along with their CRM initiative 2. Focus on MDM impacts across the landscape (ERP/CRM/Web, etc.) sales or service related 3. Focus on cleaner data flow throughout the organization starting at the source systems 4. Ensure governance to educate data custodians of the impact of their data operations across the organization 5. Provide an organizational structure to address governance issues at regular intervals Infosys 7

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