top 5 critical mistakes to avoid when creating a 360 view

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WHITEPAPER AUGUST 2014 www.hcltech.com big data & business analytics top 5 critical mistakes to avoid when creating a 360 view of customer AuthOr: john wills global director, center of excellence hcl business analytics services

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Page 1: top 5 critical mistakes to avoid when creating a 360 view

WHITEPAPER AUGUST 2014

www.hcltech.com

big data & business analytics

top 5 critical mistakes to avoid when creating a 360 view of customer

AuthOr:

john willsglobal director, center of excellence

hcl business analytics services

Page 2: top 5 critical mistakes to avoid when creating a 360 view

5 CRITICAL MISTAKES TO AVOID WHEN CREATING A 360 VIEW OF CUSTOMER | AUGUST 2014

© 2014, HCL TECHNOLOGIES. REPRODUCTION PROHIBITED. THIS DOCUMENT IS PROTECTED UNDER COPYRIGHT BY THE AUTHOR, ALL RIGHTS RESERVED. 2

Building and maintaining a single view of customer is one of the most challenging tasks for any Information Technology (IT) organization. Over time it has gone by many different names - master file, customer information file (CIF), customer dimension, and most recently master or ‘golden’ record. We at HCL, have learned a lot of hard fought lessons that we are passing along to help you significantly increase your odds of success.

Mistake #1 – Building a custom solution

The heart of a 360-customer view is a process that requires comparing records from multiple data sources and determining if they are the same entity (person, household, business). How hard could that be? Simply write a few rules to compare records and problem is solved, right? Wrong. Comparing or matching records is a science. More specifically, it is the application of statistics and probability to the nuance of variations in data quality and data structure. Just take a minute and think about how many variations of customer records you have in different systems. For example, different field names, transposed data, missing data and even language based name variations. Almost everyone underestimates the true degree of variation in their data and think ‘we have got this’. However, in our experience, 10 out of 10 times they don’t and within two years the sponsor is back to looking for a real, sustainable solution. The good news, proven, sustainable solutions are available and it can be done right the first time. The key element is to use Master Data Management (MDM) products that contain a tunable matching engine. These engines use statistics that takes into account the vast array of variability and the results are extremely accurate and better than the results you could get from a human comparing records. Mainstays in the industry including Oracle, IBM, Informatica, SAS, Tibco and others, offer this solution. They have invested millions of R&D dollars to solve this very difficult problem.

Mistake #2 – Starting with system of record instead of system of reference

For those not steeped in the world of single view and MDM, this will require some context setting. When deciding to create a single view of the customer you have to decide early on if the MDM database will serve as the system of reference or system of records. There is a significant difference in the investment required with taking one path over the other. When a MDM database is declared as the system of record, you must by definition, re-engineer all the systems that use it and replace the portion of the application that relies on customer data. Can you imagine negotiating with all system owners, planning and phasing the re-engineering of all systems? There are huge technical, political, budgetary and organizational change implications. Now you know why you have heard about single view projects that have gone on for years only to fail. System of reference is another story. In this case, the MDM database is linked to other systems in a publish and subscribe relationship. Systems publish changes to their version of a customer record and subscribe to what the MDM database sends back as the single view. The two are only loosely coupled. This does not require existing systems to be re-engineered and systems owners can chose when and how to participate over time. One other positive nuance is that systems can send the MDM database whatever record structure they use and can request back clean data in their own format or in the format of a golden record, which is a composite of fields contributed by all the other systems. This type of implementation can be quick and

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5 CRITICAL MISTAKES TO AVOID WHEN CREATING A 360 VIEW OF CUSTOMER | AUGUST 2014

© 2014, HCL TECHNOLOGIES. REPRODUCTION PROHIBITED. THIS DOCUMENT IS PROTECTED UNDER COPYRIGHT BY THE AUTHOR, ALL RIGHTS RESERVED. 3

allows you to chalk up incremental success over time. You also have the opportunity to migrate from a system of reference to system of record approach over time. So, why would everyone start with a system of reference? The only logical answer is because they are probably unaware of anything better.

One final note, MDM tool vendors use specialized terms for system of reference and record. Generally, ‘registry style’ is equivalent to system of reference, and ‘consolidation’ and ‘transactional style’ are equivalent to system of record. If that is too confusing just bring it back to system of reference and system of records.

Mistake #3 – Forcing your data warehouse to be the single view

The objective is to have an enterprise wide single view that can serve all applications including transactional and analytic systems. Some people lose sight of this goal because the data warehouse already has a customer dimension so; they think it is a natural extension. There are several problems arising out of this assumption. First, data warehouses are designed for a specific type of analysis and reporting while a MDM system functions more like a transactional system. Forcing these two architectural approaches together results in an inferior design for both and a very difficult environment to maintain. Second, data warehouses have very specific rules and patterns for updating data that are different from the usage pattern of an MDM database. Essentially, the MDM system needs to operate as a transactional database to service the enterprise while a data warehouse is designed for analysis that includes aggregations and multi-dimensional joins.

Sometimes people are tricked when their first use case for single view is marketing. You can force a data warehouse to do it, but problems start when other organizations require integration with their transactional systems. In almost all the cases, the only solution is to start over again.

The bottom line is that the MDM database is at the heart of a single view implementation and must be implemented as an independent system.

Mistake #4 – Becoming enamored with multi-domain

MDM tools can create and manage a single view of several domains including customer, product, vendor, and household. When more than one is managed, it is called a multi-domain implementation. Vendors talk about multi-domain as the Holy Grail because they can relate domains to one another; for example products a customer uses and the products supplied by a certain vendor. The problem with using relationships between domains in MDM is that, these relationships are also stored and managed in the transactional systems and the data warehouse. If you start trying to master the relationships, you have a very large and unmanageable synchronization process that is unnecessary. Make your life easier and de-risk your project by simply using MDM to manage domains independent of one another and let the data warehouse and transactional systems manage the required relationships.

Page 4: top 5 critical mistakes to avoid when creating a 360 view

5 CRITICAL MISTAKES TO AVOID WHEN CREATING A 360 VIEW OF CUSTOMER | AUGUST 2014

© 2014, HCL TECHNOLOGIES. REPRODUCTION PROHIBITED. THIS DOCUMENT IS PROTECTED UNDER COPYRIGHT BY THE AUTHOR, ALL RIGHTS RESERVED. 4

Mistake #5 – Not designing an independent customer profile/preference application

Customer profile and preference attributes such as favorite color, restaurant, pillow choice, etc., appear to be trickier to manage than one might imagine. We have seen people trying to bolt them into the data warehouse, MDM database and all kinds of operational applications. The problem is that they do not work well in any of these places. It requires a dedicated application and database design so that the attributes can be passed to any requesting system. When an application makes a request, it can simply use the same single view master ID that it received from the MDM system. This creates a modular, flexible and scalable architecture.

HCL Single Customer View Solution

HCL’s Business Analytics Services organization provides a single view of customer solution called Customer 360 that combines a big data-based customer master data repository that is tightly integrated with social data and predictive analytics to drive improved customer satisfaction, marketing campaigns and cross-sell/up-sell.

It includes pre-integrated MDM capabilities from Informatica, IBM and MongoDB, the leading big data database. It can be deployed in a fraction of the time it took for traditional MDM implementations by using a registry MDM style approach that can also be easily extended to multiple use cases including data quality, data stewardship, segmentation analytics, ‘next product’ prediction, sentiment analysis, and text analytics.

For more information, please contact HCL at [email protected].

HCL EXECUTIVE BIOGRAPHY

HCL

John Wills leads HCL’s global Center of Excellence Business Analytic Services with responsibilities for solution development, labs, intellectual property and knowledge management.

Wills has 24 years of business intelligence experience in a number of diverse leadership roles including responsibility for consulting, sales, marketing and product development.

JOHN WILLSGlobal Director, Center of Excellence

HCL Business Analytics Services

Page 5: top 5 critical mistakes to avoid when creating a 360 view

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ABOUT HCL

About HCL Technologies

HCL Technologies is a leading global IT services company working with clients in the areas that impact and redefine the core of their businesses. Since its emergence on the global landscape, and after its IPO in 1999, HCL has focused on ‘transformational outsourcing’, underlined by innovation and value creation, offering an integrated portfolio of services including software-led IT solutions, remote infrastructure management, engineering and R&D services and business services. HCL leverages its extensive global offshore infrastructure and network of offices in 31 countries to provide holistic, multi-service delivery in key industry verticals including Financial Services, Manufacturing, Consumer Services, Public Services and Healthcare & Life Sciences. HCL takes pride in its philosophy of ‘Employees First, Customers Second’ which empowers its 91,691 transformers to create real value for customers. HCL Technologies, along with its subsidiaries, had consolidated revenues of US$ 5.4 billion, for the Financial Year ended as on 30th June 2014. For more information, please visit www.hcltech.com

About HCL Enterprise

HCL is a $6.5 billion leading global technology and IT enterprise comprising two companies listed in India – HCL Technologies and HCL Infosystems. Founded in 1976, HCL is one of India’s original IT garage start-ups. A pioneer of modern computing, HCL is a global transformational enterprise today. Its range of offerings includes product engineering, custom & package applications, BPO, IT infrastructure services, IT hardware, systems integration, and distribution of information and communications technology (ICT) products across a wide range of focused industry verticals. The HCL team consists of over 95,000 professionals of diverse nationalities, who operate from 31 countries including over 505 points of presence in India. HCL has partnerships with several leading global 1000 firms, including leading IT and technology firms. For more information, please visit www.hcl.com