Eight must-ask questions for CDI projects

Consultant and author Jill Dyche recommends that companies considering planning or implementing customer data integration systems ask -- and answer -- this list of questions.

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Expert Jill Dyche helped us compile this list of must-ask questions for customer data integration (CDI) projects. The answers can assist companies in determining a viable CDI strategy -- or deciding whether CDI is the right technology to use at all.

Jill Dyche, Partner and co-founder of Baseline Consulting Inc.
Dyche is a partner and co-founder of Baseline Consulting Inc., a business analytics and data integration services firm. She is the best-selling author of The CRM Handbook (Addison Wesley, 2002) and is currently working on a new book called, Customer Data Integration: Reaching a Single Version of the Truth , with co-author Evan Levy, to be published by Wiley in the summer of 2006.

Dyche advises CDI implementation teams to discuss each of these critical questions before evaluating vendors, assigning resources or requesting funding for a CDI project. It could mean the difference between CDI success -- or failure.

What is the "need, pain or problem" that we're trying to solve?

This question pinpoints whether CDI is really the right solution. You need to understand whether this is a hammer looking for a nail or whether there's a bona fide integration need that lends itself to CDI.

For example, if the problem is simply integrating data onto one platform, modifying an existing data warehouse might be a better solution. It's important to keep an open mind, even if someone at the company is convinced that CDI is the answer.

What are our requirements -- both from a business and functional perspective?

Even though CDI is inherently very processing-oriented, when it comes to business requirements, it's important to dig into how various departments will use the reconciled customer information. Also look at drivers like cross-selling, merger and acquisition strategies, or regulatory compliance. Each of these can either be huge, hairy issues, or non-issues, depending on the company.

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If business requirements are gathered correctly and in a structured way, they should be able to inform downstream policies like scalability, performance and reliability. CDI is really much more an OLTP [online transaction processing] system than a database, so it's got its own set of processing challenges that should be understood up front.

Understanding the performance requirements will also be key in determining which "style" of CDI to use, registry (where the data linkages to source systems are kept and maintained); persistent (where the data is physically stored and maintained on a central hub); or hybrid -- a combination of those two approaches.

What data sources have critical customer information in them?

The key with CDI is that it gets little pieces of different data from everywhere. CRM systems are the low-hanging fruit, but there are definitely other systems that probably contain some really important information about customers that shouldn't be overlooked.

For example, financial systems often hold critical customer information. Companies should complete a comprehensive review of systems to ensure that all potential customer data sources are taken into account during CDI project planning.

What's the current system of record for customer data?

Warning! This question might be hazardous to your career!

The answers from various departments and data owners may uncover internal disagreement about which system holds the "correct" customer information. It's an important question to ask early on, because it can help companies uncover data problems, establish consensus on business rules and data quality metrics, and understand which departments and systems need to be part of the CDI discussion.

Who are the current de facto data owners in the company?

This is also a "loaded question" since usually people on both the business and IT sides claim to "own" the data. It's important to involve stakeholders in customer data in creating the business case for CDI. CDI projects can be fraught with politics -- especially if all of the data owners aren't included in the decision to implement CDI. It's also important that these data owners understand the implications of a CDI project and how their roles might change. We're seeing CDI adoption drive more formalized data stewardship roles.

The good news is the bad news: CDI can drive so many efficiencies that often core responsibilities go away. For instance, developers who were in charge of manual integration processes might be freed up to spend more time on application development and deployment.

What are the ideal matching algorithms for our particular data?

There's a whole litany of algorithms for matching data. Fuzzy matching, deterministic matching, probabilistic matching … it's really a complex aspect of CDI. But the vendors all have their own stories, and the more you understand your requirements, the smarter your vendor conversations are likely to be.

What is the potential impact on existing technology architecture and systems?

It's not just enough to say "yeah, we need CDI; let's start talking to vendors." It's also about what happens to existing systems and the impact to the existing technology infrastructure of adding this new hub. Because it usually relies on a Service Oriented Architecture framework, CDI can potentially touch dozens of systems within the company.

This can mean departments modifying or sun setting existing systems, or even new ways of getting data into a data warehouse or data mart. Questions about technology impacts might not be easy to answer -- but they are extremely important.

How (and when) will data stewardship be addressed?

The question, "who owns this data?", comes up on many different IT projects but the answer is mandatory when talking about CDI. Data stewardship is an important function here -- a good data steward is responsible for knowing the definition, lineage, business rules and usage of the master data he or she manages. They are the authority on what the data means and how it should be processed. For customer master data, this isn't a trivial job, so it should have accountability and performance measures attached.

CDI technologies can often be straightforward to implement. Nevertheless they can drive significant cultural, organizational and technological changes. So a company understanding its CDI readiness is arguably not a luxury -- it's a mandate.

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