BOSTON -- Not everyone has bought into the concept of customer data integration (CDI) tools -- and that played out during the keynote speech at a CDI event here Tuesday.
The idea that CDI is just a new name for old practices is similar to the thinking when customer relationship management (CRM) first emerged, expert Jill Dyche told about 50 attendees during her keynote speech at the Customer Data Integration - Americas Summit.
CDI is legitimately a brand-new approach, said Dyche, partner and co-founder of Baseline Consulting Inc. and co-author, with Evan Levy, of Customer Data Integration: Reaching a Single Version of the Truth (Wiley 2006). Until a few years ago, there were no technology tools and best practices to reconcile, standardize and cleanse customer data in real time. And, despite common misconceptions, CDI can't be done effectively with a CRM system or a data warehouse, she said. CRM systems weren't designed to deploy integrated data, and data warehouse systems weren't designed for operational data integration. That's when one audience member politely interrupted and disagreed.
Why can't data warehouses do CDI?
A data warehouse can accomplish many of the things that new CDI technology can, the attendee said (her employer's policies prevented her from sharing her name). It integrates data and could be that single version of the truth that companies seek with CDI.
Yes, a data warehouse has some similar integration functionality, but it can't deliver CDI in near real time, Dyche countered. Real-time integration, cleansing and synchronization are critical for CDI to support daily operations. The contents of a data warehouse are latent and designed to be used for business intelligence (BI) and analytics.
"Data warehouses have a different purpose … companies should let them do what they're good at, which is BI and analytics," Dyche said. "Data warehouses are only as good as the ETL [extract, transform and load] processes feeding them."
Dyche illustrated her point with an example she heard at one particular company. Although this company could run sophisticated analytics on its data warehouse to predict when a customer might churn, she said, it couldn't tell who had last talked to that customer. That's where CDI could help.
Dyche wrapped up her keynote with recommendations and best practices for companies implementing CDI:
- Implement data governance programs, which define the process and policies around data management.
- Identify business problems that require common shared data -- that's the "low-hanging fruit" when it comes to finding quick wins and ROI for a CDI project.
- Inventory business projects, understand corporate goals, and map CDI projects to key strategic initiatives.
- Establish a data vocabulary through governance programs, so the company has a common language for discussing CDI projects and other data management initiatives.
CDI in action
The first day of the conference continued with user case studies that embodied many of Dyche's recommendations. Presenters from companies such as Intuit, Amgen, Prudential, Intrawest and Royal Bank of Canada discussed how CDI helped them better understand customers and increase revenue through cross-selling, up-selling and targeted marketing.
This demonstrates that CDI is a tool to solve business problems, not infrastructure problems, according to conference chairman Bob Hagenau, vice president of product and business development for Redwood City, Calif.-based Purisma Inc. Rather than laying a foundation for yet-to-be-defined future projects, companies across industries are successfully using CDI to solve specific problems and attain competitive advantages.
"In five to 10 years," Hagenau said, "the winners will be the ones that have solved the CDI problem."
This article originally appeared on SearchDataManagement.com