News Stay informed about the latest enterprise technology news and product updates.

Seven reasons customer data integration projects fail

Customer data integration projects are susceptible to failure because they touch people, process and technology across an enterprise. Here are some common pitfalls to avoid.

SAN FRANCISCO -- Customer data integration (CDI) projects demand transformation of people, process and technology. Fail in just one area and the entire project is at risk. At the CDI-master data management (MDM) summit in San Francisco, attendees and presenters discussed the prime pitfalls and best practices of CDI projects.

1. Data model woes

Opinions vary about how to address the underlying data model issues of a CDI project, and this was a major point of discussion throughout the summit.

Large vendors are beholden to their applications … those data models were designed to support their applications. They can't offer flexibility around the data model
Anurag Wadehra,
vice president of marketing and product managementSiperian

Large vendors, like Oracle Corp., recommend using their pre-developed data models, saying that their customers have successfully used these models in hundreds of implementations and that these models can be easily customized to a company's needs. Best-of-breed vendor, Siperian Inc., countered that a predetermined data model, designed by an application vendor, can be a big reason for CDI failure.

Related information:

Visit our sister site:

Oakwood Worldwide strikes a perfect balance with data integration

Tip: Using IT practices and IT scenarios to understand SAP NetWeaver -- end-to-end process integration

SAP pros flock to SAP XI discussion

Is there hidden knowledge in 'dirty' data?

Building a business case for MDM

- Subscribe to's RSS Feed for news and tips on SAP. Add to Google

"Large vendors are beholden to their applications … those data models were designed to support their applications. They can't offer flexibility around the data model," said Anurag Wadehra, vice president of marketing and product management with San Mateo, Calif.-based Siperian. Another presenter, Bob Hagenau, co-founder and vice president at Redwood City, Calif.-based CDI vendor, Purisma, Inc., said he's heard stories of companies scrapping their entire CDI project because they couldn't agree on a corporate data model. Whatever tactic a company chooses, attendees and presenters at the summit agreed that companies should look carefully at various data model approaches and options.

2. Lack of enterprise-wide, executive support

Presenters at the summit frequently cited the need for all executives of an organization -- not just the CIO -- to be on board with a CDI project. Executive level buy-in drives cooperation with data owners, user adoption and is a fundamental requirement because of CDI's organization-wide impact. During a best practices presentation, Jeff Mendenhall, director of customer data management at Microsoft, said that they had CEO-level support for their multi-year CDI initiative currently underway.

Another company presenting their best practices, San Jose, Calif.-based BEA Systems Inc., said that enterprise-wide executive sponsorship was critical to their success. They are currently using Purisma's product in their second-generation CDI implementation.

"The CIO can be the sponsor, but all executives should be on board," said Yogish Pai, a chief architect with BEA.

3. Overarching architecture and technology issues

While opinions again vary on the right technical and architectural approach, it's clear that there is no "one size fits all" approach to CDI. A company's existing systems, potential longer-term changes and specific business requirements all play a part in determining the correct technological approach for a given project. Issues of CDI system architecture, performance and scalability are all very important to consider up front, and flexibility is critical, according to Siperian's Wadehra.

"You have to be able to fine-tune the architecture for your own project," Wadehra said. BEA's Pai agreed, saying that designing the right service oriented architecture was an important key to the company's CDI success.

4. No plan (or budget) for long-term maintenance and extensibility

Early adopters of CDI, many of whom built their own in-house systems, are now looking toward commercial products, said Aaron Zornes, chief research officer of the CDI Institute, during the summit's keynote address. They are finding out about the long-term costs and requirements of maintaining their custom systems, he said. CDI is not a one-shot deal. It's an ongoing project.

5. Lack of user adoption

Education and training have been very important to CDI success at BEA, Pai said. He considers this an extremely important part of their implementation and recommends that this be a primary part of a CDI plan, not an afterthought. Other companies at the summit recommended developing a corporate-wide marketing plan for a CDI project and associated data governance and data stewardship initiatives.

6. Not addressing data quality, governance and stewardship issues

"Garbage in, garbage out" was a common phrase used at the CDI-MDM summit when discussing the issue of data governance. CDI projects without an associated enterprise-wide focus on data stewardship and data governance will fail, many attendees said, because the source of the data problems might not be addressed. Worse yet, if users discover data problems in the context of a CDI implementation and start to distrust the data in the system, the whole CDI project can fail due to skepticism leading to lack of user adoption.

"Make sure data is reliable at the cell level," said Wadehra of Siperian.

7. Politics, pure and simple

Underlying many CDI-challenge discussions was the issue of corporate politics. During his best practices session, Mendenhall from Microsoft characterized their CDI initiative as "an inch deep and a mile wide." By definition, CDI projects can touch almost every department in an organization.

Whether it's the lack of enterprise-wide support, unrealistic timelines, inadequate budgets or data ownership issues, CDI project leaders must be social champions, as well as architectural experts. Data management can be a touchy issue, according to many attendees. Various divisions may feel that they own the data in their own systems and may be reticent to allow another system to access -- much less change -- what they consider to be their critical information. That's where executive level sponsorship, marketing, education and training can help significantly, said BEA's Pai.

Dig Deeper on SAP data management

Start the conversation

Send me notifications when other members comment.

Please create a username to comment.