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January 15, 2010

Customer Data Integration Among the Top Priorities for Companies

Filed under: Data Integration, Data Quality — Tags: , — Olga Belokurskaya @ 8:35 am

According to one of the latest researches by Aberdeen Group, issues with customer data may greatly affect organizations’ sales and marketing efforts. Besides, lack of trusted customer data and inability to target customers through customer data proved to be the top two of those issues, according to the respondents’ opinion.

This reveals the fact, that there’s still a lack of customer data integration and data quality at many organizations.

This seems strange to me, especially taking into account that experts have been talking a lot about the importance of customer data integration across the enterprise to give all the responsible a better view on who are their customers, what do they need and buy.

Even in a rather small company there could be several sources containing customer data, and not obviously those sources contain similar records, so customer data integration is the means to piece together the data puzzle.  Probably, mergers the number of which was significant in 2009 prevented numerous organizations from fulfilling their customer data integration initiatives.

Well, the fact is that more than 60 percent of Aberdeen’s survey respondents named customer data integration and other customer data initiatives among their top priorities for 2010.

December 28, 2009

Customer Data Integration to Be Among Companies’ Concerns in 2010

Filed under: Data Integration — Tags: , — Olga Belokurskaya @ 1:53 am

Well, let’s have some words on customer data integration (CDI). CDI has been one of the main concerns for different organization. Making and keeping customer data clean and convenient to work with, and getting more value from CRM systems has been in the top five of data integration challenges.

As it was mentioned in one of researches by Forrester, many organizations have changed their view on customer data integration and management (and, generally, on MDM), and started looking at it as a multiyear investment, including several phases. Though, again according to Forrester, the right approach to customer data management, and customer data integration as its significant part, still keeps being elusive.

The problem is that many enterprise CRM applications often give quite fragmented view on enterprise’s customer data, due to poor customer data integration. One more issue, the quality of customer data is often poor, so this is one of the reasons of failed customer data integration.

So, as predicts Forrester, the question of customer data integration is not solved yet, and there is a lot to be done in 2010.

June 30, 2009

Customer Data Integration vs Data Warehouse: the Difference

Filed under: Data Integration, Data Warehousing — Tags: , — Olga Belokurskaya @ 11:51 pm

The extensive world of enterprise data is quite tricky; however, it’s very important to clearly distinguish all the solutions used when dealing with data.

As customers are very important for any company, customer data is among the greatest company’s assets. In fact, customer data integration (CDI) solutions are to deliver the fullest information about customers.

However, as CDI is a software solution, and, in fact, is a clearinghouse for data synchronization and deployment, it is inevitably compared to data warehouses. There are several reasons of this confusion:

  • the aim of both solutions is to accommodate clean, meaningful information to the enterprise
  • both solutions are undoubtedly beneficial for business
  • both demand a solid partnership of business and IT

This confusion is risky, for these solutions differ in term of their positioning as well as in term of their usage. According to Jill Dyché one of the most acknowledged BI experts:

Data warehouses are designed and built to support business intelligence, and are meant for use by business people. Best practice data warehouses are those that have been planned around a set of business requirements that inform a series of applications—we call this the BI Portfolio—that are deployed incrementally to the business over time.

CDI, however, is purpose-built for operational data integration. The CDI hub is the ultimate home of customer master data that has been matched, reconciled, and certified, and is available to a series of business applications and systems (not end users). Unlike the data warehouse, which usually stores historical detail, summarized data, and time-variant information, the CDI hub stores or points to certified master data about a customer.

May 27, 2009

Why CDI Projects Fail

Filed under: Data Integration — Tags: — Olga Belokurskaya @ 1:05 am

Customer data integration (CDI) projects demand transformation of people, process and technology. If just one area fails the entire project will be at risk.

Here are common pitfalls that may turn a CDI initiative into failure, according to

  • Data model misfortunes
    Vendors usually promote those data models were designed to support their applications. They can’t offer flexibility around the data model. However, a predetermined data model, designed by an application vendor, can be a big reason for CDI failure.  Companies should look carefully at various data model approaches and options and choose those answering their needs.
  • 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.
  • No plan (or budget) for long-term maintenance and extensibility
    CDI is not a one-shot deal. It’s an ongoing project. Early adopters of CDI, many of whom built their own in-house systems, are now looking toward commercial products. They have found out about the long-term costs and requirements of maintaining custom systems.
  • Lack of user adoption
    Education and training are extremely important parts of CDI implementation and must be a primary part of a CDI plan, not an afterthought. Many companies using CDI successfully recommended developing a corporate-wide marketing plan for a CDI project and associated data governance and data stewardship initiatives.
  • Not addressing data quality, governance and stewardship issues
    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.
  • Politics, pure and simple
    Underlying many CDI-challenge discussions was the issue of corporate politics. 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.