CRM has become a hot-button topic, with companies deploying systems in the hope of providing better service and, in turn, boosting revenues.
But many CRM deployments are thwarted by faulty, inconsistent data sets that prevent user sites from having a clear, unified profile of each customer, according to users and analysts monitoring the CRM industry. While part of the problem could be solved through customer education in pre-data entry stages, software companies are beginning to tackle the problem of dealing with existing data sets.
For instance, companies such as Evoke Software and Metagenix have started selling wares intended to profile data and help clean it up. However, the problem is not likely to go away soon.
"It's massive," says Derek Strauss, CEO of US-based business intelligence applications host Assurenet, of the problems of data quality in CRM applications.
"One of the biggest issues with CRM is obviously getting to know your customer," Strauss says. "You have to have accurate information, and most of the front-end systems that deal with customers do not have accurate information about the customers. There's disjointed [data]; there's a lot of blanks in some of the critical fields."
Additionally, many business rules intended for databases have been broken, says Strauss. "Consequently, you have data integrity problems with your data."
Even such seemingly small mistakes such as being one digit off on a customer's street address can plague data sets, says Joe Butt, senior analyst at industry watcher Forrester Research. This type of problem can lead, for example, to a company sending out multiple direct mailings to the same customer, because the address is listed in two different ways in company databases. "CRM is the hot topic of the moment, but in terms of consumer data, it's probably the dirtiest data around," Butt says.
And herein lies one of CRM's biggest nemeses, for according to analyst firm Gartner, data-quality problems are a recurring hindrance to successful CRM deployments.
In a July 2001 report, Gartner wrote that more than 75 per cent of enterprises engaged in CRM initiatives cannot combine a comprehensive view of a customer with actionable, personalised advice to customer service and sales agents. A key challenge in implementing a CRM platform is "an information crisis resulting from inconsistent, inaccessible, incorrect, or out-of-synch data sources", according to Gartner. Other factors cited included an inability to prove value, a personnel shortage, and difficulty in tying together a corporate CRM strategy.
The complexity of a CRM implementation, and the role that data sets play in it, is often overlooked or downplayed at the planning stages. At least 80 per cent of enterprises underestimate the time and resources needed to cleanse and consolidate data. As a result, Gartner reports that when data-cleansing is finally undertaken, company budgets allocated for the task are usually exceeded by 200 to 300 per cent.
Integrating customer data sets is challenging, agrees IBM official Bryan Foss, a customer loyalty solutions executive in London, who has been working on CRM deployments both internally and at customer sites.
"CRM has a very broad scope,"
Foss says. Existing systems, such as manufacturing and ordering, must be integrated to enable a single view of a customer base.
"In a typical bank or insurance company, for example, there could be 50 to 150 different systems that contain customer data, and if you want to gain a single view of that customer and the value of that customer and their needs, then you need to combine that data," he says.
According to Foss, this requires pulling together different data stores, with data of varying ages on different databases. To add to the problem, existing data stores also use multiple programming languages and data formats.
"Some of the data is of poor quality. Maybe it hasn't been used for a long time, so to bring [it all together] is a big task," Foss says. "It's an enormous task. It can't be done overnight."
To tend to the problem of poor data quality, Foss and Strauss are utilising third-party data profiling software.
Foss is using Evoke Software's tool, which bears the same name as its company, to automate the process of data analysis. "Manually, it would have taken a long time. What people did [formerly] was they tended to tackle the problem during the project and the project would expand both in terms of time and money," he says.
"Using Evoke Software, you can automate that assessment process up-front. You can understand the structure of the data and understand its quality."
The product finds different relationships in customer data in multiple sources and provides information on restructuring and cleaning the data. IBM is using the Evoke product to build data warehouses and to profile data for a Siebel Systems CRM application. Once data inconsistencies and issues are uncovered, IBM uses Vality's Integrity to cleanse the data.
Evoke offers an alternative to hiring systems integrators to manually examine data files, says Rick Cortese, Evoke's president and CEO.
"Manual intervention is tedious, time-consuming, expensive, and by definition not very accurate," Cortese says. "Evoke looks at all the data, irrespective of source code and documentation, and looks at where it resides."
The problem, however, is that the cost of data-cleansing software can be prohibitive. Evoke Software costs from roughly $US400,000 to several million dollars, depending on configuration and services. Version 4.5, due in December, will feature added XML functionality and an enhanced repository for automated profiling.
At Assurenet, the company is using a rival product, Metarecon, from another US company, Metagenix. The product analyses data in source systems, including looking at data values. "It tells you early in your project where your problems lie," Strauss says.
Metarecon provides data profiling and analysis, and can also perform code generation, including producing online analytical processing specifications, according to Metagenix president Greg Leman.
Compared to Evoke, the cost of Metarecon seems a lot more affordable - coming in at $US25,000 for an entry-level version, and $250,000 to $300,000 for a standard, perpetual, enterprise licence.
Given the percentage of failed CRM implementations, it is imperative that the customer be made aware of the potential budgetary blowouts if the system is to deliver what it was acquired for in the first place. More importantly, educating potential CRM clients on the importance of "clean" data entry and setting up processes to achieve that goal should be part of the CRM sales strategy.
