Business application vendors have great products to sell, offering simplified access to complex computation models and enormous stores of corporate data. Yet, they often deliver below expectations. Poor data quality is the reason many well-planned and executed implementation projects ultimately fail.
An ERP or CRM implementation is deemed successful once the software is installed, the databases populated and all users have access to the applications they require. Once this stage of the project is attained, the vendors and installation teams usually fade into the background, certain that they have done a good job.
And in most cases they have fulfilled their task to the specifications required. Users can call up customer data, post financial data and even run complex queries with blazing response times - the foundation of a successful business application.
In most projects, one of the specifications is the transfer of data from one or more older systems into the new one. Unfortunately, this description infrequently includes ensuring the resulting information available to users is accurate and reliable. The eventual outcome is that users and executives have access to a vast store of business data, especially customer data, that is essentially worthless.
There are various reasons for this malady; the primary one, however, is people. As long as people are involved with data there will be errors - even the best trained data capture staff make mistakes. Furthermore, the Web provides us with the ability to allow people to capture and update their own data, which this makes the whole data integrity issue very challenging. Without the means to track and verify the accuracy of data, quality will be an elusive goal.
Another culprit of dirty data is convenience. Implementation teams are often under enormous time pressures, resulting in a quick-fix approach to data quality. They simply combine data from disparate systems in the manner that is most uncomplicated and delivers results the fastest, without first finding and ensuring incorrect data is excluded.
The bad news is that once data is this dirty, there is no quick or cheap solution. Any results systems produce are immediately questioned, or even rejected without a second thought, which renders the entire business application irrelevant.
Garbage in, garbage out
The spending slowdown has allowed IT leaders to take stock of what they have and brought the focus back onto the foundation of effective IT - data quality
Julian Field, MD, CenterField Software
It`s an old clich'e in business by now, but no matter how good your software is, if the data used to populate the database is inaccurate, you may as well not have the applications. Yet, as old as the clich'e may be, many companies in South Africa are faced with exactly this situation: redundant data, multiple copies of the same data with small differences in each copy and even data corrupted in a system crash that was never detected.
Companies are too focused on their systems, a natural consequence of the high cost and lengthy implementation times of business applications. Added to that is the expense and loss of productivity associated with user training. By the time these high-value issues are dealt with, there is precious little time to think about data; after all, it`s already there, ready and waiting to be used.
Data quality issues have been around since data was first stored electronically, but it`s only with the rise in the amount of data companies need to manage that the implications of dirty data are being felt.
During the years of economic boom, companies were so busy installing new technologies and reorganising their IT that data quality got lost in the mayhem. Now that businesses are more conservative, the spending slowdown has allowed IT leaders to take stock of what they have and brought the focus back onto the foundation of effective IT - data quality.
This refocusing on data has been helped along by new legislative requirements, such as Sarbanes-Oxley, HIPAA and aspects of South Africa`s ECT Act. These regulations make data quality even more critical than ever before as companies need to keep accurate records or they and their directors can be held accountable.
While some businesses may be in crisis mode due to these regulations, there are a few companies that have discovered that quality data has a far greater benefit than mere compliance. Many executives are faced with intense competition from all corners of the globe and have realised that quality products and low costs do not always win the day. These leaders are turning to their data stores as a source of intelligence to provide them with an extra competitive advantage.
The solution to dirty data, while not popular, is simple. The first step in every business application project must be the preparation of the data that will be used in the system. Without quality data, no matter how much money is spent of technology and expert skills, the result will always be garbage out and the effects will be seen on the bottom line.
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