There are few companies not facing a growing data crisis. Whether it is due to compliance legislation, increased competition or a growing reliance on data to assist in management functions, organisations across the world are being forced to take notice of their data.
In the past, data was something the IT department took care of and the rest of the company took for granted. At least, they were able to blissfully ignore their data until something went wrong and customers departed or the company ended up on the wrong track. Of course, by then it was too late to wonder why multimillion-rand business applications performed so poorly.
Most South African companies, large and small, are unaware of the importance of their data. They assume data capturers input it correctly, or hope that someone fixes it somewhere along the way. Unlike an enterprise resource planning or a customer relationship management system which has a value in executives` minds because it has been paid for and has gone through extensive implementation cycles, data is "free" and therefore does not need attention.
The reality is different and many companies have felt the financial pain of this mistake. The only way to cleanse corporate data once it is corrupted is through a data re-engineering exercise. Of course, a better solution is to run the re-engineering project when business applications are installed to ensure they start life with accurate, reliable data, but this costs money and is usually an afterthought.
What is data re-engineering?
Most South African companies, large and small, are unaware of the importance of their data.
Julian Field, MD, CenterField Software
Data re-engineering is an automated means to transform imperfect data from multiple internal and external sources into an accurate, consolidated view of the business across systems, departments and business lines. There is no quick-fix solution to re-engineering, no CD to insert and run. Data re-engineering starts with low-level data investigation, data typing and entity identification to attain the highest levels of data quality.
The purpose of this in-depth and complex exercise is to identify relationships buried in text fields and hidden across millions of records. As noted, it is a lengthy, drawn out process and it can be expensive; but failing to do it will ultimately result in inaccurate responses to end-user queries and greatly diminish the effectiveness of data analysis.
In fact, Gartner warns that information systems will fail due to poor data quality if companies do not first investigate, standardise and consolidate data from disparate sources.
But there are also other, measurable benefits data re-engineering delivers apart from knowing that customer Smith always buys what customer Jones has already bought, and having the correct contact details for both. These include:
* Improved confidence in decision-making: Data re-engineering does more than ensure data is accurate; the process also provides an understanding of the business and thereby enhances data mining results and corporate decision support capabilities. It ensures that responses to management queries are accurate, allowing users to drill down and aggregate up to any level of detail with confidence.
* Improved customer service and retention: By creating a broad view of each customer`s portfolio of products and relationships, data re-engineering enables an organisation to enhance customer service. Front line staff will no longer have to log onto multiple account-oriented systems to obtain information on a customer or prospect. They are better equipped to satisfy customer requests in less time. The logic is simple: delivering better customer service translates into better customer retention.
* Better sales and marketing opportunities: New marketing abilities created from knowing more about customers have been spoken of for a long time; data re-engineering makes them a reality. By building consolidated views of business entities, companies can launch accurate cross-product and cross-department selling and identify members of the same household for highly targeted marketing initiatives.
* Support for business re-engineering initiatives: If a company needs to restructure itself into a different physical makeup, a data re-engineering tool can assist by transforming all data from any systems into an accurate and streamlined view of the business.
Once completed, data re-engineering takes on a far more important role in the shape of each company than merely the creation of an accurate information store. It facilitates the smoother running of the company, allowing leaders to focus on strategy and growth without concerns that their assumptions are based on inaccurate data. The real-time application of these benefits also leads to cost reductions in various, sometimes unexpected areas of the business:
* Reduction of physical inventory: Data re-engineering reduces inventory by identifying anomalies and redundancies;
* Simplifies database management and reduces storage requirements for information systems;
* Reduces mailing and production costs;
* Reduces clerical staff;
* Reduces programming costs and accelerates time to market; and
* Spares costly redesigns of data models.
As noted, the most efficient use of data re-engineering is to run the project when implementing business applications instead of as an emergency measure once a data crisis is in full swing. It is a costly project, but starting IT projects on a foundation of quality data will ensure the system delivers as expected and that the results of corporate functions reliant on data can be accepted with confidence. Ignoring data integrity is like square wheels on a Ferrari: everything may look good, but don`t count on performance.
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