Business Intelligence (BI) systems and applications are designed with the goal of facilitating informed decisions by corporate management through the process of filtering and synthesizing data and other information driven by historical purchase, behavior, lifestyle and corporate events, business rules, and other trends. With effective BI tools at their disposal, senior management and others throughout the organization can more readily adapt, modify, and fine-tune business strategies with the goal of creating a competitive edge through improved business operations, reduction of costs, and increases in profitability. Business Intelligence systems and platforms in concert with Customer Relationship Management (CRM) architectures have become an integral part of many corporate desktops with the goal of improving customer service, increasing retention of existing customers, locating up-sell and cross-sell opportunities, finding new “best” customers, and otherwise maximizing revenue-generating opportunities.
However, even with the advances in technology and increases in sophistication of other business decisioning systems, the overall effectiveness within any enterprise is directly related to the data and other information being utilized to drive the answers to the questions posed. An application’s and by extension corporate management’s ability to correctly identify trends and other relative actionable sets of marketing information is directly proportional to the accuracy, validity, and relative quality of the items of information from which they are derived. The absence of quality data will inevitably lead to a lack of trust in the answers being generated and, perhaps more importantly, may cause bad business decisions to be made that may impact the future viability of the enterprise.
Problems with data quality most commonly are the result of human error and on the surface may not be recognized as representing major deterrents to the ongoing successful operation of the business. The old adage, “Garbage In, Garbage Out” comes into play more often than most would like to recognize. Proper data definitions, instructions and training to personnel, data quality controls, checks and balances, and ongoing procedural audits play an integral part in serving the larger picture in order that corporate management can create competitive advantages in this ever-expanding global e-commerce world that we live in.
The time and dollars invested in support of data quality-based initiatives which in turn are the foundation of Business Intelligence based applications serve to create further cost reductions and reduce the risk of making false assumptions based upon invalid, inaccurate, or otherwise erroneous data and information. A disciplined approach to evaluating, correcting, and purifying the various sources of information that will ultimately feed these and other types of business applications should include the following:
- Data Profiling for items of information from the various source systems in order to evaluate data content and existing quality
- Data Standardization of relevant pieces of information in order to establish consistency
- Data Matching to create a single customer view
- Household and/or Corporate Family Linkage
Business Intelligence applications, systems, and supporting platforms will no doubt continue to grow and become more widely used as another tool designed to aid businesses in their goal of gaining a competitive advantage. The success of these initiatives and the business decisions they will drive are intimately related to the quality of the data, information, and business rules that collectively are drawn against to produce the desired end result.