Published: July 18, 2008 02:54 pm            

Data mining aids decision-making

Data mining helps users to make sense of all the information within an organization. Data mining tools use decision-making processes to search raw data for patterns and relationships that may be significant.

State and federal governments rely on data mining software to locate people and companies. Generally, data mining, also called data or knowledge discovery, is the process of analyzing data from different perspectives and summarizing it into useful information. Information can be used to increase revenue, cut costs or both.

Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it and summarize the identified patterns. Data mining software finds correlations or patterns among dozens of fields in large relational databases.

Although data mining is a relatively new term, the technology is not. Companies have used powerful computers to sift through volumes of supermarket scanner data and analyze market research reports for a number of years. However, continuous innovations in computer processing power, disk storage and statistical software are dramatically increasing the accuracy of analysis while reducing costs.

Data mining is primarily used today by companies with a strong consumer focus including retail, financial, communication and marketing organizations. Data mining enables these companies to determine relationships among “internal” factors such as price, product positioning or staff skills as well as “external” factors such as economic indicators, competition and customer demographics and to determine the impact on sales, customer satisfaction and corporate profits.

Finally, data mining enables companies to “drill down” into summary information to view detailed transactional data. As an example, firms selling a number of items may find they have duplicate and inaccurate customer information in their various databases. Database inaccuracies cause problems when attempting to cross-sell and up-sell various products and services.

By using database software, companies can reduce duplicates within their databases, decrease mailing costs and increase address deliverability. Software can improve data linkages on an individual customer level. Companies can better target customers as well as develop a profile of the ideal customer. Firms can increase their database usage by integrating with marketing partners to develop new trade areas.

Online software vendors may suggest a product for you to purchase or may indicate that people who bought one product also bought others. These prompts are developed through data mining. In data mining, once you gather information and organize it, the data grows your business. Whether you use descriptive or predictive data mining it is important to avoid making a bad decision based on the data mining efforts. Avoid problems by using only good, clean, accurate data.

Second, focus on the decision, not the tool, and remember that judgment still plays an important role. A good manager using a poor tool will give you a better result than a poor manager using an excellent tool. Also, what you learn should make sense. Even if the numbers are correct, the analysis may be incorrect due to bad data, bad assumptions or other bad information. If an analysis does not make sense, then decide why the assumptions are wrong or decide why the analysis is wrong.

Finally, always test your analysis before making major decisions. Examine the results on a different part of your database or at a later time. Execute a small marketing project to determine if the approach works. Minimize your risk by testing your analysis prior to rolling out an expensive marketing program or implementing a large operational change.

At Dalton State College, classes in management information systems prepare students for careers in managing data and data systems.



Marilyn Helms is a business professor at Dalton State College.

        

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