Data mining with statistics benefits every aspect of your business
Source: www.spss.com
Copyright SPSS, Inc. 2004


Using statistics in data mining can significantly impact all areas of your organization. Statistical software can improve your competitiveness from the shop floor to the sales floor to the executive floor. Some applications where statistical analysis is having a significant impact in organizations today are:

o   Relationship marketing and mass customization techniques increase revenue
o   Credit scoring develops more effective risk management
o   Database analysis creates predictive models yielding more effective marketing programs
o   Customer attrition analysis leads to more effective revenue planning
o   Customer value analysis increases repeat business at a lower cost
o   Sales forecasting results in more efficient manufacturing planning
o   Sales territory evaluations create better coverage of sales opportunities
o   Payable analysis leads to more effective cash management
o   Product line performance rationalizes or expands product offerings
o   Employee success analysis makes recruiting personnel more effective
o   Customer service analysis eliminates sources of errors and complaints
o   Customer support analysis results in most effective staffing levels to meet demand

How companies benefit from mining with statistics
A leading telecommunications company uses statistical analysis to produce results for high-level executives that impact company-wide decisions. They use statistics almost daily on issues with the potential to affect nearly 10,000 employees in five states.

By analyzing data, they find ways to improve processes that reduce costs, increase overall customer satisfaction and strengthen their position in the market. For example, they wanted to reduce the number of repeat visits their repair technicians made.

They used statistics to analyze data to determine what variables had the most impact on repair repeats. In the end, changes to the repeat repair process significantly reduced expenses and increased customer satisfaction: the telecommunications company will save about 15,000 dispatches annually.

A chain of bath and beauty specialty stores wanted to gain a stronger presence in the market with more stores and a larger cus-tomer base. Specifically, it wanted to increase its customer database to attract more cus-tomers through direct mail.

After testing lists of prospective clients against this model, the chain increased its direct mail response rate by an estimated 250 percent. This effective targeting helped the chain grow from 18 to 165 stores.

An industrial components supplier planned to attack a new sector of their target market but needed to ensure they didn't waste their telesales effort on unprofitable prospects.

To find the best prospects, the sales force used statistics to help them analyze and order every possible combination of attributes. By applying this information they determined which prospects weren't worth a telemarketing call. This alone saved the company $80,000.

Prospects who were called produced a success rate dose to the anticipated 15 percent. This is a better rate than achieved prior to using statistics. The company was so encouraged by the process, they continue to use statistics for profiling and segmenting the customer base. Today, statistics is a vital element of their database marketing analysis.

A large financial institution has found a unique target market in its loans division: offering car loans to high-risk applicants. To offset this risk, the bank uses statistics to develop a credit-scoring model that evaluates prospects and charges them interest based on their potential risk.

By performing credit-risk analysis, this bank forecasts a decrease in loan defaults of $2 million to $2.5 million on $10 million of loans per month. They have also reduced their uncertainty because they are making decisions with the right kind of analysis.

You can't afford not to use statistics in data mining
In today's business arena, it's a constant challenge to keep up with market trends and pre-dict future outcome. To increase market share and operate more efficiently, you cannot afford not to use statistics in data mining. You must capitalize on opportunities and manage processes that impact your bottom line.

Empower knowledge workers. Statistical tools help you empower your employees to per-form more extensive data analysis, making your organization more productive and competi-tive. Who better to explore customer characteristics than marketing and sales professionals? Who better to investigate process improvement opportunities than the plant floor manager? When employees have the right analytical tools, they can give you new insight and help you manage your business more effectively.

More confidence in decisions. The ability to create ad hoc analyses and customized re-ports at your fingertips with statistical tools means you can quickly and confidently make decisions based on fact.

Summary
Powerful, flexible, advanced analytical methods, such as statistics, are must-haves in a data warehousing environment. Statistics give you the return on your data warehousing invest-ment by uncovering critical information, helping you manage your business more effectively. Today's climate of increased competition and leaner organizations makes it imperative to mine data using advanced analytical methods. Savvy business professionals understand only too well that organizations need to make the most of their data and their employees' knowl-edge to be able to compete successfully.