In the 5th Annual Survey (2011) data miners shared examples of situations where data mining is having a positive impact on society. The five areas mentioned most often were:

• Health / Medical Progress
• Business Improvements
• Personalized Communications & Marketing
• Fraud Detection
• Environmental

Below are selected "positive impact examples" the data miners shared. Complete lists are also available by following the links below.

Thirty-six data miners participating in the 5th Annual Survey described positive impact examples in this area. Medical topics mentioned by several respondents included: drug and treatment discovery, improved diagnosis, treatment compliance, and healthcare optimization / cost reduction. (All 36 health / medical responses can be seen here.)

Selected examples:

• Fast and accurate diagnosis of infectious diseases in patients admitted to ER unit. Reference: "Classification of infectious diseases based on chemiluminescent signatures of phagocytes in whole blood" by Daria Prilutsky, M.Sc.; Boris Rogachev, M.D.; Robert S Marks, Ph.D.; Leslie Lobel, M.D., Ph.D.; Mark Last, Ph.D., to appear in Artificial Intelligence in Medicine.
• Created an improved health risk model tuned to our specific population that helps employees identify their personal risk of chronic disease (CVD, diabetes, cancer), then recommends actions that they can take to avoid them. See http://cathealthbenefits.cat.com/cda/layout?m=164481&x=7 for an example.
• More than 90% of the chemicals on the market have not been tested on their potential hazards on humans and environment like carcinogenicity, developmental toxicity, mutagenicity, skin sensitization. If they would be tested in traditional way, i.e., by animal testing, it would require more than 10 million additional animals, billions of euro, and more than 50 years in time. Mathematical models (qsar models) obtained from observation data are going to help reducing, refining, and replacing animal tests in the near future.
• Using analytics to identify health plan members that are non-compliant in keeping their diseases under control (e.g. diabetes). That way the health plan can send educational literature/programs to those most likely to be out of compliance and keep them healthier..

Eighteen data miners participating in the 5th Annual Survey described positive impact examples in this area. (All 18 business improvement responses can be seen here.)

Selected examples:

• We have been using data mining techniques to improve electricity network forecasts which in turn help manage network capital expenditure costs which in turn reduces electricity bills. We have also been developing new tariff scenarios and identifying potentially energy vulnerable groups within the community.
• Using DM to develop a model to optimize the scheduling of oil shipping tankers (reduced cost to the company and positive environmental impact). Due to client confidentiality agreements I couldn't share the details of the project.
• Determining patterns associated with successful call center agents and applying those learnings in recruitment and training of agents led to increased employee, organization and customer satisfaction. That was fulfilling.
• We have used data mining for employee attrition. This will generate long term ROI of millions of dollars.
• Predictive Maintenance: the ability to maintain a machine or prevent accidents from happening. Predictive Maintenance could have prevent the tragedy in the Gulf of Mexico.

Eighteen data miners participating in the 5th Annual Survey described positive impact examples in this area. (All 18 responses can be seen here.)

Selected examples:

• As we are working mainly for a marketing audience, we have proven to make marketing more efficient (+10% revenue) and more relevant (+300% more relevant) by applying predictive analytics for targeting and customized offering.
• Netflix recommender and Google Reader's "sort by magic" have completely revolutionized the way I consume information for entertainment and news.
• Automation of keyword pricing for bidding on search engines. Automation of "good" keyword detection.
• Amazon customer experience embodies data mining.
• In a world where people are inundated with marketing, data mining can create an environment that a consumer hears what they want to hear about.
• Discover information in text. Predict who is likely to buy, migrate or churn. Improve campaigns.
• Data mining can help quality of life and assist public health interventions - by producing a model predicting the effect of an intervention. Data mining can help filter important data and information from spam and information overload.

Thirteen data miners participating in the 5th Annual Survey described positive impact examples in this area. (All 13 responses can be seen here.)

Selected examples:

• Insurance Fraud Bureau uses link analytics and data mining within Detica NetReveal to detect motor fraud . Up to date over 150 arrests have been made on organised criminal rings and seized millions of pounds in proceeds of crime reducing premium costs for us all.
• Insurance fraud detection and insurance risk estimation - better prices for better clients.
• Preventing financial transaction fraud.

Nine data miners participating in the 5th Annual Survey described positive impact examples in this area. (All 9 responses can be seen here.)

Selected examples:

• We are development model for: -Predict the flow of rivers to meet two months before the availability of irrigation water and the potential for flooding and / or drought. -Predict the occurrence of hail from a weather radar data. -Predict crop yield and production from monthly variables surveyed in the field. -Sort prevailing production systems to perform an economic analysis of production system and not for each particular activity.
• Reduction of postharvest losses through better ability to call which lines of product to commit to which storage / distribution channels.
• More than 90% of the chemicals on the market have not been tested on their potential hazards on humans and environment like carcinogenicity, developmental toxicity, mutagenicity, skin sensitization. If they would be tested in traditional way, i.e., by animal testing, it would require more than 10 million additional animals, billions of euro, and more than 50 years in time. Mathematical models (qsar models) obtained from observation data are going to help reducing, refining, and replacing animal tests in the near future.

Data miners participating in the 5th Annual Survey described positive impact examples in a very diverse set of areas, including crime detection, rhino horn fingerprinting, student retention, charity donor appeals, substance abuse treatment, genetics, pollution reduction, politics / government, risk management, cost optimization, poverty /economic planning, combustion optimization, petroleum discovery, and more. (All 44 "other" responses can be seen here.)

Selected examples:

• Better prediction than classical statistics methods for rhino horn fingerprinting. Can help busy people develop improved prediction models that can handle non-linearity and complex interactions.
• We have applied data mining in government to better estimate the social and economical return of funding programs (loans, grants, and so on) using credit scoring and data mining in general. By our estimations, these techniques translate into more jobs created, more funding programs, and in general a virtuous circle.
• I work for a charity, which is using data mining to increase the level of donation to appeals, reduce attrition in regular giving and identify likely candidates for major giving, bequests etc.
• Data mining offers tools that can improve our knowledge about risk factors in adolescent substance use.
• In our case, predicting academic performance help us detect at risk students in order to help them, so they will not quit their studies. We will also detect the high performance students to get the best of them.