Industries

Healthcare


Improve clinical care and patient outcomes, reduce fraud, and manage financial risk.

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Healthcare

Insurance


Prioritize claims, reduce risk and cost, prevent fraud, and improve customer experience.

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Insurance

Financial Services


Improve regulatory compliance, detect fraud, assess risk, and enhance customer value.

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Financial Services

Software & Technology


Analyze sensor/log data to enhance product design and user experience, and reduce attrition.

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Software & Technology

Government


Prevent fraud, waste, and abuse, improve program integrity, and deliver return on investment.

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Government

Defense & Intelligence


Detect and prevent threats, improve security, prioritize caseload, and mitigate risk.

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Defense & Intelligence

Case Studies

Government

US Postal Service


Elder Research partnered with the U.S. Postal Service Office of Inspector General to develop and deploy a custom solution to identify and prioritize questionable contracts and healthcare claims for investigation. Leads generated were 74% actionable, resulting in over $11 million in recoveries, restitutions, and cost avoidance in the first year.

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Commercial

DentaQuest


Elder Research developed a provider risk scoring model that enabled targeted intervention with low quality providers and reduced per patient cost by nearly 20 percent.

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Commercial

nTelos


By applying advanced techniques for modeling and visualizing customer records, Elder Research created a combined data and text mining solution to increase marketing efficiency and reduce churn. The model improved targeted messages which resulted in higher profitability for nTelos, a regional mobile phone carrier.

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Featured Clients & Partners

Events

  • Speaking Event

    April 5, 2018

    John Elder To Speak At Elon University Data Science Conference

    John Elder

    John Elder will speak on "The Data Science Revolution in Industry" at the Elon University Business Analytics Conference "Analytics in Action: Trends You Need to Know" on April 5, 2018 at the SAS Executive Briefing Center in Cary, NC.

    April 5, 2018

    John Elder To Speak At Elon University Data Science Conference

    John Elder

    John Elder will speak on "The Data Science Revolution in Industry" at the Elon University Business Analytics Conference "Analytics in Action: Trends You Need to Know" on April 5, 2018 at the SAS Executive Briefing Center in Cary, NC.

  • Conference

    May 8-9, 2018

    Elder Research Sponsors CSER 2018 Conference

    University of Virginia

    Elder Research will sponsor the Conference on Systems Engineering Research (CSER 2018at the University of Virginia on May 8-9, 2018. The “Systems in Context” theme is inclusive of topics across all aspects of systems and industrial engineering and related fields.

    May 8-9, 2018

    Elder Research Sponsors CSER 2018 Conference

    University of Virginia

    Elder Research will sponsor the Conference on Systems Engineering Research (CSER 2018at the University of Virginia on May 8-9, 2018. The “Systems in Context” theme is inclusive of topics across all aspects of systems and industrial engineering and related fields.

  • Speaking Event

    June 5, 2018

    John Elder Keynote Speaker At Predictive Analytics World For Business In Las Vegas

    John Elder

    John Elder will deliver the keynote address "The Greatest Scienceat the Predictive Analytics World for Business conference in Las Vegas on June 5, 2018.

    June 5, 2018

    John Elder Keynote Speaker At Predictive Analytics World For Business In Las Vegas

    John Elder

    John Elder will deliver the keynote address "The Greatest Scienceat the Predictive Analytics World for Business conference in Las Vegas on June 5, 2018.

  • Webinar

    March 8, 2018

    Webinar: Detecting Fraud Rings With Graph Databases

    Robert Han & Ryan McGibony

    Fraud is often perpetrated by groups working together. Fraud analytics uses data to detect fraud these rings. In this webinar Robert Han and Ryan McGibony share details on identifying suspicious behavior using network analysis tools such as graph databases. Register for webinar

    March 8, 2018

    Webinar: Detecting Fraud Rings With Graph Databases

    Robert Han & Ryan McGibony

    Fraud is often perpetrated by groups working together. Fraud analytics uses data to detect fraud these rings. In this webinar Robert Han and Ryan McGibony share details on identifying suspicious behavior using network analysis tools such as graph databases. Register for webinar

News

Elder Research Sponsors Tom Tom Festival Applied Machine Learning Conference

Elder Research will be a Theme Sponsor for the Applied Machine Learning Conference on April 12, 2018 at the Violet Crown theater in downtown Charlottesville. Machine Learning is a technology that helps make sense of the massive amounts of data and, in today’s world, it is the key to survival for businesses.  This day-long conference will convene researchers, entrepreneurs, and practitioners who use big data and machine learning applications on a wide variety of topics.

Jennifer Schaff Announced as a Winner of the DREAM Parkinson’s Disease Digital Biomarker Challenge

Data Scientist Jennifer Schaff, Ph.D. was announced as one of the winners of the DREAM Parkinson’s Disease Digital Biomarker Challenge. Jennifer used statistical methods to derive features and feature selection to develop the top performing submission in predicting dyskinesia severity with a 59% improvement over baseline models. More than 440 data experts participated in the challenge worldwide. The DREAM Challenge is funded by the Michael J. Fox Foundation and the Robert Wood Johnson Foundation.

Gerhard Pilcher & Jeff Deal Interviewed for The Big Biz Show

Jeff Deal and Gerhard Pilcher join Bob "Sully" Sullivan and Russ T. Nailz, hosts of the Big Biz show which airs as Sully's Biz Brew on the Youtoo America Television Network, to discuss their book Mining Your Own Businessa practical guide on analytics for organizational leaders and top-level executives. Sully's Biz Brew Schedule

Aric LaBarr Spoke on Model Validation at Duke University

Senior Data Scientist Aric LaBarr spoke on Model Validation to Masters of Statistical Science students at Duke University on October 31, 2017.

EBooks

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Mining Your Own Business

This eBook includes Chapter 3 from industry experts Jeff Deal and Gerhard Pilcher’s book Mining Your Own Business, A Primer for Executives on Understanding and Employing Data Mining and Predictive Analytics. Chapter 3 titled “Leading a Data Analytics Initiative” covers the key challenges and considerations for business leaders employing analytics to provide data-drive insight.

The Ten Levels of Analytics

Every technical project involves some sort of analytics, ranging from simply reporting key facts, to predicting new events. In this eBook we define ten increasingly sophisticated levels of analytics so that teams can assess where they stand and to what they aspire. The eBook clarifies definitions of three types of analytic inquiry and four categories of modeling technology and illustrates these levels with examples using tabular data representations commonly found in spreadsheets and single database tables. Additionally, the Levels are extended to encompass emerging data types such as time series, spatial data, and graph data, by providing data complexity as second dimension for categorization alongside algorithmic sophistication.

Top 10 Data Mining Mistakes

In two decades of mining data from diverse fields, we have made many mistakes, which may yet lead to wisdom. In this eBook, we briefly describe, and illustrate from examples, what we believe are the “Top 10” mistakes of data mining, in terms of frequency and seriousness. Most are basic, though a few are subtle. All have, when undetected, left analysts worse off than if they’d never looked at their data.

Resources

Featured Video

Gerhard Pilcher discussed the gap between the promise of analytics to transform a company and the actual results, and how adaptability and intuition by leadership can help close that gap.

Target Shuffling is a process for testing the statistical accuracy of data mining results. It is particularly useful for identifying false positives, or when two events or variables occurring together are perceived to have a cause-and-effect relationship, as opposed to a coincidental one. 

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Book Overview

COVER_Mining_Your_Own_Business.jpg

Mining Your Own Business is a practical guide for organizational leaders and top-level executives that demonstrates how to harness the power of data mining and predictive analytics, and avoid costly mistakes.

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