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Developing an Analytics Strategy: The Role of the Analytics Champion

Robert Pitney

May 25, 2018

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As outlined in Developing an Analytics Strategy: The Role of Culture, there are five facets to “cultural infrastructure” that organizations must address to realize the full potential of analytics.  This may require significant cultural change, which must begin with executive leadership, i.e. setting the “tone at the top”.  We recommend appointing an Analytics Champion to maximize value from analytics. Here, I’ll describe the key traits of an Analytics Champion and how they can set up an organization for future “wins” with analytics.

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Why You Should Attend Predictive Analytics World

Paul Derstine

May 18, 2018

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This year there will be only ONE Predictive Analytics World conference in the U.S. Billed as Mega-PAW, it will be the largest Predictive Analytics World event to date and is the premier cross-vendor conference for machine learning and predictive analytics professionals, managers and commercial practitioners. The only conference of its kind, Predictive Analytics World delivers vendor-neutral sessions across verticals such as banking, financial services, e-commerce, entertainment, government, healthcare, manufacturing, high technology, insurance, non-profits, publishing, and retail.

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Detecting Fraudulent Workers' Compensation Claims

Isaiah Goodall

May 11, 2018

BLOG_Detecting Fraudulent Workers' Compensation ClaimsHealthcare fraud is very difficult to detect because a variety of nuanced methods are employed, investigative evidence is often buried in text documents, and there can be collusion among network providers. Excessive or redundant medical services, medical coding errors, improper billing, as well as outright fraud, continue to be significant challenges for health insurers.

The Department of Labor Office of Inspector General wanted to develop an effective fraud detection solution to prioritize high-risk workers’ compensation claims for investigation.

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Developing an Analytics Strategy: The Role of Culture

Robert Pitney

May 4, 2018

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Analytics enables organizations to more effectively accomplish their mission by revealing new insights that promote better decision-making.  When first getting an analytics capability going, organizations often focus on the technical building blocks, such as constructing an IT infrastructure, obtaining analytics software, or hiring data scientists and analysts.  However, when developing an analytics strategy they often overlook whether the organization is ready, and willing to develop the “cultural infrastructure” necessary to benefit from those investments.

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Jumpstart Your Data Science Team with Experts

Isaiah Goodall

April 27, 2018

 

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Increasing numbers of mid-size and larger companies have seen the worth of analytics and are trying to build in-house data science teams to capitalize on the value of their data assets. But, hiring effective data scientists is a challenge due to the competition for this rare and expensive talent. Further, beyond the task of finding and retaining data scientists and analysts, building a working in-house analytics team is fraught with organizational challenges such as securing buy-in from business unit leaders, IT, and executive decision-makers.

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The Power of Open Data and Crowdsourcing Analytics

Paul Derstine

April 20, 2018

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Crowdsourcing, a combination of “crowd” and “outsourcing” first coined by Wired magazine in 2005 and fueled by the Internet, is a powerful sourcing model that leverages the depth of experience and ideas of a public group rather than an organizations own employees. In The Importance of CrowdSourcing Matt H. Evans points out that “Crowdsourcing taps into the global world of ideas, helping companies work through a rapid design process. You outsource to large crowds in an effort to make sure your products or services are right.” The advantages of using crowdsourcing are claimed to include improved costs, speed, quality, flexibility, scalability, or diversity. It has been used by start-ups, large corporations, non-profit organizations, and to create common goods. Wikipedia maintains a list of crowdsourced projects.

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Get Ready for Analytics Summit 2018

Paul Derstine

April 13, 2018

 

BLOG_Analytics Summit 2018Elder Research will participate in the 7th annual Analytics Summit 2018, Hosted by The University of Cincinnati Center for Business Analytics on May 14th-16th, 2018 at the Sharonville Convention Center in Cincinnati, Ohio. This year’s event will feature three high-profile keynote speakers, four technical one or two-day training sessions, one managerial half-day forum, and five analytics tracks with three presentations each.

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What is Data Wrangling and Why Does it Take So Long

Mike Thurber

April 6, 2018

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Data wrangling is the process of gathering, selecting, and transforming data to answer an analytical question.  Also known as data cleaning or “munging”, legend has it that this wrangling costs analytics professionals as much as 80% of their time, leaving only 20% for exploration and modeling. Why does it take so long to wrangle the data so that it is usable for analytics?

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Choosing the Right Analytics Problem

Admin

March 30, 2018

 

BLOG_Choosing the Right Analytics ProblemIf your organization is new to data science and predictive analytics, it can be difficult to know where to start. In our two decades of experience at Elder Research, we have found that there is often a mismatch between what companies think they should do with analytics versus what will provide the most value. While the specific problem to tackle varies by industry and business, we have found that choosing the right problem and focusing on a few key guidelines at the outset helps us deliver business value and gain support for analytics from key stakeholders.

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Improving Unemployment Insurance Claim Fraud Detection

Isaiah Goodall

March 23, 2018

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The U.S. unemployment insurance (UI) system is run and funded primarily by the individual states with oversight and support from the U.S. Department of Labor. Individual state UI programs are entrusted with ensuring benefits are paid promptly and accurately to eligible claimants, preventing improper payments (both over- and under-payments), and ensuring that employers properly classify their workers and pay their contributions promptly and accurately.

Elder Research designed and deployed an automated fraud detection solution for the New York Department of Labor Unemployment Insurance Integrity Center of Excellence. The tool was estimated to have identified 1200 claims annually before the current investigative process with annual projected savings of $972,000 in recoverable and nearly $392,000 in non-recoverable overpayments.

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Building a High-Functioning Analytics Team

Cory Everington

March 16, 2018

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This is the third in a series of blogs where Data Scientists Cory Everington and Anna Godwin discuss five Analytics Best Practices that are key to building a data-driven culture and delivering value from analytics. In this installment Cory discusses the benefits of team building and its impact on successful data science projects.

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Goodhart’s Law, Evolving Threats, and Model Monitoring

Stuart Price, Ph.D.

March 9, 2018

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In 1975 Charles Goodhart, a chief economic advisor of the Bank of England, posited “When a measure becomes a target, it ceases to be a good measure”. This idea came to be known as Goodhart’s Law and is recognized as a risk associated with key performance indicators (KPI) and implementing analytics. Any metric applied to a competitive or adversarial system will change behavior if it is perceived to make decisions that affect the system. If your adversary has a good chance of figuring out your metric, how can you keep your system from being gamed? 

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Analytics Assessment: Blueprint for Effective Analytics Programs

Robert Pitney

March 2, 2018

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If you are like me, when you first heard of analytics and its ability to benefit businesses, non-profits, and government agencies, you felt invigorated and excited, having to hold back the urge to shout “Charge!”  As a data scientist, I found this excitement to be well-founded: analytics powerfully leverages data to address important, existential questions facing any organization: 

  • Are we effectively meeting our customers’ needs?
  • Are there more efficient ways to reach our strategic goals?

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Credit Models are Winning and I’m Keeping Score!

Aric LaBarr, Ph.D.

February 23, 2018

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Classification scorecards are a great way to predict things because the techniques used in the banking industry specialize in interpretability, predictive power, and ease of deployment. The banking industry has long used credit scoring to determine credit risk—the likelihood a particular loan will be paid back.  A scorecard is a common way of displaying the patterns found in a classification model—typically a logistic regression model. However, to be useful the results of the scorecard must be easy to interpret. The main goal of a credit score and scorecard is to provide a clear and intuitive way of presenting regression model results. This article briefly discusses what scorecard analysis is and how it can be applied to score almost anything.

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Top Mistakes when Backtesting Investment Strategies

John Elder, Ph.D.

February 16, 2018

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A market index provides a tough hurdle to beat for any investment strategy. Employing an index is almost always better than a strategy that systematically picks a subset of its space or time (i.e., does portfolio-picking, or market timing ). The cost of a predetermined index is low, since no thought is required, and the long-term results over the last century of major market indices have been impressive.  So, the argument goes:  “Why waste your money paying for expensive managers who may only beat the market by luck?”

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