Nov/Dec 2013

Data is the lifeblood of analytics. Yet some of the richest data sources now available to us will not easily reveal the insights they carry, because they don’t readily lend themselves to our traditional algorithmic approaches. In fact, much of big data isn’t what we have historically thought of as “data” at all. As much as 80 percent of the world’s big data is unstructured, meaning it doesn’t fit neatly into the columns and rows that feed most analytic models. For instance, new sources of text – blogs, comment streams, device logs, chat sessions with customer service reps, Twitter feeds and other social media posts – are all proliferating, but aren’t easily analyzed using simple regression models or decision trees. However, the body of techniques known collectively as text analytics can help draw insights from these sources by translating messy, complex textual information into signals that can enhance insights to customer behavior and even help refine predictive models.

• Andy Flint

Hewlett-Packard (HP) knows there are two sides to every coin. The company has achieved new power by predicting employee behavior, a profitable practice that may raise eyebrows among some of its staff. HP tags its more than 330,000 workers with a so-called Flight Risk score. This simple number foretells whether each individual is likely to leave his or her job.

• Eric Siegel

In a previous article, I wrote about some significant challenges in the healthcare industry to adopt and leverage analytics. Barriers range from siloed data to a lack of incentives among the major stakeholders. However, there are signs of hope, especially when we look at the large payer organizations that are beginning to embrace and promote analytics.

• Rajib Ghosh

Managing the finances of a municipality is difficult enough when the federal government is functioning, but the current environment introduces a host of new uncertainties. For example, communities with a large federal workforce may see a reduction in sales tax revenue, or there may be doubts about the continued viability of programs on which local governments have traditionally relied, leaving municipalities to pick up the slack.

• Sam L. Savage
• Shayne Kavanagh

Mayo Clinic has a long history and culture of using systems thinking and advanced analytics such as operations research (O.R.) to improve patient care delivery processes. More than 100 years ago Dr. Henry Plummer, one of the first few physicians of Mayo Clinic, had a strong interest in engineering and was instrumental in bringing forth the unified medical record, conveyors and pneumatic tubes to transport medical records and correspondence, as well as the exam room color coded light system. He also applied systems engineering principles in planning Mayo’s facilities, developing its system of subways, and establishing policy and form development, all with the vision of building patient-centered delivery processes. In 1947, under the leadership of Ernest Schlitigus, a small industrial engineering team known as Procedures and Records was formed with the foresight to make systems engineering services available to support projects related to scheduling, workflows analysis and process improvement.

• Tarun Lal
• Dustin Kuchera

Simulation provides an unparalleled capability to imagine the world as it is and as it might be – a better world of efficient production, responsive supply chains and ideal healthcare delivery. The varied tools in this software survey provide a diverse set of products that allow analysts to build, view and analyze complex models for a wide range of applications. Moreover, as the culmination of over a half-century of development, simulation is far more than the “tool of last resort” as it was once described. Simulation is now a mature technology that permits varied, complex and detailed studies of the world as it might be.

• James J. Swain