Analytics. Business intelligence. Operations (a/k/a operational) research. They overlap somewhat, but each refers to a sophisticated way of analyzing information to support management decisions. You can use these techniques to get valuable evidence about marketing strategies, business performance, or government programs: Not with systematic reviews or experimental research, but with data mining and mathematical modeling. I'd like to see more collaboration between people in these fields and so-called evidence-based management.
Developing evidence. I've been looking at how people are using operations research (O.R.) to manage risk and inform evidence-based decision-making: How is the evidence developed, and how is it communicated? The Wikipedia page says O.R. is an "interdisciplinary branch of applied mathematics and formal science that uses methods such as mathematical modeling, statistics, and algorithms to arrive at optimal or near optimal solutions to complex problems. It is typically concerned with determining the maxima (of profit, assembly line performance, crop yield, bandwidth, etc) or minima (of loss, risk, etc.) of some objective function. Operations research helps management achieve its goals using scientific methods."
O.R. has many practical applications. The Science of Better.com describes it as "the discipline of applying advanced analytical methods to help make better decisions." The site is sponsored by the Institute for Operations Research and the Management Sciences (INFORMS®), a group of O.R. professionals. The Science of Better offers an excellent Executive Guide providing examples and success stories (16-page pdf). They offer practical advice, such as how to work with an O.R. professional (explaining what to expect during an initial assessment followed by analysis, prototyping, and system implementation). Although the guide doesn't actually refer to "evidence", they are describing ways to produce current, best evidence that helps executives make up their minds -- and isn't that what evidence-based management is about?
Fighting insurgents. O.R. helps people understand public policy issues and evaluate military strategies. As described in Operations Research, a journal published by INFORMS®, a recent O.R. study demonstrates why "even under best-case assumptions ...government cannot totally eradicate an insurgency by force." In “Why Defeating Insurgencies is Hard: The Effect of Intelligence in Counterinsurgency Operations – A Best-Case Scenario”, Moshe Kress and Roberto Szechtman of the Naval Postgraduate School discuss what they say is the first study of its kind to "combine military intelligence, attrition and civilian population behavior in a unified model of counterinsurgency dynamics" ($22US; Vol. 57 No. 3, May-June 2009, pp. 578-585). The researchers modeled the dynamic relations among intelligence, collateral casualties in the population, recruitment to the insurgency, attrition, and reinforcement to government forces.
The authors do a good job of explaining their findings in the research abstract, especially considering how complex such a study must be. They say in plain English: "In insurgency situations, the government-organized force is confronted by a small guerrilla group that is dispersed in the general population with no or a very small signature. Effective counterinsurgency operations require good intelligence. Absent intelligence, not only might the insurgents escape unharmed and continue their violent actions, but collateral damage caused to the general population from poor targeting may generate adverse response against the government and create popular support for the insurgents, which may result in higher recruitment to the insurgency." Rather than completely eradicate insurgents by force, the best a military can do is contain it "at a certain fixed level."
Note to the P.R. department: You could do a better job of spreading the evidence. The press release for the insurgency research article links to an obscure page about the Operations Research journal -- not the abstract, a Table of Contents, or a page where you can pay to access the article. I had to look around more than should be necessary.
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