Evidence-Based Management Blog

From ‘Winning’ to ‘The Long Tail’

Michiel Crommelinck — Tue, 10 Apr 2012 09:35:42 +0000

Why we should completely revisit the way we think about performance.

Winning
A couple of years ago, when I was a Bachelor student in I/O Psychology, I read a book by Jack Welch called ‘Winning’. As Manager of the 20^th century and main driver of GE’s successes, Welch had several interesting ideas about personnel management. More specifically, he wrote that performance at GE could be considered as a normal distribution (black curve on page header). When the X-axis indicates performance level, and the Y-axis represents the proportion of employees with a given performance level, we see that in a normal distribution there are a lot of employees who are average performers, some are very bad performers, and some are truly exceptional or ‘star’ performers. Welch made a lot of effort to reward top performers at GE and seemed to have no trouble getting rid of the poorest performing employees.

Although Welch’s ideas about the consequences of the distribution were perhaps a bit extreme, the ideas about the distribution itself was largely in line with those of the general public and of academics. We all agree that performance follows a normal (or Gaussian) curve, with a lot of employees around the mean of performance, and fewer people performing either exceptionally bad or exceptionally good.

The Long Tail
Around the same time that I was reading Jack Welch’s book, I also starting reading Chris Anderson’s bestseller ‘The Long Tail’. This book explains how some companies (e.g., Amazon) became hugely successful by extending their offer to include not just the most popular items, but also items that were sold less frequently. Anderson argued that the profits to be gained from these less popular items could still contribute greatly to overall profits, especially when such products (e.g., books) are offered online. At that time, probably like every reader of the book, I tried to find Long Tails myself.
Now, as a PhD researcher, I am often surprised by the productivity of some top scholars. Consider for example that fact that the top 25% of management authors account for 55% of publications and 86% of citations, and that 5% of the universities account for 60+% of publications (Podsakoff et al., 2008). As such, there seem to be a lot of researchers with just a few top publications, but only a few researchers with a lot of top publications. Consequently, it seems unlikely that, at least for research productivity, performance follows a normal distribution. Perhaps a Pareto distribution, with its ‘long tail’ (grey curve on header), is more accurate. At the end of the tail, you find the top scholars, who are extremely productive.

From Good to Great … to Below Average

Eric Barends — Thu, 29 Mar 2012 12:05:57 +0000

About ten years ago, my boss strongly advised me to read Good to Great. Have you read it? Chances are you have, as the book has sold over more than 2,5 million hardcover copies since it came out in 2001. In this book, Jim Collins reveals the principles behind company growth, financial performance and shareholder value.

On closer look, however, Collins’ good-to-great principles turn out to be true in the same way a horoscope is true. As David Wyld pointed out, they are fairly generic, and thus we all apply them from our own viewpoint to make them true, which is of course one of the hallmarks of pseudoscience. Additionally, the book is full of relationships that are declared by the author as causal, but may just be correlational, or even coincidental.

The risk for management guru’s who publish books praising “Excellent”, “Visionary” or “Great” companies is that their examples may create hostages to fortune. An obvious example is “In Search of Excellence” by Peters and Waterman, who were yeered and booed by the public when just two years later one third of the firms they profiled turned out to be anything but excellent. Even worse was Gary Hamel’s celebration of Enron, “Leading the Revolution”, which was still arriving in bookstores when the energy-trading company blew up in 2002.

So what happened with the companies which were praised in Good to Great? Well, as you might expected, quite a few companies have since fallen from grace. In fact, all the ‘great’ companies have declined by 43.12%, compared to the average of 41.5% for the S+P average. Additionally, Gillette was sold to Proctor and Gamble, Circuit City filed for bankruptcy and Fannie Mae was bailed out by the government. If you had bought Fannie Mae stock around the time Good to Great was published, you would have lost over 80 percent of your initial investment.

So what can we learn from this? The obvious answer is that there’s not much value in “how to” business books. As Steve Levitt rightly pointed out: “Business books are mostly backward-looking: what have companies done that has made them successful? The future is always hard to predict, and understanding the past is valuable; on the other hand, the implicit message of these business books is that the principles that these companies use not only have made them good in the past, but position them for continued success To the extent that this doesn’t actually turn out to be true, it calls into question the basic premise of these books, doesn’t it?”

Too Good to Be True: Facebook as a Medium to Spread Pseudoscience

K. Wombles — Tue, 27 Mar 2012 19:55:54 +0000

We engage in wishful thinking all the time. Infomercials continue to exist because people continue to buy the products. Diet pills fly off the shelves because we want an easy fix. The HCG diet is popular because, of course, the weight falls off when you restrict your calories to 500 a day–drops be damned.

The problem with this tendency to accept what we hear or read unquestioningly is a huge one, and one that psychologists have long been aware of. In 1990, Daniel Gilbert, Douglas Krull, and Patrick Malone showed that people “easily accept all information before it is assessed, and then laboriously recode the information that is subsequently found to be false.” Most of the time, we simply don’t bother to do that secondary assessment and false information is taken in and then shared with others.

We are constantly inundated with information too good to be true. Mass email forwards of stories that are amazing or horrifying are constantly filling our inboxes; our facebook walls are filled with friends passing along links to sites and stories that snopes.com shows to be clearly false, or that even the site linked to will show. People take satire sites like The Onion to be real, and misinformation spreads.

Another tendency online is that stories are shared and readers don’t notice the publication date and stories that have been debunked for years spread across facebook walls like wildfire. We take on fresh outrage over old stories; we hop on bandwagons because everyone else is. Facebook is a particularly good naturalistic environment to watch the spread of misinformation and the tendency of people to bandwagon in order to tighten their in-group bonding.

So what to do when you’re the hard-core skeptic in the group? Do you always directly point out the misinformation? Do you leave a link on a posting? Or do you do a sidestep of not commenting directly and instead place on your own feed the links that will provide accurate information?

Scientists and Journalists Need Different Things From Science.

Alok Jha for The Guardian — Tue, 20 Mar 2012 05:04:24 +0000

Even scientifically literate journalists could do with some self-reflection. And scientists could benefit from a better understanding of why things go wrong.

It is a truth universally acknowledged that the media, in general, could do a better job of reporting science.

There are plenty of good journalists out there, of course, carefully choosing stories, applying the filters of context, analysis and accuracy and working to ensure stories that contain science – ranging from lifestyle to politics and way beyond – get due prominence in newspapers, magazines, websites and blogs. And there are plenty of good scientists who engage, debate and contribute to the same exercise, albeit necessarily with different intents and from a different point of view.

But there’s a long way to go before anyone could feasibly argue that science is used and understood well by the general media – Ben Goldacre has plenty of grist for his mill yet.

Whose job is it, though, to make things better? I’d argue it’s the responsibility of anyone who believes that a fully functioning democracy requires robust coverage and scrutiny of science. Journalists, even the most scientifically literate ones, could all benefit from some self-reflection. And scientists, even the most media-savvy ones, could benefit from a better understanding of how and why things can go wrong.

What Effect Does Management Humour Have On Problem-Solving?

Laura Krikhaar — Tue, 20 Mar 2012 04:41:00 +0000

As someone who likes to think of themselves as possessing a good sense of humour and the ability to use it well in management situations, my eye was caught by an article from Professor Robert Wood in Organizational Psychology Review.

Robert and his team presented a framework for analysing the role of humour in managerial communications, and I was particularly struck by the ideas contained within problem-solving and face to face meetings.

Managers are warned to be wary of using humour while introducing complex information. Research from mood studies suggests that humour influences the depth-processing of information; and positive humour may lead to effort-minimising, simpler strategies to solve problems. It seems you need to temper your natural sense of humour if you need your team to solve a problem that requires deeper and more complex processing. Although using humour asides will help maintain attention and, therefore, work better when communicating simpler information.

How Leaders’ Personal Attributes and Leadership Style May Affect Followers’ Resistance to Change

Alexandra Rechlin (I/O At Work) — Wed, 22 Feb 2012 17:16:57 +0000

Does your organization go through change? I’d be willing to bet that it does, so you may be interested in what kind of impact leaders have on their followers’ intentions to resist organizational change. The authors of this study investigated how the traits, values, and behaviors of leaders explain their followers’ resistance intentions.

The participants in a recent study by Oreg & Bersom were principals (leaders) and teachers (followers) in the Israeli public school system. The more that leaders were open to an organizational change, the less their followers intended to resist the change. Leaders’ dispositional resistance to change also predicted followers’ dispositional resistance to change.

To measure transformational leadership, the authors assessed the extent that leaders used inspirational leadership, intellectual stimulation, and individualized consideration. As leaders’ transformational leadership behavior increased (especially inspirational leadership), followers’ resistance intentions decreased. The relationship between employees’ dispositional resistance to change and their resistance intentions also weakened when the leaders’ transformational leadership behaviors increased.

So what explains these findings? Read more >

The Danger of Storytelling

Eric Barends — Wed, 22 Feb 2012 16:56:02 +0000

Like all of us, economist Tyler Cowen loves a good story. But in this intriguing TED talk, he asks us to step away from thinking of our lives — and our messy, complicated irrational world — in terms of a simple narrative.

“I was told to come here and tell you all stories, but what I’d like to do is instead tell you why I’m suspicious of stories, why stories make me nervous. In fact, the more inspired a story makes me feel, very often the more nervous I get.

“So again, we should be suspicious of stories. We’re biologically programmed to respond to them. They contain a lot of information. They have social power. They connect us to other people. So they’re like a kind of candy that we’re fed when we consume political information, when we read novels. When we read nonfiction books, we’re really being fed stories. Nonfiction is, in a sense, the new fiction. The book may happen to say true things, but everything’s taking the same form of these stories.”

Correlation Is Not Causation (Part II)

Nathan Green — Thu, 02 Feb 2012 11:19:57 +0000

Repeat after me: correlation is not causation, correlation is not causation, correlation is not causation …

At times during my statistics studies I felt like Jack Nicholson in the film The Shining, in which we witness his descent into madness as he types the same sentence over and over again, “All work and no play makes Jack a dull boy. All work and no play makes Jack a dull boy … ”

“Correlation is not causation” is a statistics mantra. It is drilled, military school-style, into every budding statistician. But what does it actually mean? Well, correlation is a measure of how closely related two things are. Think of it as a number describing the relative change in one thing when there is a change in the other, with 1 being a strong positive relationship between two sets of numbers, –1 being a strong negative relationship and 0 being no relationship whatsoever.

“Correlation is not causation” means that just because two things correlate does not necessarily mean that one causes the other. As a seasonal example, just because people in the UK tend to spend more in the shops when it’s cold and less when it’s hot doesn’t mean cold weather causes frenzied high-street spending. A more plausible explanation would be that cold weather tends to coincide with Christmas and the new year sales.

Ask For Evidence!

senseaboutscience.org — Tue, 03 Jan 2012 10:33:56 +0000

Evidence matters in many of the decisions we make – as professionals, patients, consumers, voters and citizens. If you want to know whether a claim made in a policy, newspaper article, advert or product is backed by scientific evidence, ask the people making the claim to provide it. You can ask penetrating questions about evidence, whatever your experience. You just need an inquisitive mind and a desire to stand up for science in public life.

How do you ask for evidence?

If claims are not supported by evidence get in touch with the company. Companies are often unprepared to be questioned about the claims they make suggesting not many people do ask.

Questions to ask

Ask them about the science behind the claim: What kind of testing has been done (controlled, blinded tests; a clinical trial; lab studies on an ingredient)? What is the mechanism behind the science?
Ask about the status of evidence for the claim: Has the research been peer reviewed and published? Has it been replicated?

Need help?

You don’t need to be a scientist to ask for evidence. Anyone can pick up the phone or send an email asking for evidence behind any claim. But if you need more help, Sense About Science has hundreds of organizations and 5,000 scientists standing by.

How mixing work incentives put us on the horns of a dilemma

Alex Fradera — Wed, 14 Dec 2011 20:51:05 +0000

To encourage collaboration, many organisations structure incentives so that whole groups are rewarded – or not – based on their collective output. However, the groups-eye view allows for social loafing, where people shirk duties and assume team-mates will carry their load, so it’s tempting to keep everyone accountable by adding incentives to individual performance too. Christopher Barnes and his colleagues set out to see just how these mixed incentives turn out in practice.