Don’t Be Afraid of the Dark

I chided my eleven-year-old son last week on his insistence that the lights in his room be left on at bedtime (ever since seeing the “Ghostbusters” remake this summer.) “Nothing’s going to get you,” I teased him. “Don’t be afraid of the dark.”

“I’m not afraid of the dark … but leave it on anyway.” he urged me.

I will say his twin sister has no problem sleeping in pitch black so it’s obviously got nothing to do with nurture!

Kidding aside, being afraid of the “dark” or the unknown is not just an issue kids grapple with.  When I eschewed a highly-paid respectable career to pursue my dream of starting a consultancy a few years back, I was treated to a virtual smorgasbord of other people’s fears. Friends and strangers helpfully volunteered:

“I would never be able to start my own business. The stress would kill me.”

“Can’t believe you did that. What happens if everybody hates you and money runs out?”

“The problem with me is that I like to see way out into the horizon. You can’t see 2 feet in front of your face in your situation.”

“I would hate to have to scale down my lifestyle at this point.”

And on.

And on.

A lot of people know where they want to go or what they ultimately want to do but are put off by the ambiguous zone in-between their current and future states.  It’s a scary place because we don’t know what’s going to happen on the way. Because it’s dark.

So the question becomes, “How do we navigate this dark zone between where we are and where we want to be?” The answer? “Leave the lights on!”

We need to expose the issues to daylight before we decide they are indeed too big and hairy to contend with.

There are four strategies for assessing the boogeymen that reside in our psyches:

1.      Conduct triage-  I once worked on an improvement project for a large medical provider. Part of the issue was the crazy wait time in their urgent care unit. They were set up with 3 triage areas to process incoming patients. However, the triage process varied greatly depending on the provider manning the desk! The triage wasn’t working as it should. Ask yourself, is what I’m worried about really going to bring ruin to my career or family? Will it potentially cause some short term pain but worth the upside? Or maybe nobody will mock me at all? Are the risks less likely to occur than the benefits are to manifest?

2.      Ask “What’s really the worst that can happen?”– I used to hate giving presentations. But I realized (eventually) that while the audience might indeed disagree everything I had to say, if I provoked thought it was a success. The worst that would happen is a question would be asked that I didn’t know the answer to or that they were bored silly. That’s it. The human mind is second to none in its creativity. What are the specific disasters your brain has concocted for you? Take those, figure out the probability and seriousness of each, and plan preventive actions for the hairiest ones. For extra credit, plan a contingent action for the one you are most worried about in case your mitigating plan falls flat.

3.      Recognize the horizon problem–  I’ve always loved the ocean, having grown up not far from the beaches of South Carolina. As a kid, I always marveled at how far I thought I could see into the vastness of the sea. I later learned the average adult standing at sea level looking at the ocean horizon can only see 3 miles before the curvature of the earth interferes with seeing further.  Thus, the horizon problem: you can only see so far.  Those that take risks in life are faced with low visibility- that’s just part of the deal. But just because you can’t see very far out doesn’t mean there aren’t good things just around the bend. It’s just that you don’t see them yet.

4.      Resist natural inclinations– I had a person who once worked for me admit a during a performance review: “When I get scared, I get very defensive and I WILL lash out.” What’s your tendency when faced with adversity or darkness? Realize that most issues are merely actions to be properly categorized. They are usually:

a.      A problem that just needs to be solved

b.      A decision that just needs to be made

c.      An implementation that needs to be carried out

d.      Priorities that should be clarified and managed

The list above offers personal examples of how to make needed change happen. Your examples will differ but the fundamental questions are the same:

What are you afraid of in the dark?

Is it really there?

That being said, my eleven year-old still keeps the light on.

Are We Too Biased for Our Computer Overlords?

The starting NFL quarterback has had a great partial week of practice but, by the end of Wednesday, the coaches decided to tweak the next day’s drills in response to something they see in a sensory download report. The tackle sensors implanted in the pads that log direction, energy, muscle responses and other bio metrics indicate an abnormal change in recovery performance in the trapezium muscles after a vicious hit last Sunday. At precisely with 8 minutes and 31 seconds remaining in the 3rd quarter. The coaches will hold him out of plays that involve passing later in practice and the trainers will modify the physical therapy routine.  As it turns out, the QB plays deep into the next game and doesn’t miss any games for the season.  A successful intervention.

Algorithms that log data like this in sports science have mushroomed to two-thirds of all NFL teams and more than half of the NBA since 2012. Getting to this level of analytics not only serves the players well but also the fans, sponsors and teams.  Using data technology to spot potential opportunities and risk areas will continue to evolve and impact the way teams practice, game plan and substitute.  Those teams that don’t will be at a decided disadvantage.

North American sports are just catching up to the rest of the world in this respect.

Likewise, analytics is the working its way into how we market, operate and distribute as well.  Like the wave of Lean Manufacturing or the wave of outsourcing, U.S. business is now in a productivity wave- headlined by Big Data.  One of the more staggering statistics I have heard just appeared in a recent McKinsey & Co. publication. It stated one-half of all the world’s data was just created in the past 10 months.  Put another way, of all the data that mankind has EVER produced…half of it has come this year!

However, like North American sports, most businesses are having problems adopting to this. One of the issues is that despite paying to create lots of data, businesses are actually capturing very small amounts. Secondly, what is being captured is really not being used.

Does this sound familiar? It should, because we are all wired this way.

When I worked for a large consulting firm, we were trained to recognize the most commonly occurring human biases that influence our judgements and those of our clients. A few of the most well-known biases we exhibit include:

  • Confirmation bias, which refers to a type of selective thinking whereby one tends to notice and to look for what confirms one’s beliefs, and to ignore, or undervalue the relevance of evidence that contradicts one’s beliefs. For example, if you believe that your favorite football team wins big games when wearing orange pants, you will take notice of games played in orange pants, but be inattentive to the uniforms when momentous victories occur with other combinations. (This is sadly a personal example.)
  •  Mere exposure effect is the tendency for people to develop a preference for things merely because they are familiar with them. People will frequently select an alternative simply because they have seen it before, not because it’s the best answer.  It’s because of this bias we are forced to ensure the overused business axiom: “Think outside the box.”
  •  Outcome bias refers to the tendency to judge a decision by its eventual outcome, instead of judging it based on the quality of the decision at the time it was made. For example, a basketball player takes an ill-advised shot with plenty of time left on the clock and holding on to a narrow lead. The shot was a poor choice, regardless of whether it actually falls or not. This decision should be viewed negatively in both cases, but in reality he generally only gets yelled at if something bad happens.
  •  Actor-observer bias refers to a tendency to attribute our own poor outcomes to external causes that can’t be controlled, while attributing other people’s misfortunes to personal reasons. For example, imagine that you are getting ready to take a standardized test to get into graduate school. You fail to observe your own study behaviors (or lack thereof) leading up to the exam, but focus on situational variables that affected your performance on the test (i.e. the room was hot and stuffy, your pencil kept breaking, the student next to you kept making grunting noises, etc.) So when you get your results back and realize you are definitely not getting in to any grad schools, you blame those external distractions for your poor performance instead of acknowledging your own poor study habits. Of course, one of your buddies also did poorly, but you immediately consider how he often skipped prep class, never practiced, and never took notes. Never mind the same conditions.
  •  Illusory correlation refers to the concept of relating two variables even when they are not related. For example, drownings in lakes have been shown to increase when sales of ice cream go up. Therefore, the government earnestly tries to outlaw any and all ice cream products.

A review of the complete list of 105 (search Google for “cognitive biases”) leaves little doubt that in many complex decisions we see what we want to see. Relying on output from a decision support tool like a linear program for situational answers goes against our instincts.

However, there is a clear path to riding this new wave. A large part of the success rides on our ability to override our natural tendencies.

Go beyond gut instinct for doing business. Nobel Award winner Daniel Kahneman, in his terrific book titled Thinking, Fast and Slow, describes our two modes of thinking; what he calls “System 1” which is automatic, instant, intuitive and involuntary, relying on our perceptions of our knowledge and experience; and “System 2” which is more structured, controlled, analytical and effortful.  Because System 1 is automatic and requires little or no effort, we have a natural bias towards its use.  This leads us to sincerely believe a rational choice has been made, when in fact it was not!  We are often unaware of the powerful influence System 1 thinking has on our decision making and its potential for leading an individual or an organization astray.

Decisions have to be analytics oriented. Advanced analytics is the latest term for a concept that has been in use since WWII. To the computer scientist, it is called artificial intelligence; to economists it is modeling; mathematicians call it game theory; business people may use “optimization”. Whatever the term, it is a decision making process that employs mathematics, algorithms and software not only to sort and organize data, but to use that data to make recommendations faster and better than we can.

Some businesses have recently experienced the advantages of sidestepping these biases and using advanced analytics to support their business decisions. For example, a large international manufacturer operating at 100% shipping capacity was wrangling with decisions on which distribution hubs to close or expand as well as which plants should ideally supply them to maximize profits in the current environment.  After optimizing the network, the company could clearly see the benefits of switching supply sources in 6 scenarios and doing so with less purchased rail cars in the process. In addition, potentially new distribution locations were added to the mix and the overall network profitability was re-quantified.  From a cost savings perspective, the results amounted to 4% in bottom line improvement, not to mention to the role optimization played in evaluating their next acquisition.

According to one executive:

“We have been using [the linear program model] a lot, to get better information as to what we can do and if we’ll get any transportation synergies out of the deal. I have to tell you that it’s been really useful. I don’t know what we’d be doing without it…probably just looking at each other and coming out with clever answers (or maybe not that clever) just to get out of the problem of not knowing how to answer to a question.”

Overcoming our natural tendencies in complex decision making is not an easy step to take, especially when it involves relying on analytics that are faster, smarter and bias free.  Analytics has infiltrated our sports and is the latest in business operations. Is this the end of us and the beginning of the Age of the Machine?  Probably not quite yet. But just in case, to steal a line from the Simpson’s:

I, for one, intend to welcome our new robot overlords.

3 Surprising Things About Change

“What’s the use of having all these good ideas if we can’t do them?”– Exasperated Executive.


Some people can get their way by fiat: do this or else. CEOs can sell off divisions, hire people, fire people, send them to Siberia, etc. Politicians and judges legislate the changes they want and send resistors to jail if they don’t comply. The rest of us don’t have these tools and have to get a lot more creative to get others to enact change. Many organizational experts prescribe the answers to change management through complex performance system charts and tertiary personality diagrams that probably make sense on an academic level but not in the trenches.

Does it really have to be this hard and expensive?

In the terrific best-selling book titled Switch: How to Change Things When Change is Hard, the authors describe a practical framework birthed after decades of scientific research that is simple enough to remember. They rightfully acknowledge that this framework isn’t an all-encompassing panacea. However, they provide many real life examples of how using these principles resulted in getting buy-in.  And somewhere along the way, they discovered three surprises about us.

What looks like resistance is usually a result of a lack of clarity.

How many of us have vowed to “eat healthier” or make more money? Despite our internal willingness, how easy is this over the long term? For most, not very. Instead, we are urged to break the goal into doable action items: get Greek yogurt instead of ice cream, aim to hit your best demonstrated OEE for the year for an entire week straight, spend 1 hour per week more on the more profitable accounts and less time on generating new ones, etc. Identify performances that have been achieved in the past and challenge them to repeat it. Then, ramp up to a higher frequency.

What looks like laziness is often exhaustion.

Find the motivating pressure points. Sometimes, all it takes is a physical prop like a picture of a goal or a running meter that shows how much money the group is losing per hour. Other times, the folks are just trying to do too much at once. Researchers have found that self-control is an exhaustible resource, just like your muscles after doing 20 squats at the gym. So when the emotional part of the brain gets tired and starts thinking things like “it’s too hard, we’re no good at this”, the analytical part of the brain doesn’t have the strength to yank on the reins and keep pushing through the change. When people exhaust their self-control what they are really exhausting is their ability to push forward in the face of frustration. It’s your job as the change agent to recognize this and keep the muscles fresh.

What looks like a people problem is more times than not a situational problem.

Some people are just lazy and you need to get rid of them; let them go work in an environment that suits laziness. If it’s a people issue, then it obviously has to be addressed. Below is a three step process the president of an international manufacturer always follows when dealing with a people issue:

  1. Should the person be on the bus? If NO – end discussion and deal with the root cause. If YES then move to 2.
  2. What seat are they in? Why isn’t it working? Skills mismatch, training, etc? Peter principle?
  3. What seat SHOULD they be in? Let’s adjust.

The rest of us really do want to do a great job and excel. But there are situational factors that can get in the way of thinking clearly or staying disciplined when implementing change. One way to eliminate these factors is to tweak the environment. Is the regular office so busy and filled with constant interruptions that the team can’t focus for even short periods? Is the corporate culture in direct odds with the goal? Does your spouse really want to get his blood pressure down but you notice he will eat an entire large pizza if he can sit in front of the tv while doing so? While you are at it, take a look at how your reward people: Does the top selling sales person win a one on one dinner with the CEO? (Would he consider that a punishment?) What can be tweaked in what you are doing now to make implementation easier?


Simply put, change has to do with creating a downhill slope and giving the people a push. John Wooden once said, “When you improve a little each day, eventually big things occur… Don’t look for the quick, big improvement. Seek the small improvement one day at a time.”

That’s the only way it happens- and when it happens, it lasts.