It's better to give than receive...

There's an old adage that says that it's better to give than to receive.  I used to hear that a lot when I was growing up, particularly around Christmas time!  I actually didn't know this, but the saying comes from a Bible verse from the Acts of the Apostles.  And as it turns out, there's now scientific proof for this statement!  Ed O'Brien from the University of Chicago Booth School of Business and Samantha Kassirer from Northwestern University published a study in the journal Psychological Science (see "People are slow to adapt to the warm glow of giving").  They found that giving to others makes you happier in the long run and that the feeling of joy from giving lasts for a long time compared to the joy of receiving.

O'Brien and Kassirer gave college students $5 for five days in a row with the instructions that they could spend the money however they wished, though they had to spend the money the same way for all five days.  Half of the students were told to spend the money on themselves, while the other half of the students were told to spend the money on someone else.  At the end of each day, students completed a survey that assessed their level of happiness.

As shown in the graph below, the happiness level of students who spent money on themselves declined over the course of the five days, while that of the students who spent money on someone else actually stayed the same.

O'Brien and Kassirer conducted a second experiment, in which the students carried out 10 online word-search tasks, for which they were paid 5 cents.  Again, half of the group had to donate their total earnings ($0.50) to the charity of their choice, while the other half had to keep the money.  This time, the students completed the happiness assessment following each task.  Similar to the earlier results, the happiness level of the students who donated their earnings faded slightly over the course of the 10 word-search tasks, while that of the students who kept their money decreased quickly.

Admittedly, both studies were performed in the highly contrived setting of a laboratory and the study sizes were fairly small (113 students in the first experiment and 502 students in the second).  However, the size of this study was much greater than the famous study of lottery winners (which I've mentioned in the past - see "California Dreaming") that has been continually cited since the late 1970's as proof that winning the lottery doesn't make you happy (and more recent studies actually suggest otherwise).  Just as important, the staying power of the adage "It's better to give than to receive" has to count for something.  So, in my opinion, the results of the O'Brien and Kassirer study are compelling and important.  When it comes to happiness, it is far better to give than to receive...

Chiliad

According to Merriam-Webster's online dictionary, the word chiliad is defined as a group of 1,000.  The ancient Greeks defined a period of 1,000 years as a chiliad, though we now use the Latin derivation and call 1,000 years a millennium.  I chose the title for today's post because I have officially reached 1,000 posts in Leadership Reverie.  

When I first started contributing to this blog on January 2, 2016 ("First blog post"), I never actually thought that I would ever make it to 1,000 posts.  As I stated then, I've never claimed to be an expert on leadership and management.  That is just as true today as it was back then.  However, I consider myself a student of leadership.  Thomas J. Watson, former Chairman and CEO of  IBM for 42 years (1914-1956) said, "Nothing so conclusively proves a man's ability to lead others as what he does from day to day to lead himself."  Leadership has to start by looking inward at what you do with your own life.  As leaders, we owe it to ourselves and our organizations to work hard to perfect our craft.  We all should be students of leadership.

I've always liked the poem "The Road Less Traveled" by Robert Frost.  It's an easy poem to like, as Frost's message is simple and profound at the same time.  You've probably heard it before - it's the one that ends with:

Two roads diverged in a yellow wood, and I - 

I took the one less traveled by,

And that has made all the difference.

I am often asked by younger physicians and leaders what they should do to position themselves for a future career as a hospital executive.  I always chuckle a little (in a respectful way, of course) and confess to them that I never planned out my career with the intent of doing what I am currently doing now.  As a matter of record, I once told my wife that I wouldn't be caught dead being an administrator!  She reminds me of that frequently!  My journey throughout my career has been a road less traveled of sorts, and just as Robert Frost said so eloquently, THAT has made all the difference in the world.

Throughout my career, I've used writing as a way to help me remember things.  And organizing my thoughts on paper has always helped me think, reflect, and prepare myself for whatever challenges lie in front of me.  As I stated in my first post, I would write this blog even if nobody ever read it.  The fact that so many of you have read my posts is both humbling and deeply gratifying.  I thank you from the bottom of my heart.  And I look forward to chiliad #2! 

What would you think about a 12,900% ROI?

Organizations frequently use what is called the Return on Investment (ROI) as a performance metric to evaluate the profitability of a program or investment.  The ROI measures the amount of return (in monetary terms) on a particular program or investment relative to its initial cost.  It's calculated simply by dividing a program's net profit (revenue generated by the program minus the cost of the program itself) by the cost of the program.  For example, an investment that cost $100 and generated $100 in net profit (i.e. over the initial cost of $100) would have a ROI of 100%. Generally, any positive ROI is good.  However, while a good ROI can vary depending upon the type of investment, the target ROI in most cases is generally in the range of 5-10%.  

So what would you say about a program or investment that generated a 12,900% ROI?  That would be incredible, to put it mildly.  That is exactly the ROI that a group of Stanford students achieved on a project several years ago that has lessons for all of us today.  Back in 2009, Stanford professor Dr. Tina Seelig placed her students in the Stanford Technology Ventures Program into 14 teams and gave each team an envelope that contained $5 of "seed funding."  Each team had five days to develop any idea that would generate money.  Once they opened the envelope and officially received their "seed funding", they had 2 hours to execute that plan and generate as much money as possible.  

Each team was asked to send Dr. Seelig one slide describing their project, and she then gave each team 3 minutes to present their project to the rest of the class.  She heard several different ideas, including "Going to Las Vegas" or "Purchasing a lottery ticket" (both with the potential to generate a significant ROI, though with a small chance of actually generating any return).  She also heard about projects that set up a car wash or a lemonade stand, which all generated a positive ROI, even if fairly small.    

Dr. Seelig said, "Most of my students eventually found a way to move far beyond the standard responses.  They took seriously the challenge to question traditional assumptions, exposing a wealth of possibilities in order to create as much value as possible."  Dr. Seelig further explained (see her video here), "The teams that made the most money didn't use the $5 at all.  They realized that $5 was actually a limitation.  They realized that framed the problem way too tightly, and if they looked at the skills they had and the opportunities around them, that was worth a lot more."

Here are some of the more innovative projects:

• One team used the $5 to purchase several inexpensive items at a discount store and then tried to re-sell them for a profit.
• One team set up a stand in front of the student union and pumped up bicycle tires for $1. Actually, this project was so successful at first that they switched from a fixed pricing model and asked for donations instead.  Their income soared.  Dr. Seelig said, "The iterative process where small changes are made in response to customer feedback, allowed them to optimize their strategy on the fly."
• One team booked reservations at popular restaurants and then re-sold their places in line to people eager to skip the wait. This particular team also iterated quickly.  Male team members ran around town making reservations, while the female team members did the "selling" when the team noticed people were more comfortable being approached by women than men.  The team also discovered that focusing on restaurants that provided buzzing pagers was more profitable - physically switching one pager with a long wait time for one with a shorter wait time made people feel they were receiving something tangible (and also gave the team members another reservation that they could sell).

Each of the projects listed above generated a few hundred dollars.  However, the team that did the best generated $650 for a 12,900% ROI!  The students on this team determined that the most valuable asset that they could sell was their three-minute presentation time scheduled the following class day.  They decided to sell that 3 minutes to a company that wanted to recruit students in the class.  The team created a 3 minute "infomercial" for the company and showed it to all the other teams in the class.

Here is my take.  First, learning through experimentation and iteration based upon experience is absolutely essential to the success of any project or business venture.  Second, "thinking outside the box" drives innovation.  Third, challenging assumptions and avoiding framing a problem too tightly can often lead to low-risk / high-reward actions that generate incredible returns.

How to avoid criticism

I came across a great quote by the ancient Greek philosopher Aristotle.  He said, "There is only one way to avoid criticism. Do nothing. Be nothing. Say nothing."  That's it.  That's the post for today.

Handle With Care

There's a great song by the rock-n-roll supergroup The Traveling Wilburys called Handle With Care.  I remember when "Handle With Care" was stamped across cardboard shipping boxes to alert everyone that the contents within the box were fragile ("It must be Italian!").    I've been thinking a lot about the concept of "fragility" lately, particularly in the context of systems thinking.  The writer Nassim Taleb wrote a book called Antifragile, in which he defines "antifragility" as a property of systems that increase their capability to thrive as a result of stressors, shocks, mistakes, failures, or disorder.  Importantly, Taleb distinguishes "antifragility" from robustness (the ability to resist failure) and resilience (the ability to recover from failure).  I've not read any of Taleb's books (see my post "Anti-Library" for an explanation), and while I don't think he explicitly defines "fragility" as a concept of systems, I suppose that he implicitly would define a fragile system as one that performs worse as a result of stressors, shocks, mistakes, or failures.

With that in mind, I would describe our nation's commercial aviation infrastructure as "fragile". That is particularly painful for me to say, as commercial aviation is one of the prototypical High Reliability Organizations, at least when it comes to aviation safety.  Consider this.  Literally millions of computers running Microsoft's Windows operating system crashed this past Friday (July 19th) when the cybersecurity company CrowdStrike updated its software, causing widespread disruptions in airlines, banks, hospitals, and hotels.  For the next four days, thousands of commercial flights into, within, or out of the United States were canceled.  Those flights that weren't canceled experienced significant delays.

I have firsthand knowledge of these issues, as our family's flight from Seattle to Chicago on Saturday was canceled at the last minute (we were literally getting ready to board).  The airline representative told us that we would likely not be able to get on another flight until Wednesday this week.  Thankfully, we were able to get the last seats on a flight to St. Louis (thank you Alaska Airlines!), at which point we rented a car and drove to Chicago.  Our bags are still somewhere in Seattle, and who knows when we will see them again.  The Seattle airport was an absolute mess!

Hopefully we will learn from this incident.  As I reflected this weekend, it seems that flights are canceled more frequently now than they were in the past.  Even The Traveling Wilburys know about flight cancellations and delays (it says so right in their song Handle With Care - "Been stuck in airports..." they say).  However, when I reviewed the data, the number of cancellations have actually decreased over the past twenty years.  It may be that there are just more flights now than in the past, or maybe I fly more frequently now than I did in the past.  Who knows?  But as I think about this issue from a systems perspective, one thing is clear.  As the different subcomponents in a system become more tightly coupled, they become less resilient and more fragile.  There's no question that today's commercial aviation industry is highly complex, interconnected, and tightly coupled.  Under these conditions, the safety researcher Charles Perrow would suggest that accidents and disruptions are not only more common, they are inevitable - in essence, they are normal (see my post, "The Razor's Edge" for an explanation of Perrow's Normal Accident Theory).  

Fragility is an interesting concept and relatively easy to understand.  From a systems perspective, however, it is far more difficult to address.  The difficulties that our family (and many, many others) personally encountered in the aftermath of the CrowdStrike network outage is just the latest example.

"All life is an experiment"

Natural experiments have been around for a long time in public health research.  They are defined as observational studies in which an event or situation occurs allows for the seemingly random assignment of study subjects to different groups to be leveraged to try to answer a specific question.  Importantly, natural experiments are used when the traditional method of a prospective, randomized, controlled study is not feasible, due to financial, logistical, or ethical reasons.  Perhaps Ralph Waldo Emerson had natural experiments in mind when he said, "All life is an experiment.  The more experiments you make the better."

Perhaps the greatest natural experiment of all was that of the founders of the United States, who designed a form of government that they referred to as an experiment.  For example, Thomas Jefferson said, "I have no fear that the result of our experiment will be that men may be trusted to govern themselves without a master."  Notably, still to this day, politicians refer to the American system of government as an experiment!

Susanna Galli and colleagues conducted just such a natural experiment, which they discussed in a Harvard Business Review article (see also their working paper "Incentives, Peer Pressure, and Behavior Persistence"), "Incentives Don't Help People Change, but Peer Pressure Does".  Galli and her team took advantage of a particular set of circumstances to try and answer the age-old question on whether financial incentives can be used to help change behavior.  They studied the impact of a one-time employee incentive bonus on hand hygiene compliance at one California hospital.  Hand hygiene is one of the most effective ways of preventing the spread of infections in the hospital setting.

The California hospital used a team of "secret shoppers" to directly monitor hand hygiene compliance over a 90 day period.  Employees received biweekly progress reports on hand hygiene compliance.  If a specific target was achieved by the end of the 90 days, all employees would a one-time $1,200 bonus.  Uniquely, California is one of a growing number of states that employ what is known as a "corporate practice of medicine law" that prohibits hospitals from directly employing physicians.  Instead, hospitals form contracts with medical groups that employ the physicians.  As a result of this situation, physicians would not be eligible for the one-time $1,200 bonus.  At the same time, however, the hospital's hand hygiene compliance, and most importantly, the ability of the hospital to achieve the target performance that would trigger the one-time bonus, was highly dependent on physician hand hygiene compliance.  

Hospital employees (nurses, allied health professionals, etc) came up with creative ways to encourage physicians to comply with good hand hygiene practices.  For example, employees who observed physicians that demonstrated good hand hygiene practices would send celebratory emails and hand-written notes to the individual physicians.  Conversely, employees would send reminders and "nudge" emails to physicians who failed to practice good hand hygiene.  

On average, hospital employees significantly improved their hand hygiene compliance at the end of the 90-day intervention period.  They met their target and received the monetary bonus. Unfortunately, however, improved hand hygiene was short-lived, as compliance slowly fell towards historical levels and in some cases even lower levels!

Again, physicians weren't eligible for the bonus incentive.  However, hand hygiene compliance improved slowly but significantly in physicians too.  More importantly, the improvements continued even after the 90-day intervention period.  In summary, then, providing a financial incentive certainly changed behavior for the better, but the improved behavior was short-lived.  Peer pressure resulted in similar degrees of improvement in behavior, though the improvements were sustained beyond the intervention period.  

I've talked about this study in the past (see "Wash Your Hands!"), particularly in the concept of extrinsic motivation versus intrinsic motivation.  What's important to realize here is that so-called natural experiments are frequently used in the management literature to answer questions that may not be amenable to traditional methods of research.  As suggested by Emerson, "all life is an experiment."

"In theory, there is no difference between theory and practice..."

My wife and I watched the Netflix documentary ("It Ain't Over") on the legendary New York Yankees baseball catcher Yogi Berra the other night.  I highly recommend it!  There was a segment of the documentary that questioned why Berra wasn't included among the four greatest living baseball players (Willie Mays, Johnny Bench, Sandy Koufax, and Hank Aaron), as voted by the fans and announced at the 2015 MLB All-Star Game in Cincinnati, which my wife and I were lucky enough to attend!  While I did not participate in that vote, I told my wife that had I voted, I probably wouldn't have thought to vote for Berra either (I regretfully admit that I actually wasn't sure that he was still alive then).   

Today Berra is remembered more for his so-called Yogi-isms than his prowess as a ball player, which is both unfortunate and unfair.  He is arguably one of the greatest catchers to ever play the game, and he should rank right up there with some of the all-time Yankee greats.  He played 19 seasons in total, eighteen of which were with the Yankees.  He was selected to the MLB All-Star game 18 times, won the World Series as both a player and manager/coach 13 times (out of 21 total), won the American League Most Valuable Player three times, and had his number 8 retired by the Yankees.

So I feel a little guilty using one of his Yogi-isms as the title of today's post, but I do so with the greatest of respect for who he was as a player, manager/coach, and person.  While there's no evidence that he actually ever said it, the Yogi-ism goes like this, "In theory, there is no difference between theory and practice, but in practice there is..."  It certainly sounds like something Yogi Berra would say!  Regardless of its origin, it's a great quote!

There is a clear difference between the idealized state, where several different variables can be controlled as much as scientifically possible, and the real state, where we simply cannot control what happens.  We see this over and over again in research, where therapies that appear to be quite promising in early-stage clinical trials, end up falling far short of expectations in later and larger clinical trials.  Here is one of the reasons why I like quality improvement science so much.  Rather than trying to control all of the variables, we observe a system and follow what happens when we make small changes to it, which, in essence, is very similar to what clinical research does, right?  

Rather than trying to control the dependent variable by controlling for all of the independent ones, quality improvement science observes what happens to the whole system over time, using statistical process control.  If you plot the outcome of interest on the y-axis over time on the x-axis, you basically have what is called a run chart.  Even if you've never heard of a run chart, there is a good chance you have seen one before.  Daily fluctuations in stock prices are often depicted as a run chart.  For example, take a look at the run chart below of the S&P 500 price fluctuations during a certain period of time:

Even though there was a clear decrease in the S&P 500 on February 2, 2014, it doesn't appear that it has changed all that much from the beginning of January, 2014 to the beginning of April, 2014.  Traditional methods used in clinical research today would arbitrarily select a certain time period, calculate the mean and standard deviation values, and compare using a specific kind of statistical test.  But what time period do you use?  Let's look at two different ways to analyze the data above - the top graph is the monthly average while the bottom graph is the price at the start of each month:

The two graphs look very different, don't they?  The top graph makes it appear that there was an increase in the S&P 500 from February to March, which was sustained in April.  However, the bottom graph makes it appear that the S&P 500 during February was very different compared to the other three months.  Either conclusion in this case would be wrong - go back and look at the run chart in the original graph!  There really is not that much of a change in S&P 500 over the time-period of interest!

How would we know whether there was a change in the S&P 500 over time?  For this, we would need to plot the data using a control chart.  Control charts are run charts that have a couple of important and additional features - a trend line (usually the median) and upper / lower control limit lines (calculated using specific formulas, depending upon the kind of data that you have) - see the example below:

   

With control charts, there are specific rules (often called "Western Electric Rules", because they were first developed and used by the Western Electric Company in the late 1950's) to determine if there is common cause or special cause variation.  "Common cause variation" suggests that a process is stable and in control - any variation in the data over time represents normal fluctuations that often occur (such as the beat-to-beat variability in your own pulse when you are sitting down while reading blog posts!).  In contrast, "special cause variation" occurs when the process is unstable or out of statistical process control due to a specific or unique circumstance (going back to the previous example, the increase in your pulse when you go out for a run around the block on a hot day). 

If we used statistical process control rules ("Western Electric Rules") in the S&P 500 example above, the change in price over time would be shown to represent common cause variation.  Special cause variation would occur if, say there was an economic recession.  If you are interested in learning more about statistical process control, I highly recommend the following three books:

Understanding Variation: The Key to Managing Chaos by Donald Wheeler (no relation)

The Improvement Guide: A Practical Approach to Improving Organizational Performance by Gerald Langley, Ronald Moen, Kevin Nolan, Thomas Nolan, Clifford Norman, and Lloyd Provost

The Health Care Data Guide: Learning from Data for Improvement by Lloyd Provost and Sandra Murray

Statistical process control allows us to monitor changes in our process over time, i.e. in real world practice, as opposed to what happens in the strict constraints of an experiment.  So, "In theory, there is no difference between theory and practice", except for the fact that there is...