The Greatest Own Goal or the Greatest Collapse

The Greatest Own Goal or the Greatest Collapse

Last week saw the birth and collapse of the European Super League (ESL). Living in Atlanta, to me, the defeat was on a par of the Falcon’s 2017 Superbowl and Greg Norman’s 1986 Masters. On Sunday evening, there was the announcement of the formation of the ESL, comprising 12 “founding clubs” from England, Spain, and Italy. Three other unnamed clubs were soon to join, along with another five teams that would qualify annually for the 20-team competition. Within 48 hours, it was dead!

The announcement of the ESL was accompanied by a promise to “deliver excitement and drama never seen before in football,” and did they deliver!

Why was the ESL formed?

Why? Simply, MONEY. The fifteen founding clubs were guaranteed a place every year with no messy football stuff like qualifying and relegation! The teams would capture a larger share of the revenues with less risk. Expectations were that broadcasting rights might generate €4bn a year, nearly double the €2.4bn brought in by the Champions League in the 2018-19 season. 

As Martin Baumann put it, “We can sell just about anything to the Europeans. Why not our hyper capitalistic cartel-based pro sports system?” That sentiment seems very popular on this side of the Atlantic. Many other commentators pointed out that the owners sought profits before tradition, financial opportunities before culture, and self-interest before communal identity. The ESL was the logical outcome of the increasing commercialization of football and powerful few’s desire for monopolistic control. To enable the ESL, J.P. Morgan underwrote its formation with a $4 billion line of credit. 

While I like capitalism, I find it interesting the claim that this is capitalism. So saying ignores a couple of the mainstays of capitalism – no monopolies or cartels and creative destruction. The owners were not imposing an American capitalistic system on football; they sought to create an American-style cartel to reduce risk and transfer more money to themselves. This has just been done with F1 under the ownership of Liberty Media, turning the ten existing teams from car manufacturers into holders of very valuable franchise charters. Of course, technology development will slow, and the product quality fall. But we can’t let that get in the way of making money.

American sports competitions, especially the major leagues, are all effective money-producing cartels. Professional sports leagues in the United States are monopoly-like structures that ensure that the riches are spread evenly among a self-selected group. The teams stay in the league no matter how they perform. So much for the American ideal of meritocracy! 

The only economic competition they face is from rival leagues; that is why the U.S. system is a century-old marketplace of rival sports leagues. The combination of less risk and less competition for talent produces higher profits for owners. According to a ranking last year by Forbes magazine, forty-three of the world’s 50 most valuable sports teams are American – aren’t cartels wonderful! Such a structure has several results:

  • “Brand value” is not necessarily tied to on-field success. The “worst teams” in one season get the best players through draft picks the following year. 
  • It provides an inferior product, as I have discussed before. Guaranteed a place in the league means there is no need to invest in the team and deliver a good product for the fans. Recognition that the product is inferior is reflected in U.S. sports capturing a smaller share of the global viewing audience each year. 
  • It delivers more money to the billionaire owners, who theoretically have invested in the clubs. In every American sport, an inferior on-field product isn’t a reason for billionaire owners to make less money, e.g., Tampa Bay Buccanneers. The Bucs, I believe, have the worst record of any team in the NFL, even though they have two Super Bowl titles – 278-429-1. With such a record, they would have probably been relegated in European sports and no chance at any championship.

For those unfamiliar with relegation, unlike American teams, European sides play in open leagues, where the three poorest performers get demoted to a lower tier, with stingier broadcasting and sponsorship deals. The three top performers in the lower leagues get promoted to a high league reaping greater rewards. Club owners thus gamble on making it to the top, investing generously at the expense of profits.

The European model is genuinely a capitalistic one where owners take risks and invest for a potential reward. Creative destruction is evident: between 1992 and 2014, there were 45 insolvencies in the top three tiers of English football, 40 in France and 30 in Germany. 

So why did the ESL collapse? 

I believe it was because of hubris. Through hubris, the founders ignored the sport’s business model and Ben Horowitz’s sage advice, “Take care of the People, the Products, and the Profits— IN THAT ORDER.” 

Hubris

Hubris is a terrible thing and causes many failures in life and business. Only hubris can cause a few rich people to come up with an idea that generates such visceral and universal hatred, or put another way, Never underestimate the incompetence of people.” The hubris of the American owners that they could easily impose the U.S. system on European clubs showed that they were willfully ignorant of an alien culture.

Value Creation

Value creation is about “the job to be done” for the customer. The league claimed it would be an exhibition of elite football. However, with no qualification, the teams would not have had to try very hard and thus reduce the value of the “job to be done.” However, even more concerning was that the league’s criteria were not based on being the best in Europe but merely the richest. Once a world power, Arsenal is barely one of the best in England and just a bougie to Newcastle United. Arsenal currently sits ninth in the Premier League table, out of reach of Champions League qualification, and likely to miss out on the less lucrative Europa League as well. Choosing the clubs by the wealth of the owners killed any pretense at value creation.

Marketing

The key to marketing is delivering on your brand promise. The brand promise in European sports is the promise of the club’s success. The basic unit is the club in European sports, which tends to be much older and more locally rooted than any franchise and far more fervently followed. Many clubs are over a century old and ripple with local associations and mythologies. For those who want a greater understanding, I would suggest watching Sunderland Til I Die.

Not only is the club the basic unit, but there is a “holy trinity” in a football club, the fans, the players, and the manager. The owners are there to invest and collect profits. Unlike in the U.S., when a team wins a championship, the owners are never seen lifting the trophy, only the players and the managers.

Sales

The key to sales is to know your core customer, the FANS. The fans were not amused, to put it bluntly. Unlike peripatetic American sports fans, English football clubs’ fans are even more zealous and less forgiving. The Glazers, Stan Kroenke, and John Henry were pretty much despised by the fans of Manchester United, Arsenal, and Liverpool, respectively, before the ESL. If they were unaware of this, the fans that welcomed the Glazers to Manchester chanting “Die, Glazers, die!” should have been a hint. The ESL announcement only made things worse. Liverpool fans were burning effigies of John Henry outside Anfield. A banner outside Old Trafford read, “Created by the poor, stolen by the rich.” A YouGov poll found that 79% of British football fans opposed the Super League, 68% of them “strongly.”

There have been massive protests by Chelsea, Liverpool, Arsenal, and United fans at Stamford Bridge, Anfield, The Emirates, the Carrington training ground, and Old Trafford within the past 5 days. All the fans have been complaining about the money taken out of clubs rather than investing in them. Opposition was fiercer still among fans of clubs outside the ESL, some of whom burned Liverpool shirts. However, American billionaires excel at ignoring public outrage. Kroenke and the Glazer family might’ve waited out the protests until kingdom come. However, the rest of the founders abandoning the ESL gave them no choice.

Value Delivery

The key to value delivery is keeping the customer satisfied which in European sports is RIVALRY. The rivalry between teams is local, not leagues as in the U.S. Liverpool’s main rival is neither of the Manchester teams but Everton, a mile from Anfield. The ESL would have removed these rivalries. Further, ESL was not designed with these in mind, but for millions of foreign fans, in Asia and America who care less about such details. In European football, this was heresy. But overall, the ESL would have stopped the key rivalries that make European football what it is and thus reduced value delivery.

The Outcome

There were apologies all around. John Henry issued a groveling apology to Liverpool’s fans: “I’m sorry, and I alone am responsible.” This is something I don’t any U.S. fan has heard from an owner. Also, JP Morgan has apologized, which shows how much it has realized that its role might damage its chances of getting business in Europe. However, apologies are the least of the owners’ issues as hubris takes its toll. The speedy collapse presents an opportunity for the wider community [members of the Premier League] to drive a harder bargain during the auction of a new round of Premier League broadcasting rights. The result is that the ESL founders may receive a small cut this year.

However, the real threat is regulation. Boris Johnson, Britain’s populist prime minister, read the tea leaves and thus vowed to “do everything I can to give this ludicrous plan a straight red [card].” Oliver Dowden, Britain’s sports minister, wants to examine everything to stop the new league, from competition law to governance reform. His words, “Owners should remember that they are only temporary custodians of their clubs; they forget fans at their peril,” should be a stark warning. Also, the British government launched a wide-ranging review into how football is run this run. There is pressure for British clubs to adopt the German community-ownership model with fans owning 51 percent. While some point out that fan ownership did not dissuade Barcelona and Real Madrid from joining, the Spanish and Italian leagues’ financial health is more impoverished than England’s.

Who says football is boring?

 

Copyright (c) 2021 Marc A. Borrelli

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I often hear a variant of this in meetings with business leaders, when discussing their employees or the actions of their direct reports: “Why don’t they use common sense?” As Abraham Lincoln supposedly noted, “God must have loved the common man because he made so many of them,” then, surely, most of the decisions involve common sense.

We all think that all it takes is common sense; however, we all decide based on the information we have and the guides we use to make those decisions. Thus, for people to make better decisions, we need to ensure that they:

  • Are solving the right problem.
  • Have all the available information.
  • Know the “Intent.”

 

Solving the Right Problem

The first person to state a problem rarely has the best insight into the issue. However, once a problem is defined, our problem-solving and “get it done” nature kicks in, and we dive straight in. We don’t stop to ask, “Are we solving the right problem?” As a result, many decisions made solve the stated problem, but not the right one.

To prevent solving the wrong problem, make sure of the following:

  • You defined the problem and not someone else.
  • You are close to the problem.
  • You are thinking about the problem from many levels and angles.

 

Have all the Available Information

Having all the available information is challenging; however, I look to two military people to guide me. First, David Marquet, whose great advice is, “Move the decision-making to the information.” This ties in with being close to the problem above. So, move the decisions to the front lines, where people with all the available information about the situation are. The second person is John Boyd and his OODA loops, which I have written about before. OODA means Observe, Orient, Decide, Act. I would say that having all the available information is a combination of Observe and Orient.

 

Observe

Here the purpose is to observe the situation to get the most accurate and comprehensive picture possible. Information alone is not sufficient; we need to take the data and put it into context. The real skill here is identifying what is “noise” and thus irrelevant for the current decision. Ensuring you can put all the information in the correct context requires asking questions to build a comprehensive picture.

At a simplistic level, this reminds me of two stories.

A little girl asked her mom where she came from. The mother responded with the full explanation of the birds and the bees. The little girl looked a little confused, so the mother asked why? “Well,” said the little girl, “Jill next door says she is from New York.”

A car stops next to someone walking down the street, and the driver asks for directions to the nearest interstate. The pedestrian responds with directions, and the driver goes off. However, the pedestrian should have asked, “Where do you want to go?” The interstate may not be the best solution or the quickest for where the driver wanted to go.

In both cases, questions upfront result in a better answer as they help understand the issue. However, we are programmed to answer, not to question!

 

Orient

Orientation is seeing the world as it is and removing the influences of cognitive biases and shortcuts. If you properly orient yourself, you can overcome disadvantages from less information or fewer resources. However, there are four barriers to the ability to orient effectively.

  1. Cultural traditions. Much of what we consider universal behavior is culturally prescribed.
  2. Genetic heritage. We all have certain constraints.
  3. Ability to analyze and synthesize. We fall back on old habits if we are faced with new types of thinking.
  4. The influx of new information. If the environment keeps changing, it is hard to determine what is going on.

To overcome these barriers, Boyd recommended “deductive destruction,” a process of understanding our biases and assumptions and developing mental models to replace them.

As Boyd put it, “Orientation isn’t a state you’re in; it’s a process. You are always orienting.”

 

Know the “Intent.”

You will notice that I didn’t say know the “Rules”, as I feel rules are too limiting. They tend to prescribe an exact situation, and if the situation changes, then a new rule is needed. Also, rules are easy to get around. Knowing the intent is a broader guide but makes it easier to understand.

A great example was GM when Mary Barra changed the corporate dress code. GM’s dress code was ten pages long, trying to cover everything. As a result, it was complex, and I doubt anyone read it. However, Mary Barra decided to change it to “Dress appropriately.” Before the change, someone would have to go through ten pages of rules to determine if an outfit met the code; now, they have to decide whether it meets the intent. Now Dress Appropriately on its own may have caused a few issues, but in discussions among teams to explain the purpose, it didn’t take long for everyone to understand what was required.

So, when I ask CEOs and business leaders, do they have organizational clarity, they respond, “Yes.” But when I ask the following:

  • What is your BHAG?
  • What is your passion?
  • What are your core values/expected behaviors?
  • Why do you exist?
  • What is your Strategy in a sentence?
  • What is your Brand Promise?
  • Who is your Core Customer?
  • How do you make money in a sentence?

Often, they cannot answer all these questions and think that many are trivial. Yet these are the “Intents” that provide organizational clarity. If you know the answers to all these questions, you know whether an action will support the organization or not.

However, the answers to the questions are the “Intent” that helps your team know what is expected of them. If everyone knows the same answer to all these questions, then it is more likely that they will make a decision that falls within the “Intent” and meets your definition of common sense.

Returning to David Marquet, he emphasized that for people to make good decisions:

  • They need to have control, e.g., make the decision so they take ownership of the problem. If you retain the power and don’t give it, your team members will never make the decisions you want.
  • They need to be competent. Do you have the “right people in the right seats?” If you do, then they should be able to make the decisions. If not, then it is not their issue, but yours. You have the wrong people running things.
  • Organizational Clarity. Or stated as “Is it the right thing to do?” If your people know the above guides’ answers, they will know if the action supports the organization’s purpose and goals.

So next time you feel your team is not making “common sense” decisions, ask yourself:

  • Are they solving the right problem?
  • Do they have all the available information?
  • Do they know the “Intent,” and is there organizational clarity?

I think you will find that something in the above is missing.

However, a warning! This course is not easy; you are giving up control, and to make it work, you have to allow them to make different decisions. If you keep snatching power back, it will fail. 

Once you decide to go down this path, ensure that the “Intents” are answered, and everyone knows the answer. Good luck.

 

Copyright (c) 2021, Marc A. Borrelli

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So how to solve this problem?

Working with some teams recently, I have come across the following system, which, while not perfect, helps get closer to what we want to achieve. For example, let’s say the topic is “Grow repeat business.”

 

100 Ideas, No Less

When starting the process with your team, the first rule is that we will not stop with ideation until we have at least 100 ideas on the board. Not only do we need 100 ideas, but no one is allowed to criticize, demean, promote, or challenge any idea until the 100 are there. This rule’s logic is to stop ideas from being shut down by some of the dominant participants. It is hard to get 100 ideas up on the board, and we progress through them, they get crazier, but that is sometimes where the gems lie. So, following our example, we could have the following ideas:

  • Create a membership club
  • Offer discounts to repeat customers.
  • Provide value behind a paywall for member customers
  • Offer bundling
  • Offer easy returns, e.g., Zappos.
  • Provide special shopping events for repeat customers or members
  • Offer suggestions to customers based on what they have purchased.
  • Free shipping for members
  • Special shopping days for members only
  • Early access to new products for members or repeat customers
  • Send you products that we believe you want and if you don’t return them then charge for them.

As can be seen from the above, many of these ideas are common, and we have seen them with Amazon and others. However, at one time, they were all new. Also, the last one, someone might think is “crazy,” but it doesn’t matter; it is still an idea to be put down.

 

Mind Map

Once you’re over 100 and there are no more ideas, time to organize. If there are still ideas at 100, don’t stop. I find organizing through Mind Mapping the best. For those of you who haven’t done Mind Mapping, take your ideas and organize them into “topics.” Elaborate on those by creating sub-topics and use short phrases or single words to identify them. Thus, once done, your 100+ ideas are organized into subtopics within topics, so it is easier to look at what each is seeking to achieve. In some cases, the ideas are just variations on prior ideas to be lumped into one. So, again looking at the ideas above, we could organize them as follows:

Membership Ease of Use Promotions
Create a club Offer easy returns Special shopping events
Provide additional value for members Offer bundling Discounts
Special shopping events for members Offer suggestions to customers based on prior purchases Special shopping days
Free shipping for members Free shipping for everyone  
Early access to new products for members   Early access to new products for prior customers
Send products and customer decides if they want them.    

 

10% AND ?

Once we have divided everything into our subtopics, then we go through them one by one. Each person has to identify at least 10 percent of what they like about any idea and then add to it. The next person builds on the last person’s statement, again identifying at least 10% they like and then adding to it. This ensures that nothing is shut down and that the creative exercise can take place. By having to build on something regardless of whether or not you agree, forces you to find the best in it and make it better – KAIZEN. The number of participants in the meeting will determine how many times you go around. As you go around, each iteration is recorded. This process further frees the imagination as you have to identify something you like about the statement before you and add something good. At the end of this process, some excellent ideas may have been arrived at. Then you can use a multiple voting system for the participants to identify what they like best.

 

So, Give it a try!

So, give it a try; you may find you get some fascinating and novel ideas from your group. Besides, as the group’s ideas flow, you should find a greater commitment to the ideas than those that the usual dominant people promote.

 

Copyright (c) 2021, Marc A. Borrelli

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All business owners know that they and their team need to be selling continuously. As Estée Lauder put it, “I have never worked a day in my life without selling. If I believe in something, I sell it, and I sell it hard.” While many small and midsized companies seek to live up to this statement, they fail to see recruiting through the same lens.

Continual recruiting is key to the survival of a company, and it is not something that is left to chance and a time when you have a position to fill. Doing so often results, to paraphrase Barry Deutsch, “When looking for basketball talent, you get to pick the tallest pigmy.”

All companies need to be continuously recruiting. By that, I don’t mean hiring, but recruiting. It’s building a pipeline of people that you would hire if you needed someone to fill a position, or someone you would hire regardless of the position if they were available.

Recruiting doesn’t just fall on HR and the CEO, but the entire organization. To succeed, as Jim Collins says, you need “The right people in the right seats doing the right things.” Well, where do you get the right people? Here are some suggestions.

Develop your recruiting flywheel

In Good to Great, Jim Collins refers to the Flywheel Effect concept as:

“No matter how dramatic the end result, good-to-great transformations never happen in one fell swoop. In building a great company or social sector enterprise, there is no single defining action, no grand program, no one killer innovation, no solitary lucky break, no miracle moment. Rather, the process resembles relentlessly pushing a giant, heavy flywheel, turn upon turn, building momentum until a point of breakthrough, and beyond.”

I think organizations with great hiring abilities have developed a hiring flywheel where they have a process and pursue the process relentlessly until it operates with its own momentum. At that point, all others look at the organization and wonder how it does it and what is the magical change. There isn’t any, just a continual pushing for the flywheel process.

A Strategic HR person

Many organizations have a Human Resources manager. However, that role is typically a person how manages payroll, benefits, and compliance. They sit “under” Finance and ensure that employees get paid, get their benefits, and are in compliance with a myriad of rules. This role is crucial whether you have internally or outsource it.

However, few companies have a “Strategic” Human Resources person who sits in the “C” Suite. This person needs to ensure that the organization’s resources are aligned with its strategy. As the organization moves through its 13-Week plans and 3HAG, they know when additional talent is going to be needed. Hence, they are ahead of the curve, ensure that the requisite talent is hired, assimilated into the culture, and onboarded in time for their needs.

Backfilling as fast as you can when in growth mode is difficult, as everyone in the company is too stretched thin. New employee hiring decisions are often made with the thought process, “Let’s just hire someone to fill this need; if it doesn’t work out, we can get someone else.” Such a process is time-wasting and very expensive. Also, new employees are thrown into the tumult without proper onboarding, an understanding of what is expected, and an understanding of the culture. They’re thrown in because the organization needs bodies, and this can all be done later. Still, it never is, and the good employees leave.

Talent folder

Everyone on the Leadership Team must have a Talent folder. It should contain the names of anyone they have met that they believe would be a great addition to the team. They need to follow these people on LinkedIn and make sure they know where they are, what they are doing, and most importantly, keep in touch. When a position in the organization opens up, that member of the leadership team can reach out to them to see if they would be interested in joining the company. The leadership team should review their collective talent folders in each quarterly meeting. They look at the next 13-Week Sprint and the resource limitations they face, either through insufficient resources or talent.

Ask Employees for Referrals

All industries are incestuous; everyone knows people in the industry in similar roles because they all attend the same conferences, often previously worked for the same companies, or did some training together. It must be part of your culture to get your employees to nominate great people they meet as potential hires. By emphasizing behaviors and culture, your employees will know what types of people would fit. There is no better recruiting tool than a very happy and excited employee working to attract you to their firm. These people should be vetted and added to someone’s Talent Folder. If an employee nomination is hired, reward your employee. However, it is best if they are not involved in the hiring process beyond the nomination, and the nominees have to remain for a period of time.

Ask Customers and Suppliers for Talent

Your customers and suppliers know you, your company, your vision, and your culture. Ask them for people that they think would be a good fit. Especially if there is a position that you want to fill, and they know more specifically what you are looking for. If they like working with you and believe in what you stand for, they are far more likely to refer someone to you than if the opposite is true. However, this requires a great relationship with your customers and supplies. You don’t just want to ask when you need someone, but you need to make it reciprocal as well.

Check your reputation on GlassDoor

It might be easy to dismiss negative statements from unhappy employees; however, like client reviews, statements on GlassDoor matter. All prospective employees now look at GlassDoor to see how you rank and what people say about you. If there are negative statements that make the organization look bad, you can expect many “A” players to wonder if it is worth applying for your position or moving on to an organization with a better reputation. You can expect questions from GlassDoor statements to be raised in interviews, at least from “A” players. Thus, it is in your interest to ensure that you work to maintain a good profile like you would from your clients.

Have Employee Testimonials on Your Website

Most organizations have a link on their website about job openings or career inquiries. However, few have employee testimonials that reinforce the company’s culture, commitment to its employees, and great stories of how it has helped its employees achieve their goals. These testimonials can do more to recruit people who are aligned with the organization than some CEO/owner statement as it shows how the organization is “Walking the Talk.”

Good luck developing your flywheel and attracting the talent you need. If you need help, reach out, we are here to help our clients succeed.

 

Copyright © 2021, Marc A. Borrelli

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Algorithms Once More Run Amok

Algorithms Once More Run Amok

For those who have not been following the disaster in the UK with the GCSE A-level exam results, here is a summary:

The History

  • A-levels are the exams taken in the UK, which determine where students go to college. Most English students receive acceptances from universities that are conditional upon attaining specific A-Level results.
  • Due to COVID, these national exams were canceled, which left students with an uncertain future.
  • In late March 2020, Gavin Williamson, Secretary of State for Education instructed Sally Collier, the head of Ofqual (The Office of Qualifications and Examinations Regulation), to “ensure, as far as is possible, that qualification standards are maintained, and the distribution of grades follows a similar profile to that in previous years”. On 31 March, Williamson issued a ministerial direction under the Children and Learning Act 2009.
  • In August, an algorithm devised by Ofqual computed 82% of ‘A level’ grades. More than 4.6 million GCSEs in England – about 97% of the total – were assigned solely by the algorithm. Teacher rankings were taken into consideration, but not the teacher-assessed grades submitted by schools and colleges.

The Outcome

  • Ofqual’s Direct Centre Performance model used the records of each center (school or college) for the subject assessed. Only after the results of the model’s first use in August 2020, were details of the algorithm released and then only in part.
  • Students at small schools or taking minority subjects, such as are offered at small private schools saw their grades inflated than their teacher predicted. Traditionally, such students have a narrower range of marks, as these schools encourage weaker students to leave.
  • Students at large state schools, sixth-form colleges and FE colleges who have open access policies and historically have educated black and minority ethnic students or vulnerable students saw their results plummet, so the fitted with the historic distribution curve. Nearly 300,000 of the 730,000 A-levels were lower than the teacher assessment this summer.
  • While 49% of entries by students at private schools received an A grade or above, only 22% of students at comprehensive schools received such marks.
  • The fact that students are elite private schools benefited at the expense of those from disadvantaged backgrounds sparked national outrage, including protests.
  • According to some, Ofqual has barred individual pupils from appealing against their grades on academic grounds. Families should not waste time complaining but instead should contact college or university admissions offices to confirm their places in the event of unexpectedly poor grades.
  • At first, the government refused to back down and change the results, but due to the level of protest, it soon backed down.
  • The government announced that official results would be the higher of the algorithm approximation or teacher estimates of how their students would have done. On 19 August, The Universities and Colleges Admissions Service determined that with the change, 15,000 pupils were rejected by their first-choice university on the algorithm generated grades.

What is the problem?

Well, first, there is chaos, as many students are not sure they can get into their first choice universities. For many, the algorithm was just another example of how the UK educational system consistently favors those from elite backgrounds. Statisticians have criticized Ofqual’s algorithm, saying it does not have sufficient data to award grades fairly to most state schools in England, because of wide variations in results within schools and between years. Furthermore, the Royal Statistical Society has called for an urgent review of the statistical procedures used in England and Scotland, to be carried out by the UK Statistics Authority.

However, the deep questions for all of us who aren’t affected by these results are (i) how did the algorithm get it wrong? And (ii) how many other algorithms are messing up our personal and business lives without us knowing.

AI Bias

The category of algorithms known as deep learning is behind the vast majority of AI applications. Deep-learning algorithms seek to find patterns in data. However, these technologies have a significant effect on people’s lives. They can perpetuate injustice in hiring, retail,  insurance, advertising, education, and security and may already be doing so in the criminal legal system, leading to decisions that harm the poor, reinforce racism, and amplify inequality. In addition to articles by MIT and others, Cathy O’Neil laid out these issues in her 2016 book, Weapons of Math Destruction – a must-read for anyone with interest in this area. O’Neil argues that these problematic mathematical tools share three key features; they are:

  1. Opaque – especially those run by private companies who don’t want to share their IP. As a result, no one gets to audit the results.
  2. Unregulated – they do damage with little consequence to important areas of people’s lives; and
  3. Difficult to contest – the users don’t know how they were built so deflect and the providers hide behind their IP.

Also, such systems are scalable, which amplifies any inherent biases to affect increasingly larger populations.

Most troubling, they reinforce discrimination: If a poor student can’t get a loan because a lending model deems him too risky (because of his zip code), he’s then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. Models are propping up the lucky and punishing the downtrodden, creating a “toxic cocktail for democracy.”

A recent MIT article pointed out that AI bias arises for three reasons:

  1. Framing the problem. In creating a deep-learning model, computer scientists first decide what they want it to achieve. For example, if a credit card company wants to predict a customer’s creditworthiness, how is “creditworthiness” defined? What most credit card companies want are customers who will use the card, make partial payments that never take the entire balance down so that they earn lots of interest. Thus, what they mean by “creditworthiness” is profit maximization. When business reasons define the problem, fairness and discrimination are no longer part of what the model considers. If the algorithm discovers that providing subprime loans is an effective way to maximize profit, it will engage in predatory behavior even if that wasn’t the company’s intention.
  2. Collecting the data. Bias shows up in training data for two reasons: either the data collect is unrepresentative of reality, or it reflects existing prejudices. The first has become apparent recently with face recognition software. Feeding the deep-learning algorithms more photos of light-skinned faces than dark-skinned faces, resulted in a face recognition system that is inevitably worse at recognizing darker-skinned faces. The second case is what Amazon discovered with its internal recruiting tool. Trained with historical hiring decisions that favored men over women, the tool dismissed female candidates, as it had learned to do the same.
  3. Preparing the data. Finally, during the data preparation, the introduction of bias can occur. This stage involves identifying which attributes the algorithm is to consider. Do not confuse this with the problem-framing stage. In the creditworthiness case above, possible “attributes” are the customer’s age, income, or the number of paid-off loans. In the Amazon recruiting tool, an “attribute” could be the candidate’s gender, education level, or years of experience. Choosing the appropriate attributes can significantly influence the model’s prediction accuracy, so this is considered the “art” of deep learning. While the attribute’s impact on accuracy is easy to measure, its impact on the model’s bias is not.

So given we know how the bias in models arises, why is it so hard to fix? There are four main reasons:

  1. Unknown unknowns. During a model’s construction, the influence of bias on the downstream impacts of the data and choices is not known until much later. Once a bias is discovered, retroactively identifying what caused it and how to get rid of it isn’t easy. When the engineers realized the Amazon tool was penalizing female candidates, they reprogrammed it to ignore explicitly gendered words like “women’s.” However, they discovered that the revised system still picked up on implicitly gendered words, namely verbs that were highly correlated with men over women, e.g., “executed” and “captured”—and using that to make its decisions.
  2. Imperfect processes. Bias was not a consideration in the design of many deep learning’s standard practices. Testing of deep-learning models before deployment should provide a perfect opportunity to catch any bias; however, in practice, the data used to test the performance of the model has the same preferences as the data used to train it. Thus, it fails to flag skewed or prejudiced results.
  3. Lack of social context. How computer scientists learn to frame problems isn’t compatible with the best way to think about social issues. According to Andrew Selbst, a postdoc at the Data & Society Research Institute, the problem is the “portability trap.” In computer science, a system that is usable for different tasks in different contexts is excellent, i.e., portable. However, this ignores many social settings. As Selbst said, “You can’t have a system designed in Utah and then applied in Kentucky directly because different communities have different versions of fairness. Or you can’t have a system that you apply for ‘fair’ criminal justice results then applied to employment. How we think about fairness in those contexts is just totally different.”
  4. Definitions of fairness. It is not clear what an absence of bias would look like. However, this is not just an issue for computer science; the question has a long history of debate in philosophy, social science, and law. But in computer science, the concept of fairness must be defined in mathematical terms, like balancing the false positive and false negative rates of a prediction system. What researchers have discovered, there are many different mathematical definitions of fairness that are also mutually exclusive. Does “fairness” mean that the same level of risk should result in the same score regardless of race? It’s impossible to fulfill both definitions at the same time, so at some point, you have to pick one. (For a more in-depth discussion of why click here) While other fields accept that these definitions can change over time, computer science cannot. A fixed definition is required. “By fixing the answer, you’re solving a problem that looks very different than how society tends to think about these issues,” says Selbst.

As the UK A-level exam debacle reminded us, algorithms can’t fix broken systems. When the regulator lost sight of the goal and pushed for standardization above all else, the problem began. When someone approaches you with a tempting AI solution, consider all the ramifications from potential bias because if there is bias in the system, you will bear the responsibility, not the AI program.

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Where are you?

Where are you?

Last week I discussed how business trends had accelerated 5 – 10 years as a result of COVID, thus whatever the critical trends in your business were in March, take them forward 5 – 10 years, and that is where you are now. This acceleration applies to all companies, but the ones we see most easily are move to online retailing and the death of malls.

If that is where your business is, then as I have also said before you need to:

  • Revisit your BHAG. Hopefully, you have one, and make sure it is still relevant. Your Big Hairy Audacious Goal is more than just “goals,” a true BHAG is clear and compelling and serves as a unifying focal point of effort– often creating immense team spirit.  It has a clear finish line, so the organization can know when it has achieved the goal; people like to shoot for finish lines. However, if your BHAG aimed at ten years out, and we have moved 5 – 10 years in the last few months, we may have passed, or it may no longer be relevant.

  • Review your corporate mission and vision statements, again to ensure they are correct given where everything has moved;

  • Look at your “Why.” Is it relevant in a COVID/post COVID world, or does it need changing? Is it a “Why” that has relevance with your future workforce. If you are not sure about your “Why,” here is a link to Simon Sinek’s “Start with your Why” as a refresher. Millennials are here, and regardless of what you think about them, you need them. The good ones will want to work of organizations where they believe in its “Why.” Now is the time to fix it.

  • Take a hard look at your Corporate Culture, is what you live, or are they just pretty words? I have come across many examples over the last twelve weeks were organizations are flouting their cultural beliefs and not even realizing it. Look at your behaviors during this period and have you lived your culture. If not, you need to change one or the other.

  • Develop a new strategy – urgently! As I have said before, not only have we moved forward 5 – 10 years, but the game has changed. There are new rules and players. Thus you need a new strategy.

  • Revisit your capital investment plans. With a new strategy and market, your prior capital priorities are not necessarily correct. You need to revisit your investment plans and ensure that you are focused on investing in technology and processes to keep ahead of your competition.

  • Revisit “How You Make Money.” How You Make Money is a fundamental understanding of every employee in an organization. It must be something simple that everyone understands but drives the appropriate decisions making and behavior. Herb Keller at Southwest Airlines put it best with “Wheels Up.” So how do you make money, and has it changed in this new environment?

  • Revisit your capital allocation. Right now, interest rates are at an all-time low and should remain here for some time. With lower interest rates you need to revisit your capital structure, assets and operations to determine the most efficient capital allocation from a cost of capital and tax perspective and

  • Revisit your operations. Taxes are at an all-time low, but I don’t expect them to remain so as the significant increase in government debt will need financing at some point. So look at your operations and some assets, should you sell them now and reinvest the proceeds more efficiently, given where we are. One of my clients is about to sell his office building and is looking to do a 1031 exchange into a new investment property. While that is the standard consideration; however, if you expect taxes to rise and value of investment property to rise more slowly as the world adjusts to the post COVID landscape, would it be better to pay the taxes now. That is a question each person needs to determine, but one I would ask.

  • Revisit your decisions making process. As we move through a time of significant change and confusion, you need to move the decision making down from the top to where the information is. As I have said before, this is a time for effectively A/B testing outside of just the software world. Having everything flow up and down through the organization slows the decision-making process down too much for such times. To have effective decision making at the front lines, your employees need to know the Mission, VIsion, your Why, How You Make Money, and the Company’s Culture. If they genuinely understand those, they will make the right decisions for the organization.

The most beautiful thing about the current environment is you can change all of these things without too much of an issue. Because of COVID and the adjustments required, Scared Cows can get slaughtered. Prior commitments and beliefs that could not be touched are fair game.

Now is the time to implement John Boyd’s OODA Loop – observe–orient–decide–act.

While developed for military strategy, this is an ideal OODA loop environment. An organization that can process this cycle quickly, observing and reacting to unfolding events more rapidly than the competition, can “get inside” the opponent’s decision cycle and gain the advantage. Raw information or observations of the evolving situation are processed or filtered to drive all decisions regarding the problem.

While everyone is still figuring out what is happening, take advantage of the confusion and move quickly. Those organizations that emerge ahead for this crisis will have market leadership for the next decade.

 

Copyright (c) 2020, Marc A. Borrelli

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