Common Traits of Great Leadership

By Guy Higgins

I read an article in the Wall Street Journal (WSJ) recently The Seven Secrets of Great Team Captains. I came across it in Apple News under the title of You’re Picking The Wrong Team Leaders. That was the title that grabbed my attention because I think we often pick the wrong team leaders. In fact, the Harvard Business Review (HBR) just published an article The Difference Between Great Leaders and Good Ones (for the record, the author defined “good” in moral or ethical terms – not quality terms). That article described a great leader as one (my interpretation) with enormous charisma and high energy (acknowledging that such a leader could lead to ethically or morally good or bad goals). The WSJ article flatly contradicted that implication. So, I’m going to look at the seven leaders that the WSJ used as exemplars of great team captains (who were, in these cases, great leaders). Continue reading

Taking a Strain

By Guy Higgins

The phrase “take a strain” has come to mean doing the difficult work, but it harks back to the distant past with ships mooring to a dock or pier (or even a quay) in a harbor. In that sense, it meant ensuring that the mooring lines remained taut so that the ship would not move with waves and rub against or even crash into the dock/pier/quay, damaging the hull. It also meant that the crew needed to continually monitor the mooring lines and adjust them as the tide ebbed and flowed.

Okay, now that I’ve gotten that out of my system, I just read an article on cyber security that made me think about “taking a strain.” The article reported on a survey conducted by a cyber security firm. The survey found that 35 percent of cyber security professionals admitted to skipping or sidestepping their own security protocols. National Institute of Standards and Technology cyber security personnel speculate that “security fatigue” is a contributing factor. The crew is tired and the mooring lines don’t seem to be under strain here. The organization is at risk of crashing into something, and leadership (the captain or the bosun or somebody!) needs to focus the crew and pay attention. Continue reading

Thinking

By Guy Higgins

I read a couple of different and interesting articles recently:

The titles for these two articles are likely to create a question in the minds of the Noble Reader, “What the heck do these have in common?” Continue reading

More on that Cognitively Diverse “Elephant”

By Guy Higgins

Last week, I wrote (yet again – seems to be a favorite subject) about cognitive diversity and the potential to improve performance by putting it to work. This week, I’m going to “talk” about where we can actually leverage cognitive diversity and how we might do that.

First, I want to do a bit of exploring – where might cognitive diversity actually deliver value? As I thought about trying to discuss the subject of where cognitive diversity can contribute to improved performance, I discovered that that is a harder question than I initially thought it would be. Caveat – the following thoughts are (pretty much) all my own. Continue reading

The Six Hundred Pound (Diverse) Elephant

By Guy Higgins

Focusing on What Works for Workplace Diversity, an article recently published by McKinsey, discusses approaches for increasing (in this specific case) gender diversity in the workplace. Similarly, Damien Hooper-Campbell, the Chief Diversity Officer for eBay, spoke at a conference about how to increase diversity in the workplace.

The McKinsey article briefly mentions the correlation between (identity) diversity and performance right at the beginning and then promptly ignores how that improved performance might be achieved, focusing, instead, on developing ways to eliminate unconscious bias in the hiring process. Eliminating biases is good and it should pay off for any company successful in eliminating (or at least reducing those biases). Continue reading

Measuring What Matters

By Guy Higgins

I recently read an article, I’m Sorry But Those Are Vanity Metrics. I thought that the premise of the article was a very good one – will your metrics help you run your company or organization better, or are they a way to compare your company to your competition?

That question is important because the future of your company is more closely related to how well your company is being run than it is to how well you’re doing with respect to your competition. Certainly, how well you’re competing is important, but if your company is merely the best buggy-whip maker, your future doesn’t extend very far past lunchtime. Continue reading

Laziness – An Asset?

By Guy Higgins

I recently read an article titled, Being Lazy is the Key to Success, According to the Best Selling Author of Moneyball. The article describes how Michael Lewis (he would be that best selling author) spends a year or more choosing and researching a topic for a book. Mr. Lewis makes the point that being busy for the sake of being busy is a major mistake. If you’re busy with administrivia, and a big opportunity comes along, will you have the bandwidth to take advantage of that opportunity?

I think that the title of the article, while certainly eye-catching, is misleading. Further, there are other authors out there who better argue that busy-ness is an over-promoted trait.

I think that these authors make some very important points. I want to look at each of these three pieces:

  • Darwin – In this essay, the author points out that Charles Darwin, and numerous other highly accomplished men of science, “worked” notoriously short hours. Darwin actually “worked” about four hours a day. The rest of the time he devoted to long, solitary walks and engaging with family and friends. During his work periods, Darwin famously focused intensely on his thoughts and writing. His words were carefully chosen and his sentences carefully constructed. His work has been described as some of the most well constructed arguments in the history of science. His solitary walks gave him the opportunity to relax that intense focus and rebuild his energy. It also allowed his brain to manipulate ideas subconsciously.
  • The Slow Professor – In this essay, the author (a real professor) bemoans the fast pace of university education today, bemoaning the emphasis on developing marketable skills rather than emphasizing a solid (dare I say it) liberal (in the traditional sense) education. The point is that the development of an educational foundation is incredibly important since it forms the basis for all future intellectual development and life accomplishments, and that a slower pace allows a fuller exploration of ideas and knowledge.
  • The Metagame – this essay really isn’t about being lazy, but rather about focusing on the longer-term rather than the short-term future. Coach Belichick manages the team to win two to five years in the future. Mr. Buffett, similarly, invests in companies and essentially takes them private (he doesn’t have to own them outright, merely control them) by enforcing long-term strategies rather than worrying about next quarter’s “numbers.” Investing effort (whether in building and maintaining a football team or creating a highly competitive company position) is playing that “meta-game” in the title. By working to win in the future, you enhance the probability that you will always be winning in the present.
  • The Man Who Was Too Lazy – Mr. Heinlein, goes off on a tangent in his novel to describe a man who so intensely disliked work that he worked hard enough to succeed on the first try – every time. Obviously fiction, but the point is, “If you don’t have time to do it right (succeed) the first time, where will you find time to do it again.”

Years ago, I was early for a staff meeting and ran into the boss as I was getting a cup of coffee. I was somewhat surprised since the boss was supposed to be on travel, and I mentioned it to him. He smiled and wryly observed that since his travel had been cancelled, he didn’t have anything to do all day except think. I quipped that he should not let it out that he was actually thinking, and he replied something like, “Yeah, we’re too busy doing to think about what we should be doing.”

I think that all of the above points, including Mr. Lewis’ measured approach to choosing his work and researching it well and my boss’ observation about thinking, are ideas that we, as leaders, should build into the way we work. The future is more important than the present because the present is largely unchangeable, the future is not cast in concrete and can be managed – and it’s where we will be spending the rest of our lives.

Leaders should be playing the meta-game, focusing intensely on the work that they should be doing. Actually deciding what they should be doing is something that requires the time to sit back and “cogitate” about everything that bears on “the job” (and that’s almost everything). So, it’s not about being lazy – it’s about taking advantage of the way our brains work and giving ourselves time to let them work (and ourselves to re-energize).

Thoughts?

 

 

Artificial Intelligence Redux

By Guy Higgins

Last week, I wrote about artificial intelligence (AI) and highlighted some of the issues I believe exist with the application of artificial intelligence programming. I want to follow up on that with observations on another article I read this week, Do Algorithms Beat Us at Complex Decision Making?

The article described the achievements of AI-assisted programs. A major point that I noted last week was that artificial intelligence algorithms out-performed humans in areas where subjective judgment was critical (subjective meaning that quantitative assessments didnʻt play a role) – to a large degree because the AI algorithms were consistent and humans were very inconsistent (they asked radiologists to read medical images and slipped in repeats – the doctors diagnosed the repeated images differently about 80 percent of the time – thatʻs scary). Continue reading

Artificial Intelligence: Artificial – Definitely. Intelligence – Maybe Not

By Guy Higgins

There has been a spate of recent articles about artificial intelligence (AI). Some of the articles waxed positively poetic – making predictions – about the capabilities and potential of AI. Others were much more constrained in their assessment of AI performance. As I type this, I am reminded of Isaiah Berlin who posited two types of “predictors” (the people, not omens or indicators): Hedgehogs who know one thing enormously well and see everything through the lens of that deep but narrow knowledge and Foxes who know many things and see everything as influenced by a myriad of factors. Hedgehogs make extravagant predictions that are rarely right (but that get a lot of publicity when they are) while Foxes make extremely caveated predictions that are right far more often.

I suspect that we are listening to both Hedgehogs and Foxes.

I want to look at AI in one, very narrow, area – the use of AI to improve the hiring process. One of the Hedgehog articles effused about the potential for AI (including machine learning) to significantly improve the hiring process, resulting in companies and organizations hiring people with much more of the right fit for the job and the company/organization.

I find two things about such a prediction that bother me:

  • GIGO – the old programmer acronym, Garbage In, Garbage Out. There are actually two “garbage” streams possible in AI
    • The programming stream.
      • While researchers, software architects, software engineers and programmers are getting better at making software do “intelligent” things, there are an infinite number of ways in which the software can fail to yield intelligent results. That problem will never go away, but the “false positives” can be reduced to a level that is lower than the human hiring process, but there is little to no evidence that we’re there yet.
      • Another programming issue is that we really don’t know what “intelligence” is on the human level. It’s difficult to mimic something when you don’t understand the something that you’re mimicking.
    • The input stream.
      • The job description must accurately capture what it is that the hiring leader wants the person to do. I’ve posted before about the ways in which this effort goes awry. The leader may want the “person who just left” or they may use the job description that was used the last time without regard to how the company or the job has changed. The leader may establish too stringent a set of requirements, or too loose a set. The required skills may have little to do with the job. Writing a job description is both extremely important for AI to work and extremely hard – the machine cannot apply judgment.
      • The resumes must accurately reflect the actual experience and accomplishment of the applicant – not merely a clever regurgitation of the job description. A clever applicant might be able to hoax the computer with a kind of reverse Turing Test (Alan Turing was a computer pioneer – back in 1950 – who opined that a computer would be “intelligent” when it could “converse” with a person and the person could not tell it was a computer).
    • Humans have begun to accept the output of computers in an alarmingly blasé manner. I just watched the movie Hidden Numbers in which a human being (one of the heroines) had to check the results calculated by a computer (the output of which had been checked and found correct numerous times previously) because on two separate runs, the computer had generated significantly different results. Working under a pre-launch countdown deadline, she calculated the correct results in time for John Glenn to take his historic orbital flight. But she was only able to do that because someone looked at the computer results and did not accept them. I’m concerned that such non-acceptance is becoming increasingly rare. Leaders challenge assertions made by people, but they seldom challenge the results barfed out by the computer.

It seems to me that AI has a long way to go before it’s likely to be able to match human sophistication in some areas – like hiring. That does not mean that humans execute the hiring process well – only that I don’t think a machine is going to do it better right now. Computers, even those with AI routines are tools – they cannot be relied on blindly and, like any tool used expertly, can enhance human performance.

Thoughts.

Another Slant on Cognitive Diversity

By Guy Higgins

I recently read an article by Nate Silver, a well regarded political analyst. The topic of the article is why journalists were so badly in error in predicting the results of the recent presidential election. I strongly urge the Noble Readers to read the article – not for any insight into why the mainstream media got the election wrong, but rather for the lessons that apply to any organization, and, particularly, its leaders.

Mr. Silver cited James Surowiecki, the author of the book, The Wisdom of Crowds. He said that Surowiecki argues that crowds usually make good predictions when they satisfy these four conditions:

  1. Diversity of opinion. Each person should have private information, even if it’s just an eccentric interpretation of the known facts.
  2. Independence. People’s opinions are not determined by the opinions of those around them.
  3. Decentralization. People are able to specialize and draw on local knowledge.
  4. Aggregation. Some mechanism exists for turning private judgments into a collective decision.

Mr. Silver goes on to analyze how well the mainstream media satisfy those four conditions. I think that leaders would do well to analyze how well their decision makers satisfy those four conditions. Let’s take a look:

  1. Diversity of opinion – This is about cognitive diversity. Mr. Silver includes in his definition the importance of “private information.” Private information is information that none of the other members of the team have, but I would extend this to include all the dimensions of cognitive diversity – perspective, problem solving toolkits and prediction making. Many teams are not diverse, and, in fact, often actively pursue team coherence, selecting new members for their perceived “fit” with the team. If everyone thinks the same way and the same things, you only need one of them.
  2. Independence – This is related to both diversity of opinion and to the way that the team leader solicits ideas and solutions. It means that the leader can’t allow the raging extroverts to dominate a meeting with asides or even eye rolls. When soliciting ideas and opinions, everyone must participate and no one other than the person speaking can comment. I suspect that most meetings include a great deal of comment and discussion before all the ideas are out on the table – not so good.
  3. Decentralization – This is representation from all the stakeholder groups. Just like a football team can’t be comprised only of offensive tackles, a good organizational team needs to include representation from throughout the organization. For the really mature Noble Readers, this is part of what the old Integrated Project Team was supposed to do – before the idea degenerated into a fad within which any two people randomly meeting in the hallway became an IPT.
  4. Aggregation – This is really where the leader steps to the fore. The leader needs to use the solicited ideas, solutions, and approaches as a starting point to create a constructive discussion that builds from the ideas. Builds – not compromises or develops a consensus. Solomon’s approach to resolving the issue of the two mothers claiming one baby worked well when the solution had to be binary, but cutting ideas in half to achieve consensus or “splitting the difference” never gets to the best solution.

I suspect that when leaders analyze their teams in light of these conditions, they will find that they have created decision-making bodies (and even operating teams) that are suboptimal. Fixing that kind of a problem is not going to be either simple or quick, but the more quickly it is fixed, the faster performance will improve. One of the biggest issues the leader will have is ensuring that no one feels that their “ox was gored.” Just because one person’s idea was more heavily adopted and used does not mean that the ideas put forth by other members of the team were not equally valuable.

Thoughts?