Leadership


When I was in primary school I remember learning about herds of buffalo that were so vast that it would take hours for all of the animals to pass a specific point.  Herding behavior evokes visions of groups acting the same way. There is a special case that affects how work is accomplished. Self-herding affects how decisions are made based on how an initial event is tackled. Dan Ariely defines as  “our tendency to follow the same decisions we have made in the past (future decisions are influenced by previous decisions).” Self-herding is a form of cognitive bias in which an individual creates a heuristic for a specific decision, limiting the possible outcomes.  A classic example of self-herding is the rule many people develop that states that, all things being equal, given two restaurants the one with people is better. The origin of the rule many times in unknown and doesn’t get questioned. I believe I originally heard this guidance from my mother.  Even today I have difficulty going into restaurants that are empty. The first time I used my mother’s guidance the decisions translated into behavior that I rarely question even today. Restaurants might be one thing, but a decision about accepting work or using a specific framework should be a different matter but the answer is no.  (more…)

Herding for pickle beer. Who would have thought!

Herding is a pattern where an individual or team acts based on the behavior of others. Stated very simply, herding is just like the children’s game follow-the-leader.  Last year, I sat in on a discussion in an organization where being perceived as being helpful was a significant attribute for bonuses and promotions. The R&D Group (software developments) had recently been asked to implement a significant SaaS package with a due date before Thanksgiving so that the retail portion of the business would not be impacted. The date was absurd. The CIO had gathered a number of teams together to determine if the work was doable. The answer from each team as they went out of the room was no until a single team said they could do it. In quick succession, everyone changed their minds and played follow-the-leader.  All of the affected teams exhibited herd behavior. As soon as one team broke from the pack everyone followed. The cascade was exacerbated when the CIO muttered “thank-you” after the first two teams said yes. Herding in decision making effectively took “no” off the table. This type of behavior is response-driven. (more…)

 

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SPaMCAST 562 features our essay on the power of saying no.  I firmly believe that unless you have control over the amount of work you take, you are asking for a trainwreck.  The problem is that saying no is often harder than being late or over budget.  

We will also have a visit from the Software Sensei.  Kim Pries is back to kick off September with an essay titled, Real Planning. While the actual plan might not be exactly what happens in real life, the act of planning is crucial.  (more…)

Book Cover

Chapter 16, Causes Trump Statistics, was revelatory for me the first time I read  Thinking, Fast and Slow, and it was revelatory during this read. Over my career, I have been shocked many times to see a perfectly sane leader stand up and show a single statistic or estimate which promises delivery of a product at a cost or in a timeframe that is well outside of normal performance.  This chapter provides a rationale for what often seems to be less than rational. The content in this chapter helps me understand why statistical facts aren’t perceived to generate black and white answers, even when they do. Kahneman uses a story about taxi cabs to illustrate the difference between statistical base rates and causal base rates.  Statistical base rates are facts about the population but are not specific to any individual case. Causal base rates are effective because they are specific and are easily woven into a narrative about the case.   (more…)

Book Cover

 

In Chapter 15 of Thinking, Fast and Slow we explore two types of fallacies. Logical and conjunction fallacies can impact any process improvement effort, typically in a manner that does not benefit change. 

The central plot device in this chapter is an experiment performed by Kahneman and Tversky that asked sets of respondents to rank attributes by representativeness and another group to rank by probability. The experiment begins with a description of the person, Linda,  (similar to the experiment at the center of Chapter 14). A set of statements about Linda’s potential profession is then listed. In this case (as compared to the experiment in Chapter 14), there are items in the list that require the application of logic to judge. For example, one item is “Linda is a bank teller” and a second is “Linda is a bank teller and is active in the feminist movement”. The lightbulb moment from the experiment was when there are two items that have a logical relationship, respondents distinguished between the two based on the story System 1 constructs.  (more…)

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SPaMCAST 551 features our interview with Michael (Mike) Lynn.  Mike and I talked about leadership and agile. Leadership is important any time two or more people get together to pursue a goal. Mike shares his expertise, experience, and wisdom to help shine a light on the relationship between agile and leadership.   (more…)

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SPaMCAST 546 features our interview with Michael Milutis. Michael and I talk about putting people back in charge of their careers. Michael provides advice that every listener can put to use immediately and in the long run.

Michael’s Bio:

Michael Milutis is an INFP and IT generalist committed to human capital development and continuous learning within a shifting technology landscape. (more…)

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