The Novice and the Master

When coaching people in a new skill, there are several things I watch for in their development from novice to master. Insuring they have the requisite foundational knowledge can be considered a given. Tightly coupled with this is a demonstration of working from first principles. If neither of these are in place than it can be said the learner has yet to begin their journey toward mastery.

Beyond the basics, I look for signs of what’s happening behind the curtain. I watch for how they respond to challenges and conflict. And how they work through difficult decisions.

How a difficult decision is handled is an important indicator for whether an individual is a novice, a master, or somewhere in between. Where novices struggle trying to figure out what to do, masters resolve quickly. Certainly a common issue in play would be doubts about the outcome of any particular action and the probability of recovering from any associated consequences. It is also possible that the issue – either instead of or in addition to – is that the novice has become stuck at a decision node that has an uncomfortable degree of uncertainty associated with it on the front end and they are unskilled at thinking through the “disjunction,” as Eldar Shafir1 calls situations like this.

With the former issue, the tack taken by the novice is to plan out as many details as possible so as to account for every contingency and squeeze out as much doubt as possible regarding the outcome. In the later, the novice simply doesn’t have the information needed to make the decision and lacks the skill to play out n number of scenarios leading up to the decision node such that they can then evaluate subsequent paths.

An example given by Shafir has to do with a student that has just taken a rather important exam (say, for graduate school) but doesn’t yet know the results. If they’ve passed, they move forward. If they’ve failed, they have to retake the exam in a couple of months after the end-of-year holidays. On the same day, they are presented with a incredibly sweet deal for a 5-day Hawaiian vacation over the end-of-year holidays. The vacation deal is good for today and grades won’t be released until tomorrow. What does the student do?

Notice that the outcome of the exam will be known long before the vacation begins. Thus, the uncertainty characterizes the present, disjunctive situation, not the eventual vacation. Additional, related versions were presented in which subjects were to assume that they had passed the exam, or that they had failed, before they had to decide about the vacation. We discovered that many subjects who would have bought the vacation to Hawaii if they were to pass the exam and if they were to fail, chose not to buy the vacation when the exam’s outcome was not known. The data show that more than half of the students chose the vacation package when they knew that they passed the exam and an even larger percentage chose the vacation when they knew they they failed. However, when they did not know whether they had passed or failed, less than one-third of the students chose the vacation and the majority (61%) were willing to pay $5 to postpone the decision until the following day, when the results of the exam would be known.

A solution to this simple example of disjunction (Shafir provides many other examples) is for the student to ask themselves two questions:

  1. “Would I take this vacation deal if I passed?”
  2. “Would I take this vacation deal if I failed?”

If the answer is “Yes” to both or “No” to both, then the decision about the vacation deal is easy. If the answer is still mixed, then I suppose the student will have to dig a bit deeper to get at a level of leading criteria that will shake out the decision. (When I was a student, I would have had to consult my financial adviser – a.k.a. my wallet – first. The answer to everything beyond beer was “NO!”) In the experiment described above where students remained uninformed as to the outcome of the exam, they didn’t have a skill or strategy for resolving the uncertainty and were even willing to pay to make it go away!

Shafir’s work was instrumental in helping me tap into new skills for developing mastery in several areas of interest (specifically, martial arts and woodworking). Disjunction has a distinct visceral sensation for me. It gives me pause to ask questions not about potential future events, but about past events leading up to the present. I find I’m usually missing something about the history of events that either help sort out the indecision once known or cause me to think through better scenarios on emerging events that will influence the decision I’m trying to make.

References

1 Eldar Shafir’s chapter in “Cognition on Cognition” titled “Uncertainty and the difficulty of thinking through disjunctions”

Photo by Motoki Tonn on Unsplash

Drive for Teams

I recently re-read Daniel Pink’s book, “Drive: The Surprising Truth About What Motivates Us.” I read it when it was first published and I was still managing technical teams. Super brief summary: The central idea of the book is that people are mostly driven by intrinsic motivation based on three aspects:

  • Autonomy — The desire to be self directed.
  • Mastery — The urge to improve skills.
  • Purpose — The desire to engage with work that has meaning and purpose.

I find this holds true for individuals. However, when applied to teams optimizing for these three aspects can be problematic. If an individual on a team seeks to maximize autonomy, they are likely to come into conflict with the objectives of the team. For example, a software team that is tasked with developing a component that is expected to interact with several other components developed by other teams. If a single developer, in the interests of maximizing their individual autonomy, has decided to develop the component according to standards, design principles, and tools that are different from those of teammates and other teams (essentially, a local optimization,) then the result is likely to be sub-optimal overall.

Some individual autonomy must necessarily be sacrificed in the interests of effective collaboration. It’s possible, even desirable, that individual pursuits of mastery and purpose can be maintained. However, it may be necessary for an individual to focus on mundane tasks and the objectives of the team for periods of time. Finding ways to maintain a healthy balance between the intrinsic motivators and the purpose of the team is no small task and, when found, requires constant attention to maintain.

Perhaps it is possible to attach the team’s or organization’s purpose to the interests of the individual. Or sort for hiring people who have a personal purpose that is in-line with the organization’s purpose.

Concave, Convex, and Nonlinear Fragility

Nassim Nicholas Taleb’s book, “Antifragile,” is a wealth of information. I’ve returned to it often since first reading it several years ago. My latest revisit has been to better understand his ideas about representing the nonlinear and asymmetric aspects of fragile/antifragile in terms of “concave” and “convex.” My first read of this left me a bit confused, but I got the gist of it and moved on. Taleb is a very smart guy so I need to understand this.

The first thing I needed to sort out on this revisit was Taleb’s use of language. The fragile/antifragile comparison is variously described in his book as:

  • Concave/Convex
  • Slumped solicitor/Humped solicitor
  • Curves inward/Curves outward
  • Frown/Smile
  • Negative convexity effects/Positive convexity effects
  • Pain more than gain/Gain more than pain
  • Doesn’t “like” volatility (presumable)/”Likes” volatility

Tracking his descriptions is made a little more challenging by reversals in reference when writing of both together (concave and convex then convex and concave) and mis-matches between the text and illustrations. For example:

Nonlinearity comes in two kinds: concave (curves inward), as in the case of the king and the stone, or its opposite, convex (curves outward). And of course, mixed, with concave and convex sections. (note the order: concave / convex) Figures 10 and 11 show the following simplifications of nonlinearity: the convex and the concave resemble a smile and a frown, respectively. (note the order: convex / concave)

Figure 10 shows:

So, “convex, curves outward” is illustrated as an upward curve and “concave, curves inward” is illustrated as a downward curve. Outward is upward and inward is downward. It reads like a yoga pose instruction or a play-by-play call for a game of a Twister.

After this presentation, Taleb simplifies the ideas:

I use the term “convexity effect” for both, in order to simplify the vocabulary, saying “positive convexity effects” and “negative convexity effects.”

This was helpful. The big gain is when Taleb gets to the math and graphs what he’s talking about. Maybe the presentation to this point is helpful to non-math thinkers, but for me it was more obfuscating than illuminating. My adaptation of the graphs presented by Taleb:

With this picture, it’s easier for me to understand the non-linear relationship between a variable’s volatility and fragility vs antifragility. The rest of the chapter is easier to understand with this picture of the relationships in mind.

Team Composition

When a potter begins to throw a pot, she picks up a lump of clay, shapes it into a rough sphere, and throws it onto the spinning potter’s wheel. It may land off-center, and she must carefully begin to shape it until, it is a smooth cylinder. Then she works the clay, stretching and compressing it as it turns. First it is a tower, then it is like a squat mushroom. Only after bringing it up and down several times does she slowly squeeze the revolving clay until its walls rise from the wheel. She cannot go on too long, for the clay will begin to “tire” and then sag. She gives it the form she imagines, then sets it aside. The next day, the clay will be leather hard, and she can turn it over to shape the foot. Some decoration may be scratched into the surface. Eventually, the bowl will be fired, and then the only options are the colors applied to it; its shape cannot be changed.

This is how we shape all the situations in our lives. We must give them rough shape and then throw them down into the center of our lives. We must stretch and compress, testing the nature of things. As we shape the situation, we must be aware of what form we want things to take. The closer something comes to completion, the harder and more definite it becomes. Our options become fewer, until the full impact of our creation is all that there is. Beauty or ugliness, utility or failure, comes from the process of shaping.Deng Ming-Dao, '365 Tao - Daily Meditations'

Building a high-performance team from scratch is just as difficult as turning a low-performing team into a high-performing team. However, there are very different reasons why each of these scenarios are difficult.

Like the potter beginning with a lump of clay, when forming a new team we must understand what we have to work with and have a clear idea of the outcomes we want. As we shape the team, we have to be mindful of how the individuals on the team are changing – or not – and whether those changes are moving toward the outcome. If not, we either need to change the desired outcome or alter the material we have to work with, that is, change out one or more people so that the shape of the team is better suited to reaching the desired outcome. It is also important to monitor the speed at which the team is formed or shaped. Too fast, and the team may not coalesce in a way that is healthy or productive. Too slow and they may not coalesce at all, they may “tire” of the slow pace and disengage.

With existing teams, we may have a limited range of options to change the roster. This is more like the an existing piece of pottery that has been fully set.

Estimating Effort – Adaptation

I’ve been running the informed intuition (or if you prefer, “disciplined intuition”)  approach to estimating effort for close to nine months now. For the most part, it has gone very well. The primary objective – inspire and support a conversation around the effort needed to complete a story – has most definitely been realized. Along the way the process has shifted to better support both the conversation and the team’s ability to internalize the process.

Originally, it was proposed that teams rate each of the effort characteristics on a sliding scale – 1 to 10 or 1 to 15, or whatever the team decided was most useful. Feedback from the teams lead to the discovery that it is easier to evaluate each effort characteristic using the modified Fibonacci scale rather than a sliding scale. This provides continuity across the method in that everything about a story’s effort value is considered using the same scale. It also reinforces the rationale behind the use of the Fibonacci scale and seems to facilitating the team’s ability to internalize the method. They are moving more quickly when deriving effort values.

A second adaptation is the use of several sets of characteristics, depending on the type of story, the predominant functional area represented by the team, and the nature of the work. For example, a story that involves the development of a computer board has a different set of criteria from stories that involve the creation of firmware for the board or the UI/UX features of the hardware product. The sets usually contain 3 or 4 common characteristics, such as “complexity” or “dependencies.” However, the hardware board may include something like “part sourcing” or “compliance testing.” This illustrates the importance of having the team deconstruct what “effort” means in the context of their world. When they determine the characteristics, the follow-on conversations about the effort are much more robust and meaningful.

In essence, this method is a reflection of the product owner’s responsibility for the “what” of the story and the team’s responsibility for figuring out the “how” of the story. “What I want,” says the product owner, “is an estimate of the effort involved to complete this story.” The teams effort criteria demonstrate to the product owner how they arrive at any particular value.

Intuition and Effort Estimates

In his book, “Blink,” Malcom Gladwell describes an interview between Gary Klein and a fire department commander. A lieutenant at the time, the firemen were attempting to put out a kitchen fire that didn’t “behave” like a kitchen fire should. The lieutenant ordered his men out of the house moments before the floor collapsed due to the fire being in the basement, not the kitchen. Klein later deconstructed the event with the commander and revealed a surprisingly rich set of experienced-based characteristics about that event the commander used to quickly evaluate the situation and respond. The lieutenant’s quick and well-calibrated-to-the-situation intuition undoubtedly saved them from serious injury or worse.

Intuition, however, is domain-specific. This same experienced-based intuition most probably wouldn’t have served the commander well if he suddenly found himself in a different situation – at the helm of a sailboat in rough water, for example, assuming the commander had never been on a sailboat before.

In the context of a software development environment, a highly experienced individual may have very good intuition on the amount of work needed to complete a specific piece of work assigned to them. But that intuition breaks down when the work effort necessarily includes several people or an entire team. So while intuition can serve a useful role in estimating work effort, that value is generally over-estimated, particularly when it needs to be a team estimate.

Consider work effort estimates when framed by Danial Kahneman’s work with System One and System Two thinking. System One is fast, based on experiences, and automatic. However, it isn’t very flexible and it’s difficult to train. This is the source of intuition. System Two, however, is analytical, methodical, intentional, deliberate, and slower. Also, it’s more trainable. It’s when the things that are trained in System Two sink into System One that new behaviors become automatic. With work effort estimates, we must first deliberately train our System Two using a method that is more deliberate about estimating before we can comfortably rely on our System One abilities.

Once calibrated, any number of changes could signal the need to re-calibrate by employing the deliberate process. Change the team composition and the team will need some measure of re-training of System One via System Two. Change a team’s project and the same re-training will need to occur.

The trained intuition approach to estimating effort develops what Kahneman called “disciplined intuition.” Begin with a deliberate, statistical approach to thinking about work effort. Establish a base rate using the value ranges for the effort characteristics. With experience, the team can begin to integrate their intuition later in the project process. If teams lead with their intuition (as is the case with planning poker and t-shirt sizes), they will filter for things that confirm their System One evaluation. With experience and a track record of success from training their intuition, teams can eventually lead with an intuitive approach. But it isn’t a very effective way to begin.

This method also leverages the work of Anders Ericsson and deliberate practice. The key here is the notion of increasing feedback into the process of estimating work effort. The deliberate action of working through a conversation that evaluates each of the work effort characteristics introduces more and better feedback loops that help the team evaluate the quality of their decision. Over time, they get better and better at correcting course and internalizing the lessons.

It’s like learning to drive a car. A new driver will leverage System Two heavily before they can comfortably rely on System One while driving. This is good enough for most driving situations. However, it wouldn’t be good enough if that same driver who is competent at driving in city traffic was suddenly placed on a NASCAR track in a powerful machine going 200 miles per hour.

A NASCAR track might be where we would go look for expert drivers but not where we would look for competent delivery truck drivers. For work estimates on software projects, we’re looking for a level of good enough that’s a reasonable match for the project work at hand. And we’re looking for better than untrained intuitive guesses.

Memorial Day, 2020

I have forgotten where I discovered this picture. It was many years ago. I do not know who these men are or when and where this picture was taken. (If you know, please drop me a line.) I’ve copies of it on virtually every chunk of technology I own that’s capable of showing pictures as a frequent reminder and image for contemplation. It is rich in meaning in many different ways.

Judging by the amount of surrounding destruction, I’d guess these men are deep into Europe, perhaps even Germany. The uniforms suggest Spring, perhaps. Not warm enough for Summer, not cold enough for Winter. Perhaps they are toasting VE day, perhaps having survived the liberation of yet another city, perhaps having survived a recent battle, or maybe just celebrating being alive in the moment.

The soldier on the left appears to have what looks like a Thompson submachine gun on his lap, suggesting things in the area are not as casual as the wine bottle and raised glasses might suggest.

To all who have served us in the defense of Freedom and Liberty: My sincere and deep appreciation and most humble thanks.

Strategies for Remote Interviews with Team Candidates

In a recent New York Times column, Adam Grant wrote:

Credentials are overrated, and motivation is underrated. It doesn’t matter how much experience people have if they lack the drive to think creatively, work collaboratively and keep on learning. We’re not just hiring people to do a job today — we’re hiring them to make their team and their organization better tomorrow.

Once upon a time – last century, actually – employers could rely on the conferring of a college degree as evidence of a certain level of competence in the degree subject. In some areas, this is probably still true. Generally speaking, this would apply to the scientific areas of study: chemistry, physics, mathematics, etc. Unfortunately, even these area are becoming suspect as academic rigor is eroded in the interests of removing perceived barriers to this or that special interest group. To be very clear, I’m referring to the importance of thorough and complete understanding of the subject. The mine field that academia has become is indeed rife with self-inflicted and often insurmountable barriers to learning. The egregious rise in the cost of tuition, grade inflation, and credential dilution are but a few examples.

There are other factors in play. The speed at which society moves in the 21st Century is simply too fast for the four-year degree to to have any hope of staying relevant, let alone keeping up. Almost every major university offers free courses in a wide variety of subjects so it is possible for a high school graduate to craft the equivalent of a Bachelors or Masters and complete it for a fraction of the cost and in half the time. Ah, but without having completed the paper chase, how can such an industrious individual establish for a potential employer that they have the requisite competence?

Adam Grant has it right. Credentials are overrated. So how can we assess the quality and potential of team candidates? Grant identifies three key mistakes interviewers make in the interview process.

  1. They ask they wrong kinds of questions.
  2. They focus on the wrong criteria.
  3. They’re overly influenced by the best talkers.

If, as Grant suggests, job interviews are broken than conducting remote job interviews in the midst of a pandemic are significantly more challenging. In this post, I wish to speak to the second mistake identified by Grant and write about what we can do to identify our criteria, what we can do during an interview to elicit information about the candidate’s qualifications, and a strategy for improving the efficacy of remote job interviews.

Identify Important Criteria

For the sake of example, we’ll engage in a little time travel into the future and imagine having hired the perfect product owner candidate. What tasks encountered in your work day are no longer an issue with the new candidate on board? Is the product backlog now well-maintained and in a healthy state? Does the sprint runway extend out 4-5 (or more) sprints? Has a stable sprint velocity emerged (suggesting that the user stories are of higher quality and understood better by the team)? Do conflicts between areas of the business occur less frequently than in the past? Are stakeholders pleased with the results they see at sprint and increment reviews?

If our example were for a scrum master candidate, we would ask ourselves different questions for eliciting important criteria for the position. Is there less conflict among team members? Does the team understand the purpose and value for determining the effort involved to complete a user story? And again, has a stable sprint velocity emerged?

In addition to considering what hasn’t been working well (and therefore illuminating what skills you want a candidate to bring to the table) it is also important to include what has been working. It will not serve the organization if one set of problems are swapped for another. Perhaps, for example, the previous product owner was well liked by the team and helped the team maintain a positive morale, but had a poorly maintained product backlog that prevented a good approximation for a release date. It wouldn’t be much of an improvement if the new product owner kept a healthy product backlog but did so by driving the team as a tyrant might.

Test for Matching Skills

With a good feel for the criteria needed to hire the best candidate you can then craft a strategy for determining how well the candidate’s abilities satisfy your criteria. Prepare tasks for the candidate that will verify congruity between what a candidate says they can do and what they can actually do. One approach, which I use frequently, is to present the candidate with a series of scenarios, each designed to build on how the candidate responded to the previous scenario. While I may only present a candidate 3-4 scenarios, I have several dozen in the queue and present the sequence based on how well the candidates responses to the challenge.

For example, for a scrum master role – a high-touch role that requires consummate communication skills, flexibility, and the ability to solve people problems – I may present an initial scenario as follows:

“I’m going to give you several scenarios. You are free to ask any questions you wish about the scenario and state any assumptions you are making in your responses.

You are being considered for a position as scrum master for a team that is developing a healthcare related web application for use in hospitals. This team is responsible for developing the UI/UX components and works closely with another team responsible for much of the database and middle tier components. As a new scrum master, what questions would you ask of anyone in the organization to help you quickly understand what you need to do to become effective as a scrum master for your team?”

There are many things I would hope to hear in the candidate’s answer. To mention a few, I’d like to hear that they want to speak to the product owner, the stakeholders, and, of course, each of the team members. I’d like to hear that they plan to spend time in information gathering mode rather than work immediately to shape the team into some version of teams they’ve worked with at other jobs. I’d like to hear questions from them about what kinds of metrics does the team use and what have they shown.

There are no right and wrong answers to a scenario like this. Just answers that are better than others. And I don’t expect the candidate to deliver an exhaustively thorough response.

From their responses, I might learn that they are a recipe follower or that they are flexible in adapting to the needs of the business while working to establish good scrum practices. I might learn that they really don’t know scrum at all and are only good at parroting text book examples and jargon. I might hear how they would attempt to leverage several things from previous experience while acknowledging those attempts would be experiments and subject to adaptation based on feedback.

Assuming the candidate responded to the first scenario in a way that scores high marks for satisfying my criteria, I might offer the next scenario as follows:

“Assume you have been serving successfully as scrum master for this team for six months now. The product owner calls the team together and says ‘I need to swap out some of the stories in the sprint for work that marketing wants done before the end of the week.’ As scrum master, how would you respond to this development?”

As with the previous scenario, the candidate’s response would be measured against the criteria I have established for the position. Depending on what I’ve heard, I may continue to offer additional scenarios that build on the candidates developing experience with the scenario scrum team.

This strategy is pursued until I’m satisfied the candidate knows what they claim to know or not. A short interview does not bode well for the candidate. A long interview does.

(I would be interested in hearing about any questions, comments, or creative ways you’ve applied this strategy.)

Determining Effort Value – Tactics

While the concept and practice is straightforward, shifting a team from intuitive guesses about story points to a more deliberate approach for determining effort value (a.k.a. story points) can be a challenge at first. The following approach may help start the process.

  1. Begin by focusing on product backlog items (PBIs) that the team has estimated using their previous approach that are at a 5 or greater. There isn’t much to be gained by applying this approach to PBIs estimated at 1 or 2. PBIs that the team knows are a bigger effort but may not be able to articulate why that is the case are good candidates for learning how to apply this technique.
  2. Ask the team how much time it may take to complete a PBI. While I have written before about the importance of excluding time criteria when determining effort values, this can be a good place to start. It is what teams are most familiar with – for better or worse. Teams usually have not problem throwing out a time: 8 hours, 16 hours, etc.
  3. With the time estimate in hand ask the team:

“If you sit in front of your computer and start the clock, will the PBI be done if you do nothing and the estimated time elapses?”

I would hope the team would answer “No.”

  1. With the answer to the first question in hand, ask the following question:

If the passage of time alone won’t get the PBI work completed, what will you be doing (actions and behaviors) to complete the work?

The conversation that follows from this questions is the basis for determining the effort criteria the team needs to better describe what they will be doing on their way to completing the PBI. The techniques around establishing effort criteria are described in an earlier post.

How to Develop a Team Identity with A/B Testing

If you’ve ever been fit for prescription glasses, you’ve no doubt had the experience of the eye exam where the doctor flips between different lens strengths and asks “Is this better or worse than before?” It’s basically A/B testing.

This came to mind after reading a research paper authored by Dan Gilbert and Jane Ebert [1] and listening to Gilbert’s TED Talk, “The surprising science of happiness.” The key bit, as described by Gilbert:

Let me first show you an experimental paradigm that’s used to demonstrate the synthesis of happiness among regular old folks. This isn’t mine, it’s a 50-year-old paradigm called the “free choice paradigm.” It’s very simple. You bring in, say, six objects, and you ask a subject to rank them from the most to the least liked. In this case, because this experiment uses them, these are Monet prints. Everybody ranks these Monet prints from the one they like the most to the one they like the least. Now we give you a choice: “We happen to have some extra prints in the closet. We’re going to give you one as your prize to take home. We happen to have number three and number four,” we tell the subject. This is a bit of a difficult choice, because neither one is preferred strongly to the other, but naturally, people tend to pick number three, because they liked it a little better than number four.

Sometime later — it could be 15 minutes, it could be 15 days — the same stimuli are put before the subject, and the subject is asked to re-rank the stimuli. “Tell us how much you like them now.”

The result was that their previous #3 was ranked as #2 and their previous #4 was ranked as #5. This reflects what Gilbert calls “synthetic happiness.” Having been denied their #1 and #2 choices, experiment participants was forced to “settle” for a lesser choice. However, having made the choice they increased they preference for the lesser choice and thereby synthesized happiness with that choice. Just as interesting, the previous #4 choice was pushed further down the scale as if to put some distance between the previous #3 choice. In effect, distinguishing the decision to take home #3 as clearly the better choice.

All this gave me an idea for something to try with a team I’ve working with that needed to rehabilitate their team identity into something healthier. Typically, teams sour on the idea of going through an exercise like this. The team I was working with was no exception. They likened it to defining team goals – a largely tedious and uninspiring chore.

I wanted to know if I could present two possible team identity statements – A/B style – of which one would be clearly undesirable and another more in line with what I suspect the team may be comfortable. The A/B presentation would keep this simple (presenting a selection of six team identity statements as in the experiment with pictures described by Gilbert would be a non-starter.)

Offering a choice should compel them to chose one over the other. I’m counting on their brains to do what brains do. When faced with a choice, they make one. If I were to present them with a single identity statement and ask “How would you like to change this to be more in line with the identity you want?”, I’ve every confidence the room would be filled with silence.

The very first presentation had a blank page on the left and my intentionally lame and inaccurate team goal on the right.

The team was well aware “no goal” wasn’t an option and wouldn’t reflect well on their performance review with HR and management. My theory was that when faced with an empty goal and one that was inaccurate, they’d suggest something, however minimal, that was an improvement on the initial goal. This is what happened and the team then spent a few minutes tuning the goal into something a little less cringe-worthy. This began the process of converting the goal from the scrum master’s goal to the team’s goal.

Then I deliberately let a week or more pass.

On next presentation, the goal on the left was the goal they chose and tuned previously. The second choice was similar but contained one or two slight modifications intended to move the team’s identity in a more positive and healthy direction. Over the course of several months I tested – A/B/Eye Exam style – numerous team goals. “Which goal do you prefer, the one on the right or the one on the left?”

So we had a start. From here on out it was just a matter of improvement. Keying off of things the team said or did, I’d modify the “accepted” goal and present it as an option at the next opportunity.

The key  or driver in this approach, the hypothesis goes, is to set it up so that the team makes the decisions rather than having something foist upon them. The are virtually guaranteed to reject or strongly resist the latter. With the former, they have ownership in the decision. To reject their decision is to say, in essence, that they made a bad or wrong choice, a bad or wrong decision. In general, people don’t like to admit such a thing so they stick with a decision – for better or worse – if it’s a decision they made and are responsible for.

Update (2020.04.13)

Another important element in play with this approach is the anchoring cognitive bias, particularly early on. People are much more comfortable making comparisons between things than they are with coming up with something original. By presenting a blank goal and one that reflects a direction in which I want the team to move – from nothing to something positive – the hypothesis is that the team will assimilate toward more positive goals and that this assimilation will become self-reinforcing over time.

References

[1] D. T. Gilbert, J. E. J. Ebert (2002) Decisions and Revisions: The Affective Forecasting of Changeable Outcomes, Journal of Personality and Social Psychology, Vol. 82, No. 4, 503–514

 

Photo credit: Max Pixel