The Emotional Bumblebee

I finished Lisa Feldman Barrett’s book, “How Emotions Are Made: The Secret Life of the Brain,” this past week. It’s the latest exploration in my decades-long journey to better understand myself and others. There’s a lot in this book and it’s been a paradigm shift for me personally. I expect the effects from the insights gained from Dr. Barrett’s work in my professional life will be equally seismic.

As part of this exploration and effort to understand what Dr. Barrett and others are discovering, I’ve been experimenting with different ways to organize and assimilate information. For years I’ve used mind mapping and its served me well. I continue to use this approach almost daily. Ah, but the relentless advancement of technology has resulted in new tools. My current favorite (meaning the one that so far matches how my brain seems to work) is a tool called Obsidian. It’s new and is evolving quickly. I’ve been using Obsidian to organize and study cognitive biases in a way similar to Buster Benson’s work. This past weekend I began a similar process with emotions based on Dr. Barrett’s work.

It’s early but it has already yielded many important insights and benefits. I began by collecting as many words I could find (currently, 514) that are used to describe emotional states or patterns. I then entered them into Obsidian, each connected to a single node, “Words that express emotion.” Here’s a partial screen capture of the Obsidian graph:

The graph is too big to fit on a single screen and have the words show. And Obsidian does not yet have an export feature for graphs into a standard image file. So I’m limited by screen real estate. Where I take this next…I’m not sure, actually. Probably a cycle of refinement and deep dive into definitions and descriptions. I can foresee the creation of a real-time tool for assessing emotional states using a circumplex. Lots of experimentation ahead.

There is a dynamic quality to the graphs in Obsidian that is part of the fun and path-to-insights with the information. I’ve created a video to show the effect and set it to Nikolai Riminsky-Korsakov’s orchestral interlude “Flight of Bumblebee.” If/when you read Dr. Barrett’s book, you will understand why I selected the bee theme. It’s a virtual emotional bee hive inside our heads and bodies. Be sure to expand the video to full screen for maximum effect. Enjoy!

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.

We’re Good, Yes?

No.

No, we’re not.

I’m adding this phrase to my list of markers that indicate things in a relationship are still not settled. It’s another form of the “seeking forgiveness instead of asking permission” bromide. A self-printed get-out-of-jail-free card. If not that, it’s a dodge to get out from under the burden of an uncomfortable situation at the expense of leaving things tangled and for the most part unresolved.

Here’s a typical scenario.

A product owner or executive faces a decision that affects the workload on a team. Rather than work with marketing, for example, to defer their request for new features to a future release or shift the delivery date to accommodate the request, the decision maker takes the easy path, agrees to the change without adjusting anything else in the system, and drops the extra work on the team.

To make matters worse, the team is informed by email. The team is understandably upset and more than a little confused about the immediate change in course. It’s left to the scrum master to make sense of the e-grenade and deal with the shrapnel. The expected back-channeling and grousing quickly attracts the attention of a wider audience and a full-on electrical storm ensues.

After way too many expensive people are involved and someone with some skill and authority gets control of the situation, work gets renegotiated, timelines are shifted, and work that could and should have been done by the original decision maker gets done by a cadre of ancillary and executive staff.

The original decision maker circles back around to the scrum master, apologies for the “misunderstanding,” and dashes off with a wave and a “We’re good, yes?”

In all likelihood, you’re not. In fact, the difficult conversation that needs to happen is just beginning. What lead up to this explosion? How could the decision maker handled the situation better? What do they need to succeed at navigating future occurrences like this with marketing? What’s different such that the team has confidence this won’t happen again? Does the decision maker understand the consequences to taking the easy way? The hits to time, money (in terms of salaries), and morale can be significant, particularly if  scenarios like this are a frequent occurrence.

Whether you find yourself about to utter this phrase or you’re on the receiving end, know that the work to resolve the issue and move forward has only just begun. Pick up the pieces, learn from the experience, and build something better.

Thinking Agile about the Pandemic

[Note: The fact that the SARS-CoV-2 virus pandemic is on everyone’s mind has given me an opportunity to expand the scope of topics I may consider on The Agile Fieldbook. Specifically, relating current events to Agile and systems thinking.]

 

I’ve been thinking a bit deeper on the frequent comparison of flu deaths with highway traffic deaths, total US deaths in the Vietnam War, or any variety of raw number comparisons. I’m  working to get at something that feels to be an underlying mis-match in such comparisons.

Part of the challenge is that self-proclaimed epidemiology experts are popping up like Spring daffodils, busy asserting themselves as consummate experts in statistics and government policy while asserting themselves as enforcement authorities. And the Internet has been an amplifier for the echo chambers created by rabble. In short, finding the signal in the noise has become much harder. I can’t recall a time when there has been this much manufacturing and shoveling of confirmation bias around the world. Alas, it’s one supply chain that has grown significantly more robust.

At the heart of the raw number comparisons is a category mistake. Stopping at an equivalence of mortality across all categories for cause of death gives rise the category mistake. Not all causes of death should be considered equal when searching for a course of action that will affect millions – in the case of COVID-19, billions – of people. There are many differentiating factors that could be considered in the case of viral pandemics and traffic deaths. The principle one, in my view, is agency.

I can choose a robust and enjoyable lifestyle that significantly lowers my risk to death due to highway accidents (to use that number for my analysis.) In fact, I have done exactly that. A four mile commute to the office, all on local streets where the highest speed limit is 45 MPH…for exactly 3 blocks. To those that declare “But, many people can’t do this.” my reply is “Maybe.” There will certainly be outliers for a variety of reasons. But in many of these cases, the individuals are nonetheless making choices. Perhaps they don’t want to move or they don’t want to change jobs or they don’t want to up-skill or… There are likely a confluence of many choices in the mix that make it appear they are stuck or trapped. Frequently, even in the outlier cases, when circumstances press hard enough, they “find” opportunities and make changes, perhaps even subsidized by local and federal governments. But that’s a topic I’ll leave for much more qualified bloggers to tackle.

I can make other choices in the form of the car I drive or the route I drive to my destination. I can chose the time of day I drive for errands or the frequency with which I need to run them. I can chose whether to use my smart phone while driving or engage in some other distraction while driving. Or I can choose not to drive at all and take the bus, train, bike, walk, or a combination of any of those.

With a viral infection – as we are learning now – there is virtually no personal agency. The only way to avoid the adverse consequences is to severely curtail our lifestyle. Now. There’s no easing into it. No evening classes at the college annex to up-skill our ability to dodge the virus. No Ecopass that lets us leave the breathing up to someone else. Not much of any choice for replacing a stalled lifestyle with a different one because they’re all stalled.

Which gets me to the thinking behind “Mass transit kills.” It does so because its an efficient vector for transmitting biological infections. The early studies show how quickly COVID-19 spread due to air travel followed by trains, taxis, and buses in crowed urban settings. A fatal car accident, however, is a local event. First responders and surrounding communities are not at risk of death due to the now static car accident. A viral or bacterial outbreak is dynamic and spreads just by virtue of people moving around. Globally, how long would humans have to drive cars before the death toll matched that of the number of deaths that have been attributed to plagues and pandemics throughout history? And historically, plagues and pandemics moved at the speed of rats, mosquitoes, and ox carts. Today, they can move just shy the speed of sound.

Having read close to a couple dozen COVID-19 related research papers (surprisingly, none of them authored by CNN/MSNBC/FOX/CBS/ABC/NBC/BBC et. al.), the chances that we’re approaching a pandemic that won’t offer much of a lead time are increasing. The growth of human population has greatly increased the adjacent possible for animal virus’ to make the jump to humans. The probability of an asymptomatic contagious period combined with lethal morbidity increases as the adjacent possible horizon expands. If such a viral combination were to occur, mass transit will be that virus’ best friend.

My thinking is probably incomplete on this matter, so I welcome your comments.

Root Causes

The sage business guru Willie Sutton might answer the question “Why must we work so hard at digging to finding the causes to our problems?” by observing “Because that’s where the roots are.”
Digging to find root causes is hard work. They’re are rarely obvious and there’s never just one. Occasionally, you might get lucky and trip over an obvious root cause (obvious once you’ve tripped over it.) Most often, it’ll require some unknown amount of exploration and experimentation.

Even so, I’ve watch as people work very hard to avoid the hard work needed to find root causes or fail to acknowledge them even when they are wrapped around their ankles. It’s an odd form of bikeshedding whereby the seemingly obvious major issues are ignored in favor of issues that are much easier to identify, explain, or understand.

One thing is certain, you’ll know you’ve found a root cause when one of two things happen: You implement a change meant to correct the issue and a whole lot of other things get fixed as a result or there is noisy and aggressive resistance to change.

Poor morale, for example, is often a presenting symptom mistaken for a root cause. The inexperienced (or lazy) will throw fixes at poor morale like money, happy hours, or other trinkets. These work in the very short term and have their place in a manager’s toolbox, but eventually more money becomes the new low pay and more alcohol has it’s own very steep downside.

Morale is best understood as a signal for measuring the health of the underlying system. Poor morale is a signal that a whole lot of things are going wrong and that they’ve been going wrong for an extended period of time. By leveraging a system dynamics approach, it’s relatively easy to make some educated guesses about where the root causes may be. That’s the easy part.

The hard work lies with figuring out what interventions to implement and determining how to measure whether or not the changes are having the desired effect. A positive shift in morale would certainly be one of the indicators. But since it is a lagging indicator on the scale of months, it would be important to include several other measures that are more closely associated with the selected interventions.

There are other systemic symptoms that are relatively easy to identify and track. Workforce turnover, rework, and delays in delivery of high dependency work products are just a couple of examples. Each of these would suggest a different approach needed to resolve the underlying issues and restore balance to the system dynamics behind a team or organization’s performance.

Assessing and Tracking Team Performance – Part 9: Design Changes and Scope

Changes in design can either be tightly or loosely coupled to changes in scope. In general, you can’t change one without changing the other. This is how I think of design and scope. Others think of them differently.

Few people intentionally change the scope of a project. Design changes, however, are usually intentional and frequent. They are also usually small relative to the overall project design so their effect on scope and progress can go unnoticed.

Nonetheless, small design changes are additive. Accumulate enough of them and it becomes apparent that scope has been affected. Few people recognize what has happened until it’s too late. A successive string of “little UI tweaks,” a “simple” addition to handle another file format that turned out to be not-so-simple to implement, a feature request slipped in by a senior executive to please a super important client – changes like this incrementally and adversely impact the delivery team’s performance.

Scope changes primarily impact the amount of Work to Do (Figure 1). Of course, Scope changes impact other parts of the system, too. The extent depends on the size of the Scope change and how management responds to the change in Scope. Do they push out the Deadline? Do they Hire Talent?

Figure 1 (click to enlarge)

The effect of Design Changes on the system are more immediate and significant. Progress slows down while the system works to understand and respond to the Design Changes. As with Scope, the effect will depend on the extent of the Design Changes introduced into the system. The amount of Work to Do will increase. The development team will need to switch focus to study the changes (Task Switching. ) If other teams are dependent on completion of prior work or are waiting for the new changes, Overlap and Concurrence will increase. To incorporate the changes mid-project, there will likely be Technical Debt incurred in order to keep the project on schedule. And if the design impacts work already completed or in progress, there will be an increase in the amount of Rework to Do for the areas impacted by the Design Changes.

Perhaps the most important secondary consequence of uncontrolled design changes is the effect on morale. Development teams love a good challenge and solving problems. But this only has a positive effect on morale if the goal posts don’t change much. If the end is perpetually just over the next hill, morale begins to suffer. This hit to morale usually happens much quicker than most managers realize.

It is better to push off non-critical design changes to a future release. This very act often serves as a clear demonstration to development teams that management is actively working to control scope and can have a positive effect on the team’s morale, even if they are under a heavy workload.

 

How to Frame Team Development Challenges

When working with teams or organizations new to Agile and scrum, it’s common for scrum masters to face varying degrees of resistance to the new methods and processes. The resistance can take many forms ranging from passive-aggressive behaviors to overt aggression and even sabotage.

There are two things to consider when looking for ways to resolve this type of resistance.

  1. The specific issues are typically not Agile problems in the sense they won’t be solved by any specific Agile techniques, methods, or frameworks. Rather, they are people problems; issues with how people’s behavior is driven by their values and beliefs. We have to resolve the people problems in concert with implementing Agile or Agile will never be successfully implemented. We also have to be sure not to confuse the two.
  2. We need to look at these challenges as opportunities.

It’s the second point I want to focus on in this post.

To simply paint the often unpleasant experiences we have with coaching our teams in the ways of Agile and scrum as “opportunities” isn’t much of a solution. It’s weak tea and about as useful as “Let’s all just think positive thoughts and eventually it’ll get better.” Nor do I suggest we sugar coat the unpleasantness by sprinkling “It’s an opportunity!” language on our conversations. Losing your job or breaking your leg may be one of those “wonderful opportunities” born from adversity, but only after you’ve found that next better job or your leg has healed. Hustling for new work or sitting idle while in pain and healing is decidedly unpleasant.

I had something else in mind for thinking about the challenges we face as “opportunities.” It’s in the midst of the unpleasant phase where the opportunities are found that lead to success. Seth Godin speaks to this in his book “The Dip.”

The Dip is the long slog between starting and mastery. The Dip is the combination of bureaucracy and busywork you must deal with in order to get certified in scuba diving. The Dip is the difference between the easy “beginner” technique and the more useful “expert” approach in skiing or fashion design. The Dip is the long stretch between beginner’s luck and real accomplishment.

It’s the classic “things will get worse before they get better.” But as Zig Ziglar put it, “Anything worth doing is worth doing poorly–until you can learn to do it well.”

It’s important to recognize and acknowledge when you’re in The Dip. Not just as an individual scrum master on a particular team, but perhaps the entire organization as well. Solving the issues you’re encountering today is exactly what you need to do in order to be successful in the long term. The Dip is inevitable and unavoidable. Part of the scrum master’s purpose is to raise the awareness of this fact so that the underlying issues that need to be resolved can be amplified.

This is what can make serving in the scrum master role particularly unpleasant at times. It’s when you earn your pay. In general, people don’t like to look at themselves in the Agile mirror that scrum masters are charged with holding up in front of them.

The Dip is another way to describe Shalloway’s Corollary applied to teams and organizations. Unlike losing a job or breaking a leg, what we’re dealing with is actually something we most definitely should expect. The system was always going to push back. Now we’re discovering exactly how that’s going to happen. The system is showing us what needs to change in order to become a more Agile organization. No more guess work. It’s a gift. Knowing this should be cause for optimism and viewing the tasks ahead as an opportunity. The way is known. There is less ambiguity. Doesn’t mean the path ahead is easy, just better known. That alone is incredibly useful.

A final thought. “The System” that’s been in place at any organization is what it is. For better or worse, it’s been working, perhaps for decades. Anything that challenges the status quo is going to receive push back. It just happens that Agile is the current challenger. As scrum masters, we have to continually evaluate our own “system” in a way that prevents it from becoming the next version of the problem.

  • Is a particular tool, process, or method fit for purpose?
  • What problem are we trying to solve?
  • Are there aspects of the “old system” that actually make sense to keep in place?
  • Are the frustrations we’re experiencing due to the “old system” pushing back or are they the result of our own ossification around out dated or misapplied beliefs?

Assessing and Tracking Team Performance – Part 8: Taming the Wild Horses

Over the years I have come to regard projects as a boat in the ocean and relationships as the ocean.Michael Wade

Remember the phrases from earlier in the article series? Here they are again.

  • “We’re not moving the delivery date.”
  • “We’ll just have to work harder.”
  • “The team will have to put in more time until we’re caught up.”
  • “We’ll need more people on the project.”
  • “The team will have to work faster.”
  • “We’re to the point of exhaustion.”
  • “I’m losing track of all the pieces.”
  • “There’s no time for training.”
  • “Where did those errors come from?”
  • “We’re waiting on another team.”
  • “Another person quit the company?!?!”
  • “I don’t care. I get done what I get done when I get it done.”

How much more meaningful these are to you now that you understand a little more about the system dynamics that drive projects. Choose just one of these and find where it’s reflected in the model. (Figure 1)1.

Figure 1 (click to enlarge)

Now follow the impact and consequences around the various feedback loops. Reflect for a moment an ask yourself, “What can I do to help keep the system healthy and productive in light of what I now know may be happening?” There’s a lot to consider. We’ll cover several options in this article.

Moving from the outside in, the most visible nodes in the system are also influenced the least by direct intervention. These are Morale, Fatigue, and Experience. “The beatings will continue until morale improves” is, I hope, recognized as a cynical joke. While offering free coffee, Red Bull, and unlimited M&Ms may perk up employees in the short term, the long term health consequences are grim indeed. As for Experience, well, that just takes time and a great deal of effort to fully shape and mature.

Attempting to alter these nodes directly is likely to be wasted effort at best and more probably harmful. Even if some cursory improvement can be made, the underlying systemic influences – the true drivers – will still be present and will exert a far more powerful influence. It’s Conway’s Law, pure and simple. It’s better to thinking of Morale, Fatigue, and Experience as symptoms or indicators to be recognized and tracked rather than root causes to be treated. As indicators, they are incredibility powerful sources of information on whether or not changes made to other parts of the system are being successful. They are to be used, not abused.

We’ll begin by working backward from the disaster that was built up over the last several articles in the series. Let’s imagine we have a demoralized team (or teams) that are exhausted and burdened with an impossible delivery schedule. As it stands, it’s unfixable.  A sprinter has a better chance of breaking the three minute mile than this team has in delivering their project by the stated delivery date.

Let’s also assume the choice is to continue the project. The two major actions for management at the is point are to move the Deadline and reduce the amount of Work to Do in the system. These aren’t choices, they’re actions that need to be engaged thoughtfully.

Simply moving the date to some point in the future that seems “doable” is yet another gamble. Neither will moving the date instantly resolve the other systemic issues. There is a considerable amount of recovery and rebuilding to be completed. It takes time to hire the people needed to rebuild the workforce. It takes time to rebuild trust and morale among the employees that remain. Moving the deadline out will begin to relieve pressure, but it will take time for the inflamed system to cool down and find an optimal working temperature.

The challenge for this first step is: How can you go about finding what is a reasonable date for the deadline? Answering this question is dependent on what is learned by looking to other parts of the system model for data.

  • How depleted is the Workforce and how long will it take to build it back up?
  • How much of the critical talent has remained with the organization (Experience)?
  • Is any compensation (time or money) going to be offered to offset the Overtime put in on the project?
  • How much time will it take to refactor and refine the product backlogs such that work streams can are brought into alignment and Overlap and Concurrence and Task Switching minimized?
  • What tool and process changes need to be made to reduce the Congestion and Communication Difficulties?
  • What’s the Total Known Remaining Work in the system?

Probably, the best thing to do is to declare that for some time boxed period, there will be no deadline date while these and many other questions are explored. This will have a side benefit of signaling to the development teams that management is serious about finding a realistic date. This will help to start rebuilding trust between management and the development teams.

One of the factors to consider in determining whether a new deadline can reliably be set is the Total Known Remaining Work in the system. As has been discussed previously, increasing the Total Known Remaining Work puts pressure on the completion date. Similarly, decreasing the
Total Known Remaining Work by some means will increase the likelihood that the completion date can be met. Actions to take that will allow management to regain control of the work flow include:

  • Revisit the release schedule and take a phased approach with clearly defined minimum viable/valuable product deliverables.
  • Complete a detailed review of the work done to date to get a clear picture of the amount of technical and dark debt in the system.
  • Reassess the sales and marketing strategies so they are in clear alignment with the capabilities of the development and delivery system. What can be eliminated? What can be pushed to future releases? Eliminate “nice to have’s” from this list. Either the feature can be completed in a particular release or it can’t. Those that can’t are bumped to a future release.

It’s been shown that changes in one part of the system will affect other parts of the system, whether by design or not. In this article we’ve discussed how adjusting the Deadline and Total Known Remaining Work can affect each other and the entire system. When adjusted in a way that considers system-wide effects, they can help restore balance and predictability to the overall system.

Previous article in the series: Assessing and Tracking Team Performance – Part 7: “Abandon All Hope,…”

References

1The core of the model I use to assess team and organization health is based on the work of James Lyneis and David Ford: System Dynamics Applied to Project Management, System Dynamics Review Volume 23 Number 2/3 Summer/Fall 2007

Assessing and Tracking Team Performance – Part 7: “Abandon All Hope,…”

“…ye who enter here.” So reads the inscription to the Gates of Hell in Dante Alighieri’s epic poem, “Divine Comedy.” Who among us hasn’t felt on occasion that stepping across the threshold to our place of employment is like passing through the gates of Dante’s Inferno? But as the poets have told us, the way to peace is to find the path through our troubles. In this article, we’ll look into just how deeply project system dynamics can adversely affect progress and even whether or not the project is successful.

But I do want to arm the reader with a couple of rays of hope. The concluding article in this series will focus on how this system model1 can be used to good effect, how it can be used to identify problems before they grow out of control. Therein lies the path to peace. Before we get there, we need to understand several more influential feedback loops.

As the Delay to Completion becomes critical, management begins to panic. Not wanting to push the deadline out they work to influence the other three options focused on modifying the behavior of the delivery team. The end result is a team that is caught in the Work Faster, Work More, and Add People loops along with all the other associated downstream loops. The effect is compounded by the emergence of other feedback loops if teams are placed in this position for an extended period of time.

Over time, the shortcuts, hacks, and quick fixes put in place to keep the pace of progress as high as possible settle in as technical debt. They work – for now – so they don’t surface as errors for quality assurance to discover. Down the road, however, solutions hastily put in place as stop-gaps fail when later solutions require existing solutions to be more robust then they are. For example, a software method that doesn’t take advantage of multi-threading may break when a later solution needs that method to scale beyond it’s single thread capacity. The shortcut is now a defect.

Figure 1 (click to enlarge)

If the technical debt remains in place for an extended period of time, it may be covered by several release layers. When it does flip to defect status due to some later stress, it can be much more time consuming and expensive to uncover. The original developer of the code may not be available or even if she is, it could take her quite a bit of time to become reacquainted with the code. This can be thought of as a form of dark debt and is reflected in the Errors Build Errors Loop (Figure 1, J).

As the teams struggle to keep up the pace of progress and reduce the Delay to Completion, work streams start to become out of sequence. One team has an easier time at crafting their solution while another, to which they are dependent on the output, hits a significant snag and is delayed several weeks. In order to stay busy, the first team starts work on something else while the second team finishes their work. When the second team delivers, the first team is not prepared to immediately shift back to their original work stream and so their deliverable is delayed even further. Meanwhile, a third team, that was dependent on the first team’s deliverable has now been delayed by the cumulative delay of the first two teams. Teams and individuals begin to take shortcuts as delivery of interim work products become out of sync with each other. The diminished focus and desynchronization of work streams leads to an increase in the Error Fraction, which in turn leads to a further Delay to Completion. This is the Haste Makes Out-of-Sequence Work Loop (Figure 1, K).

Figure 2 (click to enlarge)

As the effects of the Haste Makes Out-of-Sequence Work Loop build,  team begin switching back-and-forth between work streams depending on who is making the most noise for the completion of any particular deliverable. This is the Thrash and Churn Loop (Figure 2, L). Switching from stream to stream or, in worst cases, task to task, places a tremendous burden on development teams and can do more to slow progress than almost anything else I’ve encountered in team management. Not covered in this model is the type of churn that occurs when parts of the project undergo redesign after work has begun on the existing design. Long term projects are particularly susceptible to adverse impacts from redesign as the changes are often farther reaching. The drivers behind a redesign can range from trivial (a new CTO has a personal dislike for a platform vendor) to critical (a security flaw uncovered in a core technical component.)

If all the loops described to this point in the article series are allowed to run uncorrected the system is likely to crash as the project becomes one massive firefighting effort. A key indicator for when this is happening is employee morale.

Figure 3 (click to enlarge)

The increased Fatigue, the growing burden of Work/Rework to Do, the unsatisfying Task Switching between work assignments all combine to causes a decrease in team Morale. This is the Hopelessness Loop (Figure 3, M). Teams are left with a powerless feeling of being caught on a never ending treadmill. And so, stepping across the threshold to the office is like passing through the gates of Dante’s Inferno.

The ripple effect from a decrease in Morale leads to a decrease in the Workforce as employees leave the organization in search of less stressful, more satisfying work. This is the Turnover Loop (Figure 3, N). The remaining demoralized employees are even less productive and unhappy employees make more mistakes, thus increasing the Error Fraction in the system. The downstream result is that the Delay to Completion increases yet again.

If corrective action isn’t taken the law of diminishing returns becomes evident and the system collapses. The cost overruns become prohibitive and the project is cancelled. Worst case, the organization runs out of resources (money, time, or both) and goes out of business. Those are bad things. In the concluding article to this series, we look at how this model can be used to read the current state of a project’s system dynamics and explore some ways we can intervene such that the system doesn’t run out of control.

Previous article in the series: Assessing and Tracking Team Performance – Part 6: It Lives! But it’s Out of Control!

Next article in the series: Assessing and Tracking Team Performance – Part 8: Taming the Wild Horses

References

1The core of the model I use to assess team and organization health is based on the work of James Lyneis and David Ford: System Dynamics Applied to Project Management, System Dynamics Review Volume 23 Number 2/3 Summer/Fall 2007

Assessing and Tracking Team Performance – Part 6: It Lives! But it’s Out of Control!

In the previous article for this series, I described three options managers could consider if moving the project deadline was out of the question.

  1. Increase employee work intensity
  2. Call for overtime
  3. Hire people

On the face of it, they each appeared to offer a path toward returning a drifting schedule to be on time. Now let’s look a little further down the road to see what happens when the juice is applied to each of these options in turn. If we implement any of these options, what are the likely consequences?

We know that errors in the work flow are unavoidable. If we encourage or pressure the development team to finish more work in less time (the Work Faster Loop1, Figure 1, C) this will result in an increase in the errors along with an increase in the amount of Work Done.

Figure 1 (click to enlarge)

This is the Haste Makes Waste Loop (Figure 1, F). In other words, the increase in Work Intensity will have a concomitant increase in the Error Fraction which means there is an increase in Errors generated. The extended consequence of pulling the Work Intensity lever is an increase in Work to Do in the form of extra Rework to Do.

OK. So Option 1 isn’t a get-out-of-jail-free card. There are strings attached. How about Option 2, call for the development team to work overtime?

Figure 2 (click to enlarge)

By increasing Overtime, the risk of Fatigue increases sharply. This results in yet another increase in the Error Fraction (tired people make more mistakes than rested people) and a decrease in Productivity (tired people don’t work as efficiently as rested people.) Both slow down Progress and increases the amount of Rework to Do in the system. This is the Burnout Loop (Figure 2, G).

OK. So Option 2 doesn’t lead to sunshine and roses. There are dark clouds and weeds in the mix. Let’s give Option 3 a go, hire more people!

Figure 3 (click to enlarge)

So we’ve beefed up the Workforce by hiring a bunch of people to join the team. With all those extra people in the mix we’ve also increased the overall Congestion and Communication Difficulties. The email traffic increases, everyone’s Inbox fills up faster, meeting attendee size increases along with the number of meetings. The signal to noise ratio decreases and miscommunication increases. This increases the Error Fraction, decreases Productive, and decreased Progress. End result: the Too Big to Manage Loop (Figure 3, H).

But that’s not all. By hiring extra people, we’ve activated the Expertise Dilution Loop (Figure 5, I).

Figure 5 (click to enlarge)

All those new hires don’t come in off the street ready to go. They decrease the depth of Experience available to focus on making progress. Experienced employees have to slow down and assist new employees in understanding the technical systems, the architecture, and development standards. New employees will need some period of time to become familiar with the work environment, project objectives,  who’s who, and where the coffee is.

As they work to understand and gain experience with the systems, new hires will necessarily make mistakes and increase the Error Fraction. While there are more workers available to focus on the product backlog, the available expertise is spread much more thinly and is collectively less experienced until such time the new workers are up to speed with what needs to be done and how. So the errors go up and Productivity goes down. The down stream effect is often a further increase in the Delay to Completion. As the saying goes, throwing more people at the problem more often than not makes the problem worse.

OK. So no unicorns and rainbows here either. More like a lot of warthogs and rain.

Looks like the first level effects were negated by the second level consequences. That’s bad enough, but the third level consequences can be even worse in that they are often much longer lasting and much more difficult to resolve. We’ll look at those in the next article in this series.

Previous article in the series: Assessing and Tracking Team Performance – Part 5: Welcome to the Labyrinth

Next article in the series: Assessing and Tracking Team Performance – Part 7: “Abandon All Hope,…”

References

1The core of the model I use to assess team and organization health is based on the work of James Lyneis and David Ford: System Dynamics Applied to Project Management, System Dynamics Review Volume 23 Number 2/3 Summer/Fall 2007