cognitive bias - Agile Doctor

9 June, 201627 June, 2016

The Five Attributes of a Good Scrum Team

One of the best experiences I can have as an Agile Coach is presenting Agile and Scrum to people with little or no experience. It grounds me and after many years of living Agile, keeps me from falling into the Curse of Knowledge cognitive bias. Between these presentations and my daily coaching practice, I am reminded yet again at the importance of forming a good scrum team. This, along with proper backlog compilation and maintenance, can make the difference between success and endless frustration. In my experience, proper scrum team formation is the area where companies who are unsuccessful in Agile transformations fail most often.

Over the years, with the help of my teams and the many knowledgeable colleagues that I have worked with, I have distilled everything I have learned and come up with five attributes of a good scrum team. I use it much like a mantra. Those attributes are: Small, Co-Located, Dedicated, Stable and Cross-Functional. That is not to say that a good scrum team will not have other elements or that you can’t witness improvement without all five, but like the sculptor who is only done when there is nothing left to take away, these five represent an ideal essence of a good team. None of these five things can be removed without real consequences to the success of the team.

Small

I write about size at length (and mention the five attributes) in a previous post, When it Comes to Software Development – Size Matters, so I encourage you to read it for some eye-opening account of a major study that confirms this fact. Suffice it to say that Software Development is about communication and collaboration. It is complex knowledge work. In a physical, manufacturing model, adding a person to the effort would result in the expected proportional increase in productivity. In software development, however, adding an additional person merely exponentially increases the number of communication channels whereby any expected increase in productivity is quickly overtaken by the number of communication channels created. There is a reason Agilists recommend small teams. Basically, you can save money because your cost per unit of productive (and quality) work decreases.

Co-Located

Co-Location seems to be an issue with all of the companies that I consult for. We know that the best software developers can be 10 times or more productive than the least. We know that face-to-face communication is multiple times better than any of the substitutes we employ when that mode is not available. We all laugh at the You Tube video “A Conference Call in Real Life”. We know that the unacknowledged creation of technical debt will cause us financial havoc for years to come. Not convinced, I encourage you to check out my blog on the High Cost of Low Cost Software Development. And yet we still continue to source our software development to low bidders around the globe. Here’s the really interesting thing. For many years I have asked a simple question – does it work? I get two answers. The majority shake their head, laugh, and provide a solid “No”. The optimists of the group say that “We have found a way to make it work.” I also see a great deal of blogs that are titled “How We Found a Way to Make Offshore Work”, but it takes little research skills to uncover the author as someone employed by a company that works offshore. Never is there an enthusiastic “Yes.” Most would bring the work back if they could, but it appears that there is a mysterious formation in many software development organizations that continues to think they are doing the right thing by piece-mealing work to various locations. I can only guess it is accounting, but I have yet to meet anyone whom I respect who actually understands software development who would recommend it.

Dedicated

I often rail against the project-centric focus of many software development organizations. For more information, I encourage you to check out my blog “Why Project Focused Mentality is Killing Software Development”. The problem is that in projects we build teams around projects so that one, especially a key employee, will be spread over multiple concurrent projects. There are a number of very serious negative effects to doing this. First, context shifting means that every time a developer must change their concentrated area of focus they will lose 15 minutes minimum. If I am working on two different projects concurrently, there is not a huge loss, assuming that I might work on one in the morning and one after lunch, but many developers are bounced from thing to thing like so many pinballs with context shifting throughout the day. Hours each day are wasted and no project gets the attention it deserves. A better way is to create a small, co-located scrum team around a product backlog and bring the work of these multiple projects to the team via their backlog. The ability for individuals on the team to not fall prey to context shifting will allow them to focus on their work, even at times leading to a state called Flow in which developers (and athletes, artists, etc) are at their peak performance. For those interested, I refer you to the work of Mihaly Csikszentmihalyi.

Stable

Project-centric thinking also results in teams that are short-lived. We put the team together for a particular period (sometimes relatively short) of time. When the project is done, the team is disbanded. This causes a number of issues. First, every team goes through a period of “storming, norming, and performing.” This is easy to see visually when you plot the velocities of multiple teams on a timeline. You can visually see the storming period as teams learn to work together as a team instead of a collection of individuals, through very low (if non-existent) velocity. In my experience, I have come to the conclusion that I expect nearly nothing from a brand new team for the first couple of iterations. It is not until they reach iterations 3, 4 or even 5 that they will reach what is their performing velocity. Therefore, every time I break up a team, I have a very high overhead associated with the team’s “storming and norming.” Another benefit of keeping the same people on teams for a longer period of time is by simply learning how to better communicate with each other over time. Since software development is about communication and collaboration, the more time we spend together, the more effective we become in communicating. I remember reading about the notion of “hyper-productive” teams from Scott Downey and Jeff Sutherland. The interesting thing is that their “hyper-performance” did not manifest until after the team had been together for some time.

Cross Functional

In some respects, cross functionality of people is a by-product of the fact that team size should be kept small. If there are 15 things I need to do to get my code into production, I obviously will not be able to do so if there needs to be an expert for each piece. The creation of “silos” is great if your goal is to create a MDD (mortgage driven development) environment. It is bad for the flow of the product. Silos create queues. Queues, if you want to deliver something quicker, are bad. I highly recommend the book Principles of Product Development Flow by Don Reinersten for a deeper understanding of queuing theory and the damage that out-of-control queues can have. This book talks about the concept of generalizing specialists. In my experience, developers are more motivated by status and mastery of new technology and ideas than any other group of people I have worked with. Creating an environment where developers are expected to know more than a single specialized domain is not only good for moving the software through the system quicker, but it also leads to greater developer engagement. A team should be responsible for all aspects of the software product and the development cycle. This cannot be accomplished without having team members who are cross functional.

Final Thoughts

An old African proverb states, “If you want to go fast, go alone. If you want to go far, go together.” In order to be successful in software development we need to understand teams and team dynamics. My many years of experience working with what I would estimate around a hundred development teams has led me to conclude that there are five basic attributes for an optimal development team – small, co-located, dedicated, stable and cross functional. I hope that these five attributes help you as you continue your quest for agility.

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14 December, 201516 December, 2015

Do Coding Interviews Work?

I have recently come across some interesting information regarding coding interviews. If you are not familiar with coding interviews, these are interviews for technical people, usually software developers, to prove that they have the ability to code so they are sometimes referred to as programming interviews. These can be either taken as a computer-based test or frequently done as whiteboard exercises. They often take the form of brain teasing riddles or binary search questions. The premise is that these coding interviews, conducted in an arbitrary environment, are a good proxy for determining whether or not someone will perform well in the real world.

As with all things, instead of relying on our human instinct, which is riddled with cognitive biases, we must rely on science to understand true cause and effect. The science has spoken loud and clear; there is no relationship between coding interviews and performance on the job for software developers. Don’t believe me; here’s what Laszlo Bock, Senior Vice President of People Operations at Google had to say on the topic:

…everyone thinks they’re really good at it. The reality is that very few people are.

Years ago, we did a study to determine whether anyone at Google is particularly good at hiring. We looked at tens of thousands of interviews, and everyone who had done the interviews and what they scored the candidate, and how that person ultimately performed in their job. We found zero relationship. It’s a complete random mess…

It appears to me that very often the interviewer is much more concerned with showing the candidate how astute he or she is as opposed to finding out whether or not the candidate is a good fit for the position. I recently read a blog post that stated that candidates should spend a great deal of time preparing for these coding interviews, in the neighborhood of about 40 hours. While this might be what it takes to “ace” such an interview, it still begs the question of whether the coding interview is actual predictive of the candidate’s ability to function in the position. It is not.

This is where the cognitive biases come in. It appears that there is a great deal of the illusion of control, which, as humans, we are highly susceptible to. We think that somehow we are able to ask some questions and magically be able to determine how one will perform on the job. I would expect there is a bit of confirmation bias because we are subject to cherry-picking our evidence to support our previously held views (i.e. coding interviews are effective) and a similar bias called choice-supportive bias which is the tendency to remember one’s own choices as better than they actually are. I am certain that a whole host of other biases can be brought forth which not only explain why we think coding interviews are effective when there is evidence to the contrary, but also the stubborn way in which these have continued to persist in spite of such evidence.

In my career I have taken a few of these interviews and I may have my own biases since I don’t recall ever getting a job offer after one of these interviews. I remember taking one many years ago on SQL and ETL. I had been doing SQL and ETL quite successfully for over a year and knew I could perform very well in the position.

Nevertheless, the test was taken not on my own computer, but a computer that I was wholly unfamiliar with, a laptop with a built in mouse. I remember that I had some frustration just with the configuration of the computer I was using. I also remember that the majority of the questions I could have easily answered had I been able to use reference materials like I would be able to do in the real world. It felt like the test was measuring how well I could fix my parachute after I had been thrown from the plane. It did not measure how I would perform on my job, but how well I had memorized simple syntax that is probably not worth memorizing.

I know there are those who will say that one should remember such commands, but given that the average programmer contributes five lines per day to the final product, does it really make that much sense? Perhaps it would be better to fill one’s mind with other more important things? What I do know is this – had I been offered the position I would have outperformed many who would happen to ace this test because I have a wealth of experience outside of the ability to memorize coding syntax.

In a recent blog post I wrote a tongue-in-cheek title, “Accenture Ends Annual Review (and Admits Earth Orbits the Sun)”. Of all my dozens of blogs (I have posted over 100 over the years), this was perhaps the most provocative of them all and certainly the most popular, with literally thousands of views. In this case it took literally decades to finally admit what science has taught us with respect to annual reviews. Therefore, I expect that coding interviews will be with us for some time to come, but at least I can look forward to the day when I write the blog “Company X abolishes the coding interview (and Admits Earth is Round).”

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7 December, 201517 December, 2015

Brainstorming – Effective Technique or Sacred Cow?

I have spent a great deal of time studying and reading about human cognitive biases and their effect on business, especially the business of software development. This past weekend I finished the groundbreaking book by Stuart Sutherland, appropriately title “Irrationality: The Enemy Within”.

Since I have made quite a bit of study on the topic previously, some of the material was either referenced by other materials or has lost its shock value since I have become thoroughly convinced of humankind’s built in propensity not only for irrational behavior, but their inability to recognize that these biases are a problem. In fact, my experience is that a large segment of our population is not only ignorant of biases but seems to revel in a willful ignorance of scientific evidence. Certainly there appears to be a great deal of cognitive bias (mostly the confirmation bias) in the debate on climate change.

My previous understanding of human cognitive bias withstanding, while the book was published in 1992, the information is still relevant, interesting and cogent. I would suppose that there are a number of things that are worthy of note, but since there is such a wealth of information in the book, I decided to choose a single instance to write about here and encourage those interested in more examples to actually get a copy of the original material.

The one thing that caught my attention and has stuck in my mind is the example of using a technique called “brainstorming” to improve creativity and productivity. For those who have lived on another planet, brainstorming is the process of getting as many ideas out as possible without judging or filtering of the ideas. It has been used for decades since its introduction by Alex Olsen in the book Applied Imagination. Olsen claimed that in his experience using brainstorming in advertising agencies resulted in 44% more worthwhile ideas than individuals thinking up ideas without the benefit of group discussion.

Ever since that time, brainstorming has been widely used to improve creativity and productivity of groups. However, here’s the kicker, since as long ago as 1958, Osborn’s claims has been subject to numerous studies which almost universally cast doubt upon the effectiveness of brainstorming. Keith Sawyer, a psychologist at Washington University in St. Louis, states: “Decades of research have consistently shown that brainstorming groups think of far fewer ideas than the same number of people who work alone and later pool their ideas.” In other words, brainstorming doesn’t work quite as well as we think it does (or should).

With scientific evidence questioning the effectiveness of brainstorming vast, the real question is why does the use of brainstorming persist? The question is at the heart of much of my agile practice in that the prime issue is not whether one is merely effective, but that one is optimal. It is obvious to me that several cognitive biases are in play in keeping brainstorming around.

There is something of the availability cascade to brainstorming “which is a self-reinforcing process in which a collective belief gains more and more plausibility through its increasing repetition in public discourse (or ‘repeat something long enough and it will become true’)” (Wikipedia). Furthermore, a whole host of cognitive biases around groupthink, herd behavior and the bandwagon effect certainly have their influence on the popularity of brainstorming. Since brainstorming “seems” to make sense it is also subject to the belief bias, which is seen when the believability of the conclusion leads us to misunderstand the true effectiveness of the process. Frankly, I would suppose that I could find literally dozens of cognitive biases, which allow brainstorming to proliferate as the “go to” technique for group creativity and productivity.

Given that brainstorming may very well not be optimal, what are the alternatives that have actually been scientifically proven to be more effective? In a 2012 article for Psychology Today, Ray Williams proposes a few modifications to the brainstorming approach:

Have groups collaborate frequently by having them in close physical proximity to each other;
Pay attention to creating physical spaces that enable good collaboration, which facilitates people frequently “running into each other” while at work;
Revise the “no criticism” script of brainstorming to encourage debate about ideas;
Use appreciative inquiry techniques, where group participants build on ideas suggested by each individual in the group.

Most interesting to me about these suggestions is how closely they align to the things that Agile (and I) speak to, namely close attention to co-location of people within an Agile team to increase good collaboration, allowing an environment where there is embracing of feedback as opposed to “failure” and using iterative feedback to improve ideas (and software) incrementally.

There are a great number of cognitive biases inherent in human beings. The first step is to be aware that these irrationalities exist. We must also acknowledge that we, as individuals, are subject to these irrationalities. Furthermore, we need to create an environment of safety that gives us the freedom and encouragement to continually explore and seek the underlying scientific truths, the “why” of what we do – the freedom to gore the sacred cows.

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1 December, 20159 December, 2015

Agile – It’s All About Making Better Decisions

I’ve been spending a lot of time recently doing research, reading and presenting on human cognitive biases. To the initiated, cognitive biases are defined as

“…a systematic pattern of deviation from norm or rationality in judgment, whereby inferences about other people and situations may be drawn in an illogical fashion. Individuals create their own ‘subjective social reality’ from their perception of the input.” (Wikipedia Definition)

In other words, cognitive biases exist when there is a gap between our perception of reality and objective reality. For example, there is the “confirmation bias” which is our human tendency to seek out or interpret information that confirms one’s existing opinions.

While the term “cognitive bias” is relatively new (it was coined in 1972 by Amos Tversky and Daniel Kahneman), researchers have already uncovered literally over a hundred cognitive biases, some which are relatively tame like the “google effect” (or digital amnesia), where there is a tendency to forget information that can be easily researched, to ones that can lead to more disastrous consequences like the Sunk Cost Fallacy where people justify increased investment in a decision based on prior investment instead of looking only at future efficacy. The Sunk Cost Effect, along with the Overconfidence Effect and Receny Effect, played a role in the May 1996 mountain climbing tragedy, made famous in the movie Everest, that resulted in the death of five experienced climbers.

A great number of cognitive biases have been found through the work of behavioral economics researchers like Dan Ariely who wrote the wonderful books Predictably Irrational and The Upside of Irrationality. Underlying all of classic economics is the concept of homo economicus, or economic man who behaves in rational ways to maximize individual returns and acts in his own self-interest. Unfortunately, this is not the case and humans often act irrationally (and predictably so) because of their inherent cognitive biases. Humans all have biases for loss aversion and would choose to avoid loss over a larger corresponding potential gain and thus act as “homo irrationalis” as discovered by behavioral economics instead of “homo economicus” as predicted by classic economics.

It is our cognitive biases that cause us to make irrational decisions. Since behavioral economists found many of these cognitive biases, it was not a great leap to see how cognitive biases would be a paramount concern for the economics of software development. In my coaching practice, a great deal of my time and effort is used in helping organizations make better decisions about software development. Many times the optimal decisions are counter intuitive to people’s inherent biases so my job (and my passion) is helping companies see the world of software development differently so that, when it comes down to making a decision, they have all the knowledge necessary to make the optimal economic decision.

One of the most prevalent biases in software development is to see the world in a mechanistic / Tayloristic manner. Taylor’s viewpoint was fine for the old world of physical work, but does not hold up in the complex knowledge work being done by software development professionals today. Unfortunately, most of the people making software development decisions are predominantly influenced by this old, less optimal way of viewing the world, and, as a result, make sub-optimal decisions. For example, in the mechanistic worldview, adding more people to an effort results in a corresponding increase in output. If there is an existing team of seven people and we add seven more then we would (if we hold this mechanistic bias) expect the work to be approximately twice as fast. However, like the behavioral economists that found the real world to be counter intuitive to homo economicus, actual studies have found that the need for increased communication of knowledge work nearly outpaces any incremental increase in individual productivity (see Top Performing Projects Use Small Teams). I have always said that if you want to double productivity of a fourteen person team all that is necessary is to create two teams of seven.

The mechanistic bias can also be seen in many of the ways that the Agile philosophy is implemented. For example, the scrum framework is often trained as a series of ceremonies and actions with little or no understanding of the reason such mechanistic actions are successful. “Scrum Masters” are “certified” with only two days of training and a simple test. The training deals with ideal situations, but when the scrum master actually has to implement scrum, he or she is woefully unprepared. In the real world compromises and decisions must be made. Without understanding the underlying “why” of agile and the basic nature of software development, the decisions and compromises that are made are not optimal. In my experience, this is why project managers are tougher to train than people with no project management experience. When faced with ambiguous information and the need to make optimal decisions, project managers tend to fall back on existing mechanistic knowledge and the decisions made range from mildly irritating to completely disastrous. As I have often pointed out, to say that one was successful with waterfall reeks of confirmation bias because it begs the question of whether or not one would have been more successful using another methodology or framework like Lean or Scrum.

In addition to the mechanistic bias, software development suffers from another bias, the project-centric bias, which is the tendency to see all work done in terms of projects. Unfortunately, the project-centric bias is so ingrained in companies that there needs to be some radical changes to the way we view software development across all areas, including accounting. Viewing work as a project when we are actually working on software products results in a whole raft of poor software economic decisions like concentrating on features more than quality and security. Remember that no one washes a rental car.

As I think back on my coaching work in agile, the blogs I have written, the many discussions I have had and the presentations I have made, I think that all of these boil down into one very simple thing – my work is all about helping people understand the true nature of the software development business process and, thereby helping them to make better decisions. Understanding our cognitive biases, therefore, is extremely important for my clients and myself because, in the end, Agile is all about making better decisions.

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