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The Psychological Reasons of Software Project Failures

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1 Nov 2019CPOL
This article discusses the psychological reasons of software project failures.

Disclaimer

This article is my personal opinion about the state of the affairs in the software engineering field. This is not intended to be a scientific paper so many statements are intentionally bold and direct to make the text short. I did my best to point the psychological reasons of software project failures based on my own observations and available sources, but I am not a professional psychologist nor statistician and I may be totally wrong.

“Our real discoveries come from chaos, from going to the place that looks wrong and stupid and foolish.”
Chuck Palahniuk

A Never-Ending Tar Pit

Failure of software projects defined as a miss of deadlines, budget overrun, missed functionality and malfunction is prevalent in the software industry. A lot has been written about the reasons of this situation, blaming unrealistic project goals, inaccurate estimates of needed resources, badly defined requirements, poor reporting, unmanaged risks, poor communication, immature technology, sloppy development practices, poor project management, stakeholder politics or commercial pressure. The most of these put weight on the management side of the development process, properly identifying it as a cause of these failures. In my opinion, which is based on years of observation, there is another factor of this misery almost totally overlooked or intentionally omitted – programmers themselves.

I’ll use the term “programmer” throughout this text to denote not only software developers, but also technical leads, architects and requirements/domain analysts, all of whom are responsible for the technical part of a software development process and are equally responsible for the success or failure of a software project.

“Smart” Programmers

The common belief among society in general and among programmer society as well is that “programmers are smart”, that they recruit from the most intelligent part of the society. I believe that this is based on a false assumption that programming a machine is difficult. I dare to disagree with this assumption as in reality, writing code is no more difficult than writing a proper culinary recipe (both being explicit instructions of how to make something). Computers are in their essence very simple machines based on basic mathematical concepts like variables, arithmetic, vectors, as well as some real-world concepts like conditional execution, repetition and delegation of work. These concepts are so basic that we either know them intuitively or are being taught about them at elementary schools. Programming does require a level of literacy, which excludes unsuitable individuals, but the claim that someone is “extra smart” because of being able to do what an average 12-year old is able to do, is a strong exaggeration. Since the distribution of human intelligence is given by bell curve, the intelligence distribution of programmers is given with the same bell curve with the left side of the diagram missing.

Image 1

Figure 1. Assumed distribution of programmer intelligence.

According to Wikipedia, a person who completes 1 to 3 years of college has an IQ of at least 104, which I suspect is the minimum for “Teach Yourself Java in 24h” type of programmers. This means that, following natural distribution, there is a considerable number of “average Joes” in the industry.

The Nature of Challenge

Coding is not a challenge. In fact, code is the last thing anybody is willing to pay for (though, ironically, it is the most important thing that gets produced in the end). The real challenge, and the real duty of a programmer, is solving problems that customers face, most likely with code but not necessarily. These problems are usually only partially “technical”, often sociological, often complex, often wicked. As problem complexity grows, the required effort, intelligence, knowledge and dedication to solve it grows as well, sometimes exponentially. Recognizing complexity, confining it and minimizing it is the ultimate goal of a programmer. This raises the bar so high that an average person might fail to present the sufficient personal qualities required for the job, and turn out to be relatively stupid.

As David Parnas states it: “I have heard people proudly claim that they have built lots of large complex systems. I try to remind them that the job could have been done by a small simple system if they had spent more time on "front-end" design. Large size and complexity should not be viewed as a goal.

The 4 + 2 Model

It is necessary to unambiguously define the stupidity in the context of programming.

“A stupid programmer is the one that puts complexity to a software product that negatively impacts another programmers, customers or a whole company, while achieving no gain from this fact and even possibly negatively impacting oneself”.

By putting complexity, I mean either failing to reduce the inherent complexity of the problem being solved with software, by using so called “brute force” solutions, or actually introducing of accidental (usually technical) complexity, that could be avoided if more thought and care was given to the solution.

By negative impact, I understand the increased workload, reduced efficiency and higher cost.

Following Carlo M. Cipolla’s work, programmers can be divided into four categories: Intelligent, Bandits, Helpless and Stupid with two additional categories of Naive and Ignorant.

Image 2

Figure 2. 6 Types of programmers.

An Intelligent programmer is able to formulate the problem and a solution in such a way that the resulting complexity is lowered for both his chunk of work and other peoples’ chunks of work.  An example would be a software module with a streamlined, coherent functionality and well defined interface that is easy to implement, test and integrate with. By putting thought into a broader scope of problem being solved, the intelligent programmer is able to achieve net positive effect for both himself and a part/whole organization as well as customers. These programmers are usually called “10x programmers” as they can outperform entire teams just by themselves.

A Bandit programmer on the other hand is mainly concentrated on his own task. His priority is to optimize his own performance at the cost of others. Such programmer usually does not attack the problem itself, but rather fights to limit the scope of his assignment (to reduce his workload or to gain more time), impacting other peoples’ assignments. Additionally such programmer sacrifices code qualities like flexibility, performance, testability, which pay in the long run, for short term gains oriented toward management recognition. Such person usually looks at the entire product from selfish perspective. The net effect of their action may be positive or negative depending whether the individual leans toward Intelligent or Stupid. Additionally such people often display a lot over-confidence and facade professionalism to support their unearned position in organizations (exposing a hot or cold arrogance). These people are usually called “cowboy coders”.

A Helpless programmer is the one that is generally dedicated towards the success of the company and praises teamwork over individualism. Being generally of the same intelligence as Bandits but with opposite goal orientation, he does his best to support the organization at the cost of his own time and performance. He tends to compromise his own designs and code quality, by introducing complexity he might actually avoid, in order to make things “easier for others”, even though it might incur more problems on him. He tends to fix other peoples’ code without compensation, work unpaid overtime, or contribute in their free time. He is usually willing to educate others in hope to benefit them or entire organization. The net effect of these actions depends on whether the individual leans toward Intelligent or Stupid. Such people usually keep low profile in the organization. They may be recognized for their inputs by direct managers but because of their negative performance reviews, caused by the avoidable complexity they willingly introduced, they are seldom rewarded for their efforts.

A Stupid programmer is the worst kind ever encountered. It is a person who generally has no idea what he is doing, often lacking any skills required in programming except familiarity with programing language. Such person is generally unable to provide anything but stopgaps that barely solve the problem being addresses. Usually, the number of defects exceeds the number of implemented features, the code is difficult or even impossible to test and it causes negative ripple effects throughout entire organization.  The low (or lack of) quality of his work impacts negatively both the organization and himself, as he often spends long hours of unpaid overtime to solve problems he has put himself into. Such people usually occupy some corners of organization keeping low profile, out of sight of management. They never advance and are generally happy to have a job.  Stupid programmers as well as Ignorant programmers get attracted to the industry by salaries only. These programmers are sometimes called “1/10 programmers” as they can bring performance of entire teams to its knees. They are generally not very abundant as they get recognized eventually, but the harm they do is disproportional to their numbers.

Additional two types of individuals are Naive and Ignorant.

A Naive programmer is the one that concentrates on his work without paying any interest to a broad picture. Naive programmer puts decent quality into his work but generally is not interested in anything beyond his assignment. He is invisible from organization perspective. He tends to work 9-to-5 precisely and rarely advances. He exposes factory line worker mindset and is easy to manage, but without proper management his performance may stall to halt if his position on vertical axis is close to zero.

The last category comprises Ignorant programmers. An Ignorant programmer’s most distinct trait is the “I don’t care”. He expresses absolutely no interest in what he does. He provides only enough quality not to get fired, without any consideration of other people’s assignment or organization goals. He is usually uncooperative and unresponsive to his workmates causing organization wide negative effect. On the other hand he may cause disruption by demanding assistance from other organization members. He exposes factory-line-worker mentality considering himself a kind of “organic compiler” who is supposed to convert set of artifacts into code without engaging much intellectual effort. He insists more on development process compliance than on actual work done. His attitude toward defects is usually “I’ll fix it in the next sprint.”. He can be managed, but despite management effort, he may not able to produce value that even compensates his salary. He may expose tepid arrogance. I personally believe that this category is most common.

Intelligence and dedication are just part of the picture which will be shown in full in the following paragraphs.

Barbarians at the Gates

According to the following article, the number of programmers in the world doubles every five years. If we boldly assume that 10 years of experience lets one to become professional and that the average person works for 40 years, this means that only one fourth of the programmer population is experienced enough to actually carry out the work properly. This number is frightening in comparison to more stable disciplines where one can expect 3 out of 4 people to be seasoned professionals and only one of them to be an apprentice. To make things worse, I dare to challenge this even further.

Misery of Education

At first, I’d like to challenge the statement that a Computer Science degree holds a considerable value. The exponential growth of programmers implies exponential demand for Computer Science teachers, and this implies that the ratio of experienced Computer Science teachers to novices is again 1 to 3. This means that most of Computer Science students are being taught by people not much older, who usually have no practical experience at all (usually PhD students). I suspect that such teaching seldom goes beyond “follow the book”. The effect is that a CS graduate is capable of writing code and not much beyond that, as there was no one to teach him what Software Engineering actually means. Of course, this is true only under the assumption that the number of student per teacher stays the same over years (otherwise, the quality of education drops even more rapidly).

The Endless Sea of Ignorance

Another important fact is the mismatch between what is being taught at universities and what industry demands. Many universities teach Computer Science whereas industry demands Software Engineering skills. The problem is that engineering skills are often impossible to teach, and they can only be learned “by doing”. This means, that in order to become a professional in Software Engineering, one needs to spend the first 10 years of his career experimenting, failing, learning from it and studying on a on his own. This requires genuine interest, dedication and some kind of passion. It makes sense to assume that the distribution of these qualities among graduates follows bell curve. If so then only about 20% of graduates spend the first 10 years of their career on deliberate learning, 60% will acquire some knowledge along the way, and 20% will learn close to nothing. This means that after 10 years, only 20% of programmers become true professionals in Software Engineering. This forms an even more terrifying view of the industry there the number of true professionals is only 5%. If we assume that the number Bandits, Helpless and Naïve among them is 50%, then the number of so called “x10 programmers” is about 2.5%.

The Fallacy of Bell Curve

The number of 2.5% harmonizes with the bell curve distribution where the number of values more distant than double standard deviation from the mean accounts for to 2.1%, but assuming that the distribution of competence of programmer is given by standard bell curve (as can be assumed in any stable engineering field) is false. Considering that three thirds of the population is more or less inexperienced and that professionalism of 50% of the rest is below average, the actual distribution of competence among programmers is heavily biased towards incompetence (see Figure 2.)

Image 3

Figure 3. Programmers’ competence distribution (red line) compared with expected distribution (blue line)

The Great Misuderstanding

Programmers are technology oriented. They get attracted to computing because of their technological bias. Their job though, is not to write code as they often think, their job is not even creating software. Their job is to solve customers’ problems and software is just one of the means to do it. Sadly, seldom do they manage to understand this.

Solving customers’ problems requires much more beyond writing code. It mainly requires acquiring domain knowledge in order to be able to even communicate with the customer. It requires diving into the world of customer to be able to understand his needs. A programmer familiar with a particular domain is not only able to code but actually to create solutions. Otherwise, he is blind. A programmer who is a domain expert is way more efficient as he can answer many more questions himself. Most programmers are ignorant of the domain. They have no interest in it. They deliberately reduce themselves to “organic compilers” because it is easier. They do not understand that the company and themselves pay the price for that.

Nerd Culture

Programmers often recruit from the nerdy part of student population, who present deficiencies in social skills. As Gerald M. Weinberg described it “Social psychologists tell us that there are different personality types […]. Among general personality traits is one which is measured along three ‘dimensions’ – whether a person is ‘compliant’, ‘aggressive’ or ‘detached’. The compliant type is characterized by the attitude of liking to ‘work with people and be helpful’. The aggressive type wants to ‘earn money and prestige’ and the detached type wants to ‘be left to myself and be creative’.

Now, every person contains a mixture of these attributes, but most people lean more heavily in one direction than the others. There is no doubt that the majority of people in programming today lean in the ‘detached’ direction, both by personal choice and because hiring policies for programmers are often directed toward finding such people.”

Many programmers-to-be choose to interact with computers instead of people because in this relation they are the ones who give orders, and computers generally don’t oppose (except when the code doesn’t compile but this is impersonal). They are those bullied skinny boys who finally found someone whey can control and dominate. They stay the same nerds as time passes, just older.

As Mr. Weinberg states: “one of the most easily identifiable personality needs in programmers is modicum of ‘neatness’ as a slight compulsion to keep one’s papers in order […]. Another essential factor is […] a small dose of ‘humility’ to prevent ‘the programmer learning a few simple techniques, feeling that he is an expert, and then being crushed by the irresistible power of the computer’ […]. The other side of the coin of humility is ‘assertiveness’, or force of character. A programmer’s job is to get things done, and getting things done sometimes requires moving around obstacles, jumping over them, or simply knocking them down.”

Throughout my career, I found out that most of these obstacles are not technical but social in nature. They require challenging other people, forcing them out of their comfort zone and saying “NO!” to managers, in other words, it requires courage. Many programmers don’t know how to deal with conflict so they prefer to avoid it (Naive and Helpless) adding their part to the ultimate failure.

Confidence of Ignorants

Despite my previous estimation of a number of non-professionals in the industry, I do not see a massive decline in numbers of programmers. I don’t encounter large number of programmers changing careers every year just because they have realized that they are not a good fit for programming. I believe that the reason for this (besides paycheck of course) is the Dunning-Kruger effect which “is a cognitive bias in which people of low ability have illusory superiority and mistakenly assess their cognitive ability as greater than it is. The cognitive bias of illusory superiority comes from the inability of low-ability people to recognize their lack of ability. Without the self-awareness of metacognition, low-ability people cannot objectively evaluate their competence or incompetence”. In other words, unprofessional programmers are not able to recognize their lack of professionalism, because they have no idea what constitutes it. They present unconscious incompetence. Additionally, they are unable to adequately judge their unprofessional peers. This means, that since true professionals are scarce, there are plenty of teams out there exclusively consisting of unprofessional programmers having high opinion about themselves, just because there is nobody on the team able to recognize their low rank. I don’t dare to make an explicit statement here, but I suspect that this effect is most prevalent among the Ignorant and Stupid.

Impotence of Leaders

On the other scale of the competence sits another filthy beast called impostor syndrome. This psychological phenomenon concerns gifted individuals who achieved the highest level - an unconscious competence. It “is a psychological pattern in which an individual doubts their accomplishments and has a persistent internalized fear of being exposed as a ‘fraud’. Despite external evidence of their competence, those experiencing this phenomenon remain convinced that they are frauds, and do not deserve all they have achieved. Individuals with impostorism incorrectly attribute their success to luck, or as a result of deceiving others into thinking they are more intelligent than they perceive themselves to be”. This means, that a part of top professionals out there (20% if we assume a normal distribution) fail to become technical leaders just because they don’t think they are professionals. These people assume that problems they successfully solve are so simple that anybody could do it, including the incompetent. They fail to recognize incompetence of their peers or fail to disclose it, conserving status quo, which in the end impacts them. I suspect that this phenomenon concerns mainly the Helpless and Naive, as well as some Intelligent that lean towards helplessness.

Guilt Driven Development

It is commonly known that programmers are over optimistic about the complexity of problem they are dealing with. In fact, unrealistic project goals, usually in terms of schedule, are among most common project failures. Many try to answer the question of how to improve programmers’ estimation abilities. I, on the other hand try, to attack the “why”. The first reason of why programmers overpromise is the lack of full understanding of the problem at the time they are asked to provide estimates. As David Parnas states: “People tend to underestimate the difficulty of the task. Overconfidence explains most of the poor software that I see. Doing it right is hard work. Shortcuts lead you in the wrong direction and they often lead to disaster.” This is a totally valid reason, but in my opinion, there is a psychological reason as well. It’s guilt.

Everybody fails to deliver. Amateurs fail 8 times out of 10. Professionals fail 2 times out of 10. Programmers inevitably fail to deliver at the beginning of their careers. Failure causes a feeling of guilt and that is the beginning of the vicious circle which works as follows:

  1. A programmer makes an optimistic promise to management.
  2. A programmer fails to deliver up to the promise.
  3. A programmer makes another overoptimistic promise in order to compensate for his previous failure.
  4. He fails again and the cycle repeats.

If nothing gets improved, the cycle can repeat throughout the entire programmer’s career. This is where the Stupid and Helpless end up (though because of different reasons). This is what causes lack of trust. This is what causes micromanagement.

There are two ways to escape from this situation. First is self-improvement. Once skills grow, tasks become easier and more predictable. One also learns to better anticipate potential obstacles that might appear along the way. This is how the Intelligent deal with it. The second is risk mitigation by undepromising, when estimates grow far way beyond what is actually required to perform the task. This is what Bandits and Ignorants end up with. This is what causes stagnation, as every progress gets seen as prohibitively expensive.

The Inevitable Failure of Agile

Agile software development is the established way of doing software these days, but it turns out it does not hold its promise very well. I’m convinced that this is because agile software development has a chance to function only when it is performed by competent, intelligent and courageous programmers genuinely interested in customer’ domain. The Manifesto for Agile Software Development states it explicitly listing its principles :

  • Business people and developers must work together daily throughout the project.” – requires customer’s domain interest;
  • “Build projects around motivated individuals. Give them the environment and support they needs, and trust them to get the job done.” – requires motivation, and passion;
  • “Continuous attention to technical excellence and good design enhances agility.” – requires competence and intelligence;
  • Simplicity--the art of maximizing the amount of work not done--is essential.” – requires competence and intelligence as well;
  • “The best architectures, requirements, and designs emerge from self-organizing teams.” – requires competence, intelligence and courage.

The failure of agile software development is inevitable. Assuming that amount of Intelligent programmers in the industry is about 2.5% (1/40), and the maximum size of SCRUM team is 9 people, the probability that the average SCRUM team consists of at least one Intelligent is less than 25%. If the team consists only of Helpless, Naive, Bandits, Ignorant and Stupid the effect is rarely positive.

Facing the failure of agile software development, companies go back to waterfall model, which is the only way to achieve anything with programmers of “factory line worker” mentality. Alternatively, they pretend “being agile” with waterfall process on top. Both are at the cost of huge process overhead that can often bring a project down. What companies fail to recognize is that you cannot substitute talent, knowledge, intelligence, dedication and care with the process. This is a lose-lose situation, as no process can actually be applied successfully because it is impossible to manage bad programmers to succeed.

A Bitter Pill

I found this enlightening quote from David Parnas:

The most often-overlooked risk in software engineering are ‘incompetent programmers’. There are estimates that the number of programmers needed in the U.S. exceeds 200,000. This is entirely misleading. It is not a quantity problem; we have a quality problem. One bad programmer can easily create two new jobs a year. Hiring more bad programmers will just increase our perceived need for them. If we had more good programmers, and could easily identify them, we would need fewer, not more.”

If the project is late, it is better to fire bad programmers than to hire more of them. At least, they will not get in the way of good ones.

Not firing programmers is a major problem as there is no sense of accountability in the industry. Actors get fired after every movie, so they feel pressure to perform well every time. Programmers, with artificially created demand, feel no pressure to exhibit high performance every time as they can switch jobs before things go bad (their incompetence gets discovered). This fosters more incompetence and stupidity.

The Thirteenth Principle

Following the 12 principles of Agile, I’d add another one: “Do not employ Stupid programmers.”

Do not deal with programmers below diagonal dashed line on Figure 2, as they produce a negative net value and will inevitably bring the software project down. Identify and fire them. A best performing mix consists the Intelligent leading the Naive and Helpless, which maybe a few Intelligent-Bandits if you can hold them tight. Additionally, beware of too many Helpless as their helplessness will hit you eventually.

A New Hope

The above text may suggest that I’m the superior programmer with an inflated ego trying to judge the less fortunate peers, but this is not the case. I hope that this text puts some light on reasons of software project failures that, in my opinion, haven’t been investigated enough. I hope that it helps developers to orient themselves within the multidimensional space I have described and find their way of improvement. I hope it helps managers to identify deficiencies of their team an implement appropriate corrective actions. It definitely helped me to understand things better, to find a bit more order in the surrounding chaos, and I hope it serves its purpose for every reader as well.

 

NOTE: You may be interested with my next article " Software Development as a Research in Domain of Value"  which brings context to the text above.

 

History

  • 28th May, 2019: Initial version

License

This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

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Comments and Discussions

 
GeneralMy vote of 5 Pin
Member 20823224-Nov-19 9:36
MemberMember 20823224-Nov-19 9:36 
PraiseInteresting approach 5/5 Pin
Member 20823224-Nov-19 9:31
MemberMember 20823224-Nov-19 9:31 
GeneralMy vote of 1 Pin
Издислав Издиславов3-Nov-19 9:14
MemberИздислав Издиславов3-Nov-19 9:14 
QuestionMessage Closed Pin
2-Nov-19 9:31
MemberShinobiKenobi2-Nov-19 9:31 
PraiseI have to agree Pin
wouterst2-Nov-19 7:18
Memberwouterst2-Nov-19 7:18 
QuestionMy vote of 5 Pin
golden.spiral208412-Sep-19 11:00
Membergolden.spiral208412-Sep-19 11:00 
QuestionMaking estimates Pin
Dean Roddey3-Sep-19 10:59
MemberDean Roddey3-Sep-19 10:59 
QuestionNo value Pin
Member 102971172-Sep-19 8:49
professionalMember 102971172-Sep-19 8:49 
QuestionThe Gerald M. Weinberg quote Pin
staffan_v10-Jun-19 0:10
professionalstaffan_v10-Jun-19 0:10 
GeneralMy vote of 5 Pin
Member 119906919-Jun-19 22:40
MemberMember 119906919-Jun-19 22:40 
GeneralMy vote of 3 Pin
tbayart6-Jun-19 0:19
Membertbayart6-Jun-19 0:19 
QuestionEvolution of a programmer Pin
KarstenK5-Jun-19 23:52
mveKarstenK5-Jun-19 23:52 
AnswerRe: Evolution of a programmer Pin
ShinobiKenobi2-Nov-19 9:34
MemberShinobiKenobi2-Nov-19 9:34 
EXACTLY! We were ALL noobs once upon a time and at the beginning programming was "hard". Some get better and some find something else to do. That doesn't make them "stupid".
QuestionManagement Pin
Member 101164324-Jun-19 0:34
MemberMember 101164324-Jun-19 0:34 
AnswerRe: Management Pin
KarstenK3-Nov-19 23:17
mveKarstenK3-Nov-19 23:17 
QuestionWell said. Check out The Brillant Paula Bean Pin
David Pierson3-Jun-19 20:43
MemberDavid Pierson3-Jun-19 20:43 
Questionit isn't the developers who matter... Pin
billschreiber1113-Jun-19 10:12
Memberbillschreiber1113-Jun-19 10:12 
AnswerRe: it isn't the developers who matter... Pin
David Pierson2-Sep-19 13:03
MemberDavid Pierson2-Sep-19 13:03 
QuestionSpelling mistake Pin
Member 27887443-Jun-19 4:04
MemberMember 27887443-Jun-19 4:04 
GeneralTruths seldom said Pin
objectvill31-May-19 8:30
Memberobjectvill31-May-19 8:30 
QuestionOutstanding! Pin
AJSON31-May-19 1:32
communityengineerAJSON31-May-19 1:32 
PraiseI think its brilliant, but you need a bit more editing. Pin
Bogatitus30-May-19 17:23
MemberBogatitus30-May-19 17:23 
QuestionNeeds more work Pin
Member 302712030-May-19 10:22
MemberMember 302712030-May-19 10:22 
QuestionClever Programmer Pin
Timv25630-May-19 8:36
MemberTimv25630-May-19 8:36 
AnswerRe: Clever Programmer Pin
DanW5230-May-19 12:40
MemberDanW5230-May-19 12:40 

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Posted 29 May 2019

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