The most important factor in software work is not the tools and techniques used by the programmers, but rather the quality of the programmers themselves.
People matter in building software. That's the message of this particular fact. Tools matter. Techniques also matter. Process, yet again, matters. But head and shoulders above all those other things that matter are people.
This message is as old as the software field itself. It has emerged from, and appears in, so many software research studies and position papers over the years that, by now, it should be one of the most important software "eternal truths." Yet we in the software field keep forgetting it. We advocate process as the be-all and end-all of software development. We promote tools as breakthroughs in our ability to create software. We aggregate a miscellaneous collection of techniques, call that aggregate a methodology, and insist that thousands of programmers read about it, take classes in it, have their noses rubbed in it through drill and practice, and then employ it on high-profile projects. All in the name of tools/techniques/process over people.
We even revert, from time to time, to anti-people approaches. We treat people like interchangeable cogs on an assembly line. We claim that people work better when too-tight schedules and too-binding constraints are imposed on them. We deny our programmers even the most fundamental elements of trust and then expect them to trust us in telling them what to do.
In this regard, it is interesting to look at the Software Engineering Institute (SEI) and its software process, the Capability Maturity Model. The CMM assumes that good process is the way to good software. It lays out a plethora of key process areas and a set of stair steps through which software organizations are urged to progress, all based on that fundamental assumption. What makes the CMM particularly interesting is that after a few years of its existence and after it had been semi-institutionalized by the U.S. Department of Defense as a way of improving software organizations and after others had copied the DoD's approaches, only then did the SEI begin to examine people and their importance in building software. There is now an SEI People Capability Maturity Model. But it is far less well known and far less well utilized than the process CMM. Once again, in the minds of many software engineering professionals, process is more important than people, sometimes spectacularly more important. It seems as if we will never learn.
The controversy regarding the importance of people is subtle. Everyone pays lip service to the notion that people are important. Nearly everyone agrees, at a superficial level, that people trump tools, techniques, and process. And yet we keep behaving as if it were not true. Perhaps it's because people are a harder problem to address than tools, techniques, and process. Perhaps it's like one of those "little moron" jokes. (In one sixty-year-old joke in that series, a little moron seems to be looking for something under a lamp post. When asked what he is doing, he replies "I lost my keys." "Where did you lose them?" he is asked. "Over there," says the little moron, pointing off to the side. "Then why are you looking under the lamp post?" "Because," says the little moron, "the light is better here.")
We in the software field, all of us technologists at heart, would prefer to invent new technologies to make our jobs easier. Even if we know, deep down inside, that the people issue is a more important one to work.
The most prominent expression of the importance of people comes from the front cover illustration of Barry Boehm's classic book Software Engineering Economics (1981). There, he lays out a bar chart of the factors that contribute to doing a good job of software work. And, lo and behold, the longest bar on the chart represents the quality of the people doing the work. People, the chart tells us, are far more important than whatever tools, techniques, languages, andyesprocesses those people are using.
Perhaps the most important expression of this point is the also-classic book Peopleware (DeMarco and Lister 1999). As you might guess from the title, the entire book is about the importance of people in the software field. It says things like "The major problems of our work are not so much technological as sociological in nature" and goes so far as to say that looking at technology first is a "High-Tech Illusion." You can't read Peopleware without coming away with the belief that people matter a whole lot more than any other factor in the software field.
The most succinct expression of the importance of people is in Davis (1995), where the author states simply, "People are the key to success." The most recent expressions of the importance of people come from the Agile Development movement, where people say things like "Peel back the facade of rigorous methodology projects and ask why the project was successful, and the answer [is] people" (Highsmith 2002). And the earliest expressions of the importance of people come from authors like Bucher (1975), who said, "The prime factor in affecting the reliability of software is in the selection, motivation, and management of the personnel who design and maintain it," and Rubey (1978), who said, "When all is said and done, the ultimate factor in software productivity is the capability of the individual software practitioner."
But perhaps my favorite place where people were identified as the most important factor in software work was an obscure article on a vitally important issue. The issue was, "If your life depended on a particular piece of software, what would you want to know about it?" Bollinger responded, "More than anything else, I would want to know that the person who wrote the software was both highly intelligent, and possessed by an extremely rigorous, almost fanatical desire to make their program work the way it should. Everything else to me is secondary. . . ." (2001).
Boehm, Barry. 1981. Software Engineering Economics. Englewood Cliffs, NJ: Prentice-Hall.
Bollinger, Terry. 2001. "On Inspection vs. Testing." Software Practitioner, Sept.
Bucher, D. E. W. 1975. "Maintenance of the Computer Sciences Teleprocessing System." Proceedings of the International Conference on Reliable Software, Seattle, WA, April.
Davis, Alan M. 1995. 201 Principles of Software Development. New York: McGraw-Hill.
DeMarco, Tom, and Timothy Lister. 1999. Peopleware. 2d ed. New York: Dorset House.
Highsmith, James A. 2002. Agile Software Development Ecosystems. Boston: Addison-Wesley.
Rubey, Raymond L. 1978. "Higher Order Languages for Avionics SoftwareA Survey, Summary, and Critique." Proceedings of NAECON.
The best programmers are up to 28 times better than the worst programmers, according to "individual differences" research. Given that their pay is never commensurate, they are the biggest bargains in the software field.
The point of the previous fact was that people matter in building software. The point of this fact is that they matter a lot!
This is another message that is as old as the software field. In fact, the sources I cite date mostly back to 19681978. It is almost as if we have known this fundamental fact so well and for so long that it sort of slides effortlessly out of our memory.
The significance of this fact is profound. Given how much better some software practitioners are than othersand we will see numbers ranging from 5 times better to 28 times betterit is fairly obvious that the care and feeding of the best people we have is the most important task of the software manager. In fact, those 28-to-1 peoplewho probably are being paid considerably less than double their not-so-good peersare the best bargains in software. (For that matter, so are those 5-to-1 folks.)
The problem isand of course there is a problem, since we are not acting on this fact in our fieldwe don't know how to identify those "best" people. We have struggled over the years with programmer aptitude tests and certified data processor exams and the ACM self-assessment programs, and the bottom line, after a lot of blood and sweat and perhaps even tears were spent on them, was that the correlation between test scores and on-the-job performance is nil. (You think that was disappointing? We also learned, about that time, that computer science class grades and on-the-job performance correlated abysmally also [Sackman 1968].)
The controversy surrounding this fact is simply that we fail to grasp its significance. I have never heard anyone doubt the truth of the matter. We simply forget that the importance of this particular fact is considerably more than academic.
I promised a plethora of "old-time" references in this matter. Here goes.
"The most important practical finding [of our study] involves the striking individual differences in programmer performance" (Sackman 1968). The researchers had found differences of up to 28 to 1 while trying to evaluate the productivity difference between batch and timesharing computer usage. (The individual differences made it nearly impossible for them to do an effective comparison of usage approaches.)
"Within a group of programmers, there may be an order of magnitude difference in capability" (Schwartz 1968). Schwartz was studying the problems of developing large-scale software.
"Productivity variations of 5:1 between individuals are common" (Boehm 1975). Boehm was exploring what he termed "the high cost of software."
"There is a tremendous amount of variability in the individual results. For instance, two people . . . found only one error, but five people found seven errors. The variability among student programmers is well known, but the high variability among these highly experienced subjects was somewhat surprising" (Myers 1978). Myers did the early definitive studies on software reliability methodologies.
These quotations and the data they contain are so powerful that I feel no need to augment what those early authors learned, except to say that I see no reason to believe that this particular findingand factwould have changed over time. But let me add a couple of more quotations from the Al Davis book (1995) "Principle 132A few good people are better than many less skilled people" and "Principle 141There are huge differences among software engineers."
And here is a more recent source: McBreen (2002) suggests paying "great developers" "what they're worth" ($150K to $250K), and lesser ones much less.
Boehm, Barry. 1975. "The High Cost of Software." Practical Strategies for Developing Large Software Systems, edited by Ellis Horowitz. Reading, MA: Addison-Wesley.
Glass, Robert L. 1995. Software Creativity. Englewood Cliffs, NJ: Prentice-Hall.
McBreen, Pete. 2002. Software Craftsmanship. Boston: Addison-Wesley.
Myers, Glenford. 1978. "A Controlled Experiment in Program Testing and Code Walkthroughs/Inspections." Communications of the ACM, Sept.
Sackman, H., W. I. Erikson, and E. E. Grant. 1968. "Exploratory Experimental Studies Comparing Online and Offline Programming Performances." Communications of the ACM, Jan.
Schwartz, Jules. 1968. "Analyzing Large-Scale System Development." In Software Engineering Concepts and Techniques, Proceedings of the 1968 NATO Conference, edited by Thomas Smith and Karen Billings. New York: Petrocelli/Charter.
Adding people to a late project makes it later.
This is one of the classic facts of software engineering. In fact, it is more than a fact, it is a law"Brooks's law" (1995).
Intuition tells us that, if a project is behind schedule, staffing should be increased to play schedule catch-up. Intuition, this fact tells us, is wrong. The problem is, as people are added to a project, time must be spent on bringing them up to speed. They have a lot to learn before they can become productive. But more important, those things they must learn typically must be acquired from the others on the project team. The result is that the new team members are very slow to contribute anything to the project at all, and while they are becoming productive, they are a drain on the time and attention of the existing project team.
Furthermore, the more people there are on a project, the more the complexity of its communications rises. Thus adding these new people when a project is late tends to make it even later.
Most people acknowledge the correctness of this fact. At the same time, it is possible to argue with some of the details. For example, what if the added people are already knowledgeable in this application domain, and perhaps even on this project? Then the learning curve problem diminishes, and the newcomers may end up contributing quite rapidly. Or what if the project is barely under way? In that case, there's not that much to bring the added people up to speed.
The opposition to the fact is best articulated by McConnell (1999), who notes that (a) ignoring the fact "remains commonplace" in practice, and (b) the fact is valid only in "limited circumstances that are easily identified and avoided."
Still, few dispute the fundamental fact here. One must be very careful in adding staff to a behind-schedule project. (For that matter, one must be careful in adding staff to any project, late or not. But it's especially temptingand especially dangerouswhen the manager is trying to accelerate progress.)
This fact accounts for the title of a classic software engineering book. The book is called The Mythical Man-Month (Brooks 1995) because, although we tend to measure staffing in people per month, not all people contribute the same amount to a project, and thus not all man-months are equal. This is especially true for those people added to a late project, whose man-month contribution may very well be negative.
Brooks, Frederick P., Jr. 1995. The Mythical Man-Month. Anniversary ed. Reading MA: Addison-Wesley.
McConnell, Steve. 1999. "Brooks' Law Repealed." From the Editor. IEEE Software, Nov.
The working environment has a profound impact on productivity and product quality.
The tendency in software projects is to try to staff them with the best people available, enlist the support of an appropriate methodology, establish a process fairly high up on the SEI CMM food chain, and let 'er rip! The problem is, there's something important left out of that mix. The setting in which the systems analysts analyze and the designers design and the programmers program and the testers testthat environment matters a lot. A whole lot.
What it all boils down to is that software work is thought-intensive, and the environment in which it is done must be one that facilitates thinking. Crowding and the resulting (intentional or unintentional) interruptions are deadly to making progress.
How deadly? There's a whole classic book that focuses on this issue. Peopleware (DeMarco and Lister 1999) spends quite a bit of its time and space telling us just how, and in what ways, the environment matters. In it, the authors report on their own studies of the effect of the work environment on job performance. They took members of a project team and separated the top quartile of performers from the bottom quartile (the top quartile performed 2.6 times better than those at the bottom). They then examined the working environment of those people at the top and those at the bottom. The top people had 1.7 times as much workspace (measured in available floor space in square feet). Twice as often, they found their workspace "acceptably quiet." More than 3 times as often, they found it "acceptably private." Between 4 and 5 times as often, they could divert phone calls or silence their phone. They were interrupted by other people (needlessly) about half as often.
It is certainly true that the individual differences between people have a profound effect on software productivity, as we have already seen in Fact 2. But this fact tells us that there is something more needed. You must get good people, and then you must treat them well, especially in providing a workable environment.
The controversy here is underground. Hardly anyone will disagree with this fact publicly. And yet when the time comes to provide office space, the field seems to revert to its old "crowd them in as closely as possible" philosophy. The money spent on additional office space is easily measured and easily manipulated, whereas the cost to productivity and quality by crowding software people into too little space is much harder to measure.
Workers say things like "you never get anything done around here" (that's the title of one of Peopleware's chapters, in fact). Managers give authority on defining workspace matters to people who think as if they were "the furniture police" (that's another of its chapter titles). And yet very little seems to change. Even in the academic world, where thinking time is valued more than in most settings, the pressure of too little space for too many people often results in crowded or doubled-up offices.
There is an old saying, "the hard drives out the soft." That is, those things that are solidly measurable ("hard" things) tend to take attention away from those that are not (the "soft" ones). This truism is about much more than software, but it seems especially relevant here. Office space measurement is hard. Productive benefits are soft. Guess which one wins?
There is one burgeoning controversy connected to this fact. Advocates of Extreme Programming argue for a way of working called pair programming. In pair programming, two software workers stay in close communication and proximity while they are doing their work, even sharing use of the computer keyboard. Here, we see intentional crowding, yet with the attendant claim that productivity and especially quality benefit. The controversy between these two viewpoints has not yet been articulated in the software literature, but as Extreme Programming becomes better known, this controversy may hit the fan.
There are several sources of information on Extreme Programming, but here is the first and best known:
Beck, Kent. 2000. Extreme Programming Explained. Boston: Addison-Wesley.
One leading advocate of pair programming, Laurie Williams, has written about it in many places, including the following:
Williams, Laurie, Robert Kessler, Ward Cunningham, and Ron Jeffries. 2000. "Strengthening the Case for Pair Programming." IEEE Software 17, no. 4
DeMarco, Tom, and Timothy Lister. 1999. Peopleware. 2d ed. New York: Dorset House.