Large-Scale Work—Part I: The Organization



Watts S. Humphrey

This library item is related to the following area(s) of work:

Process Improvement

This article was originally published in News at SEI on: February 1, 2005

With this column, I start a new series of articles about the issues faced by large-scale development projects. Since large-scale development is an enormous subject, I plan to touch only on those topics that I think are particularly interesting or especially important. I currently plan to cover two problems. First, large software projects are almost universally troubled, and second, all large-scale systems-development projects of almost every kind now involve large amounts of software. Unfortunately, this implies that almost all kinds of large-scale development projects will be troubled unless we can devise a better way to develop the software parts of these large-scale systems. The increasing need for large-scale system-development projects raises many questions and presents a significant challenge to those of us in the development business.

Emergent Properties of Systems

Perhaps the greatest single problem with large-scale system development concerns what are called the emergent properties of these systems. These are those properties of the entire system that are not embodied in any of the system's parts. Examples are system security, safety, and performance. While individual components of a system can contribute to safety, security, and performance problems, no component by itself can generally be relied on to make a system safe, secure, or high performing.

The reason that emergent properties are a problem for large-scale systems is related to the way in which we develop these systems. As projects get larger, we structure the overall job into subsystems, then structure the subsystems into products, and refine the products even further into components and possibly even into modules or parts. The objective of this refinement process is to arrive at a series of "bite-sized projects" that development teams or individual developers can design and develop.

This refinement process can be effective as long as the interfaces among the system's parts are well defined and the parts are sufficiently independent that they can be independently developed. Unfortunately, the nature of emergent properties is that they depend on the cooperative behavior of many, if not all, of a system's parts. This would not be a problem if the system's overall design could completely and precisely specify the properties required of all of the components. For large-scale systems, however, this is rarely possible.

While people have always handled big jobs by breaking them into numerous smaller jobs, this can cause problems when the jobs' parts have interdependencies. System performance, for example, has always been a problem, but we have generally been able to overpower it. That is, the raw power of our technology has often provided the desired performance levels even when the system structure contains many inefficiencies and delays.

As the scale of our systems increases, and the emergent properties become increasingly important, we now face two difficult problems. First, the structural complexity of our large organizations makes the development process less efficient. Since large-scale systems are generally developed by large and complex organizations, and since these large organizations generally distribute large projects across multiple organizational units and locations, these large projects tend also to have complex structures. This added complexity both complicates the work and takes added resources and time.

The second problem is that, as the new set of emergent properties becomes more important, we can no longer rely on technology to overpower the design problem. Security, for example, is not something we can solve with a brute-force design. Security problems often result from subtle combinations of conditions that interact to produce an insecure situation. What is worse, these problems are rarely detectable at the module or part levels.

A War Story

Some years ago, while I still worked at IBM, I was made director of programming. My organization had about 4,000 software professionals in 15 laboratories and 6 countries. While this group was responsible for developing all of the software to support IBM's products, about half of the group was working on one big system: OS/360. These people were highly capable and motivated, but the OS/360 schedule had slipped three times during the past year and a half, and no one believed any of our dates. Since IBM was starting to ship the 360 hardware without the software, the lack of a believable schedule was a major marketing problem.

Marketing argued that the customers would be willing to run their existing system software temporarily with the emulators provided with the 360 systems, but that they would not order many new systems until they had a believable plan for OS/360 software support. We needed a schedule right away, but it had to be one that we would meet without fail. If we had another schedule slip, no one would believe us again.

Before this job, I had run several software projects and also managed some large hardware projects. Therefore, I had learned that it is practically impossible to produce a reliable schedule without first producing a detailed plan for the work. Since the several thousand developers in my group had never before made detailed plans, they didn't know how to do it. What was worse, they didn't believe that planning was important. They knew how to code and test, so that is what they did. Without plans to guide them, the projects were pretty chaotic, and nobody had time to do anything but code and test.

I had to do something to make planning important. So, to get everybody's attention, I established a new operating procedure: Without a detailed plan, no one could announce or ship any software product. I even threatened to cut the budget for any project that did not have a plan. I gave the groups 60 days to produce plans and to review them with me personally. This made planning a crisis. When I got the plans, I reviewed them all and made the developers defend them. We lengthened many of the schedules but never cut a single one. In fact, I even added a 90-day cushion to every committed date.

This worked. We did not miss a single date for the next two and a half years. Soon, however, we started to eat up my 90-day cushion. We had not appreciated the consequences of a multi-release delivery plan. Every schedule slip for every release had a cumulative effect on every subsequent release. After about two years, these small schedule slips finally added up to my 90-day cushion. However, by then everybody believed our dates, so the subsequent minor schedule adjustment was not a problem. But after that, we no longer committed delivery dates to customers that were more than about a year out. By then, we were meeting all of our delivery dates, and even beating the hardware.

The project-planning procedure worked extremely well. While it imposed a demanding planning discipline on the development groups, they continued producing plans even after I moved on to another job. Unfortunately, with the mechanism we established for plan management, it was easy to add further procedures, so many managers did. Over time, this simple plan-management system became a bureaucratic jungle. The initial planning controls we established had been relatively simple and saved IBM billions of dollars. However, with the added controls, projects could no longer respond quickly to special customer needs, and bureaucracy became a big company problem.

The Tropical Rain Forest

The fundamental problem of scale is illustrated by analogy to the ecological energy balance in a tropical rain forest. In essence, as the forest grows, it develops an increasingly complex structure. As the root system, undergrowth, and canopy grow more complex, it takes an increasing percentage of the ecosystem's available energy just to sustain the jungle's complexity. Finally, when this complexity consumes all of the available energy, growth stops.

The implication for both projects and organizations is that, as they grow, their structure gets progressively more complex, and this increasingly complex structure makes it harder and harder for the developers to do productive work. Finally, at some point, the organization gets so big and so complex that the development groups can no longer get their work done in an orderly, timely, and productive way. Since this is a drastic condition, it is important to understand the mechanisms that cause it.

Organizational Growth

In principle, organizations grow because there is more work to do than the current staff can handle. However, this problem is usually more than just a question of volume. As the scale increases, responsibilities are subdivided and issues that could once be handled informally must be handled by specialized groups. So, in scaling up the organization, we subdivide responsibilities into progressively smaller and less meaningful business elements. Tasks that could once be handled informally by the projects themselves are addressed by specialized staffs. Now, each staff has the sole job of ensuring that each project does this one aspect of its job according to the rules. Furthermore, since each staff's responsibility is far removed from business concerns, normal business-based or marketing-based arguments are rarely effective. The staffs' seemingly arbitrary goals and procedures must either be obeyed or overruled.

This growth process generally happens almost accidentally. A problem comes up, such as a missed schedule, and management decides that future similar problems must be prevented. So they establish a special procedure and group to concentrate on that one problem. In my case, this was a cost-estimating and planning function that required a plan from every project. Each new special procedure and group is like scar tissue and each added bit of scar tissue contributes to the inflexibility of the organization and makes it harder for the developers to do their work. Example staffs are pricing, scheduling, configuration management, system testing, quality assurance, security, and many others.

The Enemy

Since these specialized staffs are all designed to monitor and control the projects, the projects view them as the enemy. So, if they can get away with it, the projects simply ignore the staffs. To guard against this, management establishes a review procedure where the staffs have the authority to sign off at key project milestones. If the project team does not do its job properly, the staff does not let the project proceed. What is most insidious about this situation is that the staffs are all enforcing rules that management and most objective observers would agree are needed. However, because of the tangle of approvals and sign-offs, the process consumes a great deal of the project's energy. Also, once the staffs have power, they often use that power to push pet objectives that are not strictly in their official charter.

While this review and approval strategy generally guarantees that the projects pay attention to the staffs, the projects must also surmount an increasingly complex bureaucratic tangle of approvals just to do their work. This problem is bad enough when all projects were similar but, as projects get larger and more complex, they, too, become increasingly specialized. They then must use custom-tailored processes and procedures that are almost impossible to establish in a large and complex organizational jungle. Because of the energy consumed in getting bureaucratic approvals, the projects generally have to follow a process that doesn't precisely fit their needs. Now, just like a tropical rain forest, an increasing proportion of the organization's resources are devoted to delaying or stopping projects. Because of the enormous energy required to fight the bureaucracy, the projects have progressively less energy left to design and build their products. That is when rapid growth stops.

While there is no magic solution to the problems of project scale, the situation is not hopeless, and there are useful steps we can take. Subsequent columns outline the most promising avenues for addressing these problems. I will also outline some principles to consider when working on large-scale development projects, some of the consequences of scale-related development problems, and some strategies for solving them.


In writing papers and columns, I make a practice of asking associates to review early drafts. For this column, I particularly appreciate the helpful comments and suggestions of Dan Burton, Julia Mullaney, Bill Peterson, Marsha Pomeroy-Huff, and Mark Sebern.

In closing, an invitation to readers

In this particular series of columns, I discuss some of the development issues related to large-scale projects. Since this is an enormous subject, I cannot hope to be comprehensive but I do want to address the issues you feel strongly about. So, if there are aspects of this subject that you feel are particularly important and would like covered, please drop me a note with your comments, questions, or suggestions. Better yet, include a war story or brief anecdote that illustrates your ideas. I will read your notes and consider them when planning future columns.

Thanks for your attention and please stay tuned in.

Watts S. Humphrey

About the Author

Watts S. Humphrey founded the Software Process Program at the SEI. He is a fellow of the institute and is a research scientist on its staff. From 1959 to 1986, he was associated with IBM Corporation, where he was director of programming quality and process. His publications include many technical papers and several books. His most recent books are Introduction to the Team Software Process (2000) and Winning With Software: An Executive Strategy (2002). He holds five U.S. patents. He is a member of the Association for Computing Machinery, a fellow of the Institute for Electrical and Electronics Engineers, and a past member of the Malcolm Baldrige National Quality Award Board of Examiners. He holds a BS in physics from the University of Chicago, an MS in physics from the Illinois Institute of Technology, and an MBA from the University of Chicago.

The views expressed in this article are the author's only and do not represent directly or imply any official position or view of the Software Engineering Institute or Carnegie Mellon University. This article is intended to stimulate further discussion about this topic.

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