Often, I've had to apply more effort than expected to achieve my critical objectives according to plan. I've observed that most people and most businesses face the same issue. This essay explains the problem and how to handle it.

Some years ago, at Pro-Log, we improved our project planning with PERT charts and CPM (Critical Path Method) analysis. We hired a consultant from a nearby graduate school to teach us basic PERT techniques. The course went well until the manager of our drafting department asked a real-world question: How could he best schedule his drafting resources so as to meet the needs of several projects at one time, in spite of unpredictable problems and timing changes on one or more of these projects? Unfortunately, the consultant attempted to answer the question with detailed suggestions and mathematical formulae. He got tangled up in his answer.

The Freeway analogy
Scheduling many tasks through a business is like driving cars on a freeway (See Fig. 1). The freeway has a limited capacity for handling traffic, one that depends on how many lanes it has and on road conditions. This capacity is approached at some optimum car-speed and car-density product (Fig. 1, point B). For example, it may occur with cars traveling 55 mph and separated by five car lengths or at 65 mph and separated by 7 car lengths (drivers on the San Diego freeway average 70 mph and a separated by ~ 0.5 car lengths, but that's another story).

From a management point of view, operating at peak capacity is also operating at peak efficiency. The bean counters and gurus of corporate re-engineering mistakenly try to operate business systems there.

Fig. 1:The relationships between the number of cars on a freeway, the throughput of the freeway (system efficiency), and the average driving time per mile for individual vehicles.

When a freeway operates at point A, the traffic is reasonably light and vehicle speeds are determined by individual drivers. When more vehicles enter the flow of traffic, drivers change lanes, or individual drivers go at widely different speeds, the drivers in their immediate vicinity can easily accommodate the changes. The freeway is a robust system. However, when a freeway is operating at point B of Fig. 1, typically during rush hour, the average vehicle moves more slowly and its speed is determined by the flow of traffic. Point B is in the region of peak efficiency for the freeway, but it is also a region in which the system is vulnerable to overloads that foul up everyone. The freeway at peak efficiency is an intrinsically fragile system. Another vehicle entering the flow of traffic, a car changing lanes, etc. can easily induce an overload which causes a collapse of throughput. The density of cars suddenly increases as the cars come to a screeching halt and the freeway turns into a parking lot.

At point A in Fig. 1, there are few cars on the freeway and they are loosely coupled to one another. The action of one car has little or no impact on what the other cars are doing. Each car is able to go as fast as the driver chooses and to reach its destination according the driver's plan. The "excess capacity" of the system is actually performing a constructive role: it makes the system robust, it enables each vehicle to go faster, and it increases the probability that all individual trips will be completed on-time in spite of unforeseen difficulties along the way. Point A is in the region of peak effectiveness.

Each worker and each workgroup in a company is like that freeway; the critical tasks are like the cars that have to reach their destinations within a specified time. Many people and organizations plan to work at full capacity, where that capacity is a function of their abilities and the time they put into their jobs. By loading themselves at peak capacity with critical jobs, the best possible outcome they can hope for is that all critical jobs get done, but take much longer than they'd planned. What usually happens is that these individuals and work groups become parking lots or beep-and-creep roads for critical work.

How to Plan to succeed
How can we plan in a way that avoids overloads and enables us to get critical things done on time? A partial solution comes from studying the freeway analogy: plan critical tasks at significantly less than peak capacity so that there is capacity margin for the unexpected. On the one hand, this is a difficult solution to sell to managers. They will usually challenge this kind of plan and pressure us to become fully loaded with critical tasks. These managers prefer plans that look impressive on paper to results which consistently correspond to plans. On the other hand, simply reducing the workload isn't a complete solution because, unlike a freeway, our individual and workgroup capacities are not really fixed. Capacities, like muscles, increase somewhat with proper nourishment and conditioning, and atrophy when underutilized. Our capacities shrink to fit inadequate challenges. We barely get the critical tasks done regardless of how little we plan to do.

A more accurate way of stating Parkinson's Law ("Work expands to fill time.") is: "Capabilities atrophy so as to barely complete work in the time allotted."
We can do three things as managers to prevent capacity atrophy in ourselves and in our workgroups:
1. Plan for reserve capacity.
2. Exercise this reserve so that it's available when needed.
3. Define important tasks to do after the planned tasks
are accomplished. (This adds a sense of urgency.)

My personal system for maintaining usable reserve capacity is one that works very well when I actually employ it. First I divide planned tasks into three groups:
A- Critical: must be successfully completed to succeed.
B- Important: must be 80% completed as a group to succeed.
C- Useful, but not necessary. (The C tasks are equivalent to
the spaces between cars on a freeway.)

Fig. 2: Classification of some of my tasks when CEO of Pro-Log.

Then I plan 70-80% of my available capacity for the A and B tasks, and plan the rest for C tasks. The experienced manager will laugh, or perhaps sneer at this point because by the time she plans A and B tasks she has committed well over 100% of realistic, sustainable capacity. However, when critical tasks require more than 80% of my peak capacity, it's time for me to stop and re-plan those higher level objectives and strategies that generated those tasks because my strategies are flawed, and my objectives wont all be accomplished.

As I execute my plan, the unexpected usually crops up in one or more of my A tasks and/or an unforeseen A task is added to my stack. I simply drop some of the planned C tasks and transfer my efforts to the A tasks. By the time I've finished I find that my resources were used in roughly this way: over 90% for A and B tasks and less than 10% for C tasks. I will have experienced some schedule delays, but I will have kept all critical tasks on or near their planned schedules.

Human behaviors in overload
When a business plan lacks adequate reserves and the business system goes into overload, people in the system do strange things. One of the more interesting behaviors is that they work less on A tasks and begin to devote more and more time to C tasks. I suspect that when we are in overload, we feel impotent instead of important. To boost our self-esteem we tackle tasks that are relatively easy and whose success is quick and certain. Individuals clean their desks, answer their mail, do subordinates' work (favorite choice of executives and CEOs), and complain about management (favorite choice of subordinates). Work groups shuffle paper, hold unproductive meetings, and complain about management. I have also noticed that some people in overload tend to volunteer for additional critical tasks. The act of volunteering, a C task at best, brings them a brief shot of self-esteem.

Individuals usually get out of overload by quitting, by being fired, by getting seriously ill for an extended time, by dying, or by getting transferred to a totally new job within the company. These actions reset the person to the origin of Fig. 1 and ready, with the exception of dying, to move up the capacity curve in a new job.

For a workgroup or management team that is in overload, there is only one productive choice: stop working, re-plan and chop out some of the critical tasks. If necessary, put them on the list of things to do after the other critical tasks are completed. This choice takes great management courage. None of us finds it easy to believe that everything has really degenerated to beep and creep. It is hard to admit that our choices are to do a few things to plan, or nothing to plan. We are tempted instead to hire more people and to pursue the original plan. But, hiring, assimilating, and training people is another A task dumped on an already overloaded system!

Postscript
The impetus to work at peak capacity is usually cost driven. Cost driven "optimization" is now occurring in the avalanche of corporate downsizings. It is also occurring in our medical system. In some cases a downsizing eliminates waste, in others it increases the probability that the system will go into overload. Let's look at the situation as it's developing in our national medical system.

Doctors tend to work inefficiently and then achieve their personal revenue goals by charging outlandish prices. However, patients who are willing to pay these costs can always find an excellent (though fiscally inefficient) doctor on short notice. The government and medical insurers taking over the payments for medical care are cost driven. To contain costs, they "fully load" doctors with patients. As a consequence, patients are backlogged, wait longer for medical care, and receive care of lower quality because doctors rush from one patient to the next in order to meet their patient quota for the day.

At some point, doctors and nurses will go into overload (as they do already in county hospitals), make gross mistakes, get sued, and eventually flee the medical care system in droves. When that happens, large numbers of patients will be parked in waiting rooms, like cars stuck on a freeway in rush hour. (Please note: I'm not advocating a policy or solution here, simply showing how the concepts of this article apply to our medical system.)

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