One set of loops that can help us better understand the basic interactions between a company and its marketplace is the supply/demand structure. Most everyone is familiar with the basic law of supply and demand: if demand rises, price tends to go up (all else remaining the same), and conversely, as supply goes down, price tends to go up (again, all else remaining equal). From a systems thinking perspective, this dynamic can be simply described by two coupled balancing loops that attempt to stabilize around a particular variable—in this case, price.

Supply and Demand: A Generic View

If we look at the supply/demand structure from a more generic perspective, we can use it to describe any situation in which an ability to supply a good or service is being balanced with the demand, utilization, or consumption of that product or service. This structure acts like a see-saw, with supply on one side, demand on the other, and some pivot point in the middle (such as quality, price, availability, or service) that links the consumer actions and the company’s decisions (see “Balancing Loops with Delays: Teeter-Tottering on See-Saws,” June/July 1990). The central variable serves as the “adjusting variable” because it is the signal that causes players on both sides of the see-saw to adjust the imbalance between supply and demand (see “Generic Structure”). These dynamics can occur between the company and the market-place or within an organization, where an internal function or unit (such as training or l.S.) is supplying services to other parts of the company.

For example, in the medical industry, one common adjusting process revolves around waiting time to get an appointment with a physician. On the demand side, if the wait time to see a particular physician becomes too long, patients might either try to find another provider, put off receiving care (in the hopes that the problem will “take care of itself”), or, if the problem is serious enough, go to the emergency room. If enough patients find alternate solutions, this leads to a decline in the physician’s utilization rate, which then eases the pressure on the physician’s schedule so that the wait time is reduced (B1 in “Medical Supply/Demand,” page 8). Physicians, for their part, might try to reduce the wait time for care by processing patients faster, adding physicians to their practice, or asking ancillary staff (such as nurse practitioners) to play a more significant role in patient care. All of these actions would increase the patient capacity and reduce the wait (B2).

What is important to note is that both balancing actions are usually happening simultaneously—that is, at the same time that the physicians are looking for ways to ease the patient bottle-neck, the patients are already taking action to relieve that pressure by seeking alternate providers or finding other ways to take care of themselves. Because demand is falling at the same time that capacity is rising, these actions will create another imbalance this time, with more available capacity for seeing patients than the actual demand for appointments. When this occurs, both parties will once again take action to close the gap (patients will return to their original provider because of the reduced wait time, while the physician’s practice might ease scheduling pressure) and the see-saw invariably tips in the other direction.

Seeking a Balance

This same see-saw structure of balancing capacity and demand shows up in a variety of contexts, such as service quality (hospitals, banks, car-rental shops, fast-food restaurants, I.S., training) or product availability (retail stores, specialty products, manufacturers).

Of course, most companies would like to find a way to strike exactly the right balance between the demand in the marketplace and their ability to service that demand. Unfortunately, that rarely happens. As the medical example shows, what is more likely is a pattern of oscillation as the two sides overshoot each other, adjust, and overshoot again.

In part, this behavior occurs because of several significant delays in the system: customer perception delay, company perception delay, and capacity addition delay.

• Customer Perception. It takes time for word to get around that a company cannot provide a particular product or service (this signal usually comes in the form pf rising prices, lengthening delivery delays, or declining quality). It also takes time for people to alter their usage or consumption patterns. Similarly, once a company has added capacity, it takes time for that signal to make it into the marketplace and draw customers back.
• Company Perception. Just as it takes time for customers to realize that a company can no longer meet their needs, it takes time for the company to recognize that demand for its product or service is declining. This delay is often exacerbated because companies do not act upon the information immediately, believing that the drop off in demand is either temporary or due to factors other than capacity shortfall.
• Capacity Additions. Once the company has recognized the imbalance between the marketplace demand and its ability to meet that demand, there is a further delay while the company adds the needed capacity. The length of this delay depends on the nature of the capacity being added—for example, it takes a lot longer to add capital equipment than to increase customer service representatives or improve a process.

Using the Structure

The generic supply/demand causal loop structure provides a useful starting point for exploring how internal actions and marketplace decisions are intertwined. To see how the structure can be applied to a specific problem, let’s take a look at the example of ZSearch, a research company that specializes in tracking down research articles in the biochemical industry. ZSearch had built its reputation on the quality and timeliness of its response to its customers’ inquiries. However, the company’s managers have become concerned about two recent trends: customer surveys have ranked the company below its competitors in terms of customer service, and they have noticed a drop-off in the overall number of research requests per day.

1. Define the Variables. To begin mapping out the system, first define the different parts of the see-saw: what is being “supplied,” what is being “demanded,” and what is the fulcrum around which the imbalances between the two are resolved.

In ZSearch’s case, the “supply” would be the number of customer service representatives, the “demand” would be the number of requests from customers, and the “fulcrum” would be the wait time for service. If the number of requests coming in outstrips the available capacity, an imbalance appears in the system. Customers who are stuck on the phone waiting for a customer service rep might be inclined to hang up and call one of ZSearch’s competitors, thus decreasing the wait time for service (B1 in “ZSearch’s Balancing Act”). On the other side of the see-saw, once ZSearch gets the signal that it needs more capacity, it can respond by increasing the number of service reps or raking other actions that would likewise decrease wait time (B2).

2. Identify Delays. Once you have identified the fundamental balancing loops, it is important to identify and quantify the relevant delays. In ZSearch’s case, the customer perception delay may be fairly short—it doesn’t take lung for customers to get a busy signal, put down the phone, and call a competitor (although it does take time to establish new supplier relationships).

On ZSearch’s side, there might be a long perceptual delay before ZSearch identifies the source of the drop-off in call volume and how to respond to it. At this point, it would be easy for them to blame external forces, such as aggressive competitors, rather think examining how their own policies might be contributing to the decline. However, ZSearch’s managers felt that the problem might stem from a shortage of trained service reps. They knew they could case this burden in the short term by increasing the work hours of their current staff, though they acknowledged that it would take several months to hire and train the new reps.

3. Design Interventions. When considering any potential solution, it is important Lu evaluate the action in terms of both its internal consequences and its impact on the marketplace. In particular, look for ways you can more directly influence the customers’ behavior (the demand loop), rather than simply reacting after-the-fact (the supply loop).

At first, ZSearch’s managers were at a loss as to how they could have any direct influence on their customer’s decision to hang up and call a competitor. But after some thought, they came up with with a program that they called the “superior customer service guarantee.” They promised that any customer who waited longer than 60 seconds for an available representative would receive a 40% discount on the order. It was a costly gamble, but it paid off—the guarantee not only boosted ZSearch’s reputation in the field, bur on three occasions that the demand outstripped capacity, customers were willing to wait the extra time (to get the discount) and ZSearch retained the sale.

More importantly, ZSearch received timely, valuable feedback about their response time without risking losing customers. Knowing that they now had a strong system in place for tracking their call volume and service turnaround (the demand side of the diagram), they could focus their attention on the supply side of the diagram—finding ways to keep their staffing up to optimal levels.

Larger Implications

Many organizational “crises”—poor sales, quality problems, slipping delivery times–can be traced back to the mismatch between supply and demand and how this disequilibrium is corrected. Within organizations, this plays out in pressures to outsource in order to improve service or reduce costs. But it also occurs in whole industries, as poor service or high prices attract new competitors and innovators to the industry. This is the very mechanism by which customers see quality rise as prices decline over rime in an industry.

Michael Goodman is vice president of Innovation Associates, Inc. (Waltham MA) and heads IA’s Systems Thinking Group.

Colleen Lannon Is co-founder of Pegasus Communications and managing editor of The Systems Thinker•.

Balancing Act

If the number of incoming requests outstrips capacity, an imbalance appears. This imbalance can be resolved in one of two ways: (1) customer calls drop off due to the long wait (B1); or (2) customer service reps are added in order to reduce the time it takes to process requests (B2).

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Apparently, plenty. The software found one what it called “major” problem and dozens of minor ones. My system was “moderately fragmented,” which meant that the computer had to search through the disk to find different parts of a single file, an inefficient process. No problem—that’s what maintenance programs are for. It fixed the errors, defragmented my hard disk, and I was back in business.

What I didn’t anticipate was the radical improvement in the computer’s performance after I had done this housekeeping. It blazed! Programs launched in the wink of an eye, graphic-heavy web sites loaded in an instant. As I witnessed these feats, I was reminded of my amazement at how speedy the processor was when I first plugged the computer in.

The question that puzzled me was, why didn’t I notice the computer’s performance had degraded so much? After thinking it through, I concluded that, little by little, I had shifted my expectations. The decline had been gradual, and performance was still within acceptable limits, so I easily adapted to the slower access and load times. However, if I had continued to put off the maintenance process, the computer would have eventually crashed, which certainly would have gotten my attention and caused untold difficulties.

In this case, the consequences were reversible—I was quickly able to fix the system so that it ran as efficiently as ever. But when this dynamic occurs in other situations, it can be more difficult to diagnose and the results can be more damaging.

Lowering Performance Goals

In systems thinking terms, I had experienced an example of the “Drifting Goals” systems archetype. Systems archetypes are common patterns of behavior that occur in all kinds of settings. “Drifting Goals” involves lowering our performance goals rather than

Check-ups or maintenance programs use objective measures of a system’s performance to periodically diagnose problems that might not be apparent to someone on the inside.

taking corrective actions. Sometimes we do so because these actions are undesirable, as in the case of cutting expenses in order to reach profit goals. Sometimes we’re focused on other factors that seem more important; for example, we may be so caught up with efforts to boost sales that we fail to notice that quality has slipped. And sometimes, as I experienced with my computer, because our senses aren’t attuned to gradual changes over time, we just don’t notice that performance has degraded.

The parable of the “boiled frog” is often cited as an example of the “Drifting Goals” dynamic. According to the story, if you toss a frog into a pot of boiling water, it will immediately try to jump out. On the other hand, if you put it in cold water and then gradually raise the temperature, the frog will happily swim around until it—there’s no delicate way to put this—cooks. The frog’s survival instincts are geared toward detecting sudden changes, not incremental ones. Although this fable has been questioned by scientists, it vividly illustrates what I experienced with my computer —I likely would have noticed an abrupt decline in functioning but was unable to detect a slowdown over several months. Just as the frog adapts to the water temperature, I unconsciously lowered my expectations of the computer’s performance.

Adjusting our expectations isn’t always bad, but if we’re going to change our goals, we should do so consciously. The key is to know what our objectives are and to track performance vis-à-vis these benchmarks. To that end, most manufacturing companies have mechanisms in place for monitoring adherence to quality standards. Organizations also tend to stay on top of financial and sales goals through routine reporting and analysis.

When it’s not practical to measure performance on a continual basis, as with my computer, then a regular check-up may be in order (see “Maintaining Performance Goals” on p. 8). Check-ups or maintenance programs use objective measures of a system’s performance to periodically diagnose problems that might not be apparent to someone on the inside. For instance, in a physical examination, a doctor checks blood pressure, weight, cholesterol, and other levels to ensure that they remain within healthy limits. Unless a person has a health problem that requires continual monitoring, such as diabetes or high blood pressure, checking these functions daily or weekly would be onerous—for most people, once a year is often enough. But if we put off seeing our physician for too long, changes that we’ve gradually adapted to—low-grade fatigue or a persistent cough— may compound to become health crises.

MAINTAINING PERFORMANCE GOALS

In certain systems, such as my computer, actual performance begins to fall short of desired performance over time (B1). We may not notice the shift, because our senses aren’t attuned to gradual changes, so we unconsciously lower our expectations of the systems’ performance. Rather than changing our standards, a more productive approach is to consciously be aware of this dynamic and to institute a regular check-up or maintenance process (B2). By doing so, we bring actual performance back up to speed and keep our goals on track.

Organizational Check-ups

How might we incorporate the idea of maintenance checks in an organizational setting? The goal is to cast light on changes that we may not perceive because they are so gradual while not becoming bogged down by burdensome reporting or monitoring tasks. This is especially true for areas that aren’t easy to measure, such as employee satisfaction, adherence to the corporate mission statement, or teamwork. In these cases, a maintenance process may be as simple as meeting with a partner every week to get an objective opinion of your progress on achieving a developmental goal or as complex as conducting quarterly employee surveys to evaluate morale.

Here are some ideas for making sure that performance stays steady over time:

• Identify variables that are important to organizational performance, especially those that aren’t usually on the radar scope, such as employee morale or use of productive conversation tools.
• Establish performance standards for these variables. Keep the standards visible.
• Track performance versus the standards.
• If it’s not possible or practical to track performance analytically, find a way to periodically collect input from an objective source—a learning partner, an outside coach or facilitator, a semi-annual employee survey. Experiment to find the right interval between “check-ups”—too often and you might find them more trouble than they are worth, too infrequent and problems might be on the verge of spinning out of control before you catch them.
• If you are tempted to shift a goal, be deliberate! Look into the causes and consequences of doing so before taking action.
• Learn from experience. If you’ve noticed unacceptable changes in a variable, design a maintenance program to keep it on track in the future.

If you follow these steps, you’re likely to keep your organization performing at high levels and avoid crashing the system or boiling the frog —things none of us want to do!

Janice Molloy is managing editor of The Systems Thinker and content director at Pegasus Communications, Inc.

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