Demand and Capacity Alignment

Demand and supply management continues to be a challenge for service managers. Despite the importance of this aspect of management and the impact it can have on profits, little is understood about this sometimes-ambiguous aspect of service management. Indeed, interviews show that although services use many demand and supply management options, managers do not think of this area as a whole rather working at individual pieces without necessarily recognizing how these pieces fit together.

Is it possible for services such as banks, retail establishments, and restaurants to influence when customers will desire their services? If so, how can services gain the understanding necessary to accomplish this? What options are available? On a broader scale, how should services approach the area of Demand and Supply Management (DSM) and integrate the decisions between both domains?

DSM may be both the most troublesome management problem for services and the single greatest determinant of success. Managers agree that if demand could be smoothened (thereby allowing supply to be more closely matched to demand) it would have a positive impact on profits.

This text defines, summarizes and categorizes a large number of DSM practices. This is a more comprehensive treatment than found in current literature and provides structure to this little understood area. Information from interviews with service managers gives insight into the use and value of the various options. Secondly, using empirical data from a bank, we show that it may indeed be possible for services to impact the timing of their demand, sometimes with very little cost.

Finally, decision making tools and suggestions for integrating DSM decisions are given. It is important to note that although the discussion should apply to some extent to all firms that provide services, it is primarily concerned with those services that cannot schedule customers. This is currently the area of greatest need, since firms that have the ability to schedule customers already have good tools available (e.g., yield management for airlines and hotels, network and integer programming formulations for trucking companies, scheduling heuristics for outpatient clinics).

Also, note that some services such as emergency services and insurance claim offices have virtually no ability to control demand. These types of firms are likely not at benefit from the demand management (DM) discussion, although the supply management (SM) presentation may be helpful.

‘All the activities and decisions management carries out in order to plan and implement how they will attempt to influence the level of demand for any service offered at any point in time’.

Some DM efforts are aimed at increasing demand, and some at changing the timing of demand. This paper looks primarily at those actions that change the timing of demand, although these efforts may also have the effect of increasing or decreasing total demand. Note that demand can only be managed if patterns (time and/or place) can be predicted and influenced.

While it is sometimes assumed that influencing demand is impossible (based on discussions with managers and researchers), we will see that all services we studied already use DM. At the same time, the potential for influencing when customers demand service is limited for services that cannot schedule customers. For instance, a bank likely cannot eliminate the large demand on paydays, and a supermarket cannot entirely reduce the peak resulting from customers stopping on their way home from work.

The effectiveness of various Demand Management Options (DMOs) will depend on the particular service industry, the location, and the customer base. For instance, a supermarket manager revealed that it is easier to influence the timing of demand at a store that has retired people as its primary clientele, since these people are not restricted to non-working hours.

A fast food outlet manager revealed that an outlet located downtown will generally have higher lunch demand but much lower dinner and evening demand than an outlet located in the suburbs. Despite these uncontrollable factors, services can be successful in encouraging customers to change their habits.

Almost all DM efforts represent an effort to smooth demand, to reduce the peaks and increase the valleys. In some cases this involves smooth demand for only one part of the service as occurs when a bank installs an ATM machine. The machine can handle few of the types of services the bank offers, but has the effect of reducing the demand for basic services during regular hours and increasing the demand after hours.

Service businesses, by contrast, can’t normally stockpile their output, because the time-bound nature of service delivery makes it impossible to inventory the finished service. For instance, the potential income from an empty seat on an airline flight is lost forever once that flight takes off, and the “room-nights” which constitute the basic unit of production for every lodging establishment are equally perishable.

Likewise, the productive capacity of an auto repair shop (facilities, personnel, and equipment) is wasted if no one brings a car for servicing on day when the shop is open. Conversely, when demand for service exceeds supply, the excess business may be lost. If someone can’t get a seat on one flight, another carrier gets the business, or the trip is cancelled or postponed. And if an accounting firm is too busy to accept tax and audit work from a prospective client another firm will receive the assignment.

But demand and supply imbalances are not found in all service situations. The horizontal axis classifies organisations according to whether demand for the service fluctuates widely or narrowly over time; the vertical axis classifies them according to whether or not capacity is sufficient to meet the peak demand. As a generalisation, capacity problems are more likely to exist today in service organisations that involve physical processes than in those that involve information-based processes.

What are the strategic implications for marketing managers in each instance? Organisations in point:

(i) Could use increase in demand outside peak periods, those in point.

(ii) Must decide whether to seek continued growth in demand and capacity, or to continue the status quo and those in point.

(iii) May need temporary de-marketing until capacity can be increased to meet or exceed current demand levels. Service organizations in point.

(iv) Face an ongoing problem of trying to smooth demand to match capacity, which involves both stimulation and discouragement of demand. It is the fourth category that offers the greatest marketing challenge.

Determining the Demand Pattern:

Managing demand is a major challenge for many service marketers, especially in people, processing and possession, processing services when opportunities to manage the level of physical capacity (represented by facilities or personnel) are tightly constrained. For many service organizations, successfully managing demand fluctuations through marketing actions is the key to profitability.

To determine the most appropriate strategy in each instance, we need to seek answers to some additional questions. Are demand fluctuations cyclical and, if so, what is the typical cycle period? What are the underlying causes of these demand fluctuations? Do they reflect customer habits or preferences that might be changed by marketing efforts? Or do they derive from decisions by third parties, such as employers and school setting working and classroom hours.

Alternatively, are variations in demand caused by more random events, such as weather conditions and health emergencies.

One way of smoothen the ups and downs of demand is through strategies that encourage customers to change their plans voluntarily, such as offering special discount prices or added product value during periods of low demand. Another approach is to ration demand through a reservation or queuing system, which basically inventories demand rather than supply. Alternatively, to generate demand in periods of excess capacity, new business development efforts might be targeted at prospective customers with a counter-cyclical demand pattern.

Determining what strategy is appropriate, requires an understanding of who, or what is the target of the service. If service is delivered to customers in person, there are limits as to how long a customer will wait in line; hence strategies designed to inventory or ration demand should focus on adoption of reservation systems. But if the service is delivered to goods or to intangible assets, then inventorying demand should be more feasible, unless the good is a vital necessity.

It is necessary to have a clear understanding of demand patterns to manage fluctuating demand effectively in a service business, which are as follows:

(1) Charting Demand Patterns:

First, the organisation needs to chart the level of demand over relevant time periods. Organisations that have good computerised customer information systems can do this very accurately. Others may need to chart demand patterns more informally. Daily, weekly, and monthly demand levels should be followed, and if seasonality is a suspected problem, graphing should be done for data from at least the past year’s data.

In some services, such as restaurants or health care, hourly fluctuations within a day may also be relevant. Sometimes, demand patterns are intuitively obvious; in other cases patterns may not reveal themselves until the data are charted.

(2) Random Demand Fluctuations:

Sometimes, the patterns of demand appear to be random there is no apparent predictable cycle. Yet even in this case, causes can often be identified. For example, day-to-day changes in the weather may affect use of recreational, shopping, or entertainment facilities.

Although the weather cannot be predicted far in advance, it may be possible to anticipate demand a day or two ahead. Health-related events also cannot be predicted. Accidents, heart attacks, and births-all increase demand for hospital services, but the level of demand cannot generally be determined in advance. Natural disasters such as floods, fires, and hurricanes can dramatically increase the need for such services as insurance, telecommunications, and health care. Acts of war and terrorism such as that experienced in the United States on September 11, 2001, generate instantaneous need for services that can’t be predicted.

AT&T was faced with a sudden increase in demand for services to the military during the Gulf War. During this period, 500,000 U.S. troops were deployed to the Middle East, many without advance warning. Before their deployment, these men and women had little time to attend to personal business, and all of them left behind concerned family and friends. With mail delivery between the United States and the Middle East taking more than six weeks, troops needed a quick way to communicate with their families and to handle personal business.

Communications with home were determined by the military to be essential to troop morale. AT&T’s ingenuity, responsiveness, and capacities were challenged to meet this unanticipated communications need. During and after the Gulf War crisis, more than 2.5 million calls were placed over temporary public phone installations, and AT&T sent more than 1.2 million free faxes to family and friends of service men and women.

(3) Predictable Cycles:

In looking at the graphic representation of demand levels, is there a predictable cycle daily (variations occur by hours), weekly (variations occur by day), monthly (variations occur by day or week), and/or yearly (variations occur according to months or seasons)? In some cases, predictable patterns may occur at all periods. For example, in the restaurant industry, especially in seasonal tourist settings, demand can vary by month, by week, by day, and by hour.

If there is a predictable cycle, what are the underlying causes? The Ritz-Carlton in Phoenix knows that demand cycles are based on seasonal weather patterns and that weekly variations are based on the workweek (business travellers don’t stay at the hotel over the weekend). Tax accountants can predict demand based on when taxes are due, quarterly and annually.

Services catering to children and families respond to variations in school hours and vacations. Retail and telecommunications services have peak periods at certain holidays and times of the week and day. When predictable patterns exist, generally one or more causes can be identified.

(4) Demand Patterns by Market Segment:

If an organisation has detailed records on customer transactions, it may be able to disaggregate demand by market segment, revealing patterns within patterns. Or the analysis may reveal that demand from one segment is predictable, while demand from another segment is relatively random. For example, for a bank, the visits from its commercial accounts may occur daily at a predictable time, whereas personal account holders may visit the bank at seemingly random intervals.

Health clinics often notice that walk-in or “care needed today” patients tend to concentrate their arrivals on Monday, with fewer numbers needing immediate attention on other days of the week. Knowing that this pattern exists, some clinics schedule more future appointments (which they can control) for later days of the week, leaving more of Monday available for same-day appointments and walk-ins.

5. Elements to Shape Demand Patterns:

There are many marketing mix elements. Those have a role to play in stimulating demand during periods of excess capacity and in decreasing it (demarcating) during periods of insufficient capacity. Price is often the first variable to be proposed for bringing demand and supply into balance but changes in product, distribution strategy, and communication efforts can also play an important role. Effective demand management efforts often require changes in two or more elements jointly.