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Part Five
Delivering and Performing Service
Strategy Insight
Combining Demand (Marketing) and Capacity
(Operations) Strategies to Increase Profits
In many situations, firms use multiple demand and
capacity management strategies simultaneously to
obtain optimal usage and maximize profits. Because
each strategy involves costs as well as potential service quality, customer loyalty, and revenue outcomes,
determining the appropriate mix can be a complex
decision.
Research done for a ski resort illustrates how operations and marketing data can be combined into a
sophisticated model to predict the right mix of strategies. The ski industry presents particularly interesting challenges for capacity management because the
industry sees typically large fluctuations in demand
based on: seasonal, weekly, and even daily usage patterns; unpredictable weather and snowfall; a variety
of skiing ability segments that use the resort in different ways; and demographic shifts over time. In addition, most resorts face constraints on their capacity
due to environmental regulations that limit acreage
and parking as well as the large capital investment
required for facility expansion and/or improvement.
Furthermore, as ticket prices at ski resorts have continued to escalate, customer expectations have risen.
Powder Valley (PV, a disguised name), a ski resort
in northern Utah, had consistently lost market share
for five years to its rivals. Lack of facility improvements and increased marketing efforts by its competitors were cited as likely reasons for declining
market share. To improve the situation, PV managers had proposed several marketing strategies to
increase demand on slow days and increase revenue
per customer. Operations strategies that relied on
acquisition of new terrain and new, faster ski lifts
to improve the skiing experience and reduce waiting
during peak demand periods were also proposed.
Each of these strategies had its associated costs and
less than totally predictable outcomes. Adding to
the complexity of the inherent trade-offs in the various strategies was the fact that the resort offered
multiple activities (e.g., restaurants, skiing, shopping) for customers to choose.
The researchers working with PV proposed that
the optimal profit strategy would require an integrated set of approaches representing both demand
and capacity perspectives. Using data from the
resort, they built a sophisticated simulation model to
assess the impact on customer usage, waiting times,
and profits of several different strategies that were
being considered, including:
• Price variations. Strategies aimed at leveling demand by charging lower prices for off-peak skiing.
• Promotions of underutilized services. Promotions
to attract new customer segments or shift existing customers to underutilized services.
• Information provision on waiting times. Strategies that provide information about less crowded
periods or shorter waiting times to move customers temporarily to underutilized services.
• Capacity expansion. Investments in additional
fixed capacity for skiing such as adding new terrain or expanding the number of lifts.
• Capacity upgrades. Improving or replacing existing lifts to carry more skiers and/or run faster.
As input to their model, the researchers used
historic data on daily demand, demand smoothing
and capacity expansion options, service times for
each lift, flow patterns across various lifts within
the resort, travel time between lifts, customer perceptions, and customer choice data. By combining
these marketing and operations data, the researchers showed that retaining the current customer mix,
installing two new chairs, and providing waiting
hours, and the team of specialists may number 10 people. During slow hours the team
may shrink to three, with each of the remaining persons performing a variety of other
functions. Grocery stores also use this strategy, with most employees able to move as
needed from cashiering to stocking shelves to bagging groceries.
Modify or Move Facilities and Equipment Sometimes it is possible to adjust, move,
or creatively modify existing capacity to meet demand fluctuations. Hotels utilize
this strategy by reconfiguring rooms—two rooms with a locked door between can
be rented to two different parties in high demand times or turned into a suite during
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Chapter 15
time information would maximize profits for the
resort. Adding new chair lifts with higher speeds
and doubled seating capacity within the existing terrain was a more profitable approach than expanding to new terrain. The simulation model showed
that contrary to management predictions, smoothing demand across the day through differential pricing would actually decrease profits significantly. The
model results were also useful in suggesting a priority order for the investments. The wait time signage
investment was the least expensive and offered the
largest single improvement for customers as well as
the largest single profit impact. Upgrading at least
one chair lift was the next priority.
Balancing demand and capacity can involve a complex set of decisions, and sometimes the outcomes are
not obvious, especially when strategies seem to have
contradictory objectives. For example in the PV simulation, a marketing objective of increased revenues
through attracting more customers was contradicted
by an operations objective of providing optimal wait
times for lifts. As illustrated in the ski resort research,
firms can combine marketing and operations data
into one overall model and run simulated experiments
to determine the best set of combined strategies. One
company, ProModel, has developed simulations similar
to the one described here that have been successfully
used by such service providers as American Express, the
American Red Cross, Disneyland, Chase Bank, Delta Air
Lines, JetBlue, the Mayo Clinic, and UPS. The Salt Lake
Organizing Committee for the 2002 Winter Olympics
also used a similar simulation to evaluate and successfully optimize spectator flow, emergency planning,
and transportation systems. Of course, the quality of
the decisions based on simulation models is highly
dependent on the accuracy of the assumptions in the
model and the quality of the input data.
Managing Demand and Capacity
457
Managing demand and capacity in ski resorts can be
very challenging.
Sources: M. E. Pullman and G. Thompson, “Strategies for
Integrating Capacity with Demand in Service Networks,”
Journal of Service Research 5 (February 2003), pp. 169–183;
and ProModel Corporation (www.promodel.com).
slow demand. The airline industry offers another example of this strategy. Using an
approach known as “demand-driven dispatch,” airlines often assign airplanes to flight
schedules on the basis of fluctuating market needs.9 The method depends on accurate
knowledge of demand and the ability to quickly move airplanes with different seating
capacities to flight assignments that match their capacity. The Boeing 777 aircraft
is so flexible that it can be reconfigured within hours to vary the number of seats
allocated to one, two, or three classes.10 The plane can thus be quickly modified to
match demand from different market segments, essentially molding capacity to fit
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