S. Chopra/Operations/Managing Services1 Operations Management: Capacity Management in Services Module u Why do queues build up? u Process attributes and Performance measures of queuing processes u Safety Capacity »Its effect on customer service »Pooling of capacity u Queuing Processes with Limited Buffer »Optimal investment u Specialists versus generalists u Managing Customer Service »SofOptics

S. Chopra/Operations/Managing Services2 Telemarketing at L.L.Bean u During some half hours, 80% of calls dialed received a busy signal. u Customers getting through had to wait on average 10 minutes for an available agent. Extra telephone expense per day for waiting was $25,000. u For calls abandoned because of long delays, L.L.Bean still paid for the queue time connect charges. u In 1988, L.L.Bean conservatively estimated that it lost $10 million of profit because of sub-optimal allocation of telemarketing resources.

S. Chopra/Operations/Managing Services3 Queuing Systems to model Service Processes: A Simple Process Sales Reps processing calls Incoming calls Calls on Hold Answered Calls MBPF Inc. Call Center Blocked Calls (Busy signal) Abandoned Calls (Tired of waiting) Order Queue “buffer” size K

S. Chopra/Operations/Managing Services4 Performance Measures u Revenue Related –Throughput R –Abandonment R a –Probability of blocking R b u Cost Related –Server utilization  –Inventory/WIP : # in queue I i /system I u Customer Service related –Waiting/Flow Time: time spent in queue T i /system T

S. Chopra/Operations/Managing Services5 Why do Queues Build? u Variability u Capacity utilization –Safety Capacity = capacity carried in excess of expected demand to cover for system variability »it provides a safety net against higher than expected arrivals or services and reduces waiting time

S. Chopra/Operations/Managing Services6 What to manage in such a process? u Inputs –Inter arrival times/distribution –Service times/distribution u System structure –Number of servers –Number of queues –Maximum queue length/buffer size u Operating control policies –Queue discipline, priorities

S. Chopra/Operations/Managing Services7 Queuing Theory: Variability + Utilization = Waiting u Throughput-Delay curve: u Queue Length Formula: –Prob{waiting time in queue < t } = 1 - exp(-t / T i ) where: utilization effect variability effect x

S. Chopra/Operations/Managing Services8 Levers to reduce waiting and increase QoS:  variability reduction + safety capacity u How to reduce system variability? u How to manage safety capacity?

S. Chopra/Operations/Managing Services9 Example 1: Call Center with one server, unlimited buffer u A call center has a customer service representative (CSR) taking calls. When the CSR is busy, the caller is put on hold. The calls are taken in the order received. u Assume that calls arrive exponentially at the rate of one every 3 minutes. The CSR takes on average 2.5 minutes to complete the reservation. The time for service is also assumed to be exponentially distributed. u The CSR is paid $20 per hour. It has been estimated that each minute that a customer spends in queue costs $2 due to customer dissatisfaction and loss of future business. –Safety capacity = –Customer waiting cost =

S. Chopra/Operations/Managing Services10 Example 2: Call Center with limited buffer size u In reality only a limited number of people can be put on hold (this depends on the phone system in place) after which a caller receives busy signal. Assume that at most 5 people can be put on hold. Any caller receiving a busy signal simply calls a competitor resulting in a loss of $100 in revenue. –# of servers c = –buffer size K = u What is the hourly loss because of callers not being able to get through?

S. Chopra/Operations/Managing Services11 Example 3: Call Center with Resource Pooling u 2 phone numbers –The call center hires a second CSR who is assigned a new telephone number. Customers are now free to call either of the two numbers. Once they are put on hold customers tend to stay on line since the other may be worse.. u 1 phone number: pooling –both CSRs share the same telephone number and the customers on hold are in a single queue Servers Queue ServerQueue ServerQueue 50%

S. Chopra/Operations/Managing Services12 Example 4: Call Center Staffing u Assume that the call center has a total of 6 lines. With all other data as in Example 2, what is the optimal number of CSRs that MBPF should staff the call center with?

S. Chopra/Operations/Managing Services13 Levers for Reducing Flow Time u “is to decrease the work content of (only ?) critical activities”, and/or move it to non critical activities. u Reduce waiting time: –reduce variability »arrivals & service requests »synchronize flows within the process –increase safety capacity »lower utilization »Pooling –Match resource availability with flows in and out of process

S. Chopra/Operations/Managing Services14 Sof-Optics, Inc. = Managing the operations of a customer service department

S. Chopra/Operations/Managing Services15 Call Centers u In U.S.: $10B, > 70,000 centers, > 3M people (>3% of workforce) u Most cost-effective channel to serve customers u Strategic Alignment –accounting: 90% are cost centers, 10% are revenue centers –role: 60% are viewed as cost, 40% as revenue generators –staffing: 60% are generalists, 40% specialists –Trend: more towards profit centers & revenue generators u Trade-off: low cost (service) vs. high revenue (sales) Source: O. Zeynep Aksin 1997

S. Chopra/Operations/Managing Services16 E.g.: Analysis of Service Systems u Divide day into blocks based on arrival rates u For each block evaluate performance measures given current staffing u Quantify financial impact of each action –Workforce training: reduces mean and variability of service time –Work flexibility from workforce: pools available capacity –Time flexibility from workforce: better synchronization –Improved Scheduling: better synchronization –Retain experienced employees: increased safety capacity –Additional workforce: Increases safety capacity –Incentives to affect arrival patterns: better synchronization –Decrease product variety: reduces variability of service time –Increase maximum queue capacity –Consignment program, fax, , web orders etc. S D

S. Chopra/Operations/Managing Services17 Process Structure & Resource Capabilities: Specialization Vs. Flexibility u Aggregation –single server averaging 10 minutes for service. Poisson arrivals with a mean of 5/hr. u Specialization –Service divided into two segments (one server at each segment), each averaging 5 minutes u Flexibility –Second server added, with each server performing entire service Servers Queue ServerQueueServerQueueServerQueue

S. Chopra/Operations/Managing Services18 Waiting Lines and Lean Operations u The role of limited buffer sizes u The relationship between variability and maximum buffer sizes u The supervisor as buffer capacity u Tradeoff between inventory and capacity

S. Chopra/Operations/Managing Services19 Learning objectives: General Service Process Management u Queues build up due to variability. u Reducing variability improves performance. u If service cannot be provided from stock, safety capacity must be provided to cover for variability. –Tradeoff is between cost of waiting, lost sales, and cost of capacity. u Improving Performance –Reduce variability –Increase safety capacity »Pooling servers/capacity –Increase synchronization between demand (arrivals) and service »Manage demand »Synchronize supply: resource availability