Spirit Halloween : a look at 2014 Computer SupportBy Dalitso Chapema and Robin Simon

HistorySince the opening of its first store 30 years ago in 1983 in California, Spirit has experienced tremendous growth. In 1999 Spirit Halloween operated 63 seasonal locations throughout the United States and was acquired by Spencer Gifts LLC. Since its acquisition Spirit has expanded its store base from 63 locations to over a 1,000 locations and has become the largest Halloween specialty store on the planet! Spirit Halloween stores are situated in high visibility, high-traffic strip centers and are located in 49 states and Canada.

What's the Boo About?The $8 billion Halloween industry has expanded far beyond a simple trick-or-treat. Today, the pervasive ghoulish holiday has us all in the spirit. In the last few years, the company has enjoyed explosive growth, now boasting over 1100 stores in all 50 states. Each year, they must find and rent temporary locations. They hire, train, and manage a 15,000 person temporary workforce. Every year requires the orchestration and precision of a symphony, combined with the urgency of a prizefighter slugging from behind with only a few rounds to go.Spirit has mastered this and it hasnt been an accident, but with their rapid growth there has been a new set of challenges.The 2014 season has seen 300 new stores added to an already stretched Store Support Network.Support is responsible for Setting up all computer networks via telephone supervisionTrouble shooting any non working equipmentShipping replacement equipmentAll shipping and receiving pos queriesInventory scanner and remote access

As you can see they are the life line of the operation so you can imagine why a 60 minute wait time call can become an issue to their plans for sustained growth.

What we sawTo understand we observed the call center for 4 days and also used their call logs for the last 27 days. This is what we saw

Spirit Halloween Call Centre Sample Data

# minutes per callSample123Sample MeanRange124.023.137.628.214.6217.247.414.526.433.0318.254.613.428.741.2420.812.527.420.214.9517.042.121.827.025.1620.829.519.223.210.3719.755.333.736.235.6822.912.966.334.053.4928.520.942.630.721.71016.141.415.624.425.81113.419.08.113.510.81225.637.428.130.411.81314.214.412.213.62.31460.949.834.848.526.11547.122.717.329.129.8164.333.411.616.429.11723.842.923.830.219.11820.534.820.325.214.51928.315.936.226.820.32060.224.541.542.035.72138.037.062.345.825.42230.021.18.920.021.12338.921.234.531.517.7248.09.730.115.922.12538.411.725.425.126.72615.214.010.313.24.9276.455.939.533.949.4

x-bar,R chts

X-bar and R Charts

Control Limits, X-bar ChartControl Limits, R Chart

SampleSample MeanRangeLCLUCLMeanLCLUCLR-barRange

128.214.63.141791303751.68754716927.4146692364061.158133614623.796939149714.6

226.433.03.141791303751.68754716927.4146692364061.158133614623.796939149733.0

328.741.23.141791303751.68754716927.4146692364061.158133614623.796939149741.2

420.214.93.141791303751.68754716927.4146692364061.158133614623.796939149714.9

527.025.13.141791303751.68754716927.4146692364061.158133614623.796939149725.1

623.210.33.141791303751.68754716927.4146692364061.158133614623.796939149710.3

736.235.63.141791303751.68754716927.4146692364061.158133614623.796939149735.6

834.053.43.141791303751.68754716927.4146692364061.158133614623.796939149753.4

930.721.73.141791303751.68754716927.4146692364061.158133614623.796939149721.7

1024.425.83.141791303751.68754716927.4146692364061.158133614623.796939149725.8

1113.510.83.141791303751.68754716927.4146692364061.158133614623.796939149710.8

1230.411.83.141791303751.68754716927.4146692364061.158133614623.796939149711.8

1313.62.33.141791303751.68754716927.4146692364061.158133614623.79693914972.3

1448.526.13.141791303751.68754716927.4146692364061.158133614623.796939149726.1

1529.129.83.141791303751.68754716927.4146692364061.158133614623.796939149729.8

1616.429.13.141791303751.68754716927.4146692364061.158133614623.796939149729.1

1730.219.13.141791303751.68754716927.4146692364061.158133614623.796939149719.1

1825.214.53.141791303751.68754716927.4146692364061.158133614623.796939149714.5

1926.820.33.141791303751.68754716927.4146692364061.158133614623.796939149720.3

2042.035.73.141791303751.68754716927.4146692364061.158133614623.796939149735.7

2145.825.43.141791303751.68754716927.4146692364061.158133614623.796939149725.4

2220.021.13.141791303751.68754716927.4146692364061.158133614623.796939149721.1

2331.517.73.141791303751.68754716927.4146692364061.158133614623.796939149717.7

2415.922.13.141791303751.68754716927.4146692364061.158133614623.796939149722.1

2525.126.73.141791303751.68754716927.4146692364061.158133614623.796939149726.7

2613.24.93.141791303751.68754716927.4146692364061.158133614623.79693914974.9

2733.949.43.141791303751.68754716927.4146692364061.158133614623.796939149749.4

Mean27.4146723.796939149723.7969391497

Factors

nA2D3D4

31.0202.57

x-bar,R chts

Sample Mean

LCL

UCL

Mean

Days

Sample mean

X-bar Chart for Mean Call time

Samples

LCL

UCL

R-bar

Range

Days

Range

R Chart for Mean Number of Calls

Spirit Halloween Call Centre Sample Data

# minutes per call

Sample123Sample MeanRange

124.023.137.628.214.6

217.247.414.526.433.0

318.254.613.428.741.2

420.812.527.420.214.9

517.042.121.827.025.1

620.829.519.223.210.3

719.755.333.736.235.6

822.912.966.334.053.4

928.520.942.630.721.7

1016.141.415.624.425.8

1113.419.08.113.510.8

1225.637.428.130.411.8

1314.214.412.213.62.3

1460.949.834.848.526.1

1547.122.717.329.129.8

164.333.411.616.429.1

1723.842.923.830.219.1

1820.534.820.325.214.5

1928.315.936.226.820.3

2060.224.541.542.035.7

2138.037.062.345.825.4

2230.021.18.920.021.1

2338.921.234.531.517.7

248.09.730.115.922.1

2538.411.725.425.126.7

2615.214.010.313.24.9

276.455.939.533.949.4

What we sawOn days that they received a high amount of calls they didnt have a very long wait time. Reasons for this were because on certain days they had issues that affected all stores. So it was usually a global fix. On Days that they didnt have a high volume they had significantly higher wait times. This is because the problems were isolated

Speaking to the representatives they mentioned that lot of the calls they receive can be corrected by a restart of the device giving problems. They also did say that the calls get pooled into batch that is sorted by call time and order and each one must get dealt with so in a sense the system gets clogged with a lot of simple fix items causing the backup. Days that have a high call volume due to a universal problem are the worst because all the stores call in.

SolutionThe system needs an upgraded call screening filter. All calls do not need to be handled by a support rep. Very similar to the popular numeric option menu i.e. press 1 for emergency; 2 for replacement equipment etc.Communication on large scale issues must be better and in a timely manner. If Credit Cards are not working a communication should be sent early to avoid the backlog of calls.The simplest but possibly most costly is to hire more support reps. The company hasnt increased the number of reps in three years so the call center that handled 800 stores is handling 1200 stores. The big problem is that its seasonal, and the support center they use actually doubles as the support center for Spencer's.

Very efficient company but if they are to sustain their 100 store increase year over year they need to address the support infrastructure.