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Project Proposal Prepared for: Music and Theater Department, SUNY Plattsburgh Prepared by: Taylor Manor, Project/Service Management Intern April 15, 2015 !

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EXECUTIVE SUMMARY !Objective The primary objective of this project is to develop strategies that will ensure a successful transition to a fully online ticketing system. This will be accomplished by analyzing the current ticket purchasing process and providing recommendations based upon this analysis. Enhancing ticketing functionality will:

• shorten and simplify the process of purchasing tickets for music and theater;

• reduce the workload of the will call window;

• increase customer satisfaction;

• ensure authenticity;

• and simplify event operations

Environmental Scan • Online tickets have been available for theater and music events for purchase to general admission and students,

but buyers have not had the ability to print or electronically download their tickets • A large majority of customers are aware of online tickets and utilize it.

Key Result Areas • An increase in the number of customers who print or electronically download their ticket • Decrease in the will call and box office lines • Increased level of customer satisfaction as measured by attendee satisfaction surveys • Decrease of user time on site and in lines

Next Actions • Determine the best options for theater for scanner acquisition • Utilize the marketing functions of University Tickets • Make purchasing and printing tickets as user friendly as possible • Define a process for events that ensures all staff are prepared for this transition !

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SITUATION ANALYSIS !Waiting Line Model Box Office (as opposed to the will call line) Assumptions:

1. Poisson Probability Distribution (reasonable approximation of arrival distribution)

2. Exponential Probability Distribution (reasonable approximation of service time)

3. Arrival rate is based upon the number of customers served not upon the number of tickets sold

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!!After observing the line and service at the box office, I determined a mean time per service of 42.5 seconds. Relative to that mean (42.5 seconds) you could serve 85 customers per hour.

Inputs

Unit of time 1 hour

Arrival Rate (lambda) 48 customers per hour

Service Rate (mu) 85 customers per hour

Number of servers 1

Outputs

Mean time per service 42.5 seconds

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SITUATION ANALYSIS !Waiting Line Model Box Office !

!!! The box office line on average has .73 customers waiting in line and 1.3 customers in the system which includes waiting in line and being served. This means that at any given time there is a 43.53 percent chance that there are no customers waiting in line or being served at the window. The average time of waiting in the box office line is .916 minutes and the average time a customer spends in the system is 1.62 minutes (waiting in line and being served). There is a 56.47 percent chance that the server at the box office is busy. Seeing as your server is only busy a little over half the time they are there is a strong indication that majority of your customers buy online as opposed to coming and purchasing their ticket at the box office.

Summary Measures

Average number of customers waiting in line 0.73259141

Average number of customers in the system 1.2972973

Average time waiting in line .91573927 minutes

Average time in the system 1.62162162 minutes

Probability of no customers in the system 43.53 percent

Probability that the server is busy 56.47 percent

DISTRIBUTION OF NUMBER OF CUSTOMERS IN THE

SYSTEM

Prob

abilit

y

0%

7.5%

15%

22.5%

30%

(n) customers in the system1 2 3 4 5 6 7

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SITUATION ANALYSIS !Waiting Line Model Will Call Line Assumptions:

1. Poisson Probability Distribution (reasonable approximation of arrival distribution)

2. Exponential Probability Distribution (reasonable approximation of service time)

3. Arrival rate is based upon the number of customers served not upon the number of tickets sold

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!After observing the line and service at the will call window, I determined a mean time per service of 26.33 seconds. Relative to that mean (26.33 seconds) you could serve 136 customers per hour.

Inputs

Unit of time 1 hour

Arrival Rate (lambda) 118 customers per hour

Service Rate (mu) 136 customers per hour

Number of servers 1

Outputs

Mean time per service 26.33 seconds

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SITUATION ANALYSIS !Waiting Line Model Will Call Line !

!!The will call line on average has 5.41 customers waiting in line and 6.27 customers in the system (waiting in line and time being served). This means that at any given time there is a 13.74 percent chance that there are no customers waiting in line or being served at the window. The average time of waiting in the will call line is 2.75 minutes and the average time a customer spends in the system (waiting and being served) is 3.19 minutes. There is an 86.26 percent chance that the server in the will call window is busy. Though the process time is much shorter than the box office, the waiting line is much longer. Scanners would help to shorten the waiting time in line dramatically for customers.

Summary Measures

Average number of customers waiting in line 5.41402265

Average number of customers in the system 6.27659574

Average time waiting in line 2.75289287 minutes

Average time in the system 3.191489362 minutes

Probability of no customers in the system 13.74 percent

Probability that the server is busy 86.26 percent

DISTRIBUTION OF NUMBER OF CUSTOMERS IN THE SYSTEM

Prob

abilit

y

0%

3%

6%

9%

12%

(n) customers in the system1 2 3 4 5 6 7 8 9 10

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SITUATION ANALYSIS !!

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PERCENTAGE OF THOSE WHO HAVE PURCHASED

TICKETS ONLINE VIA UNIVERSITY TICKETS FOR

EVENTS AT SUNY PLATTSBURGH BEFORE

No 59%

Yes 41%

PERCENTAGE OF THOSE WHO ANSWERED NO

THAT WOULD CONSIDER BUYING ONLINE TICKETS

IN THE FUTURE

0%

17.5%

35%

52.5%

70%

Yes No

PREFERENCE OF RECIEVING A TICKET

Num

ber o

f Peo

ple

0

2

4

6

8

Not AvailableNo Preference

Smart Phone

Print Myself

Box Office

AGE RANGE OF THOSE SURVEYED

18-24

25-39

40-49

50-59

60+

0 3.5 7 10.5 14

Results were collected from a survey conducted at the Hartman Theater

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SITUATION ANALYSIS !!Shows how the current processes of online tickets at Hartman Theater are operating through a process flow diagram

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SITUATION ANALYSIS !Shows how the current processes of online tickets for Hartman Theater are operating through a service blueprint diagram

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SITUATION ANALYSIS !Shows how the future processes of online tickets for Hartman Theater will be operating through a process flow diagram

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SITUATION ANALYSIS !Shows how the future processes of online tickets for Hartman Theater will be operating through a service blueprint diagram

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DECREASE OF USER TIME ON SITE !!!!!!!!!!

Scanners will substantially reduce the amount of time your customers spend waiting to get into an event

TARGET NUMBER OF PRINTED OR ELECTRONICALLY DOWNLOADED TICKETS

SCANNED NEXT SCHOOL YEAR

0

75

150

225

300

October December Feburary April

Printed Tickets Electonic Tickets

PROJECT PERFORMANCE !Key Performance Indicators

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RISKS AND ISSUES !1. Risks associated with scanner malfunction

2. Limited battery life

3. Possibility of network failure affecting scanners and University Tickets

4. Accidental scanner damage

5. Overlap of scanner reservations with other groups on campus

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CONTINGENCY/MITIGATION PLAN !1. Have a clear and defined back up plan to go to a paper system at the box office if necessary

2. Plan accordingly by having scanners fully charged before events and plan on having backups for long events like festivals

3. Have a list of technical contacts and phone numbers available to event staff so they know who to contact in the event of a network failure

4. Purchase lanyards for your scanners to minimize accidents

5. Reserve additional scanners at the Center for Student Involvement well before the event’s date to take priority over other groups on campus

Prob

abilit

y

Risk

Reservation Overlap

Scanner Damage

Network Failure

Battery Life

Scanner Malfunction

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• Another option theater has is to potentially buy two scanners and reserve the other two through the

student involvement center ahead of time. In the long run, buying two scanners as opposed to leasing would save 2800 by year five.

• Buying two scanners also requires room to work with in the budget. It could be suggested that:

• The Hartman theater could raise ticket prices to help with the costs and take into account labor and other costs associated with the box office and will call window.

• Have a discussion with Barry and Adrienne about contributing money to scanners and creating a scanner schedule much like an employee schedule.

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Year 1 Year 2 Year 3 Year 4 Year 5

Lease (4) 3000 3000 3000 3000 3000

Buy (4) 4600 1200 1200 1200 1200

Choosing to buy vs lease

-1600 200 2000 3800 5600

Year 1 Year 2 Year 3 Year 4 Year 5

Lease (2) 1500 1500 1500 1500 1500

Buy (2) 2300 600 600 600 600

Choosing to buy vs lease

-800 100 1000 1900 2800

RECOMMENDATIONS !1. Scanners are necessary for the online ticketing service to be completed. There are a few different options for Hartman

theater to get scanners for all four doors on events.

• One scanner cost 850 dollars to buy and 300 dollars annually for updates

• One scanner cost 750 dollars to rent for one year including updates

• If it was feasible for theater to purchase four scanners, that would be the best recommendation in the long run. There doesn't appear to room in the budget for the purchase of four scanners.

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RECOMMENDATIONS !2. Utilize the marketing functions of University Tickets by:

• Analyzing the demographics that are provided through making an account on University Tickets

• Reach out to those who have made accounts through email and update them about upcoming events

• Keep track of customer history to show you your most loyal customers and how well you are doing at getting people to come back for the next show

!3. Make purchasing and printing tickets as user friendly as possible by:

• Prominent or tactical placement of tickets link on key Plattsburgh web pages

• Having a University Tickets portal link via an icon in the My Plattsburgh App Panel (next to Moodle or Gmail icon) for students to conveniently purchase their tickets.

• Use social media to share the link to online tickets

!4. Define a process for events that ensures all staff are prepared for this transition by:

• Ensuring all employees and staff at the Hartman Theater are properly trained and informed on new procedures for events. Example (scanner use, potential for malfunction, line direction, and knowledge of University Tickets)

• Have a back up plan in the event of network or scanner failure

• Better directional signage in general and more prominent signs for will call window (if still used)

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