1. Service Processes Operations Management Dr. Ron Tibben-Lembke

2. Nature of Services • Everyone is an expert on services • What works well for one service provider doesn’t necessarily carry over to another • Quality of work is not quality of service • “Service package” consists of tangible and intangible components • Services are experienced, goods are consumed • Mgmt of service involves mktg, personnel • Service encounters mail, phone, F2F

3. Degree of Customer Contact • More customer contact, harder to standardize and control • Customer influences: • Time of demand • Exact nature of service • Quality (or perceived quality) of service

4. Restaurant Tipping Normal Experiment Introduce self(Sun brunch) 15% 23% Smiling (alone in bar) 20% 48% • Waitress 28% 33% • Waiter (upscale lunch) 21% 18% “…staffing wait positions is among the most important tasks restaurant managers perform.”

5. Performance Priorities • Amount of friendliness and helpfulness • Speed and convenience of delivery • Price of the service • Variety of services • Quality of tangible goods involved • Unique skills required to provide service

6. Applying Behavioral Science • The end is more important to the lasting impression (Colonoscopy) • Segment pleasure, but combine pain • Let the customer control the process • Follow norms & rituals • Compensation for failures: fix bad product, apologize for bad service

7. Service-System Design Matrix Degree of customer/server contact Buffered Permeable Reactive High core (none) system (some) system (much) Low Face-to-face total customization Face-to-face loose specs Sales Opportunity Production Efficiency Face-to-face tight specs Phone Contact Internet & on-site technology Mail contact Low High

8. Blueprinting Fancy word for making a flow chart “line of visibility” separates what customers can see from what they can’t Flow chart “back office” and “front office” activities separately.

9. Fail-Safing • “poka-yokes” – Japanese for “avoid mistakes” • Not possible to do things the wrong way • Indented trays for surgeons • ATMs beep so you don’t forget your card • Pagers at restaurants for when table ready • Airplane bathroom locks turn on lights • Height bars at amusement parks

14. 3 Approaches • Production Line • Self-Service • Personal attention • Degrees of personalization, • Connection to customer • Efficiency

16. Waiting Lines Operations Management Dr. Ron Tibben-Lembke

17. People Hate Lines • Nobody likes waiting in line • Entertain them, keep them occupied • Let them be productive: fill out deposit slips, etc. (Wells Fargo) • People hate cutters / budgers • Like to see that it is moving, see people being waited on • Tell them how long the wait will be (Space Mountain)

18. Retail Lines Magazines • Things you don’t need in easy reach • Candy • Seasonal, promotional items • People hate waiting in line, get bored easily, reach for magazine or book to look at while in line

19. Disney FastPass • Wait without standing around • Come back to ride at assigned time • Only hold one pass at a time • Ride other rides • Buy souvenirs • Do more rides per day

20. Fastpasses

21. In-Line Entertainment • Set up the story • Get more buy-in to ride • Plus, keep from boredom

22. Slow me down before going again • Create buzz, harvest email addresses

23. Make your own fun

24. Dumbo Ride

26. Queues • In England, they don’t ‘wait in line,’ they ‘wait on queue.’ • So the study of lines is called queueing theory. • [It’s also the only English word I know with 5 vowels in a row.]

27. Cost-Effectiveness • How much money do we lose from people waiting in line for the copy machine? • Would that justify a new machine?

28. We are the problem • Customers arrive randomly. • Time between arrivals is called the “interarrival time” • Interarrival times have memoryless property: • On average, interarrival time is 60 sec. • the last person came in 30 sec. ago, expected time until next person: 60 sec. • 5 minutes since last person: still 60 sec. • Variability in flow means excess capacity is needed

29. Memoryless Property • Interarrival time = time between arrivals • Memoryless property means it doesn’t matter how long you’ve been waiting. • If average wait is 5 min, and you’ve been there 10 min, expected time until bus comes = 5 min • Exponential Distribution • Probability time is t =

30. Poisson Distribution • Assumes interarrival times are exponential • Tells the probability of a given number of arrivals during some time period T.

31. Ce n'est pas les petits poissons. Les poissons Les poissons How I love les poissons Love to chop And to serve little fish First I cut off their heads Then I pull out the bones Ah mais oui Ca c'est toujours delish Les poissons Les poissons Hee hee hee Hah hah hah With the cleaver I hack them in two I pull out what's inside And I serve it up fried God, I love little fishes Don't you?

32. Simeon Denis Poisson • "Researches on the probability of criminal and civil verdicts" 1837  • looked at the form of the binomial distribution when the number of trials was large.  • He derived the cumulative Poisson distribution as the limiting case of the binomial when the chance of success tend to zero.

33. Capacity greater than Average

34. Factors to Consider • Arrival patterns, arrival rate • Size of arrival units – 1,2,4 at a time? • Degree of patience • Length line grows to • Number of lines – 1 is best • Does anyone get priority?

35. Service Time Distribution • Deterministic – each person always takes 5 minutes • Random – low variability, most people take similar amounts of time • Random – high variability, large difference between slow & fast people