Operations Marketing Oct 1, 2012

How Much Is Your Customer’s Time Worth?

If you are in fast food, a sur­pris­ing amount

Based on the research of

Gad Allon

Awi Federgruen

Margaret Pierson

Listening: Interview with Gad Allon on Waiting

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In the fast-food busi­ness, the old saw that time is mon­ey has par­tic­u­lar res­o­nance. An indus­try max­im sug­gests that a sev­en-sec­ond reduc­tion in cus­tomers’ wait­ing time increas­es a chain’s mar­ket share by 1 percent. 

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A study by Gad Allon, an asso­ciate pro­fes­sor of man­age­r­i­al eco­nom­ics and deci­sion sci­ences at the Kel­logg School of Man­age­ment, and two col­leagues has fleshed out that rule of thumb. Not only does their analy­sis con­firm the max­im, it also iden­ti­fies the extra­or­di­nary val­ue that fast-food cus­tomers assign to their time. Each extra sec­ond of wait­ing time at the dri­ve-thru win­dow reduces the amount that cus­tomers are pre­pared to pay for their meals by at least four cents.

This val­i­dates our belief that over­look­ing ser­vice as a com­pet­i­tive instru­ment in the busi­ness mod­el results in dis­tort­ed man­age­r­i­al insights,” explains Allon, who per­formed the study with Awi Fed­er­gru­en, a pro­fes­sor at Colum­bia Uni­ver­si­ty, and Mar­garet Pier­son, an assis­tant pro­fes­sor at Dart­mouth Uni­ver­si­ty. The project orig­i­nat­ed when Allon and Fed­er­gru­en inde­pen­dent­ly read a CNN​.com study on the nation’s best dri­ve-thrus. We con­tact­ed the firm that ran the study, obtained the data, and then start­ed work­ing on the required tools to esti­mate what we want­ed,” Allon recalls.

Burg­ers in Cook Coun­ty
To sim­pli­fy its analy­sis, the team focused on ham­burg­er dri­ve-thrus in Cook Coun­ty, Illi­nois. They chose burg­ers because of the gen­er­al uni­for­mi­ty of ham­burg­er chains’ prod­ucts and Cook Coun­ty because of both the num­ber of out­lets there — more than 200 — and their prox­im­i­ty to the Kel­logg School, which enabled per­son­al inter­views. Those inter­views, com­bined with phone calls, pro­vid­ed price infor­ma­tion for all the outlets.

The researchers also col­lect­ed detailed demo­graph­ic and geo­graph­ic data for the out­lets’ cus­tomers. We dis­tin­guished between com­muters and res­i­dents, two gen­ders and two racial groups, as well as among five age brack­ets, divid­ing the pop­u­la­tion into 40 dif­fer­ent demo­graph­ic groups,” Allon explains. We also cal­cu­lat­ed the dis­tance from the con­sumer to each out­let, using the cen­troid of the tract in which the con­sumer is located.”

But to obtain a com­plete pic­ture of the fac­tors relat­ing wait times to price sen­si­tiv­i­ty, the team also need­ed data on spe­cif­ic sales vol­umes or mar­ket shares. Obtain­ing that infor­ma­tion from cor­po­ra­tions proved impos­si­ble because, as Allon notes, firms are reluc­tant to pro­vide it, con­sid­er­ing it of the high­est strate­gic val­ue.” So he and his col­leagues used game the­o­ry to infer the numbers.

The process involved com­bin­ing two sub-mod­els. A con­sumer choice sub-mod­el focus­es on the util­i­ty val­ue that cus­tomers assign to all pos­si­ble out­comes, such as the type of meal they pur­chase along with the pur­chase price, wait­ing time, and dis­tance once they set out on a fast-food run. The mod­el also includes data on an indi­vid­ual customer’s race, gen­der, age group, and occu­pa­tion. The oth­er sub-mod­el, called vari­able cost, express­es fast-food out­lets’ costs as a func­tion of expect­ed sales vol­ume. Com­bin­ing the two sub-mod­els per­mits us to derive the out­lets’ prof­it func­tions,” the researchers explain in a paper.

One extra fac­tor com­pli­cat­ed the study. While the com­pa­nies that offer fran­chis­es set the stan­dard for wait­ing times, the indi­vid­ual out­lets deter­mine their prices to avoid ille­gal price-fix­ing. The mod­el accounts for that.

A Firm Con­clu­sion
The analy­sis by Allon and his col­leagues result­ed in a firm con­clu­sion. Both the price and wait­ing time para­me­ters have a sig­nif­i­cant impact on the consumer’s deci­sion,” they state in their paper. These results con­firm … that in the fast-food dri­ve-thru indus­try cus­tomers trade off price and wait­ing time. In par­tic­u­lar, to over­come an addi­tion­al sec­ond of wait­ing time, an out­let will need to com­pen­sate an aver­age cus­tomer by as much as $0.05 in a meal whose typ­i­cal price ranges from $2.25 to $6. This cor­re­sponds with an hourly cost rate of approx­i­mate­ly ten times the (pre-tax) aver­age wage of $18/​hour and near­ly 30 times the (pre-tax) min­i­mum wage in Illi­nois in 2005.”

These results con­firm … that in the fast-food dri­ve-thru indus­try cus­tomers trade off price and wait­ing time.” — Gad Allon

Allon and his col­leagues had not expect­ed that cus­tomers would val­ue their wait­ing time so high­ly. The direc­tion­al­i­ty of the result did not sur­prise us, and con­firmed what many peo­ple in the indus­try believe,” Allon says. Yet the extent and the robust­ness of the results were def­i­nite­ly a pos­i­tive surprise.”

Cus­tomers assigned only one-third as much val­ue to the time they spent trav­el­ing to their fast-food out­lets as they did to the wait once there. One pos­si­ble expla­na­tion is that peo­ple pur­chase their fast-food meals on the way home or from home to oth­er activ­i­ties, and thus do not asso­ciate any disu­til­i­ty with the trav­el time,” Allon sug­gests. How­ev­er, the wait­ing time once in line is con­sid­ered pure waste.”

Fast-food fran­chis­es do not lack tools to mit­i­gate the prob­lem. There are sev­er­al strate­gies that can be used,” Allon says, from out­sourc­ing’ the order-tak­ing process to a call cen­ter to employ­ing more peo­ple and using tech­nol­o­gy to speed up the food preparation.”

Sec­ond Help­ings
Allon admits their study rep­re­sents just a begin­ning. Sev­er­al impor­tant exten­sions of our study and under­ly­ing mod­el would be valu­able,” he explains. First, it is not clear whether the wait­ing time expe­ri­ence is best char­ac­ter­ized by the aver­age alone or by oth­er mea­sures, such as the stan­dard devi­a­tion and/​or a per­centile of the wait­ing time dis­tri­b­u­tion. Even if the aver­age wait­ing time is the best proxy, it is con­ceiv­able that the consumer’s util­i­ty lev­el dimin­ish­es in a non­lin­ear way with it. A sim­i­lar non­lin­ear depen­dence on the dis­tance vari­able may be explored as well.”

At the same time, Allon and his col­leagues empha­size that their work has val­ue beyond the fast-food busi­ness. Based on this mar­ket analy­sis, we show that the trend to con­tin­u­ous­ly improve wait­ing times and ser­vice lev­els can be explained on game the­o­ret­i­cal grounds, cre­at­ing a valu­able frame­work for future mar­ket dynam­ics stud­ies in var­i­ous indus­tries,” they state in their paper.

I expect the results to vary quite a bit among indus­tries, yet we now have a bench­mark against which we can com­pare these num­bers,” Allon adds. We have also out­lined one pos­si­ble method to over­come the scarci­ty of sales data.”


Relat­ed read­ing on Kel­logg Insight

Firm Size and Ser­vice Lev­el: When is it advan­ta­geous for a ser­vice-ori­ent­ed firm to dif­fer­en­ti­ate itself along ser­vice qual­i­ty dimensions?

We Will Be Right with You: Man­ag­ing cus­tomers with vague promises

Cut­ting in Line: Flex­i­ble queu­ing sys­tems may improve cus­tomer servic

Featured Faculty

Gad Allon

Member of the Department of Managerial Economics & Decision Sciences from 2005-2016

About the Writer

Peter Gwynne is a freelance writer based in Sandwich, Massachusetts.

About the Research

Allon, Gad, Awi Federgruen, and Margaret Pierson. 2012. “How Much Is a Reduction of Your Customers’ Wait Worth? An Empirical Study of the Fast-Food Drive-Thru Industry Based on Structural Estimation Methods.” Manufacturing and Service Operations Management. 13(4): 489-507.

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