Effects of dialogue design on automatic teller machine ...

HEHA VIOL. R & 1:-.JFOR\L\ TIO" TECIIVJLOGY,

2000,

VOL.

19,

r\0.

6, 441-449

Effects of dialogue design on automatic teller machine (ATM) usability: transaction times and card loss CLAUS M. ZIMMERMANNt and ROBERT S. BRIDGERt t Absolute Systems. PO Box 652179. Benmore. 20 I 0. South Africa: e-mail: czimmer!a absolutesys.com

tinstitute of Naval Medicine. Crescent Rd. Alverstoke P012 2DL. UK; e-mail: barbara.parodi(a tesco.net

Abstract. Unobtrusive observation of automatic teller machine (A TM) use was carried out to compare the efficiency and error profiles of two A TM interfaces in current use. Transaction times for the same transaction differed by 39%. Frequency of forgetting cards in the ATM differed by 96100%. The differences were attributed to the sequencing of sub tasks with respect to the goal state. The cost of a lack of ergonomics in the less efficient interface was estimated co~servatively to be US$1.7 million due to task sequencing, and between US$2 million and USS4.5 million from forgetting cards in the ATM.

1. Introduction

A TM design issues have been addressed from a number of perspectives including age (Adams and Thieben 1991, Mead et a/. 1996. Rogers et a/. 1997. Rogers and Fisk 1997). usability by the blind (Mankze era/. 1998) control modality including voice (Hone eta!. 1998). psychological attitudes to innovativeness and computers (Burgoyne er a/. 1992. Pepermans et a/. 1996 ). and attributes of A TM 's users in a marketing context (El-Haddad and Almahmeed 1992. Rugimbana and Iversen 1994). This paper was concerned with the usability of the current generation of ATM's and took the form of a comparative field investigation. Many banks use a similar technological platform for offering electronic services and competition between them is on the basis of the products they offer via this platform. However. it was observed that there were two distinctly different A TM interfaces in current use in the South African retail finance sector. This made possible a natural experiment in which the interfaces could be compared using the ergonomic criteria of efficiency (transaction time) and error. ISS"

111~4-YcYX

Figure I presents task analyses for the two interfaces. restricted to the task of withdrawing cash. El Haddad and Almahmeed ( 1992) report that 95.7% of transactions are ·fast cash withdrawal'. Other studies where users have been asked about frequency of transactions also indicate a predominance of withdrawals (Rugimbana and Iversen 1994). Rogers et a/. ( 1996) hypothesized that this could be because of lack of training, ignorance of other features or other usability aspects (unspecified). A fundamental difference between the two interfaces studied here is that dialogue I displays all functions which can be used, on entrance to the main menu which includes an exit (no more transactions) option. To get the card back. the user must command the machine to return the card by pressing 'no more transactions'. Dialogue II focuses on withdrawals on entrance and places all other functions in a separate menu, totally excluding the exit option. Exit occurs automatically once a single withdrawal is completed, with the user's card being automatically dispensed on completion of the task. A TM C provided the cash before the card. A TM B and A TM D provided the card before the cash. The principle of this dialogue forces the user to receive the cash and card automatically at the end of the withdrawal regardless of the order of items received. It was hypothesized that because dialogue I provides many functions on first entrance to the main menu and more decision steps to complete a withdrawal it would be slower than dialogue II that focused on cash withdrawal on first entrance to the main menu, and requires fewer decisions to complete the transaction. Rogers et a/. ( 1997) mention that users of all ages complain about having to wait in line to use the ATM.

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C. M. Zimmermann and R. S. Bridger

442

D~logue I (ATt>cM A) 3 Show Ma1n Menu

2 10 User

...

4. Choose Account (Accounts displayed)

2.1 Enter PIN

6. Dispense Cash & slip if , User Requests slip

5. Choose Amount

7. Show Ma1n Menu

8. End Transaction

8.1 .-

3.1 Fast Cash ,..

4.1 Display other Accounts

,.. Dispense Card

5.1 Display 5 fixed Amount ,.. options. and 1 opt1on to insert own amount

,.. 3.2 Withdrawal

All other Transactions Displayed: 3 3 Decrease Da1ly Limit 3 4 Deposit 3.5 Change P1n 3.6 Balance I Statement 3 7 Transfer 3 8 No More Transact1ons

.... 2 10 User

...

2.1 Enter PIN

3. Show Mam Menu

,..

•

,..

Figure 1.

Dialogue II (ATM B, C, D)

....

....

4. Amount

5. Confirm

chosen

Amount

3.1 Cash Amount

6. Accounts Displayed

8. Card Dispensed

10. End Transaction

8.1 .,.. Card Taken

3 2 Other/ Own Amount

3.3 Other Transactions

Withdrawal Tasks for interface I & I I.

They suggest that A TM designers should focus on maximizing turnaround time at ATMs and. within the A TM system. improving efficiency so as to minimize waiting time. Additionally it was hypothesized that the incidence of forgetting of cards would be higher using dialogue I because the secondary task of removing the card takes place after the goal state (receiving the cash) has been reached. The likelihood of leaving the cash behind in an A TM with dialogue II is less. as this is the transaction ·s goal. Hatta and Liyama (1991) provide general ergonomic criteria for an ATM. They concluded that design problems were due to a lack of compatibility between the dialogue and the user's conception of the task. Providing the card first is an example of a forcing function (forcing the user to take the card at the end of the transaction) which Preece (1994) and Norman ( 1988: 138) cite as being an important principle in good interface design. This is what Norman ( 1988) and Reason ( 1990) would term "designing for error'. Situational factors tend to predicate the loss of attention in a task such as A TM cash withdrawaL though other

situational factors can result in this error being consciously realized through environmental cues. selfcorrection. or if another person points out the error. People are prone to omit small details in their activities. especially when the task is an automatic one such as withdrawing cash from an ATM. Analogous to this would be locking ones keys inside a car. The majority of literature on A TM usability is based on self-reported user behaviour (Hatta and Liyama 1991, El Haddad and Almahmeed 1992. Burford and Baber 1993, Rugimbana and Iversen 1994. Mead et a!. 1996. Pepermans et a!. 1996. Rogers et a!. 1996. 1997. Rogers and Fisk 1997). These are useful data, however they do not reflect the specific transaction behaviour of users when they approach an A TM at a moment in time-with the exception of Burford and Baber (1993) who used a diary method to record transactions. In the present study A TM users were unobtrusively observed and subsequently interviewed at the point of A TM use to gather data to test the hypothesis that A TM performance differences could be attributed to dialogue design differences. Additionally. an attempt

Effects of dialogue design on ATM usability

was made to estimate the magnitude of any performance differences and estimate the associated costs to give an indication of the potential benefits of ergonomic input in the design of subsequent generations of A TM dialogues. As has been pointed out by Stanton ( 1998), despite the \Vealth of design methods and principles for humanmachine interaction. there is a lack of data to validate these ideas.

2. Method ATMs from South Africa's major retail banks were used.

2.1. Subjects

Subjects were members of the public. Sampling was done at peak hours, lunchtime and weekends in busy shopping centres. The investigator observed 300 members of the public using A TMs.

2.2. Procedure

The independent variables were: (i) machine type: IBM/Diebold A TM with colour display. NCR A TM with green monochrome and the newer colour displays; (ii) two distinctly different software interfaces (dialogue I used by Bank A. dialogue II used by Banks B. C and D). The subtle differences on the interfaces used by Bank B. C and D were cosmetic. as they all followed the same principal of providing a discrete withdrawal task (i.e. the user received the card, cash, and information at the end of the withdrawal). The dependent variables were: (i) frequency of card losses (forgetting cards); (ii) task specific transaction times defined as only the interaction between the user and the machine. This measure is used to estimate dialogue efficiency. Task specific cycle time on 'present transactions'. losses of cards and biographical data were manually recorded by the first author using a stopwatch. Timing commenced when the user inserted the cardthe first action required in order to use the machineand stopped when the last observable action occurred (e.g. when the machine ejected the card. slip or money last depending on the task sequence). After a subject finished using the machine. he/she was approached by the experimenter. Questions requiring the individual's response were read out. in English, and the responses marked accordingly, in a structured interview (with a response rate of about 80%).

443

Responses not understood were paraphrased until consensus on what was meant was obtained.

2.3. Data obtained I. Card loss. If lost whether stolen. lost, forgotten, retained or damaged by the machine. how often and whether near forgetting (leaving without the card. and then returning to collect the card) had also occurred. ., Consequences of the loss. 3. Details on card losses due to forgetting. including when. where and how lost and the circumstances behind the loss. 4. Subjective comments on usability and security of ATMs. 5. Transactions which the user reported to have carried out over the previous week. 6. Transactions used at the A TM immediately prior to being questioned. 7. Time taken per transaction or group of transactions on a single card insertion. 8. Personal data: • age; • type of account held; • overall period for which an A TM card has been owned; • frequency of use of A TM (habitual use); • bank(s) used.

3. Results Four interfaces were studied. However. three of the machines are essentially the same in their dialogue design, and so the data from these are pooled. as it is the effects of dialogue design which are being investigated.

3.1. Age groups

The following age categorization was used as it reflects the banks' marketing strategy as reflected in the different account types offered and costs charged to customers according to age. Ages I 0 ~ 18 was used as the first category, because this is the age at which most youth accounts can be opened. These clients do not pay service charges at their own banks. Those proceeding with higher education finish their schooling at 18. Ages 19 ~ 24 are the ages where those who would be studying at a tertiary institution would be studying. and those with student accounts are generally exempt from service charges. The 25 ~49 age group is the age group of those

... C. M. Zimmermann and R. S. Bridger

444

who would be of working age. Ages 50-64 could be classified as those nearing the end of their careers and retirement age. Ages 65 and upv.:ards \vould be classified as senior citizens. As there were few respondents in the 10-18 category. and >65 category. these categories were collapsed. Some respondents were interviewed only regarding losses. others were timed and not interviewed on losses of cards. The same categorization, biographical data and method were used for the users, so that age data can be combined. The Chi squared test for independence between age and bank used gave a non significant result (Chi square = 0.46 at p(0.05) df = 2). Table I shows the age spread amongst users. The Chi squared test for independence bet\veen age and place where the interview was undertaken proved to be insignificant (Chi square= 8.72, df= 10. p(0.05) This means that there is no evidence that the respondents' age composition and the place they were interviewed have an influence on the type of A TM used. Users answering the question regarding length of holding an A TM card possessed one for an average of 7 years (S.D. 5 years). Table 2 below shows the self reported periods of holding A TM cards. A one-way ANOV A test between users at a particular A TM proved insignificant (F = 0.406. dfbetween = 2. dfwithin = 170 p(0.05)). Thus there is no evidence to the contrary that users of different banks have held A TM cards for different periods of time. and thus on average the users have had the same exposure to A TMs.

speculative analysis was carried out to estimate the costs attributable to dialogue design. its consequences (forgotten cards and differences in transaction efficiency). and the possible savings (Appendix).

3. 3. Transact ion times

Table 3 shows frequency of transactions at A TMs. For the Chi square test between the different ATMs and transactions, fast cash as a separate option exists only for A TM A, and is essentially a withdrawal option which excludes the choice of account to be used for the withdrawal. and thus fast cash is combined with withdrawal. Balances and mini statements provide similar information, and are thus also combined together. There is a no significant difference between A TM type and transaction frequency (Chi square= 8.48, df= 12, p(0.05). Most people only make withdrawals at ATMs. At A TM A there was a relatively large proportion of withdrawals and balances made in the same transaction. It seems that these people require an account balance during their transaction- possibly to determine whether it is possible to make a withdrawal. Because withdrawals are made by the majority of users. they will be used to illustrate the effects of the different interfaces. If cash withdrawal is the commonest task, then the way the withdrawal dialogue is designed will have the greatest impact on A TM efficiency and usability.

3.2. Data analysis 3.4. Productivity of different user interfaces The data were analysed with respect to the hypothesis that differences in dialogue design influence transaction time and the incidence of card loss. In addition. a

Table I.

Banks and the age-group breakdown of the respective bank·s A TM users.

Age

>24

25 .. 49

>50

Total

Bank A Other Banks

43 69

60 110

5 II

lOR 192

Referring to figure 2. it can be seen that the fastest machine is A TM B with the mean withdrawal time being 34 seconds. It is interesting to see that the next fastest machine is ATM A's fast cash function at 35 seconds provides no account choice. and only allows a single

Table 3. Showing the frequency of transactions undertaken by users (brackets in other transactions show the number of columns combined for this category. Transaction

Table 2.

Means S.D. N

Self reported period for which an ATM card has been used by users (years). Bank A

Bank D

Bank C

7.35 5.22 53

7.57 4.72 63

8.18 5.28 57

Withdraw! Fast cash Balance on accounts Mini statements Deposits Other transactions Withdrawal and balance Total

ATM A

Other ATM's

27 9 6 5 I 4 (4) 7 59

65 0 6 0 3 9 (3) 4 90

Effects of dialogue design on ATM usability

445

Withdrawal Times 80 73 70 :

60

! 57

so

1

Ti

48 45

me (s) 40

-+-Means

43 40

/40 35

Maxdev -1:r:- M1n dev

30

20

10 '

0 ' ATM D DIALOGUE II

Figure 2.

ATM C DIALOGUE II

ATM B DIALOGUE II

Fastcash ATM A DIALOGUE I

ATM A DIALOGUE I

Withdrawal times at A TMs (in seconds).

withdrawal. The fast cash function was only used by 15% of the 60% of A TM A clients who make withdrawals (table 3). ATM B's withdrawal function is used by 80% of ATM B's clients. The next fastest machine is A TM D at a mean of 38 seconds. followed by ATM C at a mean of 41 seconds. Fast cash is not included in the statistical calculations as it is not the main withdrawal module at A TM A. Due to the larger transaction time variance in A TM A, a non-parametric alternative to ANOV A was used. The Kruskal-Wallis one-way ANOV A test showed a significant difference between A TM and time taken to complete a transaction (Chi square = 43.30 df = 3. p < 0.05). Measuring the degree of association using eta squared ( 11 2 ). a value of 0.48 is obtained. This means that 48% of the variance can be explained by dialogue type. Differences in the efficiency of withdrawals can be illustrated by regarding the fastest machine as ·1 00% efficient'. This would mean that ATM B is 100% efficient. fast cash is 98% efficient. A TM D's efficiency is 90%, ATM C's efficiency is 83%. and ATM A is 61%. Thus there is a 39% difference in withdrawal transaction time between ATM B and ATM A largely due to differences in dialogue design. Considering the small number of users using the other functions. they do not present a sufficiently representative sample to draw conclusions. Transactions such as transfers and deposits take a relatively long time. while balance inquiries are relatively short. but not much shorter than a withdrawal. Thus the mean would provide a relatively conservative estimate of all other

transactions. The combined mean times for all other transactions are 68s for A TM B. 55s for A TM D, 79s for A TM C, and 66s for A TM A for all other transactions.

3.5. Lost cards Table 4 shows cards lost. through forgetting, misplacement, theft and retained or damaged cards. A Chi square test between banks and card loss. yielded a significant result (Chi square = 6.17. df = 1. p(0.05)). There is a greater than chance likelihood that dialogue I's losses are higher than with dialogue II. Cards forgotten in the A TM are shown in table 5. The Chi square test shows this result as being statistically significant (Chi square= 12.87. df= I. p25 table l. Four largest banks in South Africa compared. Own bank clients charged Rl.60 x $ exchange rate (0.16) other banks clients charged R3.6 x S exchange rate.

(4) Estimated revenue A TM A withdrawal

(Users per annum (3) x bank A client charge x % bank A users > 25) + 3 other large banks x (users per annum (3) x non-bank A clients charge x 0 'o other bank users)

(5) ATM A fast cash

Estimated revenue

$364.168.57

(6) ATM B withdrawal

Estimated revenue

$2_902,347

(7) Estimate for revenue increase

ATM B withdrawal(A TM A withdrawal+ A TM fast cash)

Table 7.

Bank affiliation and A TM used. ATM A

ATM A Other Banks Total

2902347.9 -(798153.86+ 364168.57)

Other ATMs

47

3

5

73 76

52

Estimated waiting time calculated as 13s Transaction time figure 2

4.343,836.34

]()()X

(4343836 X (!.6 X 0.16) X 90° 1o X 57%)+ 3(4343646 X (3.2 X 0.16) X ( 10%/3))

Description

$1. 784.()35

during times of peak usage where I 00 A TMs out of the 1600 possible A TM's is used, is large enough that it should not be ignored. For this reason. a costing is estimated which it is hoped will spur further research within this area.

A 1.2. Costs a/forgetting cards in the illter{ace table 6. The comparison data are standardized using the number of users for A TM A (table 7) and the service charges used by that bank which should take into consideration that bank's market structure. The estimate is considered conservative because only 100 ATMs are used when there are 1600 belonging to Bank A. The calculation could be argued as hypothetical on one side, in that the period of hypothesized use is only five hours of the available 14 hours. and it is possible that users may not object to the extra time needed at a less efficient machine and thus peak machine time for the less efficient A TM 's could spread to 6 or 7 hours. A difference of 2 056 567 in numbers of users over one year

Replacement costs for forgotten cards could be between S2 million for magnetic-stripe cards and $4.5 million for smart cards. Table 8 shows the calculations used to obtain this figure. Forgetting is a human limitation. which in turn would be deeply linked to the individuals management of cognitive affairs. Through learning. strategies to prevent forgetting. can reduce the possibility of a repeat chance occurrence within the same individual. It would thus be reasonable to consider that the estimate could be reduced by as much as a third. however there is always the chance that an individual who has never forgotten his or her card will succumb to a slip or lapse and forget their card in the machine.

Effects ol dialogue design on A TM usability Table 8. Calculation

Formula

(I) Total users per

No. withdrawing+ no. using fast cash-+- no. making other transactions

annum

(2) No of card

forgetters

Users per annum (I) x % Bank A users x % card forgetters

(3) Card replacement cost (Magnetic stripe cards)

No. of card forgetters (2) x (Admin cost+ Replacement cost)

(4) Card replacement cost (Smart cards)

As for (3)

449

Calculation of costs of forgetting. Actual calculation

Answer

4.343.836 + 2,042. 769 + 3.256,720

9.643.326

9.643,326

X

90%

X

]6%

1.388.639

Description No. of users calculated using method in table 7

Users of bank A-table 7 o card forgetters-table 6

01

1388638 X [(7.75x0.16)

2,069.072

Assume: administrative cost for 20 minutes work by clerk earning S640 per month. 4.3 weeks in a month. 5 davs weekly. 8 hrs daily. . Magnetic stripe card costs: S0.25-S0.50 (Puri 1997)

$4.499.190

Smart card costs S2-S I 0 (Puri 1997)

~0.25]

1388638 X ((7.5 X 0.16) + 2))

References AD\\1S. A. S. and T111EBE'.. K. A. 1991. Automatic teller machines and the older population. Applied Ergonomics. 22, 85-90. B \BER. C. and Sn'. roN, N. A. 1994. Task analysis for error identification. Ergonomic.~. 37, 1923- 1942. Bt Rl ORD. B. C. and B \Br.R. C. 1993. A user-centered evaluation of a simulated adaptive autoteller. in S. A. Roberston (ed.) Contemporary Ergonomics. London. UK: Taylor and Francis Ltd. 117- 122. BtRCiOl'-L C. B .. LH11s. A .. Rot 111. D. A. and WIBLLY P. 1992. Customer reactions to automated teller machines (A TMs): a field study in a UK building society, in S. E. G. Lea. P. Webley. B. M. Young (eds) Nnr directions in economic psychologr: Theorr. experiment, and applications, Worcester. UK: Billing & Sons Ltd. EI-HADD\D. A. B. and AL\1.\H\IEFIJ. M. A .. 1992. ATM banking behaviour in Kuwait: a consumer survey. International Joumal of Bank Marketing. 10, 25-32 . H.o..rr.o... K. and Ln \\t\, Y .. 1991. Ergonomic study of automatic teller machine operability. Intemational Journal of Human Computer Interaction. 3, 295-309. Ho'.E. K. S .. GR ..O..II \\t, R .. M \CiliRr. M. C.. B..o..BrR. C. and Joi!NSO'.. G. I. 1998. Speech technology for automatic teller machines: an investigation of user attitude and performance. Ergonomics, 41, 962-981. M ..o..'