OBSERVATIONAL RESEARCH — MCDONALD’S SELF-ORDER KIOSK

yammie ng
9 min readJul 8, 2021
Photo source: brandchanel.com

More and more quick-service restaurant uses self-order kiosk. This interactive order system aims to improve restaurant operation by allocating workforce and minimum human error without affecting customer experience. The high light of this technology is to make the ordering process efficient.

Has anyone noticed that when a long queue at the cashier counter, only a few people use the self-order kiosk at McDonald’s? What is the problem leading to this phenomenon? Is it because the order process not user-friendly enough? This study is going to investigate the issue by analyzing the research data.

Fig 1: Usage of a typical cashier & self-order kiosks

RESEARCH & ANALYSIS APPROACH

FAST and CONVENIENCE ordering experiences are primary expectations and perceptions of a fast-food restaurant from the customer’s perspective. Hence, evaluating the kiosk’s performance by ordering time is the best way to assess whether the kiosk can achieve customer’s expectations or not. This research will conduct in 3 parts as below approach:

Fig 2: Approach for analysis

RESEARCH & ANALYSIS PROCESS

Part 1a: Research date - 28 June 2021 (Monday)

Venue: McDonald’s, Lockhart Rd, Wan Chai,

Time: 13:00 to 13:30 (peak hour)

Total seven McDonald’s located at Wan Chai. This district mixed with commercial & residential. Various clusters from nearly commercial buildings, schools, residential will have lunch over there. Like the situation described, few customers used three self-order kiosks, but there is a long queue at one open cashier.

During the first 15 mins observation, the average order time from the cashier is around one min, even shorter. Those customers not only the elderly but also included age group from 20 to 45.

In the next 15 mins, the observation goes to the self-order kiosk. The range of order time from 1 min to 4 mins. Those customers age is around 15 to 40. Also, malfunction found on one kiosk at the last 10 mins observation.

Fig 3: Lockhard Rd McDonald’s- Customer using cashier & kiosks (age group 20 to 45)

From the first observation research, most customers order food from the cashier as their priority, even the young cluster supposed to engage in high technology. This reflects that the age group and technical knowledge are not the significant factors affecting the kiosks usage. Moreover, the order time of the cashier is faster than the kiosk. In consequently, “Time” is the key issue obviously.

The following research will examine the slow ordering process problem of the kiosk.

The “customize selection” menu is the characteristic of McDonald’s kiosk. To define “slow” & “fast”, the first step must figure out the standard order time of each kiosk.

Part 1b: Research date - 29 June 2021 (Tuesday)

Venue A: High traffic location — McDonald’s, IFC Central

Time: 13:00 to 13:30 (peak hour)

IFC branch is one of the branches from three McDonald’s at Central. People who work in Central’s office building is the majority customer. There is a total of three self-order kiosks and one open cashier counter. Customers occupied all cashier and self-order kiosks.

Fig 4: IFC McDonald’s-Self-order kiosks & cashier occupied by customers
Fig 5: IFC McDonald’s- Total 28 customers using Self-order kiosks. Age group 15 to 45

Venue B: Normal traffic location - McDonald’s, Kennedy town.

Time: 20:00 to 20:30

Kennedy Town is a residential area. There is only one branch with a total of 4 kiosks and two cashiers in this district. Customers involve different clusters, workers, families, students, middle classes, foreigners, and the elderly. No queue at the open cashier counter and self-order kiosks.

Fig 6: Kennedy Town McDonald’s: No queue for all kiosks & cashier
Fig 7: Kennedy McDonald’s: Total 2 customers using kiosks. Age group 20 to 65

Below table shows the order time of the self-order kiosk at two locations:

Fig 8: Table shows the order time of kiosk of 2 locations

After eliminating the shortest & longest time and averaging the data by 2 clusters and locations. The above table told that the average time of each order is around 2.14 mins. It can be assumed as the standard order time of the kiosk.

Order time from the kiosk is more than double of the cashier if 2.14 mins is the standard. So, narrow down the difference will encourage the customer to use the kiosk. Part 2 research will observe the customer order behaviour to analyse the problem.

Part 2: Research date - 30 June 2021 (Wednesday)

Venue: Kennedy Town McDonald’s

Time: 19:15 to 20:00

To analysis the customer behaviours deeply, the researcher concentrates on observing two kiosks customers only.

Fig: 9 Observes customers behaviours from Affinity Mapping

During the time slot, a total of 17 customers used these kiosks. There are five customers (green colour group) whose order times are less than 2 mins. They selected determinedly without going through the whole menu in the entire process. Apparently, they decided on the item before and familiar with the menu, even the position of each item in the menu.

Some customers spent a lot of time go thru the menu and thinking about what they want. Their ordering time is longer than 2 mins (red colour group). For example, three ladies keep rolling on the main menu on the side. They repeat this action for more than 1 min. Seem they were looking for something from the main menu bar.

Fig 10: Common behaviours of customers with long order time

Base on this observation, the main menu might be the critical factor to affect the order time. Part 3 research to analyse the problem on the menu bar.

Part 3: Self-experience date: 1 July 2021 (Thursday)

Venue: Kennedy Town McDonald’s.

Order Time: 19:30

Result: Total 11 steps in 2.5 mins to order 1 Chocolate sundae

Fig 11: Ordering process of Chocolate sundae from the kiosk

Same as other customers, the researcher spent much time searching the main menu bar. There are 14 icons in the main menu, but all squeeze on one side. To maintain the icon size, McDonald’s designs the menu as a rolling bar. All icons overlap with no order. The customer can only read the whole icon until rolling to the top. The researcher did not see a “DESSERT” icon and goes to the “ALA-CARTE/MEAL” icon to look for the sundae. This process longer the order time.

Fig 12 Problem found on the main menu bar

POSSIBLE SOLUTION AFTER PROBLEM DEFINED

Given the problems mentioned above, reduce the rolling bar icon may beneficial for time-saving. After study the classification, the menu directory to be rearranged by design action grid (see fig.13):

Fig 13: Design Action grid to simplify the menu bar

• Put similar icons together: Put “MEAL”, “HAPPY MEAL”, “EXPRESS COMBO FOR 2” & “AFTERNOON COMBO” under a new Icon “MEAL & COMBO”.

Create a new by Cross over different icons: Group “DINNER (OR LUNCH) PROMOTION” “NEW/PROMOTION “and “SIGNATURE COLLECTION” under a new icon “SPECIAL PROMOTION”.

Divide icon: Separate the “ALA-CRATE/MEAL” icon to “ALA-CRATE” & “MEAL”. Put all single order items like “OTHERS” under “ALA-CRATE”. “HAPPY MEAL” & “EXPRESS COMBO FOR 2” move under the “MEAL” icon.

  • Reduce icon: Total 14 icons reduce to 5 icons from the main menu bar as below directory.
Fig 14: New menu directory to reduce the icon number

IMPACT ON BOTH ORDERING TIME & TURNOVER BY THE INNOVATION

Assume the original time to go-thru the menu bar is 30 seconds. Cut down half of the menu icon can save 15 seconds. The standard order time will reduce to 1.54 mins from 2.14 mins (based on Part 1b research findings) which is 11% less than the standard time. In terms of turnover, if the average consumption of each order is HKD 45. The total turnover of each kiosk within 30 mins will increase around 35% (See fig. 15). Certainly, this is just an ideal hypothesis with no influence from other factors (like malfunction of the machine or restaurant traffic flow). Testing must proceed for further study of the impact.

Fig 15: Hypothesis of 1 kiosk turnover if reducing the icon number

INTRINSIC FORCE OF DESIGN — INCREMENTAL INNOVATION

This innovation slightly variations on the existing menu and makes the kiosk more user-friendly without changing the core function. The ordering process will become more efficient by this improvement. According to the innovation matrix diagram below, it can interpret as “Incremental innovation”(Kylliäinen, 2019).

Fig: 16 Innovation matrix from- The Ultimate Guide with Definitions and Examples (Kylliäinen, 2019)

FINDING

Since the self-order kiosk rolled out in the US & Hong Kong in 2015 and 2018, respectively, there are 14,000 locations installed self-service kiosks up to 2020. McDonald’s CEO, Mr Steve Easterbrook, mentioned that the self-order kiosk is an excellent selling model to deliver customized food experiences for customers. Customers consumed more by the “customize selection” menu from the self-kiosk. This is a curial reason why the sales boost after the kiosk installed (Easterbrook, 2018).
Nevertheless, after the study, the “customize selection” menu complicates the order process. Customers not only spend more money but also spend more time. This against the primary concept of fast-food restaurants, “FAST” & “CONVENIENCE”. This contradiction lead customer hesitates to use the kiosk. The micro problem will not reflect in the company turnover figure. It can only find out through deep research, data analysis and observation of customer behaviours. Hence, design research plays an essential role in any design innovation process.

In terms of the research process, an explicit aim must be set up before conduct research. For instance, the researcher spent a lot of time thinking about how to define McDonald’s self-order kiosk order process is fast or slow. Every restaurant has a different menu. Thus, comparing the order time from other restaurants’ kiosks is not convincing. Finally, the researcher decides to figure out the standard order time by average the order time of 2 locations and define the “slow” & “fast” by leverage this data. This reflects if a clear purpose can drive the research approach. Otherwise, all data will become rubbish after a long research process.

Bibliography

Easterbrook, M. S., 2018. McDonald’s CEO: Offering customers new ordering options [Interview] (4 June 2018).

Kylliäinen, J., 2019. Types of Innovation — The Ultimate Guide with Definitions and Examples. [Online]
Available at: https://www.viima.com/blog/types-of-innovation
[Accessed 7 July 2021].

Images & illustrations

Fig.1 Ng.Y. (2021). Usage of a typical cashier & self-order kiosks. [Photograph] the author.

Fig.2 Ng.Y. (2021). Approach for analysis. [diagram] the author.

Fig.3 Ng.Y. (2021). Lockhart Rd McDonald’s: Customer using cashier & kiosks. [Photography] the author.

Fig.4 Ng.Y. (2021). IFC McDonald’s: Self-order kiosks & cashiers occupied by customers. [Photography] the author.

Fig.5 Ng.Y. (2021). IFC McDonald’s: Total 28 customers using Self-order kiosks. [Photography] the author.

Fig.6 Ng.Y. (2021). Kennedy Town McDonald’s: No queue for all kiosks & cashiers. [Photography] the author.

Fig.7 Ng.Y. (2021). Kennedy McDonald’s: Total 2 customers using kiosks. [Photography] the author.

Fig.8 Ng.Y. (2021). Table shows the order time of kiosks of 2 locations. [Table] the author.

Fig.9 Ng.Y. (2021). Observes customers behaviours from Affinity Mapping. [Photography & diagram] the author.

Fig.10 Ng.Y. (2021). Common behaviours of customers with long order time. [Photography] the author.

Fig.11 Ng.Y. (2021). The ordering process of Chocolate sundae from the kiosk. [Photography] the author.

Fig.12 Ng.Y. (2021). Problem found on the main menu bar. [Photography] the author.

Fig.13 Ng.Y. (2021). Design Action grid to simplify the menu bar. [Diagram] the author.

Fig.14 Ng.Y. (2021). New menu directory to reduce the icon number. [Diagram] the author.

Fig.15 Ng.Y. (2021). The hypothesis of 1 kiosk turnover if reduce the icon number. [Table] the author.

Fig.16 Kylliäinen, J. (2019). Innovation matrix from- The Ultimate Guide with Definitions and Examples. [Diagram] At: https://www.viima.com/blog/types-of-innovation. (Accessed 7 July 2021)

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yammie ng

Student of UCA — MA Design, Innovation and Brand Management