Improving service processes based on visualization of human-behavior and POS data: A case study in a Japanese restaurant Tomohiro Fukuhara1, Ryuhei Tenmoku1, Takashi Okuma1, Ryoko Ueoka2, Masanori Takehara3, and Takeshi Kurata1 1 Center for Service Research, National Institute of Advanced Industrial Science and Technology, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, JAPAN Tel: +81-3-3599-8568, Fax: +81-29-862-6548, E-mail: [email protected] 2 Graduate School of Design, Kyushu University, Fukuoka 3 Graduate School of Engineering, Gifu University, Gifu, JAPAN Abstract A case study of service process improvement based on visualization of human-behavior and POS (point-of- sales) data in a Japanese restaurant is described. We developed a human-behavior sensing and visualization suite for supporting managers and employees in actual service fields to understand and improve their service processes by visualizing both of behavior and POS data. We had an experiment using the suite in the restaurant, and confirmed that managers and employees were able to understand their ordinary processes, and make plans for improving their processes by using the suite. An overview of the suite and experiment results are described. Keywords: Service process improvement, human-behavior sensing, data visualization, POS data analysis, quality- control circle 1 INTRODUCTION (1) observe their ordinary behaviors and sales data, and Today, service industries play an important role in (2) support them to make plans for improving their economy [1]. The weight of service industries are processes, and (3) verify effects of the plan with actual gradually growing in developed countries [2]. As growth of data. We observed changes of behavior and POS data. service industries, new research fields called service This paper consists of following sections. Section 2 science, management and engineering (SSME) and describes related work and requirements for the support service engineering are emerging [2-4]. In these fields, system for improving service processes. Section 3 researches are trying to improve productivity of service describes an overview of the human-behavior sensing industries based on various approaches such as industrial and visualization suite. Section 4 describes an engineering (IE) [5,6], operations research (OR), data experiment of the suite in a Japanese cuisine restaurant. mining (DM) [7], game theory [8], sensors, and so on. Section 5 describes discussion on results. In Section 6, For understanding and improving efficiency of service we describe conclusion and future work. processes, measuring methods of processes are needed. 2 RELATED WORK In the field of IE, various methods have been developed There are several related work on service process for measuring behavior and processes such as time-and- improvement. We describe related work from several motion study [9] and work sampling [10]. Although these disciplines, and we describe requirements for the support techniques enable us to understand both of macroscopic system for improving service processes. and microscopic states of service processes, they have limitations on observing behaviors with respect to the cost 2.1 Industrial engineering approach (time and money) and comprehensiveness of data. In the field of IE, various methodologies and techniques The aim of this study is to support managers and have been developed for measuring employees’ work; employees who are engaged in actual service fields to motion-and-time study [9] and work sampling [10] are understand their current service processes major techniques to observe behavior and processes of comprehensively, and support them to improve their workers. Although these techniques are good way to processes. For this aim, we are developing a human- obtain data from work space such as factories, they have behavior sensing and visualization suite. Our suite limitations on collecting data with respect to following observes behavior of employees contiuously and factors: (1) cost of investigation, (2) comprehensiveness comprehensively at low cost by using wearable sensors of observation, and (3) privacy of customers. [11], and visualizes behavior data by combining POS For the first issue, traditional IE techniques require much (point-of-sales) data. By combining both of behavior and time and money to have an investigation because they POS data, managers and employees can understand are based on observation by human observers. Because efficiency of their processes objectively, and can make budget of each service field is limited, it is difficult to have plans for improving processes effectively. a long term investigation. We had an experiment of the suite in a Japanese cuisine For the second issue, they have limitations on collecting restaurant for measuring efficiency of service processes. data comprehensively. When managers want to evaluate In this restaurant, there is a quality-control circle (QC their service processes, they have to have an circle) which is a voluntary group of employees to improve investigation for several days or weeks. During these their productivity. We collaborated members of the QC periods, it is hard to observe every behaviors of whole circle to understand and improve their processes. We had employees through their work time because the number an experiment for about a month in the restaurant, and of observers are limited. found that the suite assisted managers and employees to The 1st International Conference on Serviceology 1 For the third issue, traditional IE techniques are not suited system called ServLab enables managers and employees to actual service fields where ordinary customers are to design and evaluate new service processes in a buying goods or receiving services. When human virtually constructed service field. Simo et al. also observers observe behavior of employees in actual proposed a test bed called SINCO for designing service service fields, they might hinder natural interactions operations using VR [21]. Hyun et al. also proposed between customers and employees. Furthermore, human service field simulator which uses the omni-direction observers might harm privacy of customers who are not immersive display to visualize a virtualized service field willing to notify what they purchased or received. [22]. These studies are suitable for designing and Although there are studies of observing behavior of evaluating service processes, however, these studies are employees and processes in service fields such as not based on analysis of actual behavior and sales data restaurants [12] and hospitals [13], it takes much time and in service fields. For improving actual service processes, money to observe processes. analysis of service fields from viewpoints of behavior of employees and various business data of the fields is In this paper, we propose a human-behavior sensing and needed. We aim to create a human-behavior sensing and visualization suite that can collect data continuously and visualization suite to improve service processes by using comprehensively at low cost by using wearable sensors. both of behavior and sales data of service fields. Our suite can work in actual service fields without harming privacy of customers because the suite only observes 2.4 Sensor based behavior analysis approach behavior of employees. Customers and employees can For understanding behavior of employees, various behave naturally in service fields. studies that use sensors have been reported. Inoue et al. 2.2 Operations research and data mining proposed an indoor positioning system that uses beacon approaches devices embedded in a building [23]. Sumi et al. proposed a sensor system that can analyze social There are many studies on improvement of productivity of interactions among people [24]. Choudhury and Pentland services from viewpoints of operations research (OR) and proposed a sensor system called sociometer that can data mining (DM). In the context of OR, studies aiming at collect human interaction data [25]. With sociometer, improving revenues are called revenue management [14, human interaction data such as who was accompanied, 15] or yield management [16,17]. how long s/he talked, and how often s/he moved can be Yield management has been developed in airline recorded. Kim et al. uses sociometer to analyze industries since 1970’s because airline companies had shoppers’ behaviors, and found several correlations risks on having flights with vacant seats; some seats can between actions of customers and interests for items [26]. be cancelled and others might not be used because Olguín and Pentland proposed an approach to measure passengers missed the flight (called no-show). For behavior of employees by using the sociometer for recovering this loss, airline companies developed the analyzing and improving productivity of employees in revenue management system that maximizes revenues organizations such as banks and hospitals [27,28]. Ara et by selling seats more than the capacity of a plane [16]. al. proposed an approach to analyze behavior data of For fulfilling seats, the system sells seats at multiple humans by linking with other data called performance prices; for leisure travelers, they want to purchase tickets indicators such as financial profit, amount of at discount rate, and for business persons, they do not communication, employee satisfaction (ES), and care about prices. The point of the system is to decide the customer satisfaction (CS) [29]. They created a feedback number of seats for selling at regular