Implementing Robo-advisor in a Danish Bank: The role of the middle manager
Implementing Robo-advisor in a Danish Bank: The role of the middle manager A critical perspective
Anne-Christine Rosfeldt Lorentzen, Aarhus University, firstname.lastname@example.org
IntroductionIntelligent machines are continuously being implemented in various types of organizations providing better performance (Davenport & Ronanki, 2018), generating new occupations and making existing jobs evolve (Manyika et al., 2018). The machines are also filling more roles in management (Fuchs, Silverstone, and Thomas 2016). Fuchs et al. (2016) categorize three such roles by their degree of autonomy and proactivity: Assistant, advisor, and actor (table 1). This paper-in-progress focuses on an advisor, which bank managers use when talking to customers.
|Creating scorecards Maintaining reports Monitoring the environment||Answering questions Building scenarios Generating options||Evaluating options Making decisions Budgeting and planning|
ApproachEthnography (see Spradley 1980) proposed itself as a helpful method, because studying people in their everyday activities help the researcher to understand the complexity, intricacy and mundanity of organizational life (see Ybema et al. 2009). Scholars as Whyte, Goffman and Beckman (Chicago School) stated that fieldwork, participant observation, and native interpretations are the essence when investigating the empirical world (Becker, Hughes & Strauss, 1961; Blumer, 1964). The empirical setting of this ethnographic study is a middle-sized Danish bank. A ‘typical instance’ (Cunliffe & Karunanayake, 2013) because banks are one the many types of organizations in which functions are continuously being automated, and an emblematic case (Silverman 2014: 73) in which involvement, dialogue, motivation, continuously educating managers, and the well-being of employees are of high priority, resulting in the organization often being nominated as one of the best places to work in Denmark. Building on Cunliffe’s (2015) recommendations, data collecting methods include observing, informal conversation (see, for example Fenton and Langley 2011) questions at meetings with top management, middle management, and employees. Interviews, participation at events, participation in strategy seminar for the top management, and document access. Furthermore, data consists of posters made by middle managers and employees. Notes were made during the activities or as soon as possible. The ethnographic data consists of approximately 292,5 hours (table 2):
|Participant observation Approximately 211,5 hours||Non-participant observations Approximately 56 hours||Informal conversations As part of the observations:||Workshop (big focus group) Approximately 8 hours||Interviews Approximately 17 hours|
|Meetings with top upper middle management/shadow||5 x 8 hour meetings with all middle managers (35)||E.g.: During coffee breaks from||Workshop with employees representing all departments in||Branch managers: 3 hours (1h40m, 20m, 1h)|
|advisory board: 75 hours Meetings with top management: 25 hours Lunch with different ‘colleagues’: 45 hours Strategy kick off event: 8 hours New years party: 9 hours Meetings and workshops with external consultants and top management/upper middle managers: 21 hours Every day work in the organization: + 38,5||5 x 1 hour morning meetings in branches 1 x 8 hour internal course on communication 1 x 3 Meeting with union people||meetings in the top management, and with the middle management group. During transportation with upper middle management when meeting consultants, and with employees to parties/activities||all 16 branches discussing strategy and in that regard also Robo-advisor.||Union people: 2 hours HR director: 3 hours (6 x 30m) Communications director: 2,5 hours (5 x 30m) Head of business development: 1 hours (2 x 30m) IT Director: 4 hours (2 x 1h + 4 x 30m) IT Implementing consultant: 45 minutes (1x)|
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