WP 1 NACHOS | Area: Implementation
Key question of the sub-project:
How can we model and learn about the preferences of staff and customers regarding innovation, and take these into account in our planning?
WP 1: Fair, individualised and reliable planning and management
PI: Prof. Dr Marlin Ulmer | Co-PIs: Prof. Dr Sabrina Jeworrek, Prof. Dr Heike Ohlbrecht
PhD student: Caroline Ihloff, M.Sc.
Innovation is transforming work processes, as well as their planning and management. For example, in manufacturing, work steps are partially or completely replaced by machines; in healthcare, diagnoses and treatments are supported by automated systems; and in goods delivery, innovative delivery concepts (e.g. parcel lockers, autonomous vehicles) are used to ensure more efficient delivery. Furthermore, shift schedules, task allocations and fulfilment processes are increasingly determined automatically and, in some areas, adjusted in real time. Both of these factors are changing the way employees (and also customers/patients) work and their working environment. Stressful aspects of the job (heavy lifting, poring over files, searching for a parking space in the city centre, etc.) can be reduced. At the same time, however, these innovations can lead to stress and dissatisfaction, for example because contact with customers is reduced, interaction with automated systems is overwhelming, autonomous decisions are not transparent (or fair), or because real-time changes make it impossible for staff to plan their day reliably. Both the benefits and the burdens are perceived differently by different employees. Some welcome the changes, whilst others are more reserved in their approach and may even seek to circumvent them. Whilst the former leads to more effective and motivated staff, the latter can result in both reduced service quality and dissatisfied staff who, in extreme cases, may leave the company. The same applies to potential customers.
This sub-project investigates how effective planning and management can take into account the individual preferences of staff (and customers). To this end, (a) preferences are modelled and (b) the ways in which planning decisions influence them are examined. Subsequently, (c) quantitative planning procedures will be implemented that integrate both effective fulfilment and individual preferences. The short- and long-term differences and impacts compared with conventional planning procedures will be analysed in extensive computational studies.
The sub-project is being carried out by PhD candidate Caroline Ihloff as part of her doctoral research.