Service Solutions for Fleet Management

The purpose of the DIMECC S4Fleet program is to research the variety of possibilities these technological breakthroughs enable in service business. The objective is to explore and exploit the possible managerial possibilities and challenges related to applying the available technologies towards a global, distributed customer base. A strong research consortium, including participants from top national universities and leading technological manufacturing firms, can lead the way for Finnish industry renewal. This collaboration and multidisciplinary accomplishments can have a remarkable impact on Finnish firms’ competitive advantage and position in international trade. Yet, as the technology offers an avenue, there is still a long leap towards profitable business and S4Fleet is designed to deliver solutions. The program is structured into three complementary project entities that are designed to cover the most critical areas in this technological renewal. The first project deals with the strategic intelligence in fleet management. The key aim is to clarify the strategic actions that need to be taken to renew the business towards profitable, data based fleet level service and solutions provision. The project builds strong knowledge on fleet management considering the changing time intervals, lengthened contract relationships, the related profitability, and required institutional transformation. The second project is built on understanding the operational requirements and consequences of this shift. To find efficient and dynamic models and tools for the fleet level analyses, companies need ways for predictability and productivity when facing the management challenge with the distributed fleet, not forgetting the customers’ holistic service experience. Finally, the third project is centered to the technology that enables this shift. The purpose is to explore the possibilities that advanced technologies have to offer for service business, based on the availability of customer information for decision-making. The project examines information network modeling; fleet platform building and data enabled maintenance models. These three projects then collaborate and share information, with the biggest contribution stemming from activities at the project interfaces and synergies from complementary work.