The human brain connectedness par excellence. Connectivity

Transcription

1 10/26/2015 Connectivity business challenge and key to success Connectivity business challenge and key to success Dr. Stefan Asenkerschbaumer Deputy chairman of the board of management, Robert Bosch GmbH Berlin, October 28, The human brain connectedness par excellence Connectivity 1) 2) Alongside the cosmos, the human brain presents the most complex opportunities for connectedness. Source: John Van Horn (2012), Mapping Morphometry and ness of the Human Brain. 2 1) Brain matter activity: high medium ring: the region of the brain affected low 2) Outermost 1

2 Logistics connects the world world trade as an indicator Since 1950, global trade has grown twice as fast as global gross domestic product. By 2030, global trade will nearly quadruple. Source: WHO (2013); HSBC Study (2013), Global Connections Report. 3 Deficits in transportation logistics World: 40% of seaborne containers transport air Transport of air alone costs shipping and logistics companies 30 bn USD p.a % of inner-city driving is the result of looking for a parking space 266 bn USD is the annual cost of traffic congestion in the 30 largest megacities alone Source: Logistik heute Magazin No. 4/2015; Destatis (2011); Roland Berger (2013), Mobility 2025; APCOA Parking Study (2013). 4 2

3 Further obstacles to efficient logistics lack of transparency delayed, incomplete part deliveries delayed information machine / production downtimes hierarchical control tooling problems incompatible standards changed requirements part-system improvements quality issues planning dilemmas Solution? 5 Demands made of logistics effect of connectivity Right goods Right quantity No change Target Right quality Right place Logistics Technologies Processes Right time Right customer Right cost Significant changes Structure Partners Connectivity creates new conditions for further development of logistics. 6 Source: as defined by Edward Grosvenor Plowman. 3

4 Connectivity exponential development Moore s Law 1) Sensors Intelligent devices Artificial intelligence 21 Nielsen s Law 2) Technical preconditions Ubiquitous communication Technical applications (bn) objects Vision of logistics: decentralized self-organization in real time. 7 1) Moore s Law: Processing power for computers will double roughly every 18 months. 2) Nielsen s Law: Network connection speeds double roughly every 21 months. supply chain Example: automotive industry Tier 1 supplier Cross-company value-added networks Tier 2 supplier manufacturing Tier 1 supplier IT platform transportation OEM New business models Customer Mobility services Flow of information Flow of materials Flow of services Based on Roland Berger (2015): Digital Transformation of Industry. 8 4

5 Vision of logistics: connectivity as driver Logistics connects the world Inefficiencies supply chain Examples of use at Bosch transportation manufacturing Cross-company value-added networks New business models Challenges Competencies Collaboration Broadband networks Data protection and security People Small and medium-sized enterprises 9 Example: connected transportation Start :00:51 Movement End :59:51 Temperature Shock Humidity Movement Humidity Light Shock count Shock value Temperature Light Sensor technology to localize Sensor technology to record physical data Real-time update of virtual map 10 5

6 10/26/2015 Example: connected manufacturing Individual objects Materials, logistics, and manufacturing processes Manufacturing network transparent, flexible, and dynamic globally integrated Digital identity identifiable and traceable 11 Example: SupplyOn cross-company value-added networks Automotive Aerospace Plants supplied Suppliers in crisis region Railway and transport Mechanical engineering Electronics together with 12,000 other companies 12 6

7 Example: new business models Other services Remote diagnosis Maintenance management Eco.Logic Motion 13 Vision of logistics: connectivity as driver Logistics connects the world Inefficiencies supply chain Examples of use at Bosch transportation manufacturing Cross-company value-added networks New business models Challenges Competencies Collaboration Broadband networks Data protection and security People Small and medium-sized enterprises 14 7

8 Challenges Develop key competencies Technological expertise Ability to develop business models Guarantee data protection and security Clear and reliable framework Single EU digital market with shared standards Expand cross-industry collaboration Industry-wide clusters Cross-company alliances / ecosystems Prepare people for change Education and training People as shapers, users, and decision makers Expand broadband networks Increase transmission speed Net neutrality Support small and medium-sized enterprises Involve small and medium-sized enterprises 1) (2014 share: 59% of value added and 57% of workforce) 2) 15 1) EU Commission s definition of SME: maximum annual sales of EUR 50m, workforce not exceeding ) Source: IfM (Institut für Mittelstandforschung) Bonn (2014). Connectity: Collaborate with SMEs Digital technologies already being used for 1) New forms of production 27% 69% SME value chains 33% 81% SME New business models 19% 63% SME Other potential efficiency gains 17% 45% SME Digital innovators SMEs (small and medium-sized enterprises) 1) Source: Commerzbank (2015), Mittelstand setzt auf Effizienzsteigerung durch Digitalisierung. Involve small and medium-sized enterprises 16 8

9 The connected world of the future and also as a creator of connectivity cities industry energy buildings mobility Logistics as part of connectivity Connectivity business challenge and key to success Thank you. 18 9