Forderung und Angebote der KÜHNE LOGISTICS UNIVERSITY an eine digitalisierte Welt. Prof. Dr. Thomas Strothotte Präsident, KLU

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1 Forderung und Angebote der KÜHNE LOGISTICS UNIVERSITY an eine digitalisierte Welt Prof. Dr. Thomas Strothotte Präsident, KLU CLUJ-NAPOCA MARCH 2015

2 KÜHNE LOGISTICS UNIVERSITY, HAMBURG BSc Mangement MSc Global Logistics MSc Management Executive MBA Logistics & Leadership English International Student Body Educating the leaders of tomorrow 17 Professors 2 Departments Logistics/SCM Management & Economics Research-oriented Excellent Ranking Results International Faculty 2

3 WHO WE ARE German level of university education taught in English 50% international students Full-time and part-time degree programs Wide range of international partner universities Extensive corporate ties Excellent career support and personal development 3

4 EXCELLENT RANKING-RESULTS Teaching: Top tier among all German management faculties Research: No. 1 in research output per professor among all private Business Schools in Germany, Austria and Switzerland No. 3 in research output per professor of all 100 German management faculties 4

5 GROWING NETWORK OF PARTNERS WORLDWIDE IPADE Mexico City Universidad de los Andes Higher School of Economics (HSE) Moscow / St. Petersburg XLRI S.P. Jain Institute of Management & Research Pyeongtaek Univ. Tongji Univ. Wirtschaftsuniversität WU Wien KU Leuven Technical University of Denmark Ecole de Management Strasbourg IGR-IAE, Université de Rennes 1 MEL, Erasmus University TU Eindhoven Chalmers University, Gothenburg USI, Lugano Koç University Özyegin University Universidad de Montevideo National University of Singapore (NUS) (Examples, overall list contains more than 50 partners worldwide) 5

6 COMPANIES HIRING OUR INTERNS 6

7 OUR RESEARCH AREAS Logistics & SCM Humanitarian logistics Maritime logistics Green logistics Sustainable operations Warehousing Service logistics Reverse logistics Intermodal transportation Transport management Management & Economics Intercultural management Leadership Risk management Pricing & revenue strategy Marketing & innovation management Service management Finance Infrastructure Economics 7

8 MSC FACTS & FIGURES Degree Master of Science (MSc) in Global Logistics / Management Target group Holders of Bachelor degree (BSc) in business, economics, industrial engineering, computer science, mathematics Duration 2 years (4 semesters), full time Class size max. 30 Language English Structure On campus lectures in semester 1, 2 and 4 Integrated internship / study course abroad in semester 3 4-months Master Thesis in semester 4 Start Annually, September 1 Admission requirements Recognized university degree (min. Bachelor) Proficiency in English language (TOEFL, etc.) Credit points 120 ECTS credits Tuition fee Euro per year (total Euro) 8

9 CAREER OFFICE & ALUMNI RELATIONS Anne Rehmet Ina Renz 9

10 OUR FACULTY 10

11 NEW PROFESSORS 2015 Associate Professor of Logistics and Supply Chain Management Asvin Goel Assistant Professor of Managerial Accounting Alexander Himme Associate Professor of Information Systems/ Computer Sciences in Logistics André Ludwig Assistant Professor of Freight Transportation: Modelling and Policy Hanno Friedrich 11

12 PHD-PROGRAM Cumulative theses (3 papers) 4-year program Funded by scholarships Possible fields: Leadership, Operations Research, Supply Chain Management, Supply Chain Strategy 12

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14 KLU AND DIGITALIZATION: SUPPLY CHAIN ANALYTICS SUPPLY CHAIN ANALYTICS LEVERAGES DATA AND STATISTICAL METHODS TO CREATE NEW INSIGHTS AND TO IMPROVE UNDERSTANDING FOR BETTER DECISION MAKING IN ALL ACTIVITIES ACROSS THE SUPPLY CHAIN. Source: KLU research report Supply Chain Analytics Gaining value from data-based decision making

15 RECENT TRENDS TOWARDS ANALYTICS CREATED HUGE EXPECTATIONS WITH RESPECT TO BENEFITS OF USING ADVANCED METHODS AND DATA Recent White Papers and Books on Big Data and Analytics BUT WHAT IS BIG DATA? 15

16 THE AMOUNT OF DATA THAT IS BEING STORED IN VARIOUS MEDIA HAS BEEN GROWING EXPONENTIALLY SINCE THE TURN OF THE CENTURY 1 EB = bytes = bytes = 1000 petabytes = 1 million terabytes = 1 billion gigabytes.

17 IDC PROJECTS THAT THE GENERATION OF STORABLE DATA WILL GROW TO APPROXIMATELY 40,000 EXABYTES BY THE END OF THIS DECADE

18 WHAT IS BIG DATA? 18

19 DATA SOURCES AND TYPES IN SUPPLY CHAIN ANALYTICS Data Sources ERP systems (e.g. SAP, Oracle) Internet (e.g. homepage, other websites) Examples Sales, capacities, inventories, production plans, supplier quotes, Consumer click streams, access statistics, consumer comments, Data archives (e.g. primary and secondary) Location data (e.g. GPS, mobile) Scans (e.g. Barcode, RFID) Weather information, financial status, consumer surveys, competitors promotions, Truck locations, consumer locations, inventory locations, Inventory information, time-stamps, Sensors (e.g. camera, temperature) Social Networks (e.g. Facebook, Google) Quality, yield, process status, Crowd behaviour, product perception via text mining, 19

20 WHY DO WE NEED BIG DATA?

21 Competitive Advantage Ease of Analysis TYPICALLY ANALYTICS IS CLASSIFIED INTO THREE LAYERS THAT EXTEND FAR BEYOND TYPICAL REPORTING Stochastic Optimization Optimization How can we achieve the best outcome including the effects of variability? How can we achieve the best outcome? Prescriptive What to do? Predictive modeling What will happen if? Forecasting Simulation What if these trends continue? What could happen? Predictive What will happen? Alerts What actions are needed? Query/drill down Ad hoc reporting Standard reporting What exactly is the problem? How many, how often, where,? What happened? Descriptive What happened? Source: Adapted from Davenport and Harris 2007, Competing on Analytics

22 ALL STAGES OF THE SUPPLY CHAIN CAN BENEFIT FROM SIGNIFICANTLY ADVANCED ANALYTICS SELECTIO N Product Design Supply Chain Design 1 Sales, Inventory and Operations Planning Supplier risk management and incoming goods projection Staff/asset planning and workload optimization Inventory projection and scenario planning Forecasting accuracy evaluation and optimization 2 Sourcing 3 Manufacturing 4 Warehousing 5Transportation 6 Point-of-Sale 7 Consumer Cost modeling to identify cost drivers Quantification of benefits from spend pooling Automatic analysis of contract compliance Scheduling of energyintensive production Statistical quality control and tolerance optimization Lot sizing and scheduling considering cost and inventories Picking zone/ warehouse space allocation Worker to picking zone allocation based on efficiency Automatic stock relocation in high rack storage areas Truck vs. rail transportation mode selection Real time routing and ramp allocation at warehouses Delivery scheduling in line with consumer patterns Source: KLU research report Supply Chain Analytics Gaining value from data-based decision making Out-of-stock detection and prevention Shelf space optimization Channel/store allocation of goods maximizing service Retail employee scheduling Credit rating to define payment terms offered Return projection to calculate outstanding inventory Product recommendatio ns based on purchase history, Fraud

23 LET S LOOK AT WELL KNOWN SUPPLY CHAIN PROBLEM: HOW TO IDENTIFY STOCK OUTS IN THE SUPERMARKET Reasons Poor inventory management Poor order management Inaccurate forecasting Goods in backroom storage room Items misplaced in store Customer reactions Buys nothing Substitutes products Postpones purchase Buys product somewhere else Financial impact Lost sales Lost customer good will Decline in market share

24 APPROACH TO DETECT OUT-OF-STOCK SITUATIONS: MANUAL 1/4 Manual approach Additional employee checks shelves frequently and refills them if necessary Pro s Easy implementation No infrastructure required Con s High labor costs Random process dependent on employee productivity

25 APPROACH TO DETECT OUT-OF-STOCK SITUATIONS: RFID 2/4 RFID approach RFID chips are attached to the products RFID scanner detects if products are removed or from the shelf or misplaced in the store Pro s Greater control over shelf inventory Constant real time updating Con s Requires additional IT infrastructure and initial investments Expensive RFID tag on every item

26 APPROACH TO DETECT OUT-OF-STOCK SITUATIONS: OPTICAL 3/4 Optical approach Optical camera attached to the shopping cart scans the shelves on customer tour and sends information regarding empty spots to the branch manager Pro s High efficiency and accuracy Standardized process Con s High initial investment costs Requires additional IT infrastructure SOURCE: McKinsey, Yinzcam

27 APPROACH TO DETECT OUT-OF-STOCK SITUATIONS: ANALYTICAL 4/4 In-stock situation Analytics approach SKU in shopping basket SKU on average in every 50th basket Out-of-stock situation SKU in shopping basket Calculate dynamic frequency of having a SKU in a shopping basket and estimate probability of having no SKU in X subsequent shopping baskets Pro s High efficiency and accuracy Standardized process SKU in shopping basket SKU still not in 150th basket Con s?

28 KLU RESEARCH TOPIC TOGETHER WITH TCHIBO EX-POST AND EX-ANTE WEATHER INFORMATION ALLOWS FOR PRECISE WORKFORCE PLANING IN THE WAREHOUSE Weather forecast on Thu Thu Fri Sat June C 4.5h 3.0mm June C 2.5h 4.0mm June C 12.5h 0.0mm Sun June C 12.5h 0.0mm Workforce required on Mon Benefits from Forecasting Accuracy Improvement Better staff planning with lower idle times Less overtime and unplanned additional night shifts Baseline sales forecast Less waiting time for customers (24 hours dispatch target) No need for staff exchange across departments Sales forecast with weather Better planning of 3PL transport capacity Note: Data sanitized Source: KLU research project Online sales on a rainy day by Kai Hoberg and Sebastian Steinker

29 ASSESSING SUPPLY CHAIN RISKS THROUGH DATA VISUALIZATION Visualization of hurricane movements Full motion visualization of hurricanes moving across the Atlantic Assessing weather induced supply chain risks Increases and decreases in size and frequency over time Understand and predict weather patterns Implemented in many statistical packages Source: SAS blog,

30 YOUR CONTACT Professor Thomas Strothotte, PhD (McGill), MBA (Columbia) Kühne Logistics University Großer Grasbrook Hamburg Germany Phone: Fax: