Bringing big data to cargo transport to improve capacity utilization.

Transcription

1 Bringing big data to cargo transport to improve capacity utilization 1

2 We solve capacity optimization in transport Global cargo transport industry: 2 Trillion+ revenues Unused (empty) capacity: Over 50% unused, transporting empty space (Davos forum) Impact of unused capacity: Staggering financial cost, burning oil, producing CO2, traffic jams 2

3 Main reasons for empty space in cargo transport Empty Space 50% 25% Long-term trade imbalances (e.g. China US) Hard to solve with technology 25% Short-term Irregularity in shipping demand We solve this half by predicting short term demand 3

4 Main controllable reason for empty space: Short-term irregularity in shipping demand 150% 100% A real life cargo trade lane, Friday departures %

5 Shipping demand depends on external factors If these are known, future volumes are predictable Weather Social Sentiment Product launches Customs Blockages Commodity Prices Ship port calls Public Holidays Political Events Exchange Rates Seasons Competitor problems Consumer Sentiment Stock prices 5

6 Past proof of concept One of our customers has achieved Our goal is to increase this to at least 80 % 90 % correct forecasts with their own efforts using just 2 external factors by a fine-tuned algorithm using large numbers of external factors 6

7 Targeted impact Today, cargo transport companies have If we achieve results similar to other predictive analytics case studies: 2-3% profit margin -15% cost = 4x profit 7

8 Targeted impact Synergy Economy - Ecology Transport companies increase profit by running less vehicles = Less CO2 emissions, less carbon fuel use 8

9 Our predictive algorithms will be packaged in a cloud-based, subscription product Cloud, SAAS product Shipping History Predictive Model Prediction empty space next 6 weeks Signals (weather, holidays,...) Deal with empty space 9

10 We will sell our product as a cloud service, on a monthly subscription fee based on usage Monthly Subscription A 5,000 50,000 EUR Based on usage: per truck per flight per container per ton of cargo per ton-kilometer Global B Regional C Small companies 10

11 Our competition offerings are inferior for cargo transport companies Supply Chain Optimization Share capacity Cost Solution fit Challenge Very expensive Poor match for transporters Trust issues Low prices 11

12 Our team is experienced, and covers all bases Co-founders Asparuh Koev Serial Entrepreneur Exit to VMWare Team (full time) Dimitar Kamenov Web developer External data Marta Stefanova MBA Logistics External data Anna Shaposhnikova Business to business sales Experienced networker Tim Koroteev Marketing Web presence Rado Nikolov 20 years programmer Math background Alex Petkov 20 years programmer Transport data expert Team (part time) Milen Nedev Machine Learning Jafar Jafarov Sales Dr. Nina Daskalova PhD statistics Predictive Analytics Georgi Baldjiev Machine Learning 12

13 Our advisory board is staffed with captains of industry Willem Mulock Houwer Former VP Carlo Ortelli Former Head of Ops Programs Geert Lagae Former Executive Louis Verbeke Managing Partner BE Marc Huybrechts President, European association of freight forwarders Prof. Dr Willy Winkelmans Founder, Honorary Dean 13

14 We are in R&D pilot mode with world s largest transport company, and two others Early 2014 Today Acceleration Pilots R&D mode (free of charge) Seed round Productize Sell Subscription 14

15 20 interested companies in our future pipeline 15

16 We have had major recognition in start-up forums this year Started with EU funding March 2013 Winner of 30,000 EUR award, EIT ICT Labs outreach competition Top 8 Pioneers Festival Top 12 Tech All Stars Top 9 ICT, European Venture Summit Top 21 Webit congress 16

17 Currently looking for 1. VC for seed round early Mentors in predictive analytics 3. Mentors in B2B SAAS business models Thank you very much! Contact: 17