big data: improving capacity utilization of transport companies
Post on 12-Feb-2017
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Higher efficiency for cargo transport (a $3 trillion industry)
With big data / predictive analytics
Transmetrics – the company
This presentation
2
Convincing business to try big data
Legacy landscape challenges
Tool set challenges
Kilometers on road are24% empty
“Full” trucks only carry 57% of capacity
EU CO2 reduction target: 124 MT / year
EUR cost reduction target:11% cost reduction
Empty space in the cargo supply chain, according to the World Economic Forum
3
Large transport companies have the most to gain
Large transport company P&L structure (typical, source: Roland Berger strategy consultants)
Net Revenue
85%
15% 7%4%
Capacity Cost
GrossProfit
DirectCosts
IndirectCosts
4%
Net Profit
-11% 2-3x
Modest decreases in capacity cost
leads to dramatic increases in profit
4
Typical situation in daily transport
Today, there is poor capacity utilization in the transport between terminals, for terminal – based products (Groupage or LTL), both domestic and international
5
Terminal Customerlocations
TerminalCustomerlocations
Transmetrics provides the missing 80% of data by predicting future customer transport bookings, based on the basis of historical data and demand variables. This results in efficient capacity plans with less empty space in vehicles.
ShippingHistory3-5 years
Customer orders
ConsolidationsLinehauls
EventsCarrier
contractsCustomers
...
+
Shopping days
Industrial seasonality
Month end
Fairs and events
Customer Forecasts
School holidays
Public Holidays
New tenders
Competitor events
Gained and lost
customersNetwork plan
changes
NewProduct
launches
Commo-dity
prices
=
Efficient Capacity Plan
ForecastedCustomer bookings
Transmetrics enables the loading factor of each linehaul to be forecasted a few days in advance
Forecast:
next Wednesda
y departure
Forecast:
next Thursdaydeparture
Forecast:
next Friday
departure
Unusedcapacity
Likely to have too much unused space: action needed
Should be OK, no need for action
Forecasted groupageorders via data mining
Likely to be overloaded, need to make
a contingency plan
VPN
Shipping history
Shipments, capacities, contracts, events
Transmetrics servers
TransmetricsCargo
transport predictive
optimization product
: SaaS product with a daily usage scenario
Customer IT systems
Transport Management
System
Transport Capacity Planning System
Reportsfor users
ForecastsOptimized schedule
runs periodically
Cloud - SaaSSubscription
€ 2,500 per country per
month
8
First commercial implementation: DPD network
First implementations
9
Implementations in discussion with
Live since October 2015
In progress (go-live Q2/2016)Romania
Transmetrics – the company
This presentation
10
Convincing business to try big data
Legacy landscape challenges
Tool set challenges
What does it mean for technology
11
CEOs are willing
to pay for
solutions to
BUSINESS problems
We have to translate
The right business problem
To a BIG DATA solution
And convince them that it will work
Idea came from talking to customers
12
Started with a very well established idea
13
Idea of Transmetrics came out in 2012 …
We already had the:
… Know how of business problem
… Understanding of data
… Understanding of algorithms
… Contacts with potential customers
… Some funding
The problem in getting a big data project going
14
Organization is overloaded with daily problems
Properties of big data ideas:
… The results are unsure
… No benefits in this quarter
… Not a “burning issue”
Normal answer is “… great idea, but not this year”
Yet … a number of challenges that took 3 years
15
Get someone to take the
idea seriously and give feedback
Get someone to give us
data to work with
(DHL Express transferred data
from October 2013 to February
2014)
Get someone to agree to
implement in production and pay for the solution
Met with over 30 transport companies
What mattered: trusting us as
people
Out of the 30, 3 companies
joined
What mattered: visionary CEO
Out of the 30, 1 company
joined
Key factor: visionary line
manager
The winning hand
16
The key factor to convince management: the BIG SIZE of potential benefits
Customer testimonial DHL
17
Key factor in acceptance: make it simple for the users
18
Key factor in acceptance: make it simple for the users
19
Transmetrics – the company
This presentation
20
Convincing business to try big data
Legacy landscape challenges
Tool set challenges
How cargo companies determine their capacity needs today
21
State of the technology at CARGO customers
22
Legacy – 1990s
Some BI / data warehouses for operational needs
No data mining capability
Hard to do large data extracts
Data sizes … 4 billion records, with 200 columns each
23
4 billion records with 100+ fields each >is much more than> 4 billon key-value pairs
Filter by multiple columnsJoinsEtc.
Data flow from origin to big data system
24
Legacy
Legacy
Legacy
Legacy
offices
Legacy
Cenralrepository
TransmetricsStaging
CSV TransmetricsDWH
VPNaccess
Customer controlled Transmetrics controlled
$3@#!!!! Transmetrics doesn’t work!!!
Late dataWrong data
System changes
The importance of
25
Data quality measurement system + sign off
Data tracing / audit logs
Automated monitoring
= Be ready to prove that “garbage in = garbage out”
= Push problem back to customer IT
Transmetrics – the company
This presentation
26
Convincing business to try big data
Legacy landscape challenges
Tool set challenges
Technology challenges for a big data startup
27
Open source / community
Performance
Support
Security
Legacy/big vendor
Cost
Privacy
Lock in
Other startups
Uncertain quality
Uncertain roadmap
Risk
Tool set
28
Big data repository: Mammoth DB • Stores main transaction data• Main analysis cube = 2.5 billion records
• Most queries take < 1 min
Integra-torServer(PC)
DB Server 1
DB Server 2
DB Server 3
DB Server 4
DB Server 5
...
One virtual database
Other tools used
Key mistakes to watch out for
29
Started with tools that don’t scale (Pentaho, web2py)
Didn’t invest in data quality framework until late
“It’s all about the data” … underestimated the UX
Thank you for your attention! Transmetrics AD | Asparuh Koev, CEO | +359 888 400 348 | asparuh.koev@transmetrics.eu
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