big data: improving capacity utilization of transport companies

Higher efficiency for cargo transport (a $3 trillion industry)

With big data / predictive analytics

Transmetrics – the company

This presentation

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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

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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

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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

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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

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First commercial implementation: DPD network

First implementations

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Implementations in discussion with

Live since October 2015

In progress (go-live Q2/2016)Romania


This presentation

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Tool set challenges

What does it mean for technology

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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

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Started with a very well established idea

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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

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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

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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

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The key factor to convince management: the BIG SIZE of potential benefits

Customer testimonial DHL

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Key factor in acceptance: make it simple for the users

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Key factor in acceptance: make it simple for the users

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This presentation

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Tool set challenges

How cargo companies determine their capacity needs today

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State of the technology at CARGO customers

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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

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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

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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

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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


This presentation

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Tool set challenges

Technology challenges for a big data startup

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Open source / community

Performance

Support

Security

Legacy/big vendor

Cost

Privacy

Lock in

Other startups

Uncertain quality

Uncertain roadmap

Risk

Tool set

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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

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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 | [email protected]

big data: improving capacity utilization of transport companies

Data & Analytics