Using data to define new logistics collaboration models: Observations from U-TURN with a focus on the Supermarket eCommerce market - Richard ...
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Funded by the
Horizon 2020
Framework
Programme of the
European Union
Using data to define new logistics
collaboration models:
Observations from U-TURN with a
focus on the Supermarket
eCommerce market
Richard Walters (richard.walters@bearingpoint.com)
Contents
Background
The Grocery eCommerce market
How we used data
Data sources
Data challenges
Data generation tools
Modelling scenarios
Results
Reducing cost and vehicle impacts
Applying the learnings (case study)
BACKGROUND
UK Grocery eCommerce:
A market facing many challenges
Against a broadly static grocery retail market, online is growing rapidly
• Growth c.17% per annum with projected value of £17bn by 2020
• Orders rising from 75million in 2014 to 170million pa in 2020
• Delivery vans rising from 10,000 to 20,000
• Future environmental impact CO2 175 m tonnes pa with NOX and PM’s
• Major concerns on traffic impacts from policy makers
The Competition amongst retailers is intense:
• UK grocery retail is highly concentrated
• All of the key retailers are involved and use online to drive customer retention
• The big six account for 85% of the market with Tesco the largest (circa 38%)
• Evidence they sacrifice margin to maintain share
• New businesses (both big and small) are entering the market – based on disruptive business models and / or
new technology e.g. Amazon, Farmdrop, HubBub and Starship
Customers increasingly searching for and expecting online retail solutions:
• 71% of shoppers have / are or will shop online for groceries – less than 10% only use online
• The customer experience is constrained by the delivery arrangements
• Customers are offered 1 hour delivery slots with 2-3 hr time reservation windows
• The most convenient slots are oversubscribed, so dynamic pricing is used to influence customers’ slot
selection to help retailers fill van capacity
• Once again this erodes margin
• Minimum order values are typically £40 to £50
4
UK Grocery eCommerce:
A market facing many challenges
3 main Supply Chain models have evolved:
• Store based picking fulfilment is the most common operating model
• As volumes have grown, there has been investment in upstream capacity e.g. dark stores and fulfilment
centres
• Dark stores are regional fulfilment that look like stores with no customers and avoid conflict with shop
customers and give some productivity improvements
• Historically – large central facilities have not proved economic. Now Ocado and Morrisons fulfil from large
central facilities with the technology provided by Ocado
• There is a cost trade off between picking and delivery – local picking costs more but the delivery is
cheaper
The Economics are Challenging and the retailers have a significant dilemma:
• Average Cost per order of c. £21, the delivery element circa £10
• Break even order c. £70 ~ embrace growth unprofitably or lose market share
• Collaboration is not on retailers’ agendas
Customer intimacy and feedback from the final delivery is a key part of the brand
Periods of peak demand are unsustainable
• So, retailers need to find ways to cut costs and improve customer choice
Click and Collect is the area of new investment:
• Increases convenience for customers and lowers costs – constrained by food control obligations - chill
• C&C growth is 30% pa in non-grocery including a widespread use of remote C&C locations e.g. lockers
• The fastest growing area of online order fulfilment, but
• Collection option for grocery almost entirely limited to ‘at the store’
• Expectation that new C&C models will drive growth in customer expectation in Grocery retail
• Customers seeking increasingly convenient options not just collection at store locations
5
USING DATA
Data Sources:
We used primary and secondary data
Primary data received from 2 retailers:
• Covering 1 calendar year and geographic area of London
• Circa 7m transactions
• Order level including order size, date, delivery time, delivery point at
postcode / sector level, and route origination
• Retailer 1 is one of the big six, retailer 2 a smaller UK player
• Data has been used with market share and demographics to synthesise
the market
Orders Weighting
A combination of Secondary data was used to
Total
Postcode
Sales
Population
Sales
Population
Sales synthesise postal sector
Online demand per retailer. For
Population Index \ Index Index Grocery
Sector
Population
method
method
method
method
example:
Orders
per Year
5,615 16,227 2,835 702
• Population statistics
1,770
AL1 1 50% 50%
AL1 2 6,716 19,411 3,392 840 • Market
2,117 and company reports
50% 50%
AL1 3 4,303 12,436 2,173 538
50% 50%
• Results
1,356 from published surveys
AL1 4 10,090 29,159 5,095 1,262
50% 50% • Undertook
3,180 in house a research survey on Consumer
AL1 5 10,529 30,430 5,317 1,317 attitudes
3,318 to Grocery Online shopping
50% 50%
7
Data Challenges:
Challenges and workarounds led to unintended benefits
Significant effort to gain data from other retailers:
• 16 meetings and various email correspondence
• Genuine interest but competitive landscape has intensified since the
outset of project
• They have become increasingly guarded about data sharing
• However retailer interaction has enabled a very in depth view of the
market to be developed and ability to test assumptions and understand
capabilities and future strategies
• This has helped to develop a community of interest – major event 14th
March 2017
• As project develops still more opportunity to interact as needed
We had to engage with a much wider retail audience:
• Key insights on evolution of customer service offer … click and collect the
area of new investment
• Key insights on opportunities for alternative forms of last mile transport
• Key insights around attitude towards collaboration
• Key insights into cost of current service
• Developed a wide community of interest that eventually led to the case
study (see later slide)
8
Data Generation:
Monte Carlo Simulation
✓ Estimate demand for 265 postcode sectors for 364 days
✓ Tesco, Sainsbury's, Asda, Waitrose, Ocado, and Morrisons
Retailer Tesco
Postcode Sector AL10 9
Annual orders 4,979
Number of
Week Day % of Orders
orders
13th Monday 0.31% 15
Tuesday 0.27% 13
Wednesday 0.23% 11
Thursday 0.26% 13
Friday 0.33% 16
Saturday 0.28% 14
Sunday 0.23% 11
Source:
Cranfield School of Management
9
Data Generation:
Vehicle Routing Problem
Supply 20 micro hubs
R1: R2:
10 vehicles are needed, 527 kilometres
Shared Model:
Source:
9 vehicles are needed, 425 kilometres Cranfield School of Management
10Modelling Scenarios:
Using Micro Hubs in the ‘To Be’ landscape
We established the typical supply chain Understanding the role for Micro-hubs
models (micro consolidation centres)
11Modelling Scenarios:
Examining Retail Collaboration
We examined the following proposed collaboration scenarios:
A. R1: Morrisons (2%), R2: Ocado (14%)
B. R3: Sainsbury’s (15%), R4: Waitrose (4%)
C. R1: Morrisons (2%), R2: Ocado (14%), R4:Waitrose (4%)
Note: Market shares are based on 2015 sales
Source:
Cranfield School of Management
12Modelling scenarios:
Identifying New supply chain structures
Picking Locations Micro Hubs around
Consumers
of Retailers Residential Areas
Picking Locations Micro Hubs around
Consumers
of Retailers Residential Areas
Picking Locations Micro Hubs around
Consumers
of Retailers Residential Areas
13RESULTS
Results:
A snap shot of the opportunities
Improvements up to:
• 23% of the total travelled distance
• 28% of the number of trucks Last Mile
• 59% of the fleet utilisation
• 12% of the total travelled distance
• 10% of the number of trucks Stem Mile
• 5% of the fleet utilisation
Source:
Cranfield School of Management
15Results:
Applying the learnings (E-Cargo bikes Case Study)
Sainsbury’s trials UK’s first grocery deliveries service by zero emission electric
cargobike
• e-cargobikes to deliver online orders to customers in Streatham, London, from
April 17th 2018
• Trial tests greener grocery deliveries in congested cities:, one e-cargobike can
deliver as much as 3.5-tonne lorry in a day
• Trial shows Sainsbury’s strategy to serve customers whenever and wherever they
want
16Results:
Applying the learnings (E-Cargo bikes Case Study)
U-TURN has been supporting and coaching the E-Cargo Bikes team through their
development of the trial with Sainsbury
Professor Alan Braithwaite used elements of the U-TURN analysis and results to:
• Provide regular sense checks and options discussions to the directors as they
pieced their way through the pre-revenue stage of their business planning and
design
• Provide data from U-TURN to validate likely volumes and drop densities to
arrive at the 2 to 3.5 mile radius number
• Supporting the design of the early trial runs, timing and productivity potential
• Coaching on the sales engagement and contractual expectations when
opening discussions with the retailers
• Reviewing the route data provided by the retailers and working on the
consequent productivity assumptions
• Creating revenue, cashflow and investment models
17THANKYOU
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