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EyeForTravel, LondonHenrik Imhof4.5.2017
The Interaction of Revenue Management and Pricingin Car Rental
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Disclaimer
The simulation results in this presentation are just for illustration purposes. They are not based on real data, nor do they reflect the pricing strategy of Sixt.
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SIXT OFFERS DRIVING PLEASURE IN MORE THAN 100 COUNTRIES: FROM 1 MINUTE, 2 DAYS UP TO 5 YEARS.
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Should Revenue Management and [dynamic] Pricing be distinguished?
„cost plus“ pricing … in travel
Ressources:unit costs /
opportunity costs
...
...
markup
cost
Revenue Management:- Supply- TOTAL demand
Pricing:- Product differentiation- Extra services required
by customer- Price Strategy per
CHANNEL AND PRODUCT
Does your organisation / system account for that split?
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Room for improvement?
feedbackloop
forecast
optimise
availability& price
analytics
operate
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elasticity estimation per product / channeltotal volume of future bookings, no-shows
calculate opportunity costsadd / move capacity
set controls
assign cars
reaction to changing trends / strategies
- Interaction of Capacity Management / RM and Pricing?- Where are the biggest opportunities?- Data science?- „Classical“ RM stuff?
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Pricing:demand curve
direct costs
elasticitymarket observationhistorical sales…
RM: opportunity costs
capacity management
future demand(across all channels/products)remaining capacity
add / move capacity
PricingRM
futuredemand
(per channel/prodcut)
Interaction of RM and PricingWhat can go wrong?
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Interaction of RM and PricingWhat can go wrong?
Pricing:demand curve
direct costs
elasticitymarket observationhistorical sales…
RM: opportunity costs
capacity management
future demand(across all channels/products)remaining capacity
add / move capacity
PricingRM
futuredemand
(per channel/prodcut)
setting a (slightly) wrong price
setting a fixed price for a period,ignoring capacity (cost) updates
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Quantfying pricing error: fixed costs per unit, no limits on capacity (text-book…)
- corresponds to long term planning decision
- price error of -10% [+10%] results in profit loss of 4% [2%]
- also applies to typical RM (system) decision on a micro time scale:
- small amount of booking time - small“ capacity changes- constant opportunity costs per unit
Ealsticity -3, unit costs 100
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The other extreme: fixed capacity at zero (variable) cost
last moments of the booking horizon… if you were to set a fixed price
- Need to be 100% right about the price?!
- In reality: booking curve tells you quicklywhether your price was right.„Threshold steering“
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Constant price for a certain period- robust within certain limits
Is this a real life situation?- Lacking the capability of dynamic pricing
update, driven by remaining capacity
In between: bid price kicks in… increasing capacity costs
parameters as before
16015014013012010510410310210110099989080502020202020
unitc
osts
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Impact of errors
Stochastic simulation, using Dynamic Programming
elasticity and capacity costs similary to earlier slides. Stochastic demand adjusted so that ca. 90% utilisation are reached in optimal control case.
Simulated Pricing errors:
a) at each time step, apply random price error of +/-10% (uniform distribution).
b) systematically, price 10% too low [too high].
For a) & b), the reference value is defined as the optimum price giventhat a) / b) is to be applied for the remaining booking horizon, i.e.the capacity impact of future (wrong) pricing is fully taken into account.
Simulated RM errors:c) the price is set once for the whole booking horizon. Optimum determined by variationof that price.
Combined Pricing & RM errors:d) apply a systematic error of -10% [+10%] on the optimum fixed price of scenario c).
Results, as compared to optimum profit:
a) 99.5%
b) 98.1% [98.9%].
Stochastic process reduces the(already small) impact.
c) 98.2%
d) 90,3% [93,2%]Stochastic doesnot help!
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Risks & Challenges
Two ways of looking at these results
Avoiding errors:
Small pricing errors have limited impact – aslong as capacity forecasts are dynamicallyadapted all the time.
Small pricing errors have devastating effect ifbase price is not adjusted dynamically tochanges in capacity.
Seeking new opportunities:
Small uplift opportunity by market / elasticityestimation alone-> seek new ideas.
Get the basics of RM / capacity control right(if you have not done so, yet…)!
related results by Lämmle (2012): Shuttling cars andleaving price fixed can achieve almost as much asdynamic Pricing. (The combined performance isbetter still, though.)
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Getting the basics right in car rental RM
A typical day
typical figures, for some cases including Franchise partners, exact values may vary.
capacity andno showforecast
transferoptimisation
fleet mix optimisation
integrate RM and channelmix pricing
1.000 in-fleetsSupply over 2.000 stations
20.000 reservations, many „last minute“for 50 different groups
8.000 unplanned returns3.000 cancellations and 2.000 no-shows
7.000 one-way-rentals2.000 Walk-Up‘s
4.000 planned transfers
plus: delivery+collection / recalls / damages+repairs / defleet due to mileage …
autocontrol
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New opportunities
customer type / preferences /
historytaylored
offer
Potential for additional revenuethrough targeted offers:- product choice / presentation, - upsell incentive,- additional services.Often much higher than through priceoptimisation alone.
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Sixt Group KPI’s – Long-term profitable growth
1) Figures 2013 adjusted for “at equity” consolidation of joint ventures
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Consolidated financial statements 2010-2015 – Key figures [EUR m]1)
OPERATING REVENUE EBIT EBT
177.3
2012
167.7
2011
189.8
2010
156.2
2015
221.8
2014
199.2
2013 2015
185.2
2014
157.0
2013
137.6
2012
118.6
2011
138.9
2010
102.3
Leasingrevenue
2015
Rentalrevenue
Otherrevenue
1,939
420
1,377
142
2014
1,645
417
1,120
108
2013
1,50596
2012
1,426
383
954 1,016
89
2011
1,373
394
896
83
2010
1,328
404
807
117
393
- update -EBT 2016
218.3
2016