The Secrets To Hotel Demand Forecasting

WEDNESDAY, MAY 27th - 9:00AM (PDT) Duetto Educational Series

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About: Nathaniel “Nat” Estis Green

Senior Global Solutions EngineerDuetto family member since Dec. 2012

Agenda

▍ What is Forecasting?

▍ Why Forecast?

▍ Do macro and micro trends impact forecasts?

▍ How do you evaluate forecast accuracy?

▍ Budgeting

▍ Questions

4

Revenue Management Introduction

“The application of disciplined analytics that predict consumer behavior at the micro-market level and optimize product availability and price to maximize revenue growth.

The primary aim of Revenue Management is selling the right product to the right customer at the right time for the right price and with the right pack.

The essence of this discipline is in understanding customers' perception of product value and accurately aligning product prices, placement and availability with each customer segment.”

Cross, R. (1997) Revenue Management: Hard-Core Tactics for Market Domination. New York, NY: Broadway Books.

Inventory /Capacity Demand

Price

$

Ever leave money on the table?

250,000 + People

7

100 room hotel

Does not forecast

Hotel 123

8

Hotel ABC

100 room hotel

Has YoY Reservation data

Tracks STLY Pricing

Has additional data sources

Ever leave money on the table?

250,000 + People

??

Ever leave money on the table?

250,000 + People

??$250ADR

Hotel 123

Ever leave money on the table?

250,000 + People

?? $350ADR

Hotel ABC

Industry at a Crossroads

12

1970s 1980s 1990s 2000s 2010s 2013

Separation of ownership, brand, and management

Product segmentation; financial engineering

First online booking; enter Expedia

Online distribution explodes complexity

Crowded value chain

Meta search; enter tech giants & new gatekeepers

Historically Travelers Booked Directly with Stay Brands

13

Consumer Stay Brands

Courtesy

Booking Brands Now Dominate Consumer Point of Entry

14

Consumer

Stay Brands

v

Booking Brands

Courtesy

Commissions Rise at 2x the Rate of Revenue Growth

39%+

2009 2010 2011 2012

%Increase

CommissionIncrease

15

20%20%24%

20%

Total Acquisition Costs

Room Revenue

Sales & Marketing Expense

Total Revenue

Retail commissions onlySource: HAMA Study 2013-2014

Courtesy

Customer Acquisition Comparative Costs as % of Revenue

16

Revenue

Cost %

3-6% 4-6%

15-25%

What is Forecasting?Getting started.

Forecasting

ConstrainedForecasts

UnconstrainedForecasts

Demand controlled by hotel capacity

Demand if capacity is not a factor

Basic Terminology

19

VarianceRolling

Forecasts Compression

Forecast-to-Budget Occupancy Forecast Accuracy

SegmentationBooking Window

Etc.

Why Forecast?See the cross-departmental impact.

21

5 Key Reasons to Forecast

Staffing ProductInventory

DevelopmentWork

PerformanceEvaluations

Pricing

Trends in ForecastingEvaluating macro and micro trends.

Big Data = Better Data

Reviews & Social Media

Competitor Pricing Data

Booking & Reservation Data

Web Shopping Regrets & Denials

Weather

Air Traffic

Traditional Revenue Management

Traditional Revenue Management

Big Data = Better Data

Reviews & Social Media

Competitor Pricing Data

Booking & Reservation Data

Web Shopping Regrets & Denials

Weather

Air Traffic

Traditional Revenue Management

Traditional Revenue Management

Big Data = Better Data

Reviews & Social Media

Competitor Pricing Data

Booking & Reservation Data

Web Shopping Regrets & Denials

Air Traffic

Traditional Revenue Management

Traditional Revenue Management

Weather

Web Site (IBE) & Air Activity

Be proactive, not reactive, with demand trends.

▍Review search date, stay dates, rate code, room type, rate, source, and country

▍Understand high-demand periods before you sell-out supply

Excel v.s Revenue Strategy Systems?

27

VS

Excel

How to Determine Forecast Accuracy?Evaluate your forecast properly.

Four Major Statistics

29

Forecast Accuracy

Simple Error Mean Simple Percent Error(MSPE)

Mean Absolute Deviation(MAD)

Mean Absolute Percent Error(MAPE)

30

100 Room Property

Hotel ABC

Four Major Statistics

31

Forecast Accuracy

Simple Error Mean Simple Percent Error(MSPE)

Mean Absolute Deviation(MAD)

Mean Aboslute Percent Error(MAPE)

Simple Error Example

▍ April Simple Error = Sum (April 6, April 13, April 20, April 27)

▍ April Monday Simple Error = -2+3+(-2)+4= +3

32

DBA 10Monday, April 6

-2

Monday, April 13

+3

Monday, April 20

-2

Monday, April 27

+4

April Monday Simple Error

+3

Four Major Statistics

33

Forecast Accuracy

Simple Error Mean Simple Percent Error(MSPE)

Mean Absolute Deviation(MAD)

Mean Absolute Percent Error(MAPE)

Simple Error Percent Example

▍ Simple Error % = Simple Error/ Room Count

▍ Simple Error % = Simple Error/ 100

▍ April Simple Error % = Sum (April 6, April 13, April 20, April 27)

▍ April Monday Simple Error % = -2%+3%+(-2%)+4%= +3%

34

DBA 10 (Simple Error)

10 (Simple Error %)

Monday, April 6

-2 -2%

Monday, April 13

+3 +3%

Monday, April 20

-2 -2%

Monday, April 27

+4 +4%

Monday April Error

+3 +3%

Four Major Statistics

35

Forecast Accuracy

Simple Error Mean Simple Percent Error(MSPE)

Mean Absolute Deviation(MAD)

Mean Absolute Percent Error(MAPE)

Mean Absolute Deviation (MAD)

▍ April MAD= Absolute Sum (April 6, April 13, April 20, April 27)

▍ April Monday MAD= (|-2|+|3|+|-2|+|4|)= 11

36

DBA 10Monday, April 6

|-2| -> 2

Monday, April 13

|+3| -> 3

Monday, April 20

|-2| -> 2

Monday, April 27

|+4| -> 4

Monday April MAD

11

Four Major Statistics

37

Forecast Accuracy

Simple Error Mean Simple Percent Error(MSPE)

Mean Absolute Deviation(MAD)

Mean Absolute Percent Error(MAPE)

Mean Absolute Percent Error (MAPE) Example

▍ MAPE = MAD/ Room Count

▍ April MAPE= Sum (April 6 MAD, April 13 MAD, April 20 MAD,

April 27 MAD)

▍ April Monday MAPE= 2%+3%+2%+4%= 11%

38

DBA 10 (MAD) 10 (MAPE)

Monday, April 6

|-2| -> 2 2%

Monday, April 13

|+3| -> 3 3%

Monday, April 20

|-2| -> 2 2%

Monday, April 27

|+4| -> 4 4%

Monday Accuracy

11 11%

Mean Absolute Percent Error (MAPE) Example

▍ MAPE = MAD/ Room Count

▍ April MAPE= Sum (April 6 MAD, April 13 MAD, April 20 MAD,

April 27 MAD)

▍ April Monday MAPE= 2%+3%+2%+4%= 11%

39

DBA 10 (MAD) 10 (MAPE)

Monday, April 6

|-2| -> 2 2%

Monday, April 13

|+3| -> 3 3%

Monday, April 20

|-2| -> 2 2%

Monday, April 27

|+4| -> 4 4%

Monday Accuracy

11 11%

*Note – there is an 8% difference between the Simple Error % and the MAPE

Best Practices in BudgetingBe efficient, effective, and thorough.

Efficient Budgeting: What’s Best?

41

1 2 3

Daily Monthly Quarterly

42

Key TakeawaysThings to think about per type of property.

Key Takeaways

43

Economy Luxury Resorts

City-Center Airport Convention Casino

Questions?WEDNESDAY, May 27th - 9:00AM (PDT) Duetto Educational Series