The document proposes solutions to improve operational and administrative efficiency at The Hive Backpackers Hostel. It summarizes the current problems with using Excel to manage operations and guest records, which results in a disorganized and manual process. Models are presented to optimize the cleaning schedule, bed sheet management, and automate guest check-ins. It also discusses using linear programming to find the optimal daily room rate to maximize profits by considering constraints like bed capacity and forecasted guest demand.

1. THE HIVE BACKPACKERS’ HOSTEL
An explorative first glance of the current state
of The Hive Backpacker Hostel and how we
seek to revolutionise it.
Seng Keong Ho
Bernard Goh
Jin Hao Ng
Andy Tanzil
Joash Yeo

2. Our VALUE proposition

3. HIVES, IN-BRIEF
Provides low-cost accommodation to backpackers
and travelers around the world
A total of 15 rooms
Opens from 7.30am to 12.00am
Strategy - Best accommodation, lowest prices
1
2
3
4

4. HIVES, The PROBLEM
NOW Simple Microsoft Excel usage to manage its
operations and keep track of guests records
RESULT
Disorganised, manual-based process,
inaccurate
PROPOSAL OPERATIONAL
EFFICIENCY
ADMINISTRATIVE
EFFICIENCY

5. 5
OPERATIONAL
EFFICIENCY

6. CLEANING SCHEDULE
Problem : Irregular check-in
and check-out timings of
customers complicate the
cleaning process
Solution : Create a model to
ensure rooms are always in
ready condition and maximise
cleaning staff efficiency

7. CLEANING SCHEDULE (MODEL)
Room
Name
Check-­‐Out
Timing(DD/
MM/YYYY
HH/MM) Clean by Timing Time Left Status
HIBISCUS1
3/3/2013
17:30
3/3/2013
18:30
60 mins
HIBISCUS2
3/3/2013
15:30
3/3/2013
16:30
-60 mins Lapsed
TIME NOW: 17:30

8. BED SHEET Management
Problem : Shortage of clean
bedsheets and lapses in bed
sheet changing
Solution : A model to churn
out the number of clean
bedsheets needed to meet
short-term demand and
optimise bed sheet-changing
schedule

9. No. of Bedsheets to be changed TODAY = 0
No. of Bedsheets to be changed in 2 days = 0
BED SHEET Management (MODEL)
Bed No Check in date Bed Sheet Change Date Change by date Days left Status
H1B1 5/3/2013 Nil 12/3/2013 6
H2B2
1/3/2013 2/3/2013 9/3/2013 3
DATE: 5/3/2013

10. HIVES, The PROBLEM
NOW Simple Microsoft Excel usage to manage its
operations and keep track of guests records
RESULT Disorganised, manual based, inaccurate
PROPOSAL OPERATIONAL
EFFICIENCY
ADMINISTRATIVE
EFFICIENCY

11. ADMINISTRATIVE
EFFICIENCY
Automating Guest Check-ins
OPTIMAL Bed Pricing

12. Problem
Check-in Date Name Amount Paid (S$)
Mon Ah Kow 45
Tues Barnabas 45
Wed Chernobyl 90
Thurs Dixie 135
Fri Elon 90
$135, Receipt to Ms Chick
$45, paid on Wed
$90, billed on Sat
Automating Guest Check-ins
Manager scours through daily
records to tally with cash/check
records

13. Check-in
Date Name Nights
Amount Paid
(S$)
Mode of Payment Payment Settled?
Mon Ah Kow 1 45 Cash Y
Tues Barnabas 1 45 Master Y
Wed Chernobyl 2 90 Visa N
Thur
s
Dixie 3 135 Cash N
Fri Elon 2 90 Check Y
Automating Guest Check-ins
Solution
A spreadsheet that correctly
captures the payment made by
every guest in real-time

14. Automating Guest Check-ins
Solution
A spreadsheet that correctly
captures the payment made by
every guest in real-time
Month of Jan’13 (S$)Month of Jan’13 (S$)Month of Jan’13 (S$)Month of Jan’13 (S$)Month of Jan’13 (S$)
Visa Master AMEX Cheque Cash
2341.51 4231.2 34.30 1045 1050.5
Month of Feb’13 (S$)Month of Feb’13 (S$)Month of Feb’13 (S$)Month of Feb’13 (S$)Month of Feb’13 (S$)
Visa Master AMEX Cheque Cash
3415.10 5302.2 344.3 1020 2340.50
Month of Mar’13 (S$)Month of Mar’13 (S$)Month of Mar’13 (S$)Month of Mar’13 (S$)Month of Mar’13 (S$)
Visa Master AMEX Cheque Cash
2341.51 43231.2 34.30 1045 1050.5
Month of Apr’13 (S$)Month of Apr’13 (S$)Month of Apr’13 (S$)Month of Apr’13 (S$)Month of Apr’13 (S$)
Visa Master AMEX Cheque Cash
2341.51 43231.2 34.30 1045 1050.5

15. • Currently converting all private rooms to dormitories
• Expansion of room capacity to approx. 3 times of current level
• Owner struggling to find the optimal daily rate to charge in
order to maximize profits
OPTIMAL Bed Pricing
Problem

16. •Goal: Find the room rate that will maximize profit
margins
•Linear Programming Model
•Subjected to constraints
•Solver implementation
Solution
OPTIMAL Bed Pricing

17. Solution
• Inputs
–Daily room rate
–Constraint values
• bed capacity
• Parameters
–Daily guest arrival rate (To be estimated & forecasted
based on previous hits in booking system)
(MODEL)
OPTIMAL Bed Pricing

18. Solution (MODEL)
• Intermediate Outputs
–Total variable cost
–Total fixed cost
–Total revenue
• Outputs
–Profit margins
OPTIMAL Bed Pricing

19. 19
DATA Collection
Monthly DEMAND
INVENTORY
Seasonal Room RATES