The document analyzes usage patterns of rooms in the Lucas Building to improve utilization. It examines frequency of usage for faculty rooms, conference rooms, classrooms and other rooms. Questions addressed include highest/lowest used rooms, daily/weekly patterns, and time of day usage. Raw user access data from May 2014 to February 2015 is cleaned. Factors considered include only faculty usage for faculty rooms and granted access. Analysis of faculty offices shows power law distribution of usage and varying usage by day and quarter. Conference room usage reflects limited use, mostly by TAs. Classroom data is insufficient to determine accommodated classes per day. Interactive plots examine relationships between room types, time, days, and months. Enhancements and limitations are discussed

1. Lucas Building Data
Team
• Rajesh Ilango
• Preetha Manohar
• Kalyan Posani
• Ajith Ramachandra

2. Goal
Analyze the usage pattern to improve the utilization of
building capacity.
•Faculty Rooms
•Conference Rooms
•Classrooms
•Other rooms are 2 Dept. Suites, 2 Staff Room, 1 Common
room and 1 Break room

3. Questions to Answer
Frequency Of Usage:
•Which rooms are being used the most/least
• Quarterly Analysis
Usage Patterns:
•What days of the week
• Daily Usage
• Weekday vs Weekend
•What time of the day

4. Rawdata
User Access Data
Masked Users
Different Rooms Data

5. Polished data

6. Factors Considered
• Only Faculty usage for faculty rooms
• Only Granted Access
• Considered data from May 2014 to Feb 2015
• Plotted Fall 2014 and Winter 2015 quarterly data
• Faculty Offices, Conference Rooms and Classrooms
• Duplicate entries by a single user on a same day for the
faculty offices were not considered

7. Faculty Offices:
Usage – High to low
Usage pattern :
• Power law distribution
Take Away:
• Share the faculty offices and vice-versa.
• Better Allocation Strategy

8. Faculty Offices:
Day-Wise and Per Quarter Analysis
Usage pattern :
• Mon-Thu heavy usage as
expected
• Usage varies drastically by
day and quarter
• Some rooms not used at
all on some days
Take Away:
• Explore the possibility of
more week end classes to
avoid conflict with other
classes

9. Conference Rooms: (By faculty)
Day-Wise and Per Quarter Analysis
Usage pattern :
• Data reflects very limited
usage

10. Conference Rooms: (All)
Day-Wise and Per Quarter Analysis
Usage pattern :
• Mostly used by TAs

11. Conference Rooms : Usage
Usage pattern :
• Heavier usage by non-faculty. e.g.: TAs
• About half the conference rooms were not used at all
Take Away:
• Re-model Conference rooms into Collaboration rooms,
giving preference of usage to Business school students

12. Classrooms : Usage
Usage Pattern
• Very limited and unclear data
• Doesn’t reflect reality
Take Away
• Existing data is not sufficient to
identify how many classes can
be accommodated in a day.

13. Interactive plots: iplots
•Interaction between
• Different Room Types
• Day of Week
• Time of the Day
• Weekend vs Weekday
• Monthly Analysis

14. Enhancements & Limitations
•No data is useless
•Never neglect data
•Limitations
•No Exit Data
•Analysis limited to Faculty usage.

15. Data Analysis
•Analysis
• Lubridate
•stringr
•Plots
• ggplot2
•iplots

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