1. Running head: FULL HF BRIEFING NOTE 1
Proposal
Re: forward to senior engineering manager
My team of professionals and I will investigate the flow of customers through the first
turnstiles into Dundas subway station during rush hour times. We will define and measure the
voice of the customer and relate it to the increasing need of functionality, when it comes to
waiting in line to receive promised quality service. Whether it be asking for directions or paying
fare, we will derive our research towards investigating what factors are involved in making a
more effective transition occur more frequently; in order, for commuters to catch their train
quickly during rush hour times. If we are successful, then we would have ultimately used the
human factors to make this single process more conveniently designed.
Briefing Note
Re: forward report to senior engineering manager
The multitudes of people that get into the Dundas subway station during rush hours is
exceedingly out of control. Considering it is the stop for Yonge & Dundas Square, which
includes The Eaton Center and Ryerson University. During rush hours it is time consuming to
get through to the operators for TTC service. The first turnstiles from each side of the entry to
the subway platform are the links to the operators, where commuters have the options to either
pay and purchase fare or direct an inquiry. My team of industrial engineers will research human
factors involved in getting through that first turnstile during rush hour which is the optimal
performance time for the data collection. Our design object is to shorten the time it takes to get to
the end of the line, in order for customers to flow inside the subway more quickly. This is a
problem for commuters since the waiting times in the waiting lines are too long. Our research
will include clocking in every time a customer gets through the turnstiles and observe the reason
for choosing to be in that line. Next, we will plot the data on a graph in order to find the standard
deviation based on the sample size. This will help us understand the upper and lower limit of the
average time it takes to get into the subway system through the first turnstiles. Our goal will then
be to use human factors and redesign an alternative process based on the analysis of the research
which will ultimately shift the upper and lower limit to a quicker average time to get into the
subway.
Our research process will cover a variety of testing in terms of limits and capabilities of
our final experimentation. Even though we have a clear objective in mind, it is important to carry
out experiments with an open ended point of view. This is called the experimental evaluation,
where the desired objective gets re-evaluated because of more possibilities that have previously
been overlooked. The research has to be defined before it can be executed. Our research criterion
has to match what the customer is looking for. Our team will conduct surveys on commuters to
begin to understand how an ideal interaction would be between turnstiles for the average
commuter.

2. FULL HF BRIEFINGNOTE 2
As we can see, the table shows the most frequent interaction with the operator is the
purchasing of the fare. The second most occurring interaction is the payment of the fare.
Technically speaking, paying the fare should not take time since it is a matter of depositing the
token or showing the metro pass. This means that people are being held back in the line for no
reason. Our design should then focus on filtering out the people who already have fare to get into
the station using the other turnstiles This is all considered preliminary data collection, since our
next step would be to understand why our design object is in particular the turnstiles themselves.
By the optimization of the turnstiles, we can allow more people into the station, but we must do
it with a degree of accuracy and effectiveness. That’s where numbers come in.
0
5
10
15
20
25
30
Fare Purchase Fare Payment Inquiry Inquiry +
Payment +
Purchase
Inquiry +
Payment
Inquiry +
Purchase
Reasons for Joining Line at Dundas Station
0
5
10
15
20
25
30
35
40
5 to 10 10 to 15 15 to 30 30 to 60 60 to 90 90 to 120 120 to 180 180 to 210 210 to 230
Frequency
Time (s)
Time in Line

3. FULL HF BRIEFINGNOTE 3
After conducting the experiment, which included timing every customer that waited in
line to get through the first turnstiles, we notice a trend in the most popular waiting times. The
lower limit would be 10 to 15 seconds of waiting, and the upper limit would be 60 to 90 seconds
of waiting. The sample size is out of 161 people within 1 hour of rush hour. As we can see, over
30 people spent less than 10 seconds in getting through the line. These are the people that already
had fare and simply waited for no reason in line. The lower limit are the people that spent 10-15
seconds, which is the average time it takes to ask for directions. The majority of the people that
spent waiting in line are the people in between the upper and lower limit. The people in the
middle, who took in between 15 to 60 seconds, are the people we are targeting to use the first
turnstiles, since it takes less than a minute to purchase fare depending on the type of payment. If
you have cash, you are closer to the lower limit, and if you are paying by debit or visa then you
are closer to the upper limit. The people around the upper limit of 60 to 90 seconds usually also
have inquiries along with their fare purchase, which takes up unnecessary time. Our goal is to
decrease the lower and upper limit to less than 30 seconds.
By accuracy development, we need only the people that are purchasing fare to get into
the first turnstiles on each end. We need to redirect the group of people that are only paying fare
to get in through the other turnstiles, which have token and metro pass portals. We also need to
redirect the people that have inquiries or need directions to other TTC personnel other than the
operators at the first turnstiles. By separating these three groups of people we will accurately
designate each of them to their respective turnstiles. This decreases the lower limit by getting rid
of the people that are simply waiting to pay fare and also decreases the upper limit by getting rid
of the people that have inquiries along with fare purchasing. More visually stimulating signage
should be put up for each respective turnstile, right by the token and metro pass portals. This
way, people will know to exit the unnecessary line and get into the station with no delays. This
development is effective since the first turnstiles should only be used to purchase fare. If only
fare purchase occurs at the first turnstiles, then the people waiting in line are all waiting for the
same purpose. Our design object is met as it now enhances the usability experience through the
first turnstiles and gets more people in the Dundas subway station in a shorter period of time.

4. FULL HF BRIEFINGNOTE 4
References
Wolfram. (2015). Histograms. Retrieved from
https://reference.wolfram.com/language/ref/Histogram.html
Wolfram. (2015). Mean. Retrieved from
https://reference.wolfram.com/language/ref/Mean.html
Wolfram. (2015). Standard Deviation. Retrieved from
https://reference.wolfram.com/language/ref/StandardDeviation.html