Community Activity

Matt Bergeron, Isaac Parlow, Paul Wendt:
2) We believe the last graphic is the most effective at giving insight into the data. This is because it does a good job at giving all of the information available in one graph, especially at a state level. We were able to see the ratios of what type of school the aid is going to for each state. Additionally, the size of the pie chart gives a good analysis of the granularity of the amount of total aid for each state, comparatively.
3) We think the total aid disbursement by school is the worst one because you can only really see a handful of university names unless you hover over other parts of the graph with the mouse.

Good – # of schools by type (pie); Total Aid (Disbursement) by School; Total Aid (Disbursement) by Loan Type; Total Aid by School Type By State
Bad – # of schools by type (bars); Avg. Loan Amount by type; Total Aid (Disbursement) by School/Type (treemap); Total Aid (Disbursement) by School/Type (bubble); Total Aid by School Type by State

-Nirja Shah and Brian Zimmie

Best- The last one titled “Total Aid by School Type By State” is the best because it shows the amount of aid given out by state. It shows the proportion of aid that is given compared to other states. In addition to that, it shows the percentage of aid that is private/ non-profit, proprietary, and public within each state. Maybe it could be improved by telling the number of schools in each state. Also, the states with small total aid amounts are hard to see and distinguish.
Bad- “Total Aid (Disbursement) by School” we agreed is the worst because the use if a tree map is ineffective because you cannot see all the school ad the amounts of aids they give. It also does not put the schools in categories.
Patrick Gilbert
Vasudha Jasthi
Frank Singer
Alyssa Munter
section:4

The best chart is the bar graph because it is the easiest to read and understand all of the information.
The worst is the graph because you only see the averages and nothing else.

Section 005
Daniel Drumm

Jared Stefanowicz
Kerry Pettit
Autumn Gindle
Arsenio Gomez
Drew B

1. Yes, shows 0 axis
2. Yes, adds up to 100
3. No, uses sum function, but says average
4. No, too many schools so most labels don’t show and it is hard to read
5. No, too many schools so most labels don’t show and it is hard to read
6. Yes, east to compare loan type amounts due to color differences
7. No, plain and hard to immediately understand
8. Yes, size represents total aid and makes it clear

My group came with a conclusion that the most efficient graph Total Aid (Disbursement) by Loan Type because it sections out information clearly and it’s easy to understand. The worst graph is Total Aid (Disbursement) by School because it’s too specific. It listed every single school and its too much information and you cant make any conclusion about the data.

Brandon Tejada
Crystal Touch
Xiangyu Kong

Section 05

Justin Hilker & Rob Corso
The most effective graphic is the Total Aid by School Type by State put on US map because it it uses the big data to filter out the important and interesting facts in the most visually pleasing way.
The least effective graphic is Total Aid by School Type by State but in an excel spreadsheet because while this is showing the same information its overcrowded with unfiltered data..

In Week 5, The class learned about the bullwhip effect. The effect is caused by customers’ demand changes affecting retailers, distributors and manufacturers. This is due to the attempt of protecting themselves from stock-outs and missed orders by keeping extra inventory. The best way to reduce the effect is to collect better information and communicate better along with making better forecasts.

On February 13th, we learned about Smart Factory Logistics and how they used IOT to cut inventory costs for hospitals and what the bullwhip effect is. Nurses spend too much of their time managing inventory, which makes them inefficient because they are spending less time with patients and more time on tasks that they should not be required to do. IOT would help manage their inventory by making inventory control more automated, giving nurses more time with patients, which makes them much more efficient. We were introduced with the Beer Game to see how the Bull Whip Effect happens in a practical exercise. The Bull Whip Effect is caused when demand forecasts are not centralized from the retailers all the way down to the manufacturers. The further down the supply chain, the more variation of demand, which is very inefficient, and can be mitigated with transparency within the supply chain.

As a marketing major, this week was the first time I learned about the bullwhip effect. The bullwhip effect is when distorted information goes from one end of the supply chain to another and creates a fluctuation in how the various entities behave. The resulting variability in forecasts, orders, and inventory levels is called the bullwhip effect. There are four causes to the bullwhip effect; demand forecast updating, order batching, price fluctuation, and rationing and shortage gaming.

In week 5, we discussed the Bullwhip Effect and the impact variability has on supply chains. This effect is the distorted information from one end of the supply chain to another that creates fluctuations in how various entities behave. High variability can result in excess inventory or shortages in stock. Many causes contribute to this phenomenon such as demand forecast updating, order batching, price fluctuations, and rationing & shortage gaming. These causes can be counteracted by sharing data, breaking up order batches, and stabilizing prices. At the end of class, the Beer game was introduced. I look forward in participating in the simulation in upcoming classes.

This week we learned about Bullwhip Effect and IOT. The bullwhip effect is when distorted information goes from one end of the supply chain to another and creates a fluctuation in how the various entities behave. Also, how IOT is an important factor that would allow inventory to be automated which would, in the long run, help the nurses/ hospital efficiency.