Weekly Question #1: Complete by May 19, 2017

Leave your response as a comment on this post by May 19, 2017. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your opinions, not so much particular “facts” from the class!

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Here is the question:

Give an example in your own experience where you saw raw data turned into information.

23 Responses to Weekly Question #1: Complete by May 19, 2017

  • I work at the Ritz Carlton as a valet supervisor. We enter tickets into our system with the type of car, the name of the guest, and license plate of the car. When the guest requests their car we use the ticket number to bring all this information together to make it useful.

    • Do any of those characteristics determine what parking spot you put them in? Closer or further from the hotel, etc.?

  • Hi Everyone!

    I worked for quite a few years as a Purchasing Manager. This is where I learned the importance and power of data. My company collected as much data as possible from sales to contacts to employees. In the purchasing department we would take the raw sales data and forecast projected sales for specific periods of times. The goal was to efficiently stock our shelves with the right mix of products. Data that had to be combined was current sales data, historical sales data, market expectations, weather expectations, car registration data, and competitive product data. This data was analyzed through various parameters, which allowed the company to produce the information of the parts and quantities should be stocked in each location of our company, while minimizing total inventory costs. This information allowed the company to dominate the competition as we always had the right part at the right time when our customers requested it.

    Have a great week!


  • I am currently working at Starbucks, and learned much about the menu. One of our most popular drinks is the caramel macchiato. When first timers come in, and ask which drink to get, I tell them to get the caramel macchiato because of the data I’ve observed from working. Most of the time, those first timers end up loving the drink.

  • I worked in SIMO Coffee as a cashier & waiter. One of important thing in my daily works is talking with customers and helping them order the the menu. When customers finish their dishes, I need to talk with them again and get their feedback about our food and service. Then, I will type the basic information about the customer like their favorite dish, whether they like spicy or not, and so on. All these information will finally comes into the database, and when next time the same customer comes, we can make some preparatory works.
    Hanqing Zhou

  • Hello! I used to work at a small bagel shop back at home called 3 Men & a Bagel. Last summer we opened up a new location. Looking at the register totals for each day of the week (raw data) we realized that this location was busiest on Thursdays & Fridays (information). Using this information, my manager put an extra person on shift for every Thursday & Friday to make sure we were prepared to serve the increased number of customers on those days.
    Daria Gbor

  • The most common times I have been able to see raw data used for information is when using GPS on my phone. Just by having the location on, Google is able to tell what locations I visit and how many times I have visited that specific location, even the days of the week that I frequent to the said location. Google also uses this information to notify me of alternate routes to use to get to certain locations, traffic delays, and recommends (or advertises) other places that are similar to the locations I visit. Sometimes it will even ask me to write a review on restaurants I ate at or attractions I visited. Watching just one little source of data used for loads of greater information is both incredible and scary. They know our patterns and where we are at all times by the use of a cell phone.

  • I work at an engineering firm and sometimes work with our marketing department when trying to quantify some of the marketing efforts. We gather information from social media, such as how many likes, shares, etc we receive and try to find trends in what we are doing that causes these numbers to fluctuate. For example: if we received more traction on twitter this month than previous months is it because we have more followers, we shared more articles, shared more industry specific content, or shared photos. Using these patterns helps to inform for future decisions on what is posted.

  • I am currently working as a manager for a call center and we use metrics on a daily basis to analyze call times, hold times, transfer calls, phone monitoring protocols and scores, reason for the call, resolution, scheduling and a slew of other pieces of hard data. All this data is collected on a monthly basis either by manually monitoring recorded or live calls, the automated phone system or our CRM software. The values are then transferred onto Excel spreadsheets and rules are made within it to organize and sort the data by other software systems. Eventually, I get a simplified version of this hard data with pretty charts and graphs that visualize the data into a more understandable piece of information. The process for analysis has then begun.

  • I was Marketing major in a China’s University. Sometimes I had to do some marketing analysis. For example, one time we did a project about wedding markets. We ran into lots of wedding dress stores in two cities. We interviewed the managers about selling history. Finally, we used this data as well as what we got from questionares to make many charts. These charts is better for viewing and understanding.

  • I currently work at T-Mobile and when pre-ordering the newest device for a customer it generates an order number. When searching that order number in our ‘order number lookup’ tool, it will display the customers name, account number, phone number, email address, make and model of the device, when the order was created, if the order was cancelled/processed/shipped, and an estimate of the delivery date.

  • I work at an afterschool that teaches karate and dance, we use data and information there everyday to keep up with all the different kids schedules. On an average day we pick up around 40 kids who come from 4 different schools. The kids ages range from 5 to 13 and they all attend different karate or dance classes. We have all the kids data stored into our computer/phones which includes different kids ages, belt level, and what type of classes they take. Using the data we have in our computer we are able to turn it into information and send the kids to their classes without a problem everyday. It is important to turn the data into information because their are 8 classes a day and it is impossible to remember who goes to which class.

  • I complete hourly rounds at work and when completing them, I am able to see previous round reports that outline the busier parts of the day or of the week. And this is helpful to delineate tasks on future days in terms of scheduling and helping to create an efficient process for room set-ups and room flips.

  • Something that I like to splurge on is make up; so when I started spending more money on it, I decided to become a member at Ulta. By doing this, I got a membership card that I would get scanned every time I made a purchase and it would track what I would buy and accumulate points. This would in turn then give me personalized coupons. Once I started building an account there with my purchase data, I started to get more personalized discounts and coupons on the products I frequently bought, in the mail. I also would get weekly email recommendations of other products “they think I would like.” I think it is really interesting how just from tracking my purchase history this company can keep making money off me by giving me coupons and discounts. By doing so they are ensuring that I will come back into the store to buy more. Really interesting when you think about it.
    -Nina Sjostrom

  • A example of raw data being turned into information that I experience is also one that many people experience as well, completing a FAFSA application. In said application, I, as well as most others, need to input numbers that represent several categories of information. These types of information include Social Security numbers, tax returns, bank statements, and investments and this information is used to determine one’s eligibility of receiving financial aid.

  • I worked at a sneaker company called Kicks USA. one thing they did was introduce scan machines on the sales floor where customers could use it themselves to scan merchandise. this helped the store track the combination of sneakers customers like in a certain area so they can purchase more of what they should buy, also tracked inventory much faster than doing it physically. this alerts managers when inventory is running low so they can restock and not lose potential sales

  • I worked at a pizza shop that held raw data that specified the number of sold of pizzas, cheesesteaks, or any various item on the menu throughout the day. It also held a list of the time in which these items were sold. This gave the managers and the owners an insight on which food item needed to be improved or better advertised. Also, there was raw data taken at the delivery locations. With this data, the managers and the owners decided where the menus needed to be dropped off more frequently. It was extremely important for the pizza shop to use this data in order to succeed.

  • I currently work at a tanning salon and we have unique sales codes for each of our products. At least once a month, we see how many of each product sold and use that data to make decisions on what to order more of and what to discontinue selling at our salon. If a product doesn’t seem to be selling, we discount it and advertise that it’s on sale. We do this because the tanning lotions go bad after a certain amount of time and it’s important to sell them so that we don’t end up losing money on the product.

  • As part of a Quality Assurance team for a major bank I was tasked with finding the root cause of incorrect loan bookings across the entire footprint. The data I had at my disposal included a large trial balance listing all of the fixed details about a loan- such as the customer name, the lender who closed the loan, the bank region in which it was booked, etc- as well as a ledger history of all transactions that occurred across all bank loans. By linking the transactional data, which signified corrections to a loan, to a particular region or type of loan, we were able to identify lending regions or loan types which were causing the greatest cost in post-loan-closing operations. This provided an opportunity to improve a process or give additional training where needed. It was amazing to see how by itself, the transactional data did not tell a great story, but when linked together into categories, a real pattern became apparent.

  • In my customer data analytics class, we analyzed raw data to determine which customers we should market to, by utilizing SPSS. We also created decision trees to group customers into different segments, and used the data collected about the number of orders, number of customers, and other demographics like age, gender, and purchased products to determine which subgroup was unprofitable. Another example of raw data turned into information, is when i visit a website or view a product online, google analyzes this data to determine which advertisements would target me best, so I get to see an ad about a product I’ve viewed when I surf the internet at a later time.

    • I am currently working with a company called Don Guanella Village as Applied Behaviour Analysis (ABA). We basically monitor our client’s’ behaviors and collect raw data base on our observations with respect to the individual’s program goals. At the end of every shift, these raw datas are posted in the system for further processing. The system will then accrue all of the raw data posted during the period . At the end of the period, the data detective will analyze them and transform them into meaningful information that will help us to provide services that will better help our clients. They also help us to make critical decision that will improve our consumers goals.

  • I worked as a food prepper a couple summers ago at a country club that hosted a lot of events. In the beginning of the summer we were testing out a new menu and would put out all of the new items in each banquet. At the end of the banquet we would see which food was eaten the most and least. About a month in we used that data to help us understand what the customers liked and didn’t like and would make more of one item than another.

  • I used to work in the United States Navy. I dealt with mine countermeasures. One of the jobs that had to be completed was the review of waterway maps that were captured by sonar. People would look over many different maps of an area to find all abnormalities that could possibly be a mine. From this list it was then reviewed by a computer program that would narrow the list even further. From here we would investigate the possible mine points and either mark the area clear or dispose of the mines in the proper manner.

  • When I use music app to play music, it collects datas about songs I listened. For example, type of the music, artist of the music, and language of the music. The app finds the same song that I liked in other users’ playlist, and it assumes I might like songs from that user’s playlist. Based on the data it collected from me and datas it collected from other users, it fromed a list of songs that I may like everyday. The more songs I liked the more accurate the list will be. This is what I experienced on how raw data turned into information.

  • In my own experiences I have seen raw data turned into information for my baseball team. Every at-bat and out are kept during each game. This is then turned into statistics of each player which include batting average, on base percentage, ect. This information helps coaches make decisions on when and where to play players during the game.

  • I see raw data turned into information through the wine classes at my job. When we taste the wine we pick out all the different attributes of the wine; the color, the transparency, the tannins, the types of prominent fruit we smell/taste, the types of prominent spices we smell/taste, the legs of the wine, and so forth. Taking all of these random characteristics about the wine we are able to pieces them all together to determine the alcohol content, the varietal, whether it is an old world or new world wine, the region, and some can even tell the age of the wine. I thought this was a fun example because it is a little different but shows that data analytics can really be utilized everywhere.

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