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SAPAnalyticsCloud_Using_ERPsim_Exercises_FinalMay2019-11.doc.pdf

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Product SAP Analytics Cloud Level Undergraduate Graduate Beginner Focus Data Analysis Authors Nitin Kalé Modified May 2019 Dr. Ed Lindoo Version 1.0

Motivation Many courses at SAP University Alliances member schools use ERP Simulation Game to introduce students to the role of integrated business processes using a business simulation game. This game simulates a commodity market wherein teams have to plan, procure, produce and sell products in a competitive environment. The goal is to strategize and run their company for profit maximization. The game is played in the SAP ERP system while an external simulator simulates the dynamic market and all the variables that influence the game. This exercise can be used during or at the end of the game to analyze game data.

PREREQUISITES Before you use this case study, you need to have an SAP Analytics Cloud account. Please follow the instructions later in this case study to request an SAP Analytics Cloud account.

The human visual system has evolved to be particularly good at recognizing patterns. Data visualization has become a standard analytical tool which capitalizes on the ability of humans to recognize patterns within massive quantities of multi-dimensional data generated by business information systems. Many scientific studies have led to the creation of visualization models that utilize human perception and cognition.

When the number of dimensions is small, we can use standard graphing techniques for visualization e.g. bar charts, line charts, histograms, pie charts and scatter plots.

When the number of dimensions is large, there are several novel techniques for visualizing such data. They are categorized into the following major areas 1 – For more information on these visualization techniques, please refer to the journal reference in the footnote.

A. Pixel-oriented Techniques a. Space filling curves b. Recursive pattern c. Snake-Spiral d. Circle segments

B. Geometric Projection Techniques a. Parallel coordinates b. Scatter plot matrix c. Hyperbox d. Trellis display e. Self-organizing maps

C. Icon-based Techniques a. Star glyphs b. Color icons c. Stick figures d. Chernoff faces

D. Hierarchical and Graph-based Techniques a. Dimensional stacking b. Cone trees c. Mosaic plots d. Fractal foam

1. The ERPSim game is played by teams over several rounds (up to 8 rounds of 30 virtual days each). They sell up to six products at a time from a possible 12 products that the market

1 Keim D. A., Kriegel H.-P. Visualization Techniques for Mining Large Databases: A Comparison , Transactions on Knowledge and Data Engineering, Vol. 8, No. 6, Dec. 1996, pp. 923-938.

Data Visualization

Data Visualization for ERPsim

consumes. The products are all muesli cereal2 in various flavors and box sizes. The teams must forecast demand, run MRP, procure, produce, price and market their products for sale.

2. Figure 1 shows the entire cash to cash cycle in the game. The transactions in bold are decision points that teams must make and execute. They are considered strategic in nature. The transactions that are gray are considered operational in nature. They are automated by the simulator. Additionally, teams can run analytical reports at various points in the game to monitor and strategize.

Figure 1

3. Data from an actual game have been extracted from SAP ERP and stored in an Access database. Then queries have been written to report important findings. The results have been exported to Excel.

4. Your job is to analyze these results as requested in the following assignment

2 http://en.wikipedia.org/wiki/Muesli © SAP AG Page 3

We will now use SAP Business Analytics.

1. Launch Google Chrome. If you don’t have it, install it as it’s the only browser that work well.

2. Click the link below to go to SAP Cloud Analytics https://higher-education.us10.sapanalytics.cloud (Note: if your browser does not default to Chrome, you will need to copy the URL and paste it into Chrome)

3. You now see a screen that looks like this:

The first time you come here you’ll need to click the Register button to get the following screen:

Be sure to register with your Nova email address. Any email other than Nova are wiped from the system on a weekly basis!

4. After you register, you’ll get a screen that looks like this:

Using SAP Business Analytics

https://higher-education.us10.sapanalytics.cloud/

Note that it sends an email to your Nova email account for verification.

5. Here’s the email that you should get. Just click on the button to activate your account.

You’ll be taken to a screen that looks like this:

Click the Continue button to get the following screen.

You’re taken to this profile page where you can tweak things if you want to (optional). Now, log out from the profile page and go back to the sign in page:

https://higher-education.us10.sapanalytics.cloud Sign in with your Nova email and password that you created. BE SURE TO WRITE YOUR PASSWORD DOWN!

6. Once the system loads, in the top left corner of the screen click on the 3 little bars (Next to

Home):

a. Click Create, then Story

b. Next, click on Add a Canvas Page

Next click on Chart

https://higher-education.us10.sapanalytics.cloud/

c. Models have already been created for us and are found in the Public folder.

Click on the Public folder and you’ll see a screen that looks like this:

Now click on Models

Select ERPsim Dataset

d. You are now ready to begin charting! 7. Choosing measures and dimensions

a. What is a measure? A measure is a field on which calculations can be made. These are fields of business interest for analytics. e.g. revenue, profit, quantity sold. The calculations can sum, min, max, average, count etc. Measures are also called key figures or facts.

b. What is a dimension? A dimension is reference information about a measure. It provides context for the measures. E.g. customer, time, product. Revenue by customer is an example of how you would report a measure by a dimension.

Figure 2

1. Interface a. Look towards the top right of the screen. See the boxes labeled Comparison, Trend,

Distribution, etc.? These allow you to change to various types of charts. Select the bar chart.

b. Add Revenue to the Measures and Product to the Dimensions c. You will now see a screen that looks like this:

d. Play around with some of the controls like sorting. Hover over the Product line within

dimensions. You’ll see a filter icon pop up. Change the filter to look only for 1kg items. e. Add team to color and see what happens. f. Explore, have fun and get used to the system before moving on.

2. We are now ready to manipulate and visualize this data

a. Several charting options are available for visualization on the right side of the screen – bars, lines, pies, geographic, scatter/bubble, maps, radar, tag cloud etc.

b. Using the appropriate charting technique, answer the following questions. Hints are provided for each question.

NOTE: Log off and back on before you begin the exercises below to ensure that all the filters and settings you applied above in testing are gone!

Note, each question is worth 10 pts.

Exercises

Analytics Cloud 1 – Revenue by Team

Question: Which team had the highest revenue? What was the revenue? Time 10 min

Hint: Use a column chart. From Measures, drag Revenue into Y-Axis, from Dimensions, drag Team into Y-Axis. Find the sort tool next to the database name and change Sort of revenue to descending. Use Save to save the visualization as Q1. You do not need to submit a screen shot, just place your answers below.

Analytics Cloud 2 – Revenue by Product

Question: What product had the highest revenue? What was the revenue? Time 10 min Zeist 10 Min.

Hint: Use a column chart. Y-Axis – Revenue, X-axis – Product. Save As Q2. You do not need to submit a screen shot, just place your answers below.

Analytics Cloud 3 – Revenue by Team and Round

Question: Display the trend of revenue over rounds for each team. Time 10 min

Hint: Use a line chart. Y-Axis – Revenue, X-Axis – Round, Legend Color – Team. For this answer you do need to submit a screen shot. Alt-PrntScrn on some computers will copy the screen to the clipboard, you can then paste it into this document. If that doesn’t work you can save this as Q3. Then use the back arrow to get the main screen where you see Q3 has been saved. Click on that and when it comes up you can right click on it and save the picture to your computer. Once it’s saved to your computer you can launch it and typically copy/paste into this document. just place your answers below. If that doesn’t work, try a screen capture program.

Analytics Cloud 4 – Revenue by Team and Product

Question: What is the market share of each team by product? Time 10 min

Hint: Use a Column chart. X-Axis – Revenue, Y-Axis – Product, Trellis Rows: Team, Save as Q4. For this answer you need to submit a screen shot. A screen shot of just the first team is all that is needed here.

Analytics Cloud 5 – Revenue by Distribution Channel and Product

Question: Are there any products that don’t sell in specific distribution channels? Time 10 min

Hint: Use a heat map. Area Color – Revenue, Area Name – Distribution Channel & Area Name2 – Product. Save as Q5. For this answer you need to submit a screen shot.

Analytics Cloud 6 – Price by Product and Team

Question: What was the highest price paid for 1kg Raisin Muesli? Which team sold the most expensive Muesli? What did team MM sell the Muesli for? Time 10 min

Hint: Use a column chart. Y-Axis –Price, X-Axis – Team. Legend Color – Product. In the resulting chart, add a rank of top 1 for product. Save as Q6. A screen shot is not needed here, just your 3 answers.

Analytics Cloud 7 – Quantity by Team and Product

Question: Which team sold the most quantity of muesli? For that team, what was the most sold product and for how much? Time 10 min

Hint: Use a tree map (under Heat Map). Area Weight – Quantity, Area Name – Team. Click on the team with the highest number and select filter. Next, add Product to Area Name. What was the largest quantity that this team sold? What was the name of this product? No screen shot necessary, just your two answers. Save as Q7.

Analytics Cloud 8 – Revenue and Price by Product

Question: What three products have high price and high revenue? Time 10 min

Hint: Use a Bubble chart. Measures: Y-axis: Quantity. X-axis: Price. Color: Product, Bubble Width: Revenue. Be sure there are no filters applied. Save as Q8. No screen shot necessary, just your three answers.

Analytics Cloud 9 – Highest revenue on a day

Question: Show the days on which individual teams did not have any revenue. What team made the highest revenue on a single day (which round)? Time 10 min

Hint: Use a Heat Map. Measures: Color: Revenue. Dimensions: X Axis: Round and Team. Dimensions: Y Axis: Day. Save as Q9. Here we need a screen shot of your results which should look like a lot of light green and dark green squares. Don’t forget to write your answer to the second part of the question.

Analytics Cloud 10 – Highest revenue for a product on a single day

Question: What product on what day and round brought the highest revenue (for which team)?

Time 10 min

No Hint! Save as Q10. Screen shot not needed, just your answers.