Select Page

This blog series aims to introduce Tableau parameters and demonstrate how to use them in data analytics. First, we will establish what parameters are, and why they are an indispensable tool in self-service analytics. Then, we will use three use cases to illustrate how parameters can solve business problems.

#### Content

1. What is a Tableau Parameter
2. Why are Parameters Important
3. Use Cases:
• Dynamic Benchmarking (Part I)
• Payback Period Sensitivity Analysis (Part II)
• Dynamic Moving Average (Part III)

In the previous blog, we discussed why parameters are an indispensable tool for dynamically enriching business insights. We also illustrated how we can use parameters to solve business problems through the Dynamic Benchmarking example. In this blog, we will continue our journey and perform a Sensitivity Analysis on Payback Period. More specifically, we will demonstrate how to use parameters to reflect the effect of changing assumptions on investment decisions.

#### 3. Use Cases

##### 3.2 Payback Period Sensitivity Analysis

Companies frequently make investment decisions, from bidding for another business to procuring a new CRM software. It is rarely the case that there is only a single investment option, instead there are often multiple candidates to choose from. Some of the popular methods for comparing different investment options include, the Internal Rate of Return (IRR), Return on Investment (ROI) and Payback Period. The payback period is the length of time an investment reaches a breakeven point. Therefore, the shorter payback, the more attractive the investment.

The problem is that payback periods are calculated based on the total investment cost and the average cash inflows, which are all assumptions. Should any assumptions change, for example, a decrease in average cash inflows, our estimate for the payback period will change. Can we quickly test different assumptions without having to go back to our data set and alter the values each time?

###### The Solution:

We can replace static values in the assumptions with parameters. We can then test the sensitivity of our assumptions by adjusting the value of parameters.

###### Step 1: Creating a dummy data table

The values in the Avg. Cashflow per month and Initial Investment fields are not important, as they will be replaced with parameter values. The important thing is to create the Project field that indicates which investment projects we will be comparing.

###### Step 2: Creating an Initial Investment Parameter for Each Investment Option
1. Right click on an empty space in the Data Pane, and select Create Parameter. (Please refer to Part I for more details)
2. In the Edit Parameter window that pops up, configure the setting as below. We will set the minimum to 0 (as we cannot have negative investments).
3. After creating the parameter for Option A, right click on it and select Show Parameter.
4. Repeat the same steps for Investment Option B and Option C.

###### Step 3: Creating a Monthly Cashflow Parameter for Each Investment Option
1. Right click on an empty space in the Data Pane, and select Create Parameter. (Please refer to Part I for more details)
2. In the Edit Parameter window that pops up, configure the setting as below. Again, we will set the minimum to 0 (as it doesn’t make sense to have negative cashflows in this scenario).
3. After creating the Monthly Cashflow parameter for Option A, right click on it and select Show Parameter.
4. Repeat the same steps for Investment Option B and Option C.

###### Step 4: Creating a Calculated Field that Calculates the Payback Period Based on the Parameters

Just by creating a parameter will not make our charts dynamic, we need to relate the created parameters to some other tools or functions in the Viz.

1. We are calculating each Investment Option’s Payback Period by dividing its Initial Investment Parameter by its Monthly Cashflow Parameter. This will return the number of months needed to breakeven.

###### Step 5: Creating the Bar Chart for Displaying the Payback Periods
1. Drag the Project pill onto the Columns shelf and the Payback Period calculated field onto the Rows shelf.
2. Colour by Project to make the projects easier to distinguish.
3. Drag Payback Period onto the Label Marks Card.

###### Final Viz in action:

When our assumptions change, we can simply update the Initial Investment and Monthly Cashflow parameters with the new values. The payback periods will be recalculated with these updated values, and the bar chart will be updated automatically!

In Part III of this series, we will demonstrate how parameters can help reduce noise and strengthen our insights on time series data. See you there!

##### Author: Martin Ding

Martin earned his Honours degree in Economics at the University of Melbourne in 2011. He has more than 7 years of experience in product development, both as an entrepreneur and as a project manager in robotics at an AI unicorn. Martin is expecting to receive his Master’s degree in Data Science from CU Boulder at the end of 2022. Martin is excited about data and it’s power to transform organizations. He witnessed at first hand of how instrumental data driven decision making (DDDM) was in leading to more team buy-in and insightful decisions. Martin joined the Data School to systematically enhance his knowledge of the tools, methodologies and know-how of Data Analytics and DDDM. When not working, Martin enjoys readings, cooking, traveling and golf. He also thoroughly interested in the practice of mindfulness and meditation.