Achieving targets
1. Achieving targets
The exercises in this lesson will help our general manager answer two main questions. First, we will look at two ways to break down who played at which position in a given year. Second, we will look at ways to see if the team is on track for meeting certain expectations. Let’s start by looking at two types of visuals which show shares of a whole. We’ll focus in on the 2013 Seattle Mariners, setting one filter where the year is 2013 and a second filter where the franchise is Seattle. For our first visual, I will add a pie chart of stolen bases by player. Seattle had a very small number of stolen bases that year but enough people stole at least one base that it’s hard to see much here. If we change this to a treemap, it’s a little easier to see relative share sizes, though I need more space to make it clear. I can add stolen base counts by enabling data labels on the format menu. This is an okay use of a treemap, but the best use of one is to work with hierarchical, categorical data. Each of these players played at some position, so if I add that position to “Group,” above name and team, then we can shrink the size of the treemap and still get nice fidelity. Let’s add a table. This table will include name and team, as well as number of stolen bases. Now that I’ve done that, let’s continue. Enable Drill Mode by selecting the single down arrow. When Drill Mode is active, selecting a level will drill down and expand all elements in that level. If I select outfielders, I get just the people who played in the outfield. Next, let’s add a gauge. A gauge needs a value, like batting average. To make best use of a gauge, you also want a target and a maximum value. I’ll create a new target measure of Great AVG = 0.270. The best a team can realistically hit is 0.300, so let’s create another measure, Max AVG, and set it to that value. Putting these measures where they belong, it’s clear that Seattle outfielders were not great at batting in 2013. Let’s now perform some conditional formatting. Suppose I want to change the font color on the table to red for any player with 10 or more stolen bases. For tables, I can navigate to Conditional formatting, enable it for font color, and I get to make some choices. I’ll choose “Rule” from the drop-down list and set the field to stolen bases. I’ll say at least 10 stolen bases and fewer than 200--the single-season record is 138, so that’s a safe number to choose. Now Michael Saunders shows up as red. If I navigate up and sort by stolen bases, we can see that he’s the only player with 10 stolen bases that year. Key Performance Indicators, or KPIs, track performance over time versus expectations. Let’s create a new page and see how they work. I’ll add a filter on the Seattle Mariners franchise for all years 1969 and forward, as that was when the team joined the league. Next, I’ll add a new KPI visual. We’ll use batting average as the indicator, year as the trend axis, and our great batting average as the target goal. We can see that the team did not meet that goal in 2020--they were terrible, batting just .226 as a team. Let’s add another KPI, this time looking at stolen bases versus caught stealing. A 2:1 ratio of stolen bases versus caught stealing is great, so let’s create a target caught stealing percentage of 0.5, that is, no more than 1 caught stealing per 2 stolen bases. I’ll also create a measure for caught stealing percentage. Drag those measures on and it looks bad, but that’s not quite right. Their ratio of stolen bases to caught stealing was better than 3:1, but we show that as a bad thing! To fix that, navigate to the format menu, select color coding, and change the direction to “Low is good.” Now we can see that the 2020 Mariners were on the right side of that measure. We’ve looked at a lot here. Now it’s your turn to try things out.2. Let's practice!
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