In trying to understand political trends in the U.S., I sometimes default to creating maps. They are beautiful visualizations of voting results. But sometimes maps provide a snapshot of one election or one period in time in a way that does not facilitate viewing trends over time.

Here is an example, looking at each state’s delegation in Congress after the 2018 midterms (limiting it to the Lower 48 for the moment):

The nice feature of this visual is that it is in a format we know (map) and clearly shows the red and blue sections of the country. But if…

With the upcoming midterm elections, I have seen a lot of discussion about turnout and the impact it will have on the election results. With that in mind, I wanted to take a look at a state that had a close result in 2016, and see just how much a difference turnout may have made. While finalizing this, just in the last couple of days, I have read articles citing the approve/disapprove polling for President Trump amongst black voters, and also regarding gerrymandering and claimed voter suppression tactics in Michigan. …

In my last story on a time series of strikeouts in baseball, I noted that one potential explanatory factor for the increase in strikeouts over time is the introduction of specialty pitchers. The hypothesis is that tired starters are being removed earlier in games and fresh relief arms brought into games. I threatened another post to consider this hypothesis, and here it is!

First, for this analysis, the summary-level MLB data won’t suffice, as we will want to look at strikeouts by inning (rather then just in aggregate) to determine:

(1) do starters get strikeouts more or less frequently than…

What is more fun than data analysis? Data analysis with baseball trend data, that’s what! It is being said this year that most Major League Baseball at bats are ending in either a strikeout or a home run. That is an exaggeration, of course, but it does seem to be true that these two outcomes are becoming increasingly common for at bats. I was wondering if the strikeout trend was even true and, if so, when this trend may have started. Using the Lahman database, let’s look at the history.

First, let’s look at our raw data showing the number…

In my previous post on pricing, I showed a way to dramatically reduce the analysis required for a pricing decision. In this post, we will take it a step further and show that, in a significantly more complex example, we can still simplify the decision-making process. As an added bonus (!), we can generalize our result to something that makes intuitive sense and can be applied to quickly generate scenario analyses where needed.

Recall our example where we manufacture cars. We have a high-end offering priced at $40,000. The margin we earn on each sale is $4,000. Now we are…

You have been there. You create a Salesforce report with killer content only to be underwhelmed by the report formatting options in Salesforce itself. Some folks may have paid for add-ons to make the formatting of these reports more automated. You may be using Tableau to import the data and make the output more visual and elegant. You can try XL-Connector or G-Connector for Salesforce, which will allow you to retrieve your report right into Excel or Google Sheets, and keep the formatting consistent from retrieve to retrieve. I have had good luck with both of these.

Another approach I…

In many years of working with business teams, I have seen them spend countless hours making their pricing analyses more and more precise. More and more insights and analytics are demanded, assumptions questioned and tested, and often results are nonetheless doubted in the end. Not to mention that slow action hurts performance in many industries. I propose that the solution to this is not intuitive — to get at a higher quality answer, the prescription is ironically to be less precise and flip the analysis around to spend more of the value-added time of your decision-makers actually discussing the current…

Stuart Zussman

Finance professional passionate about technology and building scalable processes

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