In this “how to” post, we will review how to use our Table Explorer table chaining function in SEC documents, as well as the major updates we integrated with our recent v3.9 release.
Broadly speaking, you can do a LOT with tables in Sentieo.
- Export one or all document tables into Excel
- Search only within table (s) using our popular “in:table” shortcut
- See side-by-side historical tables (very useful for annual filings like proxy statements)
- Export PPT/PDF tables to Excel
But none of these functionalities come close to what Table Explorer can do. Table Explorer uses a machine learning model to identify, chain, and visualize reported data. This is done in an auditable, transparent fashion, with added one-click flexibility for elements such as YoY and QoQ changes, common size statement conversion, and more. Analysts save countless hours with this ability to quickly chain tables, as well as visualize data and trends.
We will start with a simple example: the income statement. Table Explorer chains either 8-Ks, or 10-Qs/10-Ks. Since Q4s are not always reported, we create “synthetic” Q4 statements with one click. We use Adobe’s income statement as an example. Watch the video to find out more.
In this second video, we cover the balance sheet. Similar to the income statement video above, we have an easy adjustment for Q4 balances. We go over the Netflix balance sheet, starting with their most recent filing.
In this next video, we cover the cash flow statement. Cash flow statements are often presented in a cumulative fashion: 3-month in Q1, 6-month in Q2, 9-month in Q3, and 12-month in Q4. In this specific example, we use Mondelez International, the global snacking giant. We convert to quarterly with just one click. (We even came up with a new word for this function: “to quarterize”).
Table X does not stop here. You can export your chained data to Excel and to our data visualization tool, Plotter, for further work. You can save the data into your Sentieo Notebook to add to a full thesis.
The video below reviews these steps. We extract and chain Adobe’s income statement, convert it to “common size,” then visualize and export the percentage split of service vs. product revenues for the company. We then export to our main data visualization tool Plotter, where we overlay two of the thousands of data sets included in Sentieo, and finally, we save the chart in our Notebook for use in our full-blown thesis on the company.
Table X works on other tables too. For example, you can extract your own KPIs or any other table-based data. While some KPIs might be available from the standardized data providers, not all are, and extracting your own means greater confidence in your data through our on-screen auditing function. In this fifth video, we show you how. We extract and chain Chipotle’s KPI tables, and we quickly visualize the trends in average unit volumes and comparable store sales.
After Table X was released to rave reviews earlier this year, the number one request was handling line item renaming. With the latest product release, we created a Row Merge/Demerge capability to address this workflow. We show you how in this video. In the example here, Crocs, a footwear company with a wholesale and a retail business, reports a quarterly store count by geographic region. However, the company changed its line item name from “Europe” to “EMEA” recently, creating a discontinuity in this specific data set. We show how to merge the two rows and how to check that the mapping is correct.
In the final, and most technical, video we show you how Table X handles a specific type of table called a “roll-forward” table. A standard use case for this is a company reporting a change in balance over the quarter, where we have the starting balance on top of the table, any changes below that, and then we have the ending balance at the bottom. In this specific example, we chain Chipotle’s unit openings/closings table from their 10-Qs and 10-Ks, and then make a few quick adjustments to add a Q4 column with the correct starting/ending balance, and intra-quarter additions. We also demonstrate the importance of visualizations. Unit openings are clustered in Q4, and this plays a role in forecasting the annual revenues due to the backend loading.
To find out more about Sentieo’s Table Explorer, or any of the other features in our complete workflow research platform, please get in touch with us.