Ready to write Python code 4x faster?
The Mito report process will end up saving my team and I countless hours during the year with the ability to take complex reporting data and turn it into useable information for our Stakeholders. We’re able to automate complex reporting structures. Now we can easily run a script to give us a neat, concise report that we can give to our key stakeholders. One of the things we don’t have is extra time and we are never sure when we will be asked to produce this data. - Margaret, Vice President.
The special events team hosts conferences throughout the year. Once inivitations are sent out, Margaret, Olivia, and John track RSVPs so that each business unit’s key stakeholder, typically a Managing Director, can follow up with people they’ve invited, keep facilitators in the loop, and make sure that all attendees are approved for the sessions they’ve registered for.
Every Monday, Wednesday, and Friday, Margaret, Olivia, and John spend 45 minutes to an hour updating their RSVP reports and sharing them with key stakeholders within the firm. Because hundreds of invites are sent out, response numbers can change in just a couple of hours, making reports go stale fast. It’s common for the registration team to get requests throughout the week asking them for a new run of the report outside of their typical M/W/F cadence.
Generating the Report in Excel
The first report that the Special Events team automated tracked the number of in-person vs. virtual attendees broken out by attendee category.
To create it, Margaret would log into Eventbrite, the conference management system, download the most up to date registration data as an Excel file, and build the report manually.
Because the data exported from Eventbrite breaks the attendees into 35 different attendee types, the data is too granular to easily consume. Margaret goes through row by row and buckets the data into more sensible chunks: Speaker, Limited Partner, General Attendance, VIP, etc.
This bucketing and consolidation process is where she spends the bulk of her time building each report.
Automating the process with Mito
Since Margaret, Olivia, and John had never used Python before, they decided to use Mito to automate their reporting. Mito is a spreadsheet that generates the equivalent Python code for every edit to the spreadsheet, so Margaret, Olivia, and John were able to generate a Python script largely the same way that they built their report in Excel each time — using spreadsheet functionality!
The events team built a script that imports the Eventbrite data, buckets the responses, and downloads an Excel file just like the one they created manually.
Automating this report increased efficiency exponentially. Since generating the report is such a fast process now, I can pull the updated report a few minutes before our meeting so the numbers we look at are up to date. Previously, I had to pull the data and manipulate different registration breakouts from internal vs external invitees, in person vs virtual. The whole thing was a very manual and time consuming. — Olivia, Associate.
Now, each time they need to recreate the report, it takes less than a minute!
Automating More Reports
In the two weeks since Margaret, Olivia, and John automated their first Excel report, they’ve since automated two more, saving themselves close to seven hours a week of repetitive report generation. And other special events teams across the firm have built their own Python automations using Mito.
More Like This
Automating Spreadsheets with Python 101
How to tell the difference between a good and bad Python automation target.
10 Mistakes To Look Out For When Transitioning from Excel To Python
10 Common Mistakes for new programmers transitioning from Excel to Python
Research shows Mito speeds up by 400%
We're always on the hunt for tools that improve our efficiency at work. Tools that let us accomplish more with less time, money, and resources.
3 Rules for Choosing Between SQL and Python
Analysts at the world's top banks are automating their manual Excel work so they can spend less time creating baseline reports, and more time building new analyses that push the company forward.