Most campaigns view polling data, logistics, and demographics as fundamental to winning an election. More likely, data science and cloud computing will win the day. Credit: Parker Johnson / Markus Spiske A year ago I wrote about the importance of leveraging cloud computing and data science to win elections, pointing to the 2020 campaigns, which come to a conclusion today. The basic assertion was that technology, focusing on the true meaning of data, would count more than traditional robocalls and door-to-door campaigning, since you’re able to understand more about the electorate, and thus target more effectively. The campaigns won’t let you talk to their data nerds, but they all have them. Data science approaches and the use of cloud computing allow the campaigns to come to some hidden conclusions that can boost their candidate’s chances. Sophisticated calculations and analytics are able to derive patterns in the data that those viewing the data in traditional ways won’t see. For example, data science can find undecided voters who are likely to vote for a particular candidate and come up with a motivation for them to vote. It can tap into opposition to a local bill that really has nothing to do with the federal election, and use that issue in the messaging to get another 10 percent of undecided voters, with more than 80 percent of them voting for your candidate. Compare this precision versus a “spray-and-prey” approach where you blast out messaging and hope it hits a few undecided voters. A human brain can’t find these types of patterns in the data. You need advanced analytics that use machine learning to find things you did not know existed. The ability to weaponize massive amounts of seemingly innocuous data is something that was nice to have back in 2012, but in 2020 it’s mandatory to put more odds in your favor. Modern campaigning is really about data wars and strategic targeting of voters rather than promoting ideas. In this world, ideas are dynamic; how the campaign messaging is viewed depends on who the campaign wants to view it. You may see a different message than your neighbor does. Deep analytics and AI have discerned that you and your neighbor are motivated by different issues, so you are each given different messages to drive your behaviors. The result: The campaign with the best data science approaches and the ability to leverage cloud computing as a force multiplier will likely win. I’m not sure this what the Founding Fathers saw coming, but here it is. Related content analysis 7 steps to improve analytics for data-driven organizations Effective data-driven decision-making requires good tools, high-quality data, efficient processes, and prepared people. Here’s how to achieve it. By Isaac Sacolick Jul 01, 2024 10 mins Analytics news Maker of RStudio launches new R and Python IDE Posit, formerly RStudio, has released a beta of Positron, a ‘next generation’ data science development environment based on Visual Studio Code. By Sharon Machlis Jun 27, 2024 3 mins Integrated Development Environments Python R Language feature 4 highlights from EDB Postgres AI New platform product supports transactional, analytical, and AI workloads. By Aislinn Shea Wright Jun 13, 2024 6 mins PostgreSQL Generative AI Databases analysis Microsoft Fabric evolves from data lake to application platform Microsoft delivers a one-stop shop for big data applications with its latest updates to its data platform. By Simon Bisson Jun 13, 2024 7 mins Microsoft Azure Natural Language Processing Data Architecture Resources Videos