Like so many mature companies with decades of expansion, Chick-fil-A’s data had become a patchwork of siloed pockets spread across the organization. Collective company data was often inaccessible to analytics staff, or required notable IT assistance. There were also frustrating instances of large transactional data sets going unused because even seasoned staff were uncertain how to realistically process them given the constraints of an aging legacy toolset. And as Chick-fil-A Manager of Supply Chain Analytics Justin Winter relates, the pressures of modern analytics had ultimately caught up with the company. “You have to constantly figure out how to reinvent. How do you reinvent as a leader, as an analyst, and also the tools in the system and the processes? How do you continue to innovate to stay on top of growth in the business?”
Regarding the supply chain department, Winter states, “the business is demanding the insight. Like tell me why this matters, point it out to me, and I want it real time and I have 45 other questions I want you to provide information for. So we really had to change and adapt to be able to answer these questions and more.”
Chick-fil-A analysts in the trenches felt that even the simplest data query had grown too time-consuming, and called for a solution that could deliver deeper insights fast. Also, many analysts felt particularly handcuffed by existing tools because they weren’t coders. They had lots of data, but couldn’t use it effectively. The team wanted the ability to rapidly process large amounts of data without writing any code.
Winter didn’t want to introduce a tool that would complicate his staff’s lives and introduce even more complexity to Chick-fil-A’s existing analytics toolkit. He knew that Chick-fil-A needed to be able to easily join data from multiple sources and empower both data analysts and line-of-business users to perform their own analytics quickly and be able to explore their data more to enable innovation.
“We had all these reams of transactional data from stores and, literally, just had no way to do anything of any value with it. I suggested let’s figure out if in 24 hours, we can take all that data, load it into [Amazon] Redshift and have responsive reporting and analytics on that. And sure enough, in 24 hours our IT group, which has just been an incredible partner for us, actually pulled it off. It was great because they got all the data there, and you could get a response as long as you could write SQL code.”
The Chick-fil-A team has marketing analysts who have smart business skills, but are not trained in complex SQL and hierarchical queries. “We sat down to answer a specific question, and it would take four hours with any one of the three tools that we were using. How do you connect the skills that the analyst has with the availability of the systems? We tried directly connecting Tableau to it, but when you try to do a filter on Tableau on five billion records, it just doesn’t work well.”
Winter remembered hearing about another company using Alteryx to prep, blend, analyze, and do analytics on data in preparation for using Tableau to report on it, and he decided to download a free trial of Alteryx. “I built a workflow in 10 minutes on our first day that queried five billion records in 20 seconds. And immediately I realized there is something going on here that is really cool and powerful.” Through this exploration and discovery, Winter and his team committed to adopt Alteryx and test the collective ways it could be used across the organization. Winter’s team was also excited to find the necessary path for them to fluidly integrate Amazon Redshift and Tableau reporting. They use Amazon Redshift for data warehousing, Alteryx for extraction and manipulation, and then Tableau Server for presentation.