Big Data Meets the Beer Industry
Beer making, of course, remains a very human-centric industry.
In December, Deschutes Brewery, the nation’s tenth largest craft brewer, announced plans to lay off 10% of its workforce. Declining sales and volume were cited as the reason, a familiar refrain as the craft beer market hits a saturation point.
For most brewers, a layoff that significant would also mean cut distribution and production. But Deschutes has no such plans, thanks to a decision made just under four years ago to incorporate Internet-connected sensors into the brewing process.
Beer making, of course, remains a very human-centric industry. Traditionally, workers have manually sampled and analyzed beers during the production to determine when the beer should be moved from one of the nine brewing phases to another, a process called phase shift. Transferring a beer from one step to another too early or too late impacts the quality of the final product.
Like many breweries, Deschutes, based in Bend, Ore. kept the records of those samples and analysis. Then it decided to put it to work by tapping Microsoft and OSISoft to use data crunching in the cloud to predict transition times during production. The results helped streamline the brewing process and helped the company do more with less.
“When you’re struggling with capacity or have a layoff, you don’t want to invest in another asset,” says Brian Faivre, brewmaster at Deschutes Brewery. “We’re no longer staffing the personnel to be able to operate 24/7. We’d normally have to make a sacrifice and historically that would be either quality or lost capacity or the happiness of our employees. … This is an opportunity to say we have strong confidence in this model.”
The framework for the predictive analysis has been built into all of the brewery’s 50 or so tanks, which range in capacity from 100 to 1,000 barrels—3,150 to 31,500 gallons. Currently, the actual shift in stages is done manually after brewers confirm the readiness of the brew, but Faivre says they company is looking to automate that.
The net effect of tapping data in the brewing process? Deschutes is able to reduce the fermentation process by 24 to 48 hours per batch. That gives the brewery a chance to increase its annual production without buying additional equipment.
So far, Deschutes stands alone in using sensors and data crunching to assist with the brewing, but Faivre says some other brewers, including Sierra Nevada, have visited to learn more.
The project has also spawned an open source data collection project among craft brewers, who share their historical records of how long it takes to move beer in production between the various stages.
“The majority of these folks, they might have sensors, but they write [the data] down on a piece of paper or in a spreadsheet,” says Faivre. “This is a way to structure and collect that data for them in a database and get them to a space where they’re building a database of that data so they can do things better in the future.”
He continued: “In the craft industry, to make that sort of adjustment is hard. Now, people are becoming comfortable with it. They see it as a tool, rather than something trying to take their job.”
With the reduction in work, Deschutes is now looking for new ways to leverage its data crunching tools. The usual practices, like predictive analysis that alerts when equipment is about to break, are being explored, but the company is also thinking about more industry-specific possibilities.
One of those could lie in using a mass spectrometer to measure flavor.
“We have all these recipes in the database,” says Faivre. “Right now, we have match data to these recipes, so we’re getting lab analysis so we’re able to get measurements of the various compounds in these. That’s where I want to go next, to take all the data, and really try to see if we can crack the nut of what combinations lead to these characteristics that consumers are so interested in that are so polarizing. There’s not an exact formula for figuring that out as a brewer.”
That analysis isn’t meant to remove the human element from developing beers. Rather, it’s meant to speed up the process. Sometimes before a brewer hits upon a successful formula, they’ll go through 100 or more iterations of a beer, looking for the exact flavor they want. Technology could help cut the number to 10.
Admittedly, for some brewers, that could take some of the fun out of the job. The best beer makers are about one-third mad scientist, experimenting with things you may never expect to be mixed with hops and malts—and often coming up with delicious new styles.
To ensure that tradition stays alive, Deschutes has a test plant that brews one barrel at a time, constantly experimenting and putting the results out in its tasting room to see how fans react to it. (Data on those small batch beers is recorded the same way it is in larger beers, in case the experiment is a resounding success.)
“Craft beer is something where so much of your soul and heart goes into it,” says Faivre. “So the concept of taking anything out of that can be a touchy subject. It’s one of those things where you have to build trust. You have to have the conversations. This is a tool. We’re not turning the way we make beer over to machines and engineers, but it’s a way to be more efficient.”