The use of what is commonly called “big data” can play a key role in the operation of any craft brewing company. How that data is gathered, analyzed and implemented can make a large difference in the efficiencies and profitability of any sized brewer, from new startup to the established multi-state operation.
Nearly all brewers realize that attention to detail is a hallmark of the industry. This includes execution of a daily routine that ensures ingredients are mixed and formulated properly, then properly processed through a kegging and bottling system, and, in the end, results in the replication of a high quality product. This must be accomplished with a production output necessary to sustain profitability.
The overall brewing process must be completed with as little waste as possible. Any variation, large or small, can slow down the operation, impede production, and compromise taste. The end result can be a slowdown in delivery times, loss of customers and a large increase in overall costs. In order to maintain consistency, many in the industry are now turning to data gathering systems. These systems can include software that can be automated to accumulate hundreds of pages of information. However, the challenge for most becomes not only the collection of the data itself but also how to sift through it, decipher it and put it to use to improve business operations.
Fortunately new data gathering software has been created specifically for the craft brewing industry. Not only can the software be utilized to eliminate the mountains of data which may be pertinent to other types of businesses but not to brewers, but it can also monitor key areas of operation impacting the brewer’s’ specific brewing process.
This software can be customized to monitor and even improve mashing-plato (balling), temperature (conversion) and raise times. It can provide information on lauter tun-first wort plato, lost Hansel plato, number of bed cuts, runoff time total and grain out time. Items such as brewkettle-kettle full plato, wort cooling, fermentation, time from fill to attemporation, centrifuge turbidity, yeast brink, filter and CIP can also be tagged as needed.
The software can help the brewer with full system monitoring, setup alerts based on production and performance, watch output comparisons by day and time, and track inventory and materials. Some of the automated software can also provide cloud based reporting for 24/7/365 access on a PC, laptop or mobile device. It can work with all servers and workstations, and multiple devices. The software may also be compatible with any PLC including Siemens and Allen-Bradley devices.
The newer software can be adjusted to provide only the most crucial reports and information. Instead of continuously polling and storing data, it can focus on specific program triggers and collect specific data at specific points in time, at specific process conditions. This provides a detailed comparison from one day’s operation to the next, enabling the brewer to make adjustments as necessary.
A brewer can also find programs that provide a full system back-up, support and updates. Some systems are fully customizable to meet the needs of the individual brewery. Corporations and multi-national beer producers have used various forms of big data processes for many years. Big data has helped them not only monitor and improve the manufacturing process but also with pricing and marketing.
Now, craft brewers of all sizes can enjoy the benefits of data gathering and analyzation. The development of new software programming, combined with the ease of cloud-based reporting, can help the brewer greatly improve business operations while greatly increasing profits.
David Moye is a principal with Forensic IT, a firm providing big data solutions to companies nationwide and co-founder of DataSnare software for the brewing industry. Moye has some 25 plus years of experience as a software engineer and solution architect. Along with at least a half a dozen core programming languages, he is a certified DBA in Oracle and Sybase and has spent years working with MS-SQL and MySql.