Home / Blog / From Beer to Bits to Beer

From Beer to Bits to Beer

Copper brewing vats stand inside the Beck’s brewery, operated by Anheuser-Busch InBev NV, in Bremen, Germany, Image credit: Beck’s

Over this last week end we had our youngest son visiting us: he is working at one of the biggest brewery group. He is engaged in a program that takes him to experience the various aspect of the company business, from manufacturing (brewing) to logistics, from marketing to sales … Surely a good opportunity to look at the forest through the trees.

I was impressed by a phrase he reported from his current boss. They have been discussing the future of the brewing business and his boss told him:

you should look at this company as an Information Technology company that happens to sell beer

I found this quite interesting. At first glance beer and bits have very little in common (and most people would likely opt for beer over bits). Yet, as I started to think about the Digital Transformation affecting more and more sectors (verticals) it started to make a lot of sense.

A lot of the “brewing” business is not about the beer, rather the logistics of taking the beer from the brewery (in this case from a multitude of breweries) to the delivery points (shelves, pubs, …). Because of this the big players have started to collect (more and more in an automatic way) data from the logistic chain and are using those data to finely tune both production and delivery.

An impressive demonstration of the advantage provided by managing the whole value chain in bits has been seen during the pandemic. The closing of pubs has deeply affected the distribution and the “flow” of beer. Beer to a certain extent is similar to electricity on the grid. The amount produced needs to equal the amount consumed. You can store beer much better than electricity but storage comes at a cost and you cannot store beer for an extended period of time (most beer are best consumed within a 3 to 6 months period).

Thus the importance of continuous feedback from the selling points on what and how much is consumed. This is a huge amount of data continuously flowing back to the breweries (to the corporate headquarter). Data analytics can help pinpointing and predicting consumers’ shifts and anticipating them by changing production levels.

This is all about the present, having the beer generating bits to regulate the value chain.

The next step is to use bits to predict future customers’ needs, and possibly influencing them. Digital Twin technology is already in use in some breweries, courtesy of Siemens – watch the clip- and artificial intelligence is used in several stages of the brewing biz, including, would you have guessed?, creating new beer flavours.

Data accrued in the manufacturing, in the supply and distribution chain and possibly the ones gathered from the customers and users (drinkers…) can create a virtual space to define new strategies and even test them before moving to the implementation. This is not going to get rid of “tasters” nor of the need for trials but for sure it will allow the exploration of many more strategies evaluating their implication on the whole value chain before moving to concreate experimentation.

Nice to see how beer, the oldest drink (or, if you prefer, the first to be invented) is now transitioning to the cyberspace.

About Roberto Saracco

Roberto Saracco fell in love with technology and its implications long time ago. His background is in math and computer science. Until April 2017 he led the EIT Digital Italian Node and then was head of the Industrial Doctoral School of EIT Digital up to September 2018. Previously, up to December 2011 he was the Director of the Telecom Italia Future Centre in Venice, looking at the interplay of technology evolution, economics and society. At the turn of the century he led a World Bank-Infodev project to stimulate entrepreneurship in Latin America. He is a senior member of IEEE where he leads the Industry Advisory Board within the Future Directions Committee and co-chairs the Digital Reality Initiative. He teaches a Master course on Technology Forecasting and Market impact at the University of Trento. He has published over 100 papers in journals and magazines and 14 books.