The Changing Landscape of the Foodservice Industry – Part 2

This is the second installment in a two-part series on major changes taking place in the US foodservice industry. In the first installment we looked at some of the key challenges, deriving from traditional industry practices in sales & marketing that impede optimal performance by manufacturers, distributors and operators in the sector. This second installment will take a closer look at converging technologies that are poised to shake up the industry, and look at ways for industry players to benefit from these developments with intelligent, coordinated approaches to technology-driven solutions.

For manufacturers of foodservice products an important and often elusive goal is to gain visibility into the factors shaping and influencing downstream demand. The view from upstream is obscured by one or more layers of intermediation separating products from their end customers. Manufacturers typically set aside the largest part of their sales and marketing budgets for payments to trade partners, but evidence suggests that these expenditures do little to improve their understanding of actual downstream demand. Whether on their own or in collaboration with trade partners, manufacturers need to make better use of the data that can provide accurate intelligence about what is happening downstream. The good news is that the data are available, and new technologies are converging to enable manufacturers to capture information from which to make better sales & marketing decisions. The challenge is to get around the obstacles that are preventing this from happening.

social networking is changing the way people decide where, when, what and with whom to eat

The end point of the foodservice value chain, of course, is the patron. In a perfect world restaurant operators would be able to predict how many patrons are showing up at their doors every night of the week, and what quantities of which menu offerings they would be ordering to eat and drink. They could then place orders upstream in total accordance with this knowledge. The world is not perfect, though, and no restaurant owner has such powers of clairvoyance. What they do have, increasingly, is the benefit of something that barely existed just a few years ago – social networking technology. More and more of the decisions that people make on a daily basis – including where, when and with whom to eat meals – are utilizing the many technological tributaries of the social networking phenomenon. For their part, restaurant operators have also been figuring out how to get into this game. Even the independent local establishments that lack the large corporate infrastructure of national chains are able to use these new digital tools to better understand their own markets and to control their own marketing – to reach out to potential diners with offers and other targeted inducements to patronize their tables. In so doing they are gaining actionable insights with which to better estimate demand. In turn, they can place orders to their suppliers with a higher level of confidence that these orders are a reasonably accurate reflection of what their customers will actually be ordering, when and in what quantity.

The presence of social networking technology is increasing the quantity and quality of digital signals coming from downstream markets. But there is another rapidly evolving technology that has the ability to amplify these signals even more powerfully up the value chain. That is predictive technology for sales and marketing decisions. Predictive technology applies rigorous quantitative methods to arm sales and marketing decision makers with recommendations to target the right customers with the right products, promotions, pricing and timing. This approach feeds on data signals – the more the better across as many customer-product combinations as possible – and helps to untangle the many diverse factors affecting demand at a very granular level. The algorithms that power predictive technology solutions can capture the digital demand signals coming from operators and patrons downstream, analyze them and provide useful intelligence to managers in corporate headquarters as well as sales professionals on the front line – information that can help them make decisions based on more than just guesswork. This can result in a higher likelihood of success for every offer presented to a customer.

This convergence of two powerful technology trends offers potential benefits throughout the foodservice value chain. For manufacturers the big question – going back to the discussion in the opening paragraph of this post – is how to get past the obstacles that impede the view downstream. There are different ways of doing this, and best practices are likely to evolve over time. One path to greater demand clarity can occur through better and more comprehensive collaborative processes with trade partners. Midstream distributors have their own set of challenges in the current environment – for example managing profit margin stability under conditions of unusually high volatility in week-to-week revenue movements alongside steadily increasing COGS trends for key products and categories. More accurate forecasting for price and other demand levers – assortment, promotions and sales force effort – can result in more predictable margins without the wild fluctuations seen today. That in turn can provide an incentive for distributors to be willing to look at alternative models to the stultifying “pay to play” template for trade spend that prevails today – including closer upstream collaboration.

Thanks to the growing capabilities afforded by social networking technology restaurant operators are steadily improving their ability to understand the intricacies of their markets and plan their foodservice purchases accordingly. Their upstream suppliers in turn can apply predictive technology solutions to identify where their promotions, sales efforts and deal bundling will most likely fall on the most receptive ears. Manufacturers who figure out how best to tap into these more accurate and better-amplified data signals will likely be rewarded with a clearer and farther view downstream.

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