How can foodservice manufacturers overcome disruption and data challenges to thrive in the 21st century?
Until fairly recently, foodservice manufacturers weren’t all that affected by tech and data trends. But that is about to change. We expect 2020 to be a watershed moment in foodservice’s adoption of AI and data analytics. In the next 20 years, we’re going to see more changes than in the last 200 years. And in 2020, forward-thinking foodservice companies will get ahead of the curve by adopting a data-driven mindset.
What steps should companies take to prepare for this change? In this article, we’ll discuss the trends shaping the foodservice industry, the challenges manufacturers must overcome on their way to being data-driven, and how real-life companies are taking advantage of cutting-edge technology to become more competitive and relevant.
Trends Currently Shaping the Foodservice Industry
First, let’s look at the big picture. Overall, there are three dominant trends currently affecting the foodservice industry.
Trend 1: Massive Disruption
Across the foodservice ecosystem, we’re seeing food trends mushroom almost overnight. For example, think of meat alternatives like Beyond Meat or Impossible Meat and diet movements like keto. There are also alternatives to traditional restaurants, like pop-ups, ghost restaurants (i.e. delivery-only restaurants) and meal delivery services (think DoorDash or Grubhub). These have lower overheads than traditional dine-in restaurants, and they’re proving tough competition.
Trend 2: The Data Explosion
Next up, we have the sheer proliferation of data. We’re not just talking about the quantity of information coming in, but also the variety of data types and sources. Plus, there are new kinds of rich data like video, mobile, location, etc. And the data landscape changes constantly. It’s not a good scenario for legacy systems; they’re simply not equipped to handle this.
Trend 3: Everything’s AI, ML, and Data-Driven
This isn’t a bad thing, but it requires companies to adjust.
For example, think about navigating a car trip using a traditional printed map versus GPS. Maps are static; they can’t update themselves to reflect new construction or reroute you around traffic jams. And they demand a certain amount of skill to use!
GPS, on the other hand, is very simple to use. It updates and reroutes without human input. It doesn’t require any skill beyond typing information into an interface. And it tells you exactly how to get from point A to point B. But underneath, the workings are highly complex, technology heavy and dynamic.
Similarly, shifting to a data-driven approach can help companies make faster and better decisions. It can hugely simplify the information-gathering process for the end user. But underneath, it requires a complex technical setup to function properly. And, like any organizational change, it has a learning period.
Adapt or Fail
So, what does all this mean for your company? Essentially, it means this: Change is coming to the foodservice industry. And it is incumbent upon foodservice leadership to start adapting to it now. The tech revolution doesn’t leave much room for organizations that don’t embrace it.
The recently released (fall 2019) backstory of Blockbuster vs. Netflix is an excellent example. Blockbuster could have bought Netflix in 2000, but they didn’t. The CEO thought it was a joke. Fast forward to 2019, and tech giant Netflix has 150 million subscribers worldwide and is worth $115 billion. And Blockbuster? They filed for bankruptcy in 2010; a single, privately-owned franchise store in Bend, Oregon, USA, is all that’s left of a once-mighty brand.
Now, most foodservice companies are using data. And I’d venture to say that all foodservice leadership wants to thrive as we move into 2020. So, what’s preventing a full-scale conversion to data-driven operations?
Key Challenges to Data Analytics Adoption at Foodservice Manufacturers
- A few problems seem to surface repeatedly when we discuss why analytics adoption is lagging amongst foodservice manufacturers:
- With the commercial aviation industry poised for more growth and change, we can expect to see AI continue to play an integral part in its function. We’ll see applications that go beyond marketing, beyond customer experience, and beyond profitability. We’ll see a shift towards more and greater AI applications in every aspect of the industry.
- “Distributors aren’t sharing their shipment data.”
There’s a persistent belief that manufacturers need access to distributors’ shipment data. It’s arguably the number one complaint we hear when engaging with a new foodservice manufacturer client. Distributors don’t want you, the manufacturer, going direct to their customers—obviously.
When you have data analytics, this dynamic changes drastically in two ways:
- You could get distributor data if you offered your distributors value in return. The insights and recommendations you can offer your channel partners will help YOU and YOUR DISTRIBUTOR sell more. A win-win situation breaks down this long-standing barrier.
- YOU DON’T NEED DISTRIBUTOR DATA WITH DATA ANALYTICS: With advanced analytics on data you already have access to (like coupons and trade promotions), you can actually estimate distributor data with an actionable level of accuracy.
Either way, there is a positive impact on sales and market share for foodservice manufacturers.
- “We don’t have analytics skills in-house.”
This is a common and very real issue. Many foodservice companies don’t have a data analytics team; they may not even be sure how to use what data they have. So they opt to build their skills first and then catch up with the competition later.
This is another mistake. Start today and use what you have. Don’t wait to find perfect data, hire or train the right skills, or develop the right team. If analytics is well outside your expertise, partner with a service provider and learn from them. This is often a great way to delve into advanced analytics; you can benefit from your partner’s experience and depth of technical understanding.
- “We need more (or better) data.”
Most foodservice sales and marketing, when they do put their data to use, just focus on gleaning insights from pockets of data. In reality, their data usage is suboptimal: internal and external data is separated, valuable in-house data goes unused, and decisions are made based more on business experience and intuition than on the data itself.
The point is that you probably have more and better data than you realize, i.e. operator rebate data, distributor bill-back data, etc. Expand how you use what you have. You can see immediate impact when you do this.
Takeaway: Don’t wait for perfect circumstances. Start now.
It’s better to use what you have and get an imperfect start towards being data-driven than to wait for perfectly complete data and the perfect in-house analytics team. We can’t emphasize enough the importance of learning and adopting advanced analytics without delay. Waiting for perfection will only put you further behind your competitors.
How Foodservice Innovators Are Using Data to Power Growth
Some foodservice companies have already begun reaping significant benefits by adopting AI and other forms of advanced analytics. We know it can be done; below are some very short examples:
- Optimizing SKU mixes by location, demographics, etc. to drive sustainable growth pockets.
- Focusing on accounts where they have an “unfair” advantage (i.e. by identifying high potential indexes and drilling down into product and region).
- Quickly finding at-risk accounts (i.e. determining where there’s a gap between expected and actual volume).
- Identifying and acting on emerging trends, such as demographics, trade area profile, lifestyle/media, beverages, and flavors.
For a more detailed look at what’s possible with AI, check out this Fortune 100 foodservice manufacturer’s case study. They used a variety of advanced analytics (including AI, deep neural networks, collaborative filtering, and ensemble models) to identify the best mixes by region, category, brand, SKU, and even individual outlet. In a short time, this has produced higher incidence rates, more incremental value, and more value growth across categories.
However, organizations need to do more than just copy others’ success; it’s important to stay alert to developing trends. Two that will have a sizeable impact on foodservice are video analytics and location data. Video analytics (in which people wear a body camera that records real-world actions and interactions) shows tremendous promise as a way to pick up on very subtle signals of intent, sentiment, and customer behavior.
External location data is another hugely influential trend that foodservice manufacturers and operators alike need to embrace. Location and points-of-interest (POI) data from companies like SafeGraph are very rich, and can be harnessed to produce better-informed decisions about consumer preferences, retail trends, and brand preferences. For example:
- Anonymized aggregated location data from mobile phones can be used to understand shopper demographics, visitation patterns, and paths to purchase.
- Foot traffic analysis can show the most popular brands in an area and determine regional brand preferences.
- Consumer movement patterns can help marketers understand brand affinities.
- Visitor demographics give a visual demonstration of how visits and visitors to a place change over time; it also shows other places visitors go.
Once again, we urge foodservice manufacturers—not just operators—to start using this type of data sooner rather than later; its insights confer a huge competitive advantage to early adopters.
Don’t Wait to Get Behind the Data-Driven Trend
The last ten years have brought massive changes to how we use data; the next 20 years are going to be highly transformative in the foodservice industry. Technologies like machine learning and AI will become increasingly more integrated with every aspect of business, moving from helping us find insights and make decisions to helping us think, create, and connect with the rest of the world.
For companies at a crossroad in adopting newer data analytics, the decisions made in the next few months are going to impact future performance significantly. Some will choose to ignore the tech revolution and do things as they’ve always been done. Some will adopt new technologies slowly, piecemeal, replacing only what they must. Others will make 2020 the year to start using data across the organization. In this, take a lesson from Blockbuster and Netflix. Companies who ignore progress risk fading away; companies who adopt it grudgingly will survive, but with a struggle, and companies who embrace data analytics as a way of life will thrive.
Perfect teams and perfect data sources aren’t the keys to success. An adaptive mindset and a willingness to learn and educate oneself and one’s team are. Start your journey today – use what you have, develop partnerships with data science experts, and begin creating an impact. Then build on your results. It’s time for the foodservice industry to fully embrace data-driven decision making.