How CPG Brands Can Turn Covid Pains Into Long-Term Gains

Kunal Kohli

5 minutes

Too Fast, Too Furious

As we crawl our way out of the pandemic, I wanted to share some of the lessons I’ve seen from high-flying brands that have made it through the worst of it—scarred but surviving, thriving but bursting at the seams. 

If ever there was a catalyst for growing pains, it’s the pandemic, which threw brands for every loop in the book. But the challenge of transforming skyrocketing sales into a consistent growth pattern has been around for ages. 

Over the course of my career, I’ve witnessed some incredible success stories that all begin in the same place: growing pains. Growing pains are what I’d call a good problem—but good problems are only good if they evolve; or, better yet, if the people charged with solving them evolve around them. Here’s how they did it.

Challenges

Solutions

Empty shelves at a grocery store during the height of Covid panic buying, March 2020 [Unioncrate]
Empty shelves, March 2020 (Credit: Twitter)


Mo’ Money, Mo’ Problems

A few years ago, one F&B brand I’m close with experienced incredible growth, tripling its sales seemingly overnight after a new product launch was successful beyond its most aggressive expectations. 

Another brand, a manufacturer of mostly shelf-stable items, saw their sales grow from $5M pre-COVID to finish at $25M in 2020 due to demand during COVID. 

Another, a manufacturer of cleaning products, 10x’d sales in March and April alone. After years of minimal DTC success, it became a household name after gaining distribution in 10,000 doors nationwide. 

But with this incredible growth came challenges, all of which led to revenue being a fraction of what it could have been, and expenses ballooning at a higher percentage of revenue. Here are the three main challenges I saw across the board.

[Related: How a Category Leader Uses Unioncrate’s AI to Rapidly Meet Demand During Covid-19]

3 Key Challenges

fast-gains-rising-costs

1.  Fast Gains, Rising Costs

When brands experience distribution gains faster than they have planned for, this is what typically happens next: more capital outlay, manufacturing backups, empty shelves, and overworked teams. And to make up for it, they pour salt on the wound by taking on increased shuttling and logistics costs and hefty co-packer fees to ensure their inventory—or whatever is left of it—will be in the right place at the right time.

lean-but-no-longer-mean

2.  Lean But No Longer Mean

Sometimes, everything piles on at once: sales orders, raw goods shortages, labor shortages, rushed decisions, manufacturing requirements, higher COGs, you name it. A lot of companies prefer to keep things lean and fixed costs down, but without the right systems in place, being too lean can be a real detriment. 

It certainly was for the aforementioned brand that had triple-digit gains, where there was still only one person who handled all of the planning. That team member created complex spreadsheets with multiple tabs and multiple formulas. Plus, this person had a tough time coalescing numbers from various teams who all had their own view of the sales landscape. The brand simply didn’t have the resources to enable its staff to keep up with demand.

rushed-decision-making

3.  Rushed Decision-Making

As it is with investing, the same goes for running a brand: making rushed (emotion-driven) decisions almost always ends up being quite costly. We’ve all been there; it comes with the territory. 

A number of brands I’ve worked with, all of which were growing like crazy, have had to make last-minute tweaks due to unforeseen disruptions. This meant going back to their manufacturer, rush-ordering packaging, and paying extra for last minute trucking, because of time constraints and fear of stockouts. Plus, manufacturers and co-packers had scheduled line times for these brands but also other brands, which led to severe delays of course. As a result, each co-packer ended up having to bring in overtime labor, which meant hits to these brands’ margins.

Uniting AI + Human Intelligence for Truly Agile Planning [Unioncrate]


3 Key Solutions

The worst thing you can do about these problems is… nothing. This isn’t always obvious, since many brands assume that they’ll figure it out, that things will just fall in line after a while. But not changing up internal processes means you’re just going to be doing the same thing expecting different results; you have to invest in making structural and procedural changes. One short-term solution to many of these problems is to implement the right ERP, which helps with centrality and day-to-day operations. 

But a long-term solution takes it a step further: How best to stay ahead of unknown demand? That’s the key framework for the following solutions.

ai-heavy-lifting

1.  Let Artificial Intelligence Do the Heavy Lifting

The term Artificial Intelligence is commonly used to refer to machine learning algorithms that have high levels of accuracy. I know some incredible demand planners, teams of them, but their manual forecasting and processes are usually no match for the speed and precision of AI-driven sales, inventory, and distribution forecasts.

Machine learning models are trained to constantly seek out and identify dynamic relationships, both short- and long-term, between historical sales and seasonality data, historical inventory data, product transitions data, trade spend data, and much more. This can lead to higher forecast accuracy and free up capital, as well as slash hours from brands’ planning processes. 

Ironically, these predictive capabilities are typically the result of a team of data scientists who have tuned a set of advanced machine learning algorithms on a specific set of data.


[Related: How to Leverage AI and Upgrade Your Demand Planning Process in the New Year]

human-insights

2.  Make Room For Human Insights

Despite advances in machine learning applications, human insights are still important to the demand forecasting and supply chain planning process on a number of fronts, including added visibility, collaboration, and accuracy. 

Algorithms do not have boots on the ground, so to speak; humans do. Sales and supply teams, for instance, will always possess unique insights that only they (or a select group of people) are privy to, such as new distribution gains and last-minute promotions. As a result, brands should implement a functionality that allows sales, marketing, supply, and finance teams to manually adjust AI-generated forecasts, or their own internal forecasts, with inputs that may impact future sales, including distribution changes, new marketing investments, supply constraints, and other buyer communication. On top of that, this information should be approvable and viewable to all relevant parties, company-wide, for increased collaboration and visibility. Remove the silos!

During uncertain times, the ability to augment forecasts from the field, for instance, can be a stabilizing—and powerful—force when demand shifts unexpectedly. 

centralize-automate
The Next Evolution of Supply Chain Planning [Unioncrate]

3.  Centralize and Automate

The traditional supply chain planning process is way too manual and siloed. The lack of real-time data links across departments will lead to low forecast accuracy, low business performance, and missed opportunity. Brands need a platform, a system, or software that easily unifies supply chain, financial, and operational data—creating a sort of digital brain for business that will make demand planning that much easier, faster, and more precise, all while eliminating blind spots from forecasts.

For my money, these 3 solutions are sure to put hyper-growth brands on the path to long-term success.

About Unioncrate

Unioncrate is an AI-powered Supply Chain Planning Platform that gives CPG brands the technology they need to compete and win in a rapidly changing consumer landscape. Our automated demand and supply forecasts deliver unmatched accuracy, collaborative visibility, and actionable intelligence, simplifying a manual-heavy process and slashing hours from your week.


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