Member Exclusive   //   December 10, 2024

DTC Briefing: How scaling brands are tackling inventory management

This is the latest installment of the DTC Briefing, a weekly Modern Retail+ column about the biggest challenges and trends facing the volatile direct-to-consumer startup world. More from the series →

As direct-to-consumer brands grow and enter wholesale, many brands find it more difficult to accurately forecast inventory.

Many companies, especially bootstrapped brands or those with limited cash flow, start out with simple inventory forecasting models that are built in Excel and are based on data points like weekly and monthly sales, as well as seasonal factors like holidays and promotional periods, that grow with their own sales. But as more channels like marketplaces and physical retail partners are added, brands say manual inventory management becomes more difficult to operate accurately.

Many big enterprise software providers, like Netsuite and SAP, can be expensive for early-stage startups and have unnecessary bells and whistles for the brand’s size. Some brands say they are sticking with the inventory management models they built from scratch until they’re large enough to need expensive software. But over the past few years, a number of business-to-business startups have popped up aiming to help build better inventory management systems for DTC brands still working toward the $100 million revenue mark. 

One of these vendors is Toronto-based Moeselle, which launched in 2020 and offers automated inventory management to early-stage DTC and CPG brands. The company closed a seed round of 2.1 million Canadian dollars in October to help it grow its team and continue building its tools. The company’s program is being used by direct-to-consumer brands like beauty brands Everist and Sahajan, along with luggage maker Monos.

Moselle founder and CEO Lakhveer Jajj said the concept for the company came about after he worked with smaller brands that were struggling to manage inventory in an efficient and profitable manner. “We describe ourselves as like an inventory autopilot that helps forecast planning and inventory replenishment for brands,” he said. Moselle offers a proprietary AI-powered model that allows brands to plan inventory purchases and generate real-time forecasts based on daily sales data input modifications. Brands can do so by syncing Moselle with their Shopify and Amazon stores as well as their 3PL.

Many of the larger SaaS players are geared toward medium and large businesses and can cost thousands of dollars to use. “We’re taking a very deliberate bottoms-up approach to the market by working with smaller, emerging brands,” Jajj said. Some of Moselle’s competitors that provide similar services include Cogsy, Centro and Syrup Tech, all of which have launched within the past four years. Moeselle’s rates start at $250 a month for DTC brands, with the customized rate increasing the more secondary channels a brand has

So far, demand from young e-commerce brands is increasing, with the number of Moeselle clients doubling from 2023 to 2024. The company’s recent seed round will go toward hiring more engineers and building out new granular tools that help more packaged goods and apparel brands manage aspects of their inventory planning, such as raw material sourcing across the supply chain. 

Haircare brand Everist, which launched in early 2021, is currently testing Moselle as part of a larger forecasting strategy. Everist co-founder Jessica Stevenson told Modern Retail that as the company is scaling up fast, “we’re always looking at new tools to see how we can do this better and sort of be flexible and move with the changing needs of the business.”

“I think the biggest challenge we face is making sure to have historical data accuracy that we can rely on as we grow,” Stevenson said. 

Coming from corporate beauty, where forecasting software like SAP and Netsuite are used, Stevenson said many startups require a system that’s more tailored to their trajectory. “Our method has been to create a manual process and see how things work first before adding new tools or AI,” she said.

“Right now, we’re 85% direct-to-consumer,” Stevenson said. However, the company wants to lay a foundation for accurate demand forecasting as it enters wholesale retail. On the DTC side, early on Everist was able to handle its two to three times annual growth with a manual methodology of inputting weekly and monthly sales data into tools like Excel. 

“This yea,r we had nine to 10X growth, so we’re bringing in secondary tools to test,” she said. The brand chose to run the Moselle program in parallel with its in-house system to see how it works. In beauty, there are nuanced inventory challenges like formula changes and bundled SKUs, which Stevenson said can get complicated. Other challenges also include having the cash flow on hand when planning upcoming stock orders.

“As we scale, we have tried to prioritize some of our retail partners to make sure that they have that seamless experience,” Stevenson said. That means sometimes items might be temporarily out of stock on Everist’s DTC site, and the brand has to manage customers’ expectations about when stock can be replenished. “We typically build out our forecast much further in advance for wholesale,” she said, which is tricky due to beauty retailers expecting shipments within a couple of weeks.

Earlier this year, Everist launched at 500 Whole Foods locations, its first major retail partner. Whole Foods requires brands to work with the retailer’s main distributor, UNFI, which adds another level of complexity. “It’s easier to manage smaller accounts where we can make quick decisions and work close together,” Stevenson said.

There’s no perfect solution for startups, as each wholesale partner they add will come with its own quirks and complexities. In the meantime, some startups are sticking with manual solutions.

Katie Williams, senior director of ops at Huron, currently oversees the logistics, shipping and customer experience at the skincare startup. Her role involves forecasting demand and managing inventory levels based on weekly and monthly sales. Roughly 55% of Huron’s business comes from Amazon, 45% comes from its DTC website and the rest comes from gyms and specialty boutiques.

Right now, Huron’s approach is a fully manual process, though the brand has explored some digital tools in the past. “What I do every week to prepare is pull in the prior week’s sales and any incoming POs that we’re sending out to Amazon,” she said. “All lives in this giant Google Sheet that I update every week.” 

“Right now, we’re a 25 SKU company,” Williams said. “But when we’re a 65 SKU company, whatever I’m doing right now is not going to work.”

“Ultimately, what I look for in a tool is whether it can do all the tasks I can do manually and without a ton of startup investment and time,” she said. To date, all the inventory tools Huron considered are built for larger e-commerce companies. “So they come after smaller brands trying to help us grow and scale, but it doesn’t fit what we need now,” Williams said. 

Williams is working with a third-party vendor called Mandrel on cost-of-goods management. “That has been really helpful to be able to gather all of my Excel sheets and to systemize on the platform,” she said. Still, Williams said some type of automation provider will be necessary as Huron’s product line grows and bigger wholesale partners sign on.

Even with more sophisticated models being built, there are forecasting hurdles smaller brands with fewer resources run into. The main challenge is that many retailers — especially large chains — are unwilling to share real-time inventory data that can be fed into systems like Moselle. This is something that’s still challenging on our end,” Jajj said. “We want to spend more time building positive relationships with retailers but also call out nefarious behavior.”

Everist’s Stevenson said having limited transparency from partners can have a big impact on accurate planning. “I think there has been a gap in the past with a lot of retailers not sharing their full sales data,” she said.

As brands add more of these retailers, machine learning and automation tools become a necessary investment. Still, Williams said, “I think the big pillar of inventory management is just knowing that you’re never going to be able to get it 100% accurate, especially at a small brand.” 

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