Wholesale forecasting is a tricky balancing act..
Brands need retailers to commit early so they can buy the right amount of inventory, place production orders, plan fulfillment, and protect margins. Retailers, on the other hand, are trying not to get stuck with too much inventory in a market that keeps changing under their feet.
Additionally, outdoor apparel and footwear brands are dealing with skewed production timelines, shifting consumer demand, tariff uncertainty, and retailers who are understandably more cautious about big seasonal commitments. Meanwhile, buyers are asking for more flexibility: lighter prebooks, better replenishment, more in-season support, and more evidence that the products they are committing to will actually move.
That’s a considerable amount of pressure, and the natural reaction most brands have is to try and lock forecasting into a rigid system in order to better predict returns on the season. That would be a mistake.
So how can brands use better forecasting to make wholesale more flexible for everyone?
That was one of the most interesting threads in our recent conversation with Grant Mahan from Sunski. Grant runs sales operations at Sunski, a brand that has built a strong wholesale business while also managing DTC, drop ship, group sales, corporate buying, multiple 3PLs, and a growing product mix.
You can listen to the entire conversation with Grant on the Between The Drops podcast.
Sunski is not a heavy prebook business in the same way many outdoor apparel or footwear brands are. Sunglasses behave differently than jackets, boots, or seasonal technical apparel. But that is exactly what makes Sunski’s perspective useful. They have had to build a wholesale model that depends less on massive early commitments and more on forecasting, replenishment, operational discipline, and retailer support.
As Grant put it, “People don’t like to commit to pre-booking at a large scale.” And yet Sunski has still found ways to get a read on demand, support retailers, and plan inventory with confidence.
This reliance on a better feedback loop, instead of tight predictions, is the future of wholesale forecasting for many brands.
When retailers say they want to go lighter on prebooks and replenish more in season, they are not setting out to make doing business with them more difficult. They are trying to reduce risk.
A buyer placing a large prebook order is making several bets at once:
Will the color sell?
Will the size curve be right?
Will consumers still want this style three to six months from now?
Will the brand be in stock when they need to reorder?
Will the retailer have flexibility if the product does not move?
Those are, at times, hard predictions to make, and demanding orders based on those theoretical outcomes is a lot to ask.
And from the brand side, it is also fair to say “We need commitments.” Outdoor footwear and apparel brands cannot always wait until the season starts to understand demand. They need to book factory capacity, buy materials, manage inventory across channels, plan allocation, and communicate expectations to their 3PL or warehouse teams.
Both sides are right. Retailers do not want to absorb all the risk. Brands cannot operate without predictability.
The middle ground is actually just better forecasting.
Grant summed up that middle ground well when he talked about giving “the reps and buyers the tools to know and be confident in what they’re buying,” while also creating “flexibility” if something is not working.
That is the balance every wholesale brand should be trying to create: more confidence upfront, more responsiveness in season.
A common mistake in wholesale planning is treating forecasting as a production exercise only.
How many units should we make?
How many do we need from the factory?
When does inventory need to arrive?
Those are essential questions, but they are not enough.
Modern wholesale forecasting needs to connect several layers of the business:
Product demand: What styles, colors, sizes, and categories are likely to perform?
Retailer demand: Which accounts are likely to need what, and when?
Channel demand: How should inventory be balanced between wholesale, DTC, marketplaces, drop ship, and distributors?
Regional demand: What is happening by geography, climate, activity, or store type?
Fulfillment demand: What volume should your 3PL or warehouse expect by week, month, or season?
Replenishment demand: What products should be kept available for in-season reorders?
Grant described how Sunski tightened up forecasting by getting better at both inventory planning and fulfillment communication. Sunski’s planning team looks at buying decisions based on sales data, but they also created a process to share forecasts with 3PL partners based on the channel each warehouse supports.
“We’re in a really good cadence,” Grant said. “You do it quarterly and then you re-forecast when things change or there’s moments of whatever goes on in the world.”
For outdoor brands, that might mean building an initial forecast before sales meetings, updating it after preseason orders, refining it after major trade shows or rep feedback, and then adjusting again once early sell-through data starts coming in.
You can’t just forecast once and hope you nailed it. There are too many variables and elements that can change the trajectory of a season. So, instead, smart brand will forecast, then re-forecast again and again as needed. The goal is to keep getting less wrong.
A lot of wholesale decisions still happen with incomplete information.
A retailer says, “This style is not moving.”
A rep hears, “The account needs help.”
A brand wonders, “Is this a one-store issue or a broader product issue?”
Without sell-through data, everyone is working from anecdotes. Sometimes those anecdotes are right. Sometimes they are misleading.
Grant made the point clearly: “Sell-through data, understanding what’s going on instead of just being an email, being like, ‘Hey, this isn’t moving.’ How can we — it’s like, well, let’s look at the information. There’s tools out there.”
That is where wholesale gets more flexible.
When brands have access to better sell-through data, they can do more than react to complaints. They can identify where a product is actually selling, where inventory is stuck, and where replenishment would make the biggest impact.
For an outdoor footwear brand, that might mean seeing that a waterproof hiking boot is overperforming in the Pacific Northwest but underperforming in warmer markets. Instead of marking the product down everywhere, the brand can help move inventory to the right regions, adjust future buys, and support the accounts with real demand.
For an apparel brand, sell-through data might show that a women’s insulated jacket is strong in core sizes but weak in fringe sizes. That insight can inform replenishment, future size curves, and preseason recommendations for similar accounts.
For a technical accessories brand, sell-through might reveal that a certain colorway performs better in specialty outdoor stores than in broader lifestyle accounts. That can shape assortment guidance and help reps recommend better buys the next season.
It might be something as simple as floor positioning, or too many competitive options in the store.
The more brands can see what happens after the order ships, the better they can support what happens next.
That is also central to how Envoy B2B thinks about wholesale. B2B e-commerce should not just be a place where retailers place orders. It should be part of the feedback loop between brands, reps, and retailers — helping brands educate accounts, capture demand, support replenishment, and increase sell-through.
Retailers do not just want brands to ship product. They want brands to help them succeed with that product.
Grant framed this as a trust issue. Brands need to give retailers enough support “to know that they can commit and have flexibility.”
That flexibility does not have to mean unlimited returns or open-ended risk for the brand. In fact, Grant was clear that reverse logistics is expensive. Receiving product back, inspecting it, crediting it, and making it available again all cost money.
But flexibility can mean clear guardrails.
For example, a footwear brand could use forecasting and sell-through data to create account-specific reorder recommendations before the retailer runs out of key sizes. An apparel brand could identify slow-moving colors early enough to support swaps, promotions, or regional transfers before the end of the season. A hard goods brand could use pre-order demand to prioritize allocation for retailers most likely to sell through.
You can’t remove all rish.. That will never happen. But you can make the risk more visible, more shared, and more manageable, ultimately minimizing it for every party involved.
A better forecast allows a brand rep to walk into a buyer meeting with a story, instead of just a line sheet.
Here is what sold last season.
Here is what similar accounts bought.
Here is what replenished the fastest.
Here is where we saw missed demand.
Here is what we recommend for your store.
Here is how we will support you if the season shifts.
That is a very different conversation than, “Here is the new line. How many do you want?” And it’s a significantly more effective approach.
Forecasting is a data problem, but it is not only a data problem.
Sales reps often know things the spreadsheet does not. They know which buyers are excited, which stores are cautious, which accounts had a rough season, which territories had unusual weather that impacted sales, and which products are getting attention in appointments.
The challenge is to get that knowledge out of conversations and into the planning process.
That is why brands need a clear rhythm for collecting rep feedback before, during, and after the selling season. This can be simple at first:
Ask reps to tag high-confidence opportunities.
Capture buyer objections during line reviews.
Track products that retailers consistently ask about.
Record which SKUs retailers wanted but could not get.
Separate true demand from “nice to have” interest.
Compare rep expectations to actual orders and sell-through.
Over time, those inputs make the forecast stronger.
This is especially useful for outdoor apparel and footwear brands because product performance is often tied to territory. A trail running shoe, insulated boot, rain shell, sun hoodie, or fleece midlayer may perform very differently depending on climate, store format, local activity, and customer base.
The tighter you can make your forecast to a region or territory, the more accurate that forecast will be.
One of the most practical parts of the Sunski conversation was Grant’s point about 3PL communication.
Sunski meets regularly with its 3PLs. Sometimes the meeting is five minutes, sometimes it’s thirty. But the cadence matters more than duration, because fulfillment partners can only perform well when they know what is coming.
“The more information you give them accurately, the better that they can be,” Grant said. “A lot of brands struggle to forecast well. It’s hard.”
For wholesale brands, this is easy to overlook. Forecasting is often viewed as something that helps sales and inventory planning. But it also helps the warehouse.
If your 3PL knows a large pre-season wave is coming, they can plan labor. If they know a key account has routing requirements, they can prepare. If they understand which channels they are fulfilling for, they can avoid surprises.
That matters because flexibility is not just about having inventory. It is about getting that inventory to the retailer fast enough to capture demand.
Grant talked about fulfillment speed as a competitive advantage, especially in high season. “We can’t miss weekends in high season,” he said. The reason is simple: if a retailer misses a selling weekend because product is late, the opportunity may be gone.
For outdoor brands, that can be huge. A late shipment of sandals, rainwear, hiking boots, or cold-weather accessories can miss the moment. Better forecasting helps prevent that.
There is a temptation to make forecasting feel bigger and more complicated than it needs to be.
More dashboards.
More spreadsheets.
More meetings.
More models.
More tools.
But better forecasting usually starts with better discipline.
Do you have clean product data?
Can you separate wholesale, DTC, distributor, and drop ship demand?
Do you know which orders are prebook versus at-once?
Can you see sell-through by retailer, region, category, or style?
Are reps capturing useful buyer feedback?
Are forecasts updated when the world changes?
Are 3PLs getting the information they need early enough?
Grant made a related point when talking about data quality and AI: “Garbage in, garbage out.” If the data is poorly structured, you will not get good answers.
That is a good reminder for brands looking at AI forecasting tools or more advanced analytics. Technology can help, but only if the underlying wholesale process is sound.
A B2B platform, ERP, planning tool, or reporting dashboard should not create more silos. It should help teams see the same information, make better decisions, and act faster.
Here is a simple way outdoor brands can start making wholesale forecasting more flexible.
Do not treat all wholesale orders the same. A preseason commitment, an in-season reorder, and an urgent at-once fill-in all tell you different things.
Prebooks help you understand buyer confidence.
At-once orders show immediate need.
Replenishment shows real consumer demand.
Tracking those separately gives you a cleaner read on the business.
For apparel and footwear, SKU-level forecasting matters. A jacket is not just a jacket. A boot is not just a boot.
Size curves, color preferences, regional climates, account types, and channel behavior all matter. A black waterproof boot may be an evergreen replenishment item. A seasonal color may need a tighter buy and faster read.
Replenishment should not depend only on the retailer noticing they are low. Brands can be proactive.
If a product is selling through quickly, reps should know. If an account is at risk of stocking out in key sizes, they should know. If a retailer is sitting on the wrong mix, the brand should help solve it early.
Use historical order data, sell-through, account type, and rep input to create better recommendations.
For example:
“Stores like yours typically sell 60 percent of this category in three core sizes.”
“This color performed best in mountain markets last spring.”
“This style had strong replenishment last year, so we recommend a deeper opening order.”
“This item is trend-driven, so buy lighter upfront and plan to chase demand.”
That kind of guidance helps buyers feel more confident.
A forecast made six months ago should not be treated like a promise from the universe. Things change.
Weather changes.
Tariffs change.
Consumer demand changes.
Retail traffic changes.
Inventory availability changes.
Set a cadence to revisit the forecast and make decisions while there is still time to act.
Share expected order volume with warehouses and 3PLs. Flag key account windows. Identify routing requirements early. Make sure replenishment inventory is actually available to ship.
A forecast that never reaches operations is only half useful.
Wholesale flexibility does not mean chaos. It does not mean retailers order whatever they want whenever they want and brands carry all the risk.
It means building a system where decisions are informed by better data, cleaner communication, and stronger partnerships.
Prebooks still matter. Seasonal planning still matters. Reps still matter. Retail relationships still matter.
But the brands that win will be the ones that can combine early demand signals with in-season responsiveness. They will help retailers buy smarter upfront, replenish faster when the product is working, and make adjustments when it is not.
That is how forecasting becomes more than an internal planning exercise. It becomes a wholesale growth strategy.
Grant said it simply: “Help me help you.”
That is the job of better forecasting. Help the brand buy better. Help the rep sell better. Help the retailer commit with more confidence. Help the warehouse prepare. Help the customer find the product they want when they are ready to buy.
For outdoor apparel and footwear brands, that is the opportunity.
Don’t aim for a perfect forecast out of the gate, but a better feedback loop that leads to more effective, accurate, and reliable forecasting.
Want to listen to the entire conversation with Grant? Click here check out it on the Between The Drops podcast.