In this solo instructional video, Omar from Moov warns DTC founders about the hidden dangers of forecasting without reliable data. He explains how optimistic, assumption‑driven forecasts create a cycle of stockouts, overstock, cash being trapped in inventory, margin compression, and reactive operational stress. An anonymized low‑seven‑figure brand example illustrates how a spreadsheet‑based forecast built on last‑year memory and ad‑growth assumptions led to missed hero‑SKU inventory, rushed freight, forced promotions, and strained supplier relationships. Omar then outlines a practical, decision‑grade demand planning framework: use 8‑12 weeks of sales velocity per SKU, separate demand into baseline, marketing‑driven, and event‑driven buckets, forecast top‑selling (A) SKUs individually and group long‑tail (B/C) SKUs, implement reorder‑point guardrails, and label forecasts with confidence levels. He advises founders to ignore fancy forecasting tools, daily granularity, and complex seasonality models until data is clean, focusing instead on weekly velocity and cash protection. The video ends with a teaser for mistake #3 (process vs. supply‑chain problems) and an invitation to reach out for personalized help.
Chapters
Hi guys, it's Omar here. Welcome back to the series where we talk about the expensive mistakes that look responsible on paper but quietly wreck your supply chain later. This is mistake number 2. It seems smart because forecasting sounds like planning, but here's what happens 18 months from now when you're trying to scale. Have you ever placed what felt like a safe inventory order? And somehow you still stocked out, or the opposite, you ordered heavy because you were confident and now you're staring at a warehouse bill thinking, why do I have 8 months of this? I've seen brands do this and lose money on both sides, lost revenue from stockouts and cash trapped in slow movers at the exact moment they needed it for marketing. So it needs to be very aligned when it comes to that. And the wild part is they thought they were doing the, the mature thing. They were forecasting. They, they weren't just using data. So what is forecasting without data? It's basically when you forecast, it's mostly just based on vibes, gut feel, and optimism dressed up in a spreadsheet. It usually sounds like we're probably going to grow 20% month over month. Last launch went well, so this next one should be similar. We feel like the SKU is about to pop or our ads are improving, so demand will follow. Let's just order enough so we don't stock out again. So these are just really common things that even I usually hear from founders that think that their supply chain is going well. And to be fair, it seems smart because forecasting feels like what real businesses do. You're trying to be proactive, you're trying to avoid chaos. But here's the catch. If you don't have clean inputs, the forecast isn't planning, it's a story. And stories do not protect cash. Forecasting without data is basically building an inventory plan on top of assumptions that haven't earned the right to be trusted yet. Here's why it gets expensive later. And I want you to picture the 18 months from now version of you or your brand. At the beginning, forecast without data creates small misses. You order a little too much of one thing, you get a little bit of, you'll get a little bit excited. So you slightly under-ordered your hero SKU. The panic expedite once or twice. So we've heard this, I'm just going to ship a couple of error packages. So I'm just going to expedite a little bit. On a couple of my shipments. Annoying, but survivable. But when the brand grows, now you have more SKUs, more variants, more channels, more ad spend, and usually more complexity in the supply chain too. And the cost of being wrong multiplies. You trap cash when you need it the most. Basically, when the forecast is wrong, you buy inventory you don't need yet. That cash is now sitting on the shelves. So you start making dumb trade-offs like, let's pause new product development, or let's cut ad spend, let's delay hiring, or let's run a promo we didn't want to run. Not because the business is failing, but because the cash is stuck in boxes. Brands that overbuy slow movers often underbuy winners because cash is trapped. So get this cycle: stock out of the thing that sells and then overstock the thing that doesn't. Run promos to clear inventory. Margin gets worse. Cash gets tighter. Then you stock out again. This is, this is a very, very common cycle that we hear all the time here at Moov. It feels like bad luck, but it's actually just a forecasting system problem. So when forecasting is unreliable, everything seems reactive. Procurement becomes panic orders. Logistics becomes expediting. Customer service becomes apology emails. The warehouse becomes, where do we even put this? You are not scaling operations, you are just scaling stress. Forecasting without data means your POs are inconsistent. Suppliers hate inconsistency because it makes their planning harder to do. So this is what you're gonna be hearing. MOQs increased or lead times increased. You haven't guaranteed production slot or price is higher now, and you're thinking it's the supplier's fault. Sometimes it is, but a lot of times it started with you not having a stable plan backed by real demand signals. So let me give you a real example, anonymized. So we worked with a brand doing low 7 figures, lots of product variants, solid marketing team, and they were convinced forecasting was their next grown-up step. They had a forecast model that looked legit, like tabs, charts, formulas, the whole thing. But when we asked that data— that what data is driving these numbers, it was mostly last year's memory of performance, or another thing we heard was assumptions from our ads growth, or a target revenue number they wanted to hit, and a bunch of manual overrides because the sheet is never quite right. So this is all something that we hear a lot of these confident DTC owners are going through. So what happened? They revamped inventory on SKUs they thought would be winners, and they didn't build a proper baseline of actual sales velocity per SKU. 3 months later, their hero SKU selling was selling faster than expected and stocked out. Their future hero SKU barely moved. They tried to shift ad spend and they didn't have inventory depth on the winners, and they ran promotions to move slow inventory, which crushed margin. Then freight got expedited for the hero SKU to recover, which crushed margin again. So now they had less cash, worse margin, more stress, and their forecasting sheet looked even less accurate because their business got messy. When we rebuilt their approach, their answer wasn't a fancier forecast. It was a simpler, cleaner, and a more honest forecasting model. So here's what to do instead. If any of those sort of remind me of your, remind you of yourself, here's things that you can do, especially if you're not a huge brand yet. You don't need a perfect forecast. What you need is a decision-grade demand plan. So keep it simple. Start with sales velocity, not goals. Velocity is reality. Goals are ambition. So you take your last 8 to 12 weeks of sales by SKU and calculate average weekly unit sales, trend direction, flat, up, or down, and variability. Is it stable or spiky? If you only do one thing, do this. You can separate the demand into 3 buckets. So this is, this is What move— this is the move that instantly becomes, and it makes planning a little bit clearer. Baseline demand. This is definitely what sells even when you do nothing special. Or marketing-driven demand, what moves because of campaigns, ads, or pushes. And event-driven demand, launches, holidays, big promos, influencer moments. Most brands blend these together and call it a forecast. And that's how you get fooled. So forecast at the SKU level for winners and category level for everything else. You don't need to forecast 400 SKUs with the same effort. Forecast top sellers, your A items individually. Group the long tail B and C items into buckets. This keeps your planning sane and it reduces how often you overthink tiny SKUs. So you must have definitely heard of grouping into ABCs. That's typically what it is. So this is where brand gets it backwards. A reorder point system is like guardrails, lead time, buffer, reorder trigger based on actual velocity. That alone prevents the biggest disasters. Forecasting is great, but if you reorder logic, is broken, your forecast is just a decoration. So you need to add confidence levels instead of pretending that you know. So this is huge. Not all forecasts are equal, so label them. High confidence, stable velocity, stable supply. Medium confidence, some trend, some variability. Then you finally have low confidence. You have your new products and a volatile demand. Then you just adjust how aggressively you buy. The goal is not to be right all the time, but the goal is to achieve and to avoid being catastrophically wrong. The permission is what you can safely ignore. Now, let me give you permission to ignore some stuff because I know some of you are thinking, okay, Omar, do I need advanced forecasting software? Do I need AI? Do I need a data warehouse? Simple answer is no. Here's what you can safely ignore at this stage. You can ignore the fancy forecasting tools until your data is clean and consistent. You can ignore forecasting down to the day. Weekly is fine for most brands. You can also ignore complexity seasonality models if you don't have at least 12 to 24 months of reliable sales history. You can even ignore perfect accuracy. You're aiming for good enough to protect cash. And service level. And mind you, if you're early, your job is not to predict the future perfectly. Your job is to build a planning rhythm where reality updates the plan quickly and cash stays protected. So that's mistake number 2, forecasting without data. It seems smart because forecasting feels like control. So, but here's what 18 months from now when you're trying to scale, you're either out of stock. On the only thing people want, or you're sitting on a pile of inventory you can't turn into cash fast enough. So next episode, we'll be hitting mistake number 3, and this one's going to hurt because it's the one that, that makes brands think that they have a supply chain problem when they actually have a process problem. If you want, I can break those things down. If you also want, you can reach out to us and we can perhaps talk to you guys and you guys can give us your pain points and we'll see how we can support a couple of these things. So that's it for me for this episode. Thank you so much for watching.
