For small or midsized businesses (SMBs) like you, demand forecasting likely ranks just as highly as January inventory reconciliation on your fun scale, which is to say, very low. But you know that doing demand forecasting right is critical to ensuring your multi-channel product business succeeds in an evolving, digital-centric economy.
That’s why we’re taking the time today to clearly define demand forecasting, dissect the common demand forecasting mistakes SMBs like you may be making, and describe exactly what you need to do to avoid (or fix) them.
Let’s jump in!
Demand forecasting is the process of determining how much product your customers will want and when they’ll want it based on historical sales data, customer trends, seasonality, promotions, lead times, and external factors (e.g., market conditions, supplier reliability, and logistics challenges). It’s different from demand planning.
Demand planning is what you do in response to your demand forecasting. Both are important for optimizing your supply chain operations and inventory levels as well as for aligning your production and distribution strategies.
Demand forecasting’s importance explains why it’s so important to get it right. You want to keep your sales flowing, your customers happy, and your supply chain (and cash flow) moving, results that are only possible when your demand forecasting is on point.
But getting it right is hard. There are forces outside of your control (and sometimes in your control) that can work against you. Think volatile markets, complex operations, and gaps in your data—all of which can lead to inaccurate decision making and poor forecasting.
And unfortunately, you as an SMB are more susceptible than your larger competitors to battling them
Being small or midsized comes with huge benefits. Unlike big corporations, you have less red tape to cut through when making crucial operational decisions. You can build more personal relationships with your customers. And you can cultivate a reputation that sets you apart from the big-box competitors.
Still, for all your flexibility and uniqueness, there are downsides to being smaller. You may:
These factors can trigger poor demand forecasting. Instead of ordering product based on data-driven knowledge, you’re ordering based on guesswork. And you know where guessing gets you: stockouts and lost revenue or excess inventory that ties up your cash.
No matter how you look at it, doing demand forecasting by hunch costs you, but you can avoid all this if you understand, and stop, the demand forecasting mistakes you may be making.
Intuition can help you manage small, simple inventories, but as soon as more customers find you and the orders start flowing, the increased complexity will skew your gut feelings. Historical data shows how demand ebbs and flows over time, allowing you to use patterns, trends, and cycles to adjust your ordering.
Seasonality and demand fluctuations are part and parcel of running a modern product business. If you don’t monitor these expected and changing conditions and adapt your demand planning accordingly, you’re setting yourself up for inventory chaos.
Like cash, data’s role in business is decidedly kingly. You must have data to make accurate forecasting outcomes, but your data can’t be segregated in different applications. For you to make strategic forecasts, you must have updated, accurate, and easily accessible information backing every decision.
Spreadsheets have been helping businesses visualize, calculate, and analyze their data for decades. Unfortunately, spreadsheets can’t scale with a growing business, they provide static (not real-time) information, and they’re flashpoints for operational risk (e.g., human error, outdated formulas, and version control issues). This all adds up to negative inventory outcomes.
Supplier lead times, or the time between when you place an order with a supplier and when you receive it, is one of the factors in business you can’t control. That’s why you need to pay attention to this timeframe (whether long or short depending on your suppliers), which can, and will, affect your inventory levels.
External demand factors, such as the supplier lead times we just discussed, should be part of your demand forecasting calculations. Market conditions, supplier reliability, and logistics challenges all determine if or when you can get your products. Your job? Ensuring that you’re taking these factors into account when predicting as well as fulfilling customer demand.
Do you assume that once you’ve made your demand forecast, you’re good to go? It’s not an assumption you want to make. You should be reviewing and adjusting demand up or down on a monthly basis based on sales trends, market changes, promotions, new product launches, and more.
Effectively managing anything in business requires that every team is working off of a shared playbook. For demand management, this means ensuring your sales, purchasing, and supply chain/operations teams have the same goal, which, in this case, is ordering the right amount of products to meet customer demand without clashing over sales goals and operational efficiency. This also means making sure you’re using the same data, which is a requirement for making accurate demand forecasts.
If you aren’t making or haven’t made any of the demand forecasting mistakes we’ve just listed, then you’re a unicorn in the product business world. Most businesses have made a demand management misstep or two but getting back on track is easier than you think.
Following are some best practices for getting your inventory planning in line:
These tried-and-true strategies will help you get your demand forecasting A-game on, but if you’re concerned about how to implement them, then we have one more piece of advice: invest in an all-in-one, affordable, and cloud-based inventory management software (IMS) like Cin7.
Cin7 provides the centralized database, AI-powered demand forecasting tools, and seamless integrations across e-commerce solutions, marketplaces, and accounting applications you need to make demand forecasting effortless.
With Cin7 IMS and its 700+ integrations (including Xero, QuickBooks, Shopify, Amazon, and more), you have a single, real-time system that synchronizes your data from every application. Cin7 delivers real-time inventory visibility and empowers you to get your products into your customers’ hands quickly and efficiently.
Add to these capabilities Cin7 ForesightAI, a tool that helps you manage your demand forecasting as well as automate reordering and eliminate stockouts and overstock, and you have a complete inventory management solution.
Shay Lawrence, founder and owner of CaliWoods, took a chance on Cin7 and ForesightAI, and it paid off big time. “ForesightAI lets me see what we have in stock and know what we need to order per supplier with a click of a button. We’re able to make sure that our stock is accurate to the day. It takes the manual errors out of it, it saves us time, and it saves us money in terms of not running out of stock or not ordering too much.”
All that historical data you need to predict demand? It’s in Cin7. Plus, Cin7 will automatically analyze it, your performance, and emerging patterns so that you can forecast up to 24 months in advance, which means you’ll be ordering the right stock at the right time.
Spreadsheets? Gone. Managing seasonality, demand fluctuations, supplier lead times, and external demand factors? All done in Cin7. And working with accurate data, reviewing forecasts regularly, and ensuring cross-team alignment? All taken care of with Cin7 and ForesightAI.
“ForesightAI was probably the big page turner for us,” Shay says. “It’s super, super helpful.”
If you want a super, super helpful solution that helps you avoid or fix your demand forecasting mistakes, request a free Cin7 demo today!
While more data is better, a minimum of six months of sales history can provide useful patterns, especially when combined with market research and qualitative insights.
Use data from comparable products, gauge pre-launch interest through sign-ups or pre-orders, and use industry benchmarks as a starting point, then adjust quickly based on early sales data.
When spreadsheets become unmanageable or forecasting errors start costing you real money in stockouts or excess inventory, it's time to consider AI tools, like ForesightAI.
Perfect accuracy isn't the goal; consistent improvement is. Aim to reduce your forecast errors over time by regularly reviewing your performance and adjusting your methods.
Warning signs include frequent stockouts or overstocks, spending more time managing spreadsheets than analyzing insights, and discovering conflicting data between team members.