Learn what inventory forecasting is, why it’s important, and best practices for future-proofing inventory forecasting.
Learn what inventory forecasting is, why it’s important, and best practices for future-proofing inventory forecasting.
Inventory forecasting is a predictive measurement of customer demand used to to optimize inventory levels. The accuracy of inventory forecasting affects a merchant’s production levels, warehousing costs, and ultimately their bottom line.
In plain terms, inventory forecasting helps you optimize your supply to meet demand: If your inventory forecast is too high, you may have to discount product to move it off the shelf. Too low? You could face stockouts.
To calculate inventory forecasting — also known as demand forecasting — it is critical to consider variables like Average Daily Volume (ADV), lead time for replenishing stock, and sales trends.
Inventory forecasting is a high-level function, and fast-growing merchants may not feel that they have the internal resources to include it in their business planning. However, inventory forecasting is important for healthy and sustainable growth. Below are some of the top benefits of accurate inventory forecasting for your business.
Inventory is most merchants’ greatest investment. Inflated inventory carry costs mean there is less capital available to invest in product development, hiring, and automation. Accurate inventory forecasting will give you confidence that you won’t run out of stock without tying up all of your capital.
Many suppliers offer bulk order discounts, but merchants operating on a just-in-time supply chain model likely aren’t able to fully take advantage of those discounts. Accurate inventory forecasting allows you to strike a balance between getting the best possible price for your inventory without the risk of over-ordering.
Every time your ecommerce storefront or marketplace listing experiences a stockout is a missed opportunity for a sale. Accurate inventory forecasting gives you the confidence that you’re snagging every potential sale.
Similar to other operating costs like inventory shrinkage, some misalignment between supply forecasting and demand forecasting is inevitable. These inaccuracies largely occur simply because of the inability to forecast demand through the lens of production. This is especially true of merchants who may rely on more than one supplier. An increase in demand creates a “bullwhip effect” which ripples demand throughout the supply chain, and unless all suppliers can scale up to meet the demand of product orders, shortages occur.
This goes hand-in-hand with stockouts. According to a study from Univ. of Colorado at Colorado Springs and The London Business School, stockouts are a leading contributor to inventory forecasting disruption.
Along with monetary losses due to stockout, merchants face a higher cost than just the price tag on a product: In an international study, Harvard Business Review found that 26% of customers will opt to buy a substitute product from a different brand if the customer’s brand of choice is out of stock.
In the video below, Jimmy Mitchell, Ware2Go’s Senior Director of Business Operations, explains some of the compounding effects that stocking out can have on a merchant’s operating costs and profitability.
Wit big box stores competing on market share and price, and the growth of e-commerce giving consumers more choice, one thing has become unavoidably clear: the margin for error on key KPIs like inventory forecasting are thinner than ever before.
For years merchants could only conduct inventory forecasting based on the previous fiscal year, assuming the same demand year-over-year and testing the market as they scaled up. However, technological advancements and greater access to data made it possible to see industry-wide trends on when consumer buying patters. But as these buying cycles became industry knowledge, it left little room for competitive advantages.
So, how are small to mid-sized businesses addressing the current state of inventory forecasting and taking the lead? There are certainly obstacles in the way, not the least of which is that we’re now living in a 1-click purchase marketplace where customers expect 2-day shipping. In fact, 37% of customers expect SMBs to ship faster than big box stores.
However, there is a way to work smarter, not harder and put optimization at the forefront. By adopting the following best practices, merchants like sports recovery drink O2 have been able to provide 98% on-time delivery and 99% 1-2 day shipping, even during the historic disruption of the marketplace and logistics chain in 2020.
Industry buying cycles are generic and don’t take into account your market position, unique differentiators, or the strategic marketing that is growing your business. Furthermore, industry-wide data can’t help inform warehousing decisions that will ultimately determine if your business can meet consumer expectations for shorter shipping times.
Internal teams running the numbers adds time, effort, and the risk of human error, but automating your Inventory Forecasting all in one place — and from all sales channels — can be done with the backing of smart technology.
Even better? With digital warehousing, data analysis can now be used to understand not just customer demand, but where that demand is coming from geographically. This means that merchants get better inventory carry costs and lower overall fulfillment costs because they’re shipping from the optimal locations. When merchants have the right inventory stocked in the right warehouse locations, it becomes much easier to meet consumer expectations for fast shipping.
Common insights that digital warehousing can provide include:
Typically this type of supply chain expertise is reserved for enterprise brands with the resources to hire a team of supply chain experts from procurement specialists to analysts. However, new applications of machine learning and artificial intelligence (AI) in the supply chain, merchants of all sizes can access in-depth business intelligence to make smarter decisions around inventory placement.
According to Brian Gallagher, Chief Technology Officer at Ware2Go, machine learning helps merchants make more tailored decisions and even act proactively rather than simply responding to events after they’ve occurred.
With off-the-shelf software, the relationship tends to end after purchase, and merchants are left on their own to understand and implement tools that calculate inventory forecasting. But it doesn’t have to be this way. Merchants should be able to hold their Warehouse Management System (WMS) provider accountable to promises made, including data-based service license agreements (SLAs) and 99.5% cycle count accuracy.
At Ware2Go, we take a consultative approach with our merchants, regularly running analyses to understand your specific sales cycles and the geographic locations of customers with pinpoint accuracy so you know exactly how much inventory to stock and where to stock it.
Few small to mid-sized merchants will have the internal bandwidth to track and analyze historical sales data and market trends via traditional spreadsheet methods. As the 3PL industry has evolved to better serve the needs of SMB’s many tech-forward 3PL’s are now offering inventory forecasting tools as part of their platform.
These forecasting tools rely on machine learning and AI to automate and simplify processes that would otherwise take a team of experts to manage manually. They can show sku-level health at-a-glance, alert when a stockout is imminent, and recommend reorder points and quantities.
By partnering with an outsourced fulfillment partner, businesses of all sizes can leverage best-in-class technology to forecast demand, grow sales, and improve their bottom line.