Let the data tell you how dead something is, let a person decide how to deal with it. This should be systematic, repeatable and testable.
What is dead stock?
Dead stock is inventory (sat in your warehouse) that’s never going to be sold to a customer.
Unchecked, dead stock can be the silent killer of an otherwise successful business because it hammers profitability and ties up working capital. Whilst inventory is often a brand's single largest expense, many are bad at keeping on top of it.
How does it happen?
A (non-exhaustive) list of how brands end up with dead stock:
Lack of experience (particularly in startup and scaleup businesses) leads to buying on gut feel alone, resulting in overbuys on the initial new product development (NPD) purchase
Poor forecasting of sales and demand planning
Cannibalisation; newly launched / preferentially marketed products eat into the sales potential of other products
Seasonality and shifts in consumer taste make product less popular
Product not even being listed for sale - you’d be surprised how often we see this
No data-driven approach to managing stock through all stages of its lifecycle
These are the more obvious costs of holding excess inventory like warehouse storage costs, people costs associated with moving, counting, and looking after the inventory.
Capital investment:
Committing cash to inventory that doesn’t sell means the same money can’t be used elsewhere. Working capital is critical in all business cases especially if a brand operates with thin margins or are aggressively scaling year on year.
Missed opportunity:
What is less obvious and visible is the cost of the missed opportunity - dead stock is inventory that is very unlikely to sell at full margin and depending on its age, its presence on a brands site may have a detrimental ‘halo effect’ on the entire site. There is a concept that the human brain perceives value as an average, and not as a sum, so an old, out-of-fashion line listed in a PLP of your site can actually drag down the overall perceived value of your brand and lead to even fewer sales than if the product were not present at all.
So how do we fix it?
The answer is relatively simple (in theory), nurture stock throughout its life cycle in a data-informed way:
Use comparables when planning an NPD buy, to ensure that you are purchasing optimally in the first instance (this is dramatically enhanced by good product attribution through your tech stack).
Control catalogue width. Often the quickest way to increase growth in a business is to increase the width of the offering - meaning expansion of ranges, launching of new categories (e.g. fashion brand launching athleisure or sleepwear, for instance) - but this makes the management of stock increasingly complex and difficult.
Keep a history of inventory levels by SKU so that sell-through can be easily calculated for analysis.
Keep restock purchasing separate from open-to-buy (OTB). Unless you have a very specific target mix of styles / product types, let the data do the talking when it comes to depth of restock and where possible don’t let your OTB budgets throttle the potential of your existing lines.
Overlay your marketing calendar on your sales trend to understand how your baselines are affected during promo periods, then overlay your future marketing plans to influence your buys.
Identify dead stock early and have a plan of attack of how to deal with it. Combine data with human input here - let the data tell you how dead something is, let a person decide how to deal with it. This should be systematic, repeatable and testable. Some examples of this:
Increasing levels of discount over a period of 60 days
Bundle products together (can be quite labor intensive)
Run dedicated clearance sales
Look for alternative exit paths through partner resellers
If possible, see if supplier will accept product back as returns, particularly if the stock is dead due to quality issues
Learn where to draw a line under it. In the case of very old styles etc., these products may now be doing your brand more harm than good. In this instance donation or liquidation is often the best option
All of these techniques combine a strong data-informed approach with human input and decision making. You can’t have an effective stock management program without both of these elements.
At least some degree of dead stock is unavoidable in businesses with a stocked model that do not make-to-order but by employing the proper systems and processes it is something that can be kept at a manageable level.
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