Inventory overload? Predictive analytics could be the solution

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Budgeting for a business is a difficult task – and one contingent on proper inventory planning. Too much inventory – or just the wrong inventory – and you’ll find yourself drowning in worthless products, while not enough of the right inventory will hold down your company’s earning potential. But how do you know what to stock and how much, especially in changeable, trend-driven industries? Today, the answer is all about predictive analytics.

Brick and mortar businesses have struggled to keep up with online stores, in part because of the problem of inventory, but predictive analytics offers a solution – one these businesses have begun to embrace by hiring data scientists. With data scientists as part of the core buying and sales teams neighborhood businesses, department stores, and other brick and mortar, can keep up with the near unlimited inventory found in online shops. And complementing the work of data scientists, of course, is analytics software designed to bring new perspective to the work of purchasing.

It’s time to stop struggling with your inventory and embrace smarter buying practices. Particularly in businesses where large inventory investments are financially untenable, it’s the only way to compete with digital brands.

What Makes A Sale

To an outside observer, sales seem both simple and inscrutable. The simple part is that people make purchases either out of necessity – eggs, a mattress, clothing – or out of desire – toys, televisions, or art. But things become complicated when issues of the particular arise. What motivates someone to buy a Ferrari rather than a Ford or a truck instead of a van? Or to choose between two shirts in different colors?

The answers are rarely obvious, and this is where inventory management intersects with predictive analytics – in an attempt to determine what sales are coming up and improve purchases and profits.

Purchasing And Placement Problems

Predictive analytics allows businesses to solve several key product purchasing problems. With expensive items like vintage engagement rings, for example, it’s cost prohibitive for most businesses to keep a large stock on hand; the upfront expenses are too large. In order to buy smarter, then, these businesses can track evolving purchasing trends and focus buying on styles that are currently popular and work on downsizing stock that’s temporarily out of style.

It’s much harder to predict an item like vintage rings or other minor markets than it is routinized trends like day-to-day clothing or even groceries. It’s also easier to manage inventory for chains than for single businesses – the ability to move products around based on uneven sales data works to your company’s advantage.

You can guarantee people will want long sleeve shirts during the back to school season or bathing suits during spring break, but you can’t be sure they’ll sell equally well in a residential area and an urban business district. Having ongoing data lets you move those items around to maximize sales.

At its core, we’ve always done some level of predictive analytics in stocking stores, even before we had the complex software to do it. Some neighborhood grocery stores stock primarily Mexican ingredients in the international row, while another stocks Asian ingredients, even though they’re part of the same chain – this is a predictive gamble based on demographics, but modern information-management takes it to the next level.

Stop losing money to poorly planned stocking and start assessing upcoming trends to boost business income. Overstocking on unsellable items, overspending on expensive, high-risk products, or understocking items that are in high demand are all ways poor planning can hold your company back. The right software, plus in-house data analysts, can set your company on the path to financial success and set you free from excess products. It is possible to buy smarter.

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