Healthy commerce is impossible without inventory management.
Inventory management system is a set of tried-and-true methodologies which keep your business organized. It oversees all inventory and stock items - from delivery to a warehouse and to a customer shopping cart.
It saves time, money and human resource, by figuring out exactly how much inventory is needed on-hand, and by preventing shortages and overstocks.
The faster your business grows, the more sophisticated and accurate inventory management system you need.
If properly run, inventory management can not only save you money but also generate you a constant cash flow. Remember, goods and products in the warehouses do not bring anything if they sit on the shelves, they are NOT cash in this case. They have to be integrated into the company’s cash flow management.
“Inventory management is a thing that affects cash, sales, costs and expenses directly. The better inventory system you have, the better cash flow you obtain”.
Some products in your warehouse need more attention than others, some are bestselling top goods and some have a modest financial impact. ABC technique is all about sorting and prioritizing.
There are 3 key categories:
A (high-value products, small in number, with low frequency of sales): They require the most attention and should be monitored more closely. They have a greater impact on cash flow and sales, but they are not in a constant high demand. They are quite unpredictable.
B (moderate in value, moderate in number, with average sales frequency): These goods are in the middle. it is important to monitor them preventing the risk of their transformation into the A or C category.
C (low-value products, large in number, with high sales frequency): These products generate sales, they are easy to predict, and they exit warehouse shelves quickly and easily. They are self-sustainable money-makers.
ABC technique helps to forecast demand and optimizes inventory by analyzing product’s trendiness among customers, but this method is rather time-consuming and if applied alone, without an intelligent inventory management system, requires human resource involvement. And experts mention that this method has a risk of simply missing out the products that are just starting to be trendy.
Developed in 1913, and refined later, this formula serves vendors for years, identifying the optimal number of goods to order, minimizing costs for buying, storage and delivery. It assumes that demand, order and storage costs are constant and steady.
Q - economic order quantity (units)
S - ordering cost per purchase
D - demand in units
H - carrying cost per unit
This model if applied alone, requires a very good understanding of math, and very detailed data, while hiring a consultant or an employee for these calculations is money- and effort-consuming. EOQ calculating specialized software can be a solution and an efficient investment for micro, small and medium enterprises.
It does not account seasonal or economic fluctuations and does not allow combining several products in one order, which limits its effectiveness for large retail businesses.
The definition of Minimum Order Quantity (MOQ) is pretty straightforward: it refers to a minimum quantity of goods that retailers have to order from their suppliers to keep their relationship active. In other words, if your order does not reach the MOQ threshold set by the supplier, he won’t accept and fulfill your order.
How to make this indicator helpful for the inventory management process? For supplier businesses the benefits are evident: by promoting in-bulk shopping, they can secure faster inventory turnover and get profits. For retailers the benefits are not so understandable, as they are simply forced to buy more by complying with the requirement set by the supplier.
However, usually, the higher MOQ is set by the supplier, the less retailer has to pay per unit. For instance, if you buy products in bulk, you can get a lower price per unit. Additionally, if you as a retailer comply with MOQ requirements established by a supplier, this contributes to maintaining steady partnerships which are very important. Steady and healthy relations between suppliers and retailers usually mean competitive prices and valuable deals for both.
FIFO technique is a simple straightforward approach to inventory management, that says that the oldest stock sells first, or in other words, the first items coming to the warehouse are first items sold.
Easy real-life example of FIFO is milk in a supermarket. Milk purchased later is being hidden in the back of the shelves, and the milk supermarket buys first, is on the front of the shelf. FIFO can be used for perishable goods, with an expiration date.
FIFO is easy to use and simple to understand, though it proves its efficiency when the prices are more or less steady. And of course, there is no guarantee that oldest items will be inevitably sold first, and the risk of product reaching its expiration date and spoilage are rather high.
On the contrary, we have a LIFO inventory technique, which assumes that the newest items purchased are sold first, and the most recent pricing is used to determine the price for the customers.
LIFO can be potentially used for businesses selling non-perishable goods, which have a long shelf life.
Most retailers stick to the FIFO technique, but some businesses choose LIFO to lower their taxable income and get tax advantages. The trick is simple - upon assuming that the prices are rising, the newest inventory will be sold at a higher cost, and this will decrease profits lowering the taxable sum.
Invented by Toyota in 1940s, JIT method is an inventory planning technique which means that you keep very low or zero inventory, and get the goods to your warehouse only when they are required. Inventory levels and requirements are based on current sales trends. For instance, when an order comes, it triggers the whole supply chain from scratch, while during no-orders season JIT method promotes “zero inventory” model.
As JIT technique minimizes stock levels, it reduces the likelihood of goods being spoiled or expired, and importantly, it reduces the risk of having excess items, that will need to be liquidated.
Popularized by Toyota, JIT technique has become almost iconic, and many business people have been using this strategy as a primary one. Yes, its potential for saving and earning costs is great, but it includes certain risks as well.
One of the main drawbacks of this technique is a great dependence on the suppliers and contractors who can leave the retailer with almost nothing if they fail to fulfill the order. And a sudden spike in demand can also badly affect stability of the supply chain.
But if you are able to build a reliable network of trusted suppliers and contractors, this system can work perfectly well, especially if an automated system helps you to implement JIT more effectively, intelligently managing vendors and purchase orders, and reducing delays.
This technique involves an agreement with the contractor to pay him only when his product sells. For example, a wholesaler places stock on the shelves of a retailer but keeps the rights and ownership of the stock until it is sold. And at that point retailer buys the consumed stock. Sure, this method involves a risk and demand uncertainty and a very extreme degree of trust from the wholesaler.
Within consignment technique retailers can enjoy the benefits of offering a broader range of products to their customers, without freezing his capital, and at the same time retailer is able to return unsold items at no cost.
Wholesaler, or contractor, is the one who takes greater risks, but he can enjoy some pleasant benefits, like putting marketing costs of the product on the shoulders of retailer or testing new products.
Backordering is an inventory management model, which implies taking orders and receiving payments for the goods which are out-of-stock. Simply said, accepting an order from a customer for a product which is out of stock, but not showing it to customers. Once the order is placed, you order stock and replenish it. And you get the order as soon as possible. Seems interesting, so it is.
It seems to be a dream model, but it should be accurately and perfectly managed in terms of logistics. Imagine, a retailer monster dealing with hundreds of different sales a day. Here the problems may begin if improperly managed. But at the same time, backordering is a high-stakes “game”, which can increase sales and cash flow, and lower overstock risks and decrease storage costs. Many businesses are willing to take this risk. And again, sophisticated inventory management systems can help to mitigate these risks.
These seven techniques are just the basics, fundamental and trusted methods of inventory management. There are even more practices to learn and follow - for example, dropshipping. The best thing about it is that today’s intelligent inventory systems can help you to combine and adapt these best techniques to your unique needs, make them highly customizable, effective and cost-saving.
Demand forecasting is a set of ongoing processes aimed at estimating and predicting the amount of merchandise (products or services) customers will purchase in the future (during a particular period of time - week, month, quarter, year, etc.). We use the word “ongoing”, as demand forecasting is a continuous process, not a one-time action. You have to actively work to improve your predictions - conduct market studies, explore your customers behavior and shopping trends, or invest in demand planning software.
Mistake in demand forecasting can cost you thousands of dollars spent on costly dead stock or lead to lost sales - that happened to Nike after they made an error in demand forecasting for Air Jordans and lost huge sums of money not being able to meet customer orders.
Demand forecasting is a very complicated process, it uses a mix of quantitative statistical data (sales figures), expert intuition and experience-based assessments, market trends and competitors performance.
Most commonly, demand forecasting uses historical sales data as a basis and other trends (seasonality, promotions) as additional factors. However, even the most sophisticated calculations can not guarantee a 100% forecasting accuracy.