As a business grows, ensuring sales data is accurate can become more and more of a challenge. And when businesses are still small, owners can easily overlook the importance of maintaining oversight of data. But the reality is that accurate data is extremely important to the long term success of a business, and inaccurate data can have catastrophic consequences on inventory management.
In this article, we explain two major consequences of poor data for a business, including the accumulation of unsellable stock to the unexpected drying out of highly popular stock.
How does ‘poor data’ occur?
The main way that businesses end up with poor data is by failing to keep on top of the inflow and outflow of inventory, including everything from raw materials to finished products. For example, smaller businesses just starting out may overlook this task assuming that their output isn’t large enough to merit record keeping — this is a big mistake.
On the other hand, larger businesses can end up with poor data because they simply don’t have the time, resources or staff with the right skill set to be able to keep on top of their data. Poor data can also occur when sufficient research has not been done to predict which stock items will be popular — and unpopular — in future.
These circumstances often lead to data that is inaccurate, out of date or insufficient, which has huge knock-on consequences for inventory management and most importantly, sales and profitability.
Consequence 1: Unsellable stock
One of the major consequences of having poor data is accumulating unsellable stock in inventory. This stock is unsellable usually because it either is no longer in demand and therefore is very unlikely to be sold, or it is seasonal stock, meaning it is only in demand during a particular timeframe (e.g. Easter). Another reason you may end up with unsellable stock is if it is perishable and has passed its expiry date.
So how does poor data lead to unsellable stock? This can happen where the data used for sales projections and inventory orders is out of date. For example, while the historic data may suggest that item A will be in high demand in the next few months, that data may no longer be accurate. In this hypothetical situation, it may be that item A was only popular previously because of a particular trend, which is now waning. When inventory managers use this data to purchase another round of inventory, item A ends up gathering dust on the shelves.
How to get rid of excess stock
Consequence 2: Depletion of key stock
A related consequence of poor data is the depletion of key stock which is in high demand from the customer base. This can happen when poor data is used to calculate requirements for a future inventory order, which doesn’t accurately show the popularity of a particular item. Let’s say that records of sales were not recorded at all, or were not recorded consistently. In this situation, the data would suggest that, for example, item B would not be in demand and therefore there would be no need to order it in future. If this data was used, it is missing key information, resulting in an insufficient supply of item B, leading to seriously dissatisfied customers.
Learn about how to classify stock for better inventory management
To ensure you don’t make the mistakes described above, we suggest you use cloud-based inventory management software to keep your stock levels up-to-date and accurate. Doing so will help you make projections about future sales trends and therefore, enable you to effectively prepare your inventory for future spikes and drops in demand.