What is it, and Why Does it Matter to My Business?

Back in this previous blog, we discussed how important it is that retailers get their inventory management right – in a nutshell, making sure you have the products your customers want available in the right quantities, so you neither lose sales from running out of stock, nor end up with piles of unwanted products you cannot shift.

In this blog we want to pick up on that second point – guarding against overstocking and ending up with unsold goods, which can bite hard into your margins. This is part of the fine balance involved in demand forecasting. If your predictions about demand turn out to be too high, you can find yourself with a large amount of capital tied up in stock you have bought but cannot sell.

There are various tricks and strategies used in inventory management to mitigate this risk, such as ABC analysis, which categorises products by value and focuses purchasing efforts on goods with the best margins and best volumes. But even then, while this hedges bets towards stock that is likely to deliver the best returns, it is nearly always based on historical data and doesn’t account for the fact that demand for products can change.

This is where an understanding of the product life cycle comes into its own.

Product life cycle explained

The product life cycle is a model for how demand for items changes over time. In brief, it describes how, when new products are released onto the market, demand often accelerates quickly through a ‘growth’ phase, before eventually plateauing at a peak we can describe as the ‘mature’ phase. Eventually, demand for nearly every type of product will start to decline again.

Within this basic outline, there are a lot of different variables to consider. The life cycle of products in some verticals – for example, fashion apparel and other goods with a high level of seasonality – can be very short, characterised by sharp acceleration in demand followed by rapid decline with just a short plateau in between. For other goods – think of named brand grocery staples, for example – the cycle is very different, with a more or less constant plateau in demand lasting many years.

It also has to be understood that the demand curves described by the product life cycle represent averages only. Demand for some goods will follow a ‘classical’ curve very closely, but others will show considerable up and down variation from the mean while still broadly following the general trend. Demand for such items might be described as erratic or ‘lumpy’.

Making use of product life cycle

So how does all of this help retailers? Put simply, by gaining insight into how demand for different items might vary over time, the product life cycle helps retailers make smarter decisions about their buying and inventory. Ultimately, it mitigates against the risk of overstocking, giving you an idea of when to start considering scaling back supply of even your best-selling items in anticipation of a decline.

Equally, turning that around, even with the most ‘lumpy’ sales trends, product life cycle can give you the insight to hold your nerve when you see a sudden dip in sales for a product, telling you the difference between a temporary blip and what is likely to be a longer-term trend.

Of course, you might have guessed by now that in order to deliver these insights effectively, the product life cycle requires data, and lots of it – extensive records of sales patterns over a suitable period of time, providing enough information from which to identify trends and draw solid conclusions.

That is why, although the product life cycle concept has been around for a while now, it has only relatively recently started to be used widely on the shop floor. That’s because manually gathering and analysing the volumes of data required to interpret the life cycles of a store full of goods is a gargantuan task, one which has only really become practical with the arrival of digital systems. That’s where EPOS comes in.

With the ability to log and track every sale, modern EPOS systems automatically create the kind of large-scale data sets which are perfect for gleaning accurate pictures of product life cycles. All you need then is a software tool capable of processing the raw data into meaningful intelligence – software such as EazyStock’s inventory optimisation platform, which uses product life cycle as one of its key analytical models for helping retailers to accurately forecast demand.

It’s just one more example of how far EPOS systems have evolved beyond being simple cash registers logging sales. For the modern retail business,