Chapter 10

Inventory management

1. Building the perfect assortment

Inventory management gives a retailer the ability to offer its customers a vast array of items without having to store everything in its own warehouse. And this is true for a pure ecommerce retailer, as well as those within an omni-channel strategy.

Often, the majority of items in an online assortment are being ordered from a supplier once an order has been placed by a customer; that means that the constraints that apply to traditional inventory management are removed. This enables a retailer to offer an extensive range and a high volume of products on its website. Although the decision of what to stock still has to be made.

In the world of ecommerce, things can happen and change at the drop of a hat and it is imperative that quick decisions are made. As a result, retailers need to monitor their stock continuously to ensure it does not become outdated. The answer to how to identify a few thousand products from the millions of options, not only once but also constantly, boils down to a fact- and cost-based model.

Retailers need to consider the cost of holding items that are in stock in their warehouse, the obsolescence-risk and capital for each of them. Purchasing larger batches means less time spent per product in all phases of the ordering process, and retailers can take advantage of freight-free limits and cheaper means of transportation. In contrast, ordering only against customer orders means the cost of warehousing moves towards zero, but ordering costs increase significantly when a retailer sources in small batches that are needed urgently.

The advice is to compare both models and proceed with the cheaper one. This is because it makes sense to stock cheaper items that sell reasonably well and keep the expensive goods that, perhaps, do not sell so well at the supplier’s warehouse.

It sounds easy, but it is collecting and retaining cost data and then running an efficient process that become the hard part.

When we talk about cost data, the aim should always be how to maintain continuous improvement. Focusing on a subset of products would be a good starting point; perhaps the most challenging or those that are integral to the bottom line. It is actually not that hard to design such an approach into a well thought out and automated system. The results can be seen relatively fast to improve the decision-making process.

2. Capitalising on data within the supply chain

Because so much data can be captured automatically online, retailers need to work out how they can best leverage the data within their supply chain planning and analytics to improve both inventory management and demand forecasting.

Unlike when customers visit a store, where it is near on impossible for a retailer to track where a customer goes and what items they look at, online makes it easier to monitor and record the customer journey. Product views, for example, are an important data source for a supply chain manager as they can be used within the supply chain planning and analytics tool.

Bringing viewing rates and click data into your supply chain can help identify those items that need to always be in stock. By reviewing such data, delivery times can be reduced, customer experience improved and savings made by the retailer.

Pricing plays an important role in any retailer’s business. The online environment not only makes it easy for customers to see a competitor’s price for the same item, but retailers too, who can take advantage by reflecting a competitor’s price within their own planning system.

Analysing sales volumes against retail pricing enables retailers to understand in detail the price elasticity of different products, which makes for more precise pricing decisions and improved demand forecasting.

It can be, however, difficult to tie forecasting directly to price changes because there are a variety of factors that influence sales. An example could be not enough data on a single product or the times between sales increases being too short to be useful. Results that are achieved semi-automatically through exception-based workflows are typically best as they highlight big price changes.

3. Forecasting sales with or without returns?

Product returns are a big consideration to every retailer with an online operation, and return rates rise significantly when customers are not able to see, touch or try products. Furthermore, when customers are unable to return the item back to store and have to mail them, the cost of returns becomes relatively higher.

Monitoring returns data as well as sales data undoubtedly helps to identify problematic brands, categories or items.

A question that is asked often is whether forecasting should be based on sales, including returns. We advise forecasting them separately, rather than trying to forecast sales including returns. With sales forecasts, the aim is to maximise availability – a retailer needs to know what will be shipped and, most importantly, when, irrespective of whether it will be returned or not. Forecasting returns separately also provides a clear overview of the associated costs and requirements, for example, logistics capacity, which therefore aids both the operational and financial planning.

In order to take returns forecasting to the next level, retailers can calculate it in two ways: first, as a separate independent time series, and then as a percentage of sales – tracking the differences between the two provides an early indication of whether the rate of returns is rising too much. If the independent forecast clearly starts to surpass the percentage-driven forecast, it means the trend is pointing to the wrong way. Action should therefore be taken. A budget for returns can also be used as an alert threshold and can help make decisions about what levels of returns are acceptable within the retailer’s overall financial and business plans.

If a retailer wants to really take advantage of the return forecast, it could be used to test different what-if scenarios. For instance: ‘So, if I have an increasing rate of sales of X and an increasing rate of Y of returns, what would that mean in terms of DC operations in total, end-of-season stock, markdown-costs or total margin?’ – having a system that manages all this information, and keeps it available, enables operations to be managed more efficiently and helps support strategic decisions affecting the retail offering and returns policy.

4. Avoiding a stock imbalance between online and stores

Many will recall that it was only 10 years ago that senior retail executives were still looking at the world of ecommerce and saying, in a few words: ‘It’s not for us.’ Oh, how the world has definitely changed since! With the rise of ecommerce, many traditional retailers have established an online presence to complement core business operations.

The whole ecommerce concept is still relatively new, and volumes often are quite small, but can grow at pace. The supply chain strategies in response can vary somewhat. Retailers can, however, optimise inventory levels whilst maximising sales across all channels.

A number of companies have decided to operate separate warehouses for online and for stores. Often, this is due to physical constraints: such as the DC currently responsible for delivering to stores cannot hold more stock, or the picking process (single items for online and cases for stores) differs too much. When this occurs, it is relatively straightforward simply to calculate forecasts separately for both warehouses and replenish them separately. This is, of course, far from ideal from a stock-holding perspective. As a retailer has to buffer against uncertainty in both warehouses, they are likely to end up having notably higher stock in the business than they would with a single-stock-pool scenario. Plus, there is still a risk – particularly if their forecasting process is not precise enough – that one channel sells better than predicted and the other not so well, with the result that the retailer creates a stock imbalance: no stock for online and too much for its stores, or the reverse. This may lead to lost sales, mark-downs or costly shipments between warehouses.

5. Planning delivery methods more accurately

Quite often, when discussing ecommerce, the view is somewhat simplified by the assumption that the online world is synonymous with home delivery. These days, though, we know that simply is not the case. The more options a retailer offers to its customers, the more complex the supply chain becomes, and that complexity understandably has implications when planning.

From delivery to the door, picking up items from a store, a special collection point or even sometimes the warehouse – the delivery options for customers have increased. Thankfully, in most cases, a business’s basic operations are unaffected by the choice of delivery method. A retailer sells items on its website and then delivers them to the customer from its warehouse with only the delivery address being different.

When it comes to the model of click & collect from store, adding collection information to each store’s sales figures supports the supply chain, as it provides a better idea of the stores that are proving to be the most popular collection points for customers. Moreover, such data can be linked to assortment management. If a product is ordered regularly for collection from a particular store, then it could be added automatically to the store’s range, saving on future delivery costs and protecting margins.

However, a slightly different approach to click & collect is needed in the e-grocery sector, because goods typically are picked from the store rather than from a warehouse. In such a model, a retailer would need to operate in a different way; combining click & collect orders with the store forecast as well as integrating the order and inventory management process to include online sales so as to ensure there is enough stock instore.

For a retailer to have a clear view of the value of the different delivery options to the business, it is beneficial to use the relevant data in its supply chain system to analyse and report on which delivery method is being used more and when. A business might, in some cases, take a step further and forecast different methods separately. This would make it possible to plan delivery operations more accurately and enables them to spot patterns and changes in the market faster.