3 Ways you can optimize your assortment productivity
Merchandisers and planners have the difficult task of creating optimised assortments that meet the requirements of our modern retail environment. An optimised assortment seeks to trim-down the selection to the best-selling items, while also giving a deep enough selection to provide for the customer needs. This includes certain ‘unique items’ that customers expect to find in store – these might be the only reason they shop with you in the first place, so they will walk away if they aren’t on the shelf.
Consumer demands today change more rapidly than ever, there is an ever-growing number of SKUs, and a variety of sales channels that all have their own intricacies. All these combined make it incredibly hard to create assortments that are fully optimised for every possible sales-point. Increasingly complex supply chains have also contributed to this situation, as retailers have to juggle the costs of procurement with the demands for certain brands and products.
If just one of these factors ‘pulls the lever’, the retailer needs to reassess their total assortment to ensure it remains as profitable as possible – it is a problem of immense complexity.
To solve the problem of complexity, the solution needs to be simple in nature but fundamentally powerful. In this article we examine and evaluate 3 key areas where simple decision-making can have powerful impacts in creating an optimised assortments for online, in-store and multichannel retail. By taking bold and critical decisions on an operational, tactical and strategic level, you can achieve a more effective and profitable assortment in the long-term.
Finding the perfect mix for a productive assortment
Assortment planning essentially seeks to create an in-store solution to the ‘shopping needs’ of the customer when they come to buy. As there is a range of different customers with distinct needs, the total assortment has to be deep and broad enough to capture the demand of these shoppers. As a retailer you want to target those specific customers who are likely to spend the most during their visit to the store, app, or website.
An optimised assortment needs to reflect real consumer demands as closely as possible. This is best achieved when retailers adopt a customer-centric merchandising process. This gives retailers the maximum opportunities for growth, by perfectly meeting customer demands. When combined with customer insights, retailers can effectively guarantee the loyalty of customers, because they can ensure they always have what the customer wants when they come to buy. This is the incredible positive impact of having the right assortment, whether online or offline.
The main benefits of having an optimally productive assortment can be summarized as:
- Increased merchant and planner productivity
- Increased revenue due to improved assortment performance in width and depth
- Increased customer loyalty
- Satisfying consumer demand (happy customers)
- Increased profitability
- Increased operational efficiency
With all these benefits, it is clear that the value of assortment optimisation can be very great. In fact, it can increase ROI by several percentage points. The problem remains however: how to determine the optimal assortment, given the immense complexity of the market?
Addressing the sources of complexity
There are considerable benefits from having an optimised assortment. Retailers who succeed in this enjoy increased sales, a growing market share, and more loyal customers.
However, creating the right mix of products in the assortment (and the right assortment for each sales channel) is a difficult task. It is made more difficult by the growing complexity of managing the interactions between consumer demands, product availability, new innovations, operational costs, and shifting trends.
Leading causes of growing complexity in getting the right assortment mix
There is an ever-increasing number of SKUs, and each of these represents a ‘sales possibility’ of its own, plus an exponentially growing number of combinations with other SKUs that might be bought together. Each brand also seeks to create innovations and new products, thereby generating more SKUs to assess and rank.
Smaller brands may produce fewer SKUs, however there is a growing number of new, small brands. These present an immediate question for assortment planning: which of these should be stocked, and do they replace existing products?
Pressure on shelf-space
The overhead costs that retailers must meet are ultimately divided across the available shelf-space and the sales/revenue that this yields. For the customer, they want to be able to easily find the ‘one product’ they need, without getting tired of looking for it, so the total shelf space is ultimately limited. Each square centimetre has to ‘pull its weight’ by contributing to an optimised assortment that drives bigger, better sales.
Supply chain complexity
Complexity within the supply chain itself can influence which products end up on the shelves. This can happen due to restrictions in MOQs or replenishment frequencies, which either limit or set minimum levels of stock. As supply chains become more complex, there is typically an increase in lead-time, which also makes it more important to make the right decisions about assortment.
Customers expect the full range of shopping possibilities, and this means catering for all possible pathways that the customer might take. If they come into a store to pick up an online purchase, there is an opportunity to add value with an extra sale, for example. Online shoppers have different priorities too – they are looking to find the ideal combination of choice, price and convenience. Assortments for online shopping can therefore be much more diverse, but products still need to fit with what’s demanded and what can be realistically fulfilled.
3 steps to manage your assortment effectively
There are three levels at which straightforward decision-making can greatly reduce the complexity of the problem, and these have immediate impacts on assortment optimization.
Operational level decisions should be finely tuned to responding rapidly to present customer needs, and these should always seek to ensure that there is sufficient amount of the right stock at the right time.
Keeping a tight focus on just the daily retail activities, we can use real-time sales and consumer demand data to inform daily operational decisions about which items are needed on the shelf today, for any given retail location. On the shop floor it is immediately apparent when certain SKUs are selling fast – because they need frequent replenishment. Daily decisions can be made while accounting for stock margin for display and in-store buffer stock. Sales velocity information can then be fed by merchandisers, back up the chain to allocators who now have better insights about the wants and needs of the customers.
The tactical level decisions will approach the problem of assortment optimization using a multi-axis rationalization of stock performance. It sounds complex, but this boils down to answering the question of ‘how much and where’.
Tactical decisions, taken every 14 to 21 days, will be made based on characteristics like overall sales, profitability, cost effectiveness, and shelf-space. Stock managers will determine the relationships between stock and sales to assess the optimal allocation of SKUs for each retail location.
A key part of these tactical decisions is the delisting of underperforming SKUs and the substitution or addition of new ones, as well as understanding which items are sufficiently unique that they act as a lightning rod for the sales of more profitable SKUs. According to research from McKinsey, by addressing new or previously underrepresented consumer demands, retailers can experience revenue growth of 2-4%.
Decisions taken at the strategic level are taken with a bird’s-eye view of the enterprise as a whole. The primary strategy for both retailers and suppliers should be to get closer to the customer, thereby meeting their needs better and (hopefully) becoming their go-to for whenever they need the goods that you supply.
Although decisions at the Tactical and Operational level are frequently subservient to strategic priorities, it should be the other way around. Strategic decisions should be led by the data that is fed up the chain from operational and tactical insights – at least in part. Strategic decisions should be reviewed on a rolling basis every month, and again when the season in question is over. This can help inform better strategic decisions in the future.
When decisions about assortment are divided along these distinct areas of a retail enterprise it becomes much easier to gain clarity where it counts. Operational decisions need to consider the tactical or strategic objectives, and vice versa. Although each level has its own area of focus, these assortment decisions ultimately need to be integrated across the whole enterprise, with information flowing freely. This will ensure that the maximum throughput is achieved across the width of the enterprise.
After an implementation period of 4-6 weeks, there should be enough data for the retailer to evaluate the value of the assortment, and decisions can be taken that have immediate effects on profitability.
In order to give a meaningful relative value (or weight) to one SKU compared to another, a system is needed that can provide detailed analytics. When retailers apply these well to inform their assortment optimization there is a proven capability for them to increase margins by 4% or more.
The most powerful analytics are those based on the most granular data. Data points such as sales per week, sales per store or sales per basket can all provide retailers with a realistic determination of the contribution of each SKU to total revenue. Such granularity can reveal which purchases are linked together, including unique items that may be less profitable but are non-negotiable for the customer. This ensures that the evaluation of economic performance reflects real customer demands and behaviour. The value of granular insights is also apparent when it comes to potentially introducing new products. An advanced analytics-based assessment will help the retailer to form a realistic prediction about the impact of a new product, based on how it affects the customer experience.
Retailers who can use detailed analytics to better understand the customer are able to be more customer-centric, and therefore make decisions that bring real value to the entire enterprise.
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