This article, by our own Linda Whitaker, was published in RIS News»
As retailers seek out new business tactics to lure back the customers they lost during the recession, they will find that one of the most profitable strategies is creating a customer-centric supply chain.
However, one reality retailers must face is that the recession has created a new consumer paradigm. According to a new report by PricewaterhouseCoopers and Retail Forward, entitled “The New Consumer Behavior Paradigm: Permanent or Fleeting,” customers will not bounce back to their old shopping habits, as “seventy-two percent of all shoppers recently indicated that their shopping behavior has changed significantly or somewhat as a result of the economic environment”. The report suggests that shoppers will be more deliberate and purposeful in their spending, giving way to a more practical consumerism. However, it also predicts that these shopper behaviors may change as the recession eases.
Since we know no one can foretell the future to know exactly how and when behaviors will change, our take on this study is that consumer behaviors have changed and will continue to change, and that retailers need to actively seek new ways to engage them (especially the younger generations), and be ready to continually adjust their product mix accordingly.
With this new paradigm in mind, retailers must take a step back from their businesses to understand how to engage today’s new consumer.
Some questions that retailers should ask themselves:
What are your customers looking for when they walk into the store? Why are they buying that item? Does their buying strategy map to the one you have for the product? What are they not buying? How much are they buying? How often are they buying? Are they buying it at the same store?
To fulfill changing customer demand in your supply chain, you have to start at the store, and it comes down to the two basics: breadth and depth.
What and Where:
There are the tried and true ideas behind why customers select a certain product (the customer product strategy) when supporting customer demand: Price, impulse buys, destination items, etc. But customers today have a huge wealth of information at hand when deciding what to buy, and therefore they can include many new inputs (as well as the tried and true). These customer demand choices indicate their product preferences, and will be inputs into the customer buying strategy, and hence need to be included in your product strategy.
Preferential signals (Inputs to the customer strategy): Price, convenience, fashion-forward, technological, locally made, organic/sustainable, ethical, necessity, value, quality, size, color, style, brand, culture.
Ideally, you have a host of customer data that lets you not only map customers to purchases, but also link the changing customer buying strategy with your product strategy, and this may be different by location. If you do not have customer transaction and purchase information, you can use product/store level demand as a proxy, perhaps supported with market data. It will be important in this changing environment that these product/location strategies are continually monitored and updated.
Once you can assign the product strategy at a location level, you can tackle the breadth issue, i.e. the assortment. Most retailers cannot operationally manage unique store level assortments, and need to assign clusters that are often constrained. Care, supported by process, timely information, and optimal systems are needed to manage the conflicts between desired ranges, and operational constraints: space, fixtures, and assortment planning groups.
How Much and When:
When you assign a strategy to a product/location to drive assortment decisions, this same strategy should be used to drive depth. For example, a key destination item may need a very high service level so that your customer will not be disappointed.
In order to best meet these strategies and keep inventory performance high, the time phased aspects of the local customer demand need to be taken into account:
Circumstantial signals: The time of day or week activity occurs, holidays, local events and promotions, sports schedules, weather, seasonality and regional demand.
Putting it all Together
Retailers need to have the ability to assess and continually change with the patterns at each store based on the local signals and behaviors of their customers. In order to increase margin, achieve proper stock levels and align assortments with customer demand, top down simplifications in the inventory planning process must be removed.
Stores that can quickly process customer behavior and turn it into inventory execution will have an immense advantage in today’s marketplace. This means creating a dynamic inventory plan that is highly reactive to local demand fluctuations, allowing the retailer to be flexible and respond to how their customers are behaving now. This enables the customer to have product available when and where they want it, in the right size, the right color, and the right style at every store and in every channel.
Linda Whitaker, Chief Scientist, Quantum Retail, is one of the leading practitioners of retail science in the country. She provides the research, innovation and advanced science for Quantum Retail’s solutions. Prior to co-founding Quantum Retail, Linda spent the past 17 years developing optimization and scientific solutions for complex retail problems in replenishment, logistics, pricing, promotion and consumer behavior at Retek Inc. and HNC.
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Location clusters. We all know them and some love them. They have their place, especially in larger retail organizations. It’s important to think about why they exist before determining when and how to utilize them.
There are a variety of demand signals that need to be monitored on a local level, these signals include: the time of day activity occurs, local events, sports schedules, weather, seasonality, social trends and local buying habits. To add to this already complex problem, this must be done at a SKU/store level, in real-time to optimize profit from perishables. Grocers are one of the only retailers who have a legitimate need to plan inventory by the hour in order to avoid situations of ‘scarcity and abundance’.
Because the majority of non-perishables are shelf stable with long code dates, the time-phased element to the demand, delivery, and sale is related to carrying cost, customer service levels and the cost of money invested. The majority of allocation/distribution projects tend to focus on determining how much inventory to push to a given store. Theoretically these items can remain in the store until someone buys them or until they are marked down as part of a clearance initiative.
Grocers and food retailers now need a new approach to forecasting, SKU rationalization, assortment planning and order planning. Retailers who can meet the specific needs of their customers at a local level will become much more successful.
To place inventory in the most efficient and profitable way, merchants can define product objectives, like minimum credible display and service levels, which should be used to decide each inventory placement decision. This enables retailers to make sure every product is in their assortment for a reason.
The days of paper coupons may be even shorter than we thought if supermarket chain A&P’s mobile phone text-coupon program is any indication of a new trend to save shoppers money.
The term localization is arguably the hottest word in retail merchandising today. Getting the products to the store that the local market wants, in the right quantity, in the right color, in the right size and priced to sell it at the highest possible margin is the Holy Grail of any retailer merchandiser. Adding constraints such as price elasticity, markdowns, supply chain, knowledgeable customers is one thing but when a merchant is constrained by her own internal systems; that’s another problem entirely.
1. Optimizing inventory:
Retailers today have much better visibility into what is happening at the store level, however much of this data never gets turned into actionable knowledge. Retailers need to start tapping into the hidden value that is locked in the massive amounts of data that retailers have stored from decade’s worth of history. The most common remark made by tier one retailers is along the lines of, “Our company has spent millions of dollars and years gathering and storing data, but what we lack is the ability to gain any real value or competitive advantage from our efforts.”
During the late 70’s retailers began storing massive amounts of data. They used tapes, punch cards, reel-to-reel devices and eventually disk arrays to capture all aspects of their business. By the early to mid 80’s consulting firms began to promise large returns from conducting “data analysis” initiatives. These events did provide some return and provided some logical analysis of the history contained within the stored data.
There are additional short-comings to analyzing and optimizing the data. To start, neither analysis nor optimization was designed to force a retailer to take action. Both data management processes are delivered as a set of “best case” scenarios that require additional manual effort before any value is realized.
