Unleash marketing and merchandising creativity with decision process automation

Automating processes like markdowns drives bottom-line results and allows more time to tailor the shopping experience.

“Know the customer.” It’s a retailing mantra that’s been repeated ad nauseam since the dawn of the 21st century. Nonetheless, today’s successful retailers are only now replacing the product focus that dominated the 20th century with a deep understanding of the consumer that is constantly updated and refined. How are these retailers getting there? They start by evaluating detailed consumer data from multiple sources to understand who the best customers are, combined with what and how they like to buy. Unfortunately, just “knowing the customer” isn’t enough in today’s rapidly changing retail world. 
 
Retailers need to anticipate and shape future demand to come as close as possible to satisfying each customer’s unique needs. Achieving this at a detailed level requires automated processes enabled by scalable solutions with the latest in predictive analytics and optimization capabilities. The ultimate goal is more than having the right product in stock at the right price; it’s about tailoring the entire shopping experience to create an emotional bond with the customer. In effect, this means turning today’s multichannel retail enterprise – in a consumer’s eyes – from “the store” to “my store.”

The first priority is for each retailer to understand the customer segments that really matter and what is needed to provide a tailored shopping experience. Here are four steps that are critical to this process:

• Understand which customer segments matter through the use of intelligent clustering solutions. Northern Tool learned that some valuable customers weren’t receiving their catalogs and rectified the problem.
• Conduct deeper analysis of market baskets, shopping patterns and lifecycle purchase histories. In Europe, Office Depot has a detailed understanding of its customers.
• Select merchandise that best matches the desires of customers based on which stores they shop at. See how the sporting goods and clothing retailer Sport Chalet does that.  
• Use detailed planning and forecasting to help anticipate demand across all stores and channels for each item sold. Take a look at how AutoZone knows store by store which products sell.

With this information, retailers know whom to target and how to fulfill demand. The bigger question is how to execute this in a timely, cost-efficient manner. Can you personalize customer communications, merchandise each store with the right assortment displayed via the most effective layout and optimize pricing in each individual store without hiring an army of analysts? With decision process automation (DPA), the answer is yes.

DPA solutions are not the typical ad hoc tools used by a few specialists to execute one-time analyses – because no team of specialists could manually conduct analyses in a timely fashion at the level of detail needed. These business applications automatically execute and apply analytics to business processes. This automation is the key to enabling the delivery of just the right offer to each consumer, deployment of exactly the right assortment to each store and optimization of each price for millions of stock keeping units (SKUs) on a regular basis. 

DPA integrates analytics and optimization routines into process workflows to increase decision-making capabilities, but it is not just about the analytics. The analytics are the critical enabler and the “brains” behind the automated decisions, but they must be complemented by a highly configurable workflow that allows users to quickly evaluate exceptions and execute the remaining manual process activities.

The decision process automation spectrum runs from automated analytical support to solutions that fully automate business processes. Further along the automation spectrum, some functions can be more fully automated, limiting human involvement to exceptions. These include revenue optimization, direct marketing campaigns and automated replenishment.

DPA allows the retailer to embrace a consumer-centric approach across all marketing and merchandising activities. For instance, retailers can move away from exclusive use of mass media broadcasting focused on telling consumers what they should buy by shifting the marketing mix toward direct media that support the formation of the desired emotional bond. Meanwhile, merchandisers can stop thinking in terms of what product “we should sell” and instead come closer to satisfying each consumer’s unique demand.

Revolutionizing customer interaction with DPA
In the bygone days of the mass market, retailers could successfully market their products with a single set of messages broadcast over the mass media. Although broadcast media can still play an important role in the overall marketing mix to help generate awareness, that must be complemented by more direct interactive campaigns to form the connection needed to turn consumers into loyal customers of “my store.” This starts with direct marketing campaigns that are tailored to each consumer’s profile and projected future shopping patterns. Historically, direct marketing meant sending the same offer to all customers, with rudimentary analyses focused on weeding unresponsive consumers from the mailing list. Today’s marketing world requires decision process automation using sophisticated marketing automation and campaign optimization solutions that tailor the offers, information, campaign timing, frequency and delivery vehicles. In this way, all profitable customers can have the right level of interaction that meets their needs and maximizes retailer profitability. Most importantly, because the retailer personalizes and tailors the messaging to customer needs, the direct marketing activities can contribute significantly to a retailer’s ability to establish the desired emotional bond.

Outbound direct marketing activities are just the start of the 21st-century customer relationship process. The latest marketing automation solutions enable real-time interaction with consumers, whether through the Internet, in-store kiosks or the latest handheld devices. This revolution blends these multiple channels to provide integrated cross-channel shopping experiences where customers have pervasive visibility of the latest offers and products combined with choice and control over how they interact with the retailer. Automating inbound marketing activities provides customers with a truly customized experience. It is “my store,” not “the store.”

Merchandising to consumer demand
To fulfill the “my store” promise, the in-store and online shopping experience must meet the expectations created by marketing. The most important ingredients are the components of the merchandise mix, such as assortment, inventory, price, promotion and space planning. Of course, in-store service and décor are important, but multiple research studies indicate that customers need to easily find the items they want at a reasonable price on each shopping visit. A retailer will not remain “my store” for long if a shopper never finds what he or she is looking for.

A retailer must brew this customized mix for thousands of stores, tens of thousands of SKUs and millions of stocking locations. Because the level of detail required is so massive, manual processes cannot achieve this. But DPA can.

The level of DPA applied will depend on the merchandise characteristics. Most products fall into two primary groups:

• Basics/fast-moving consumer goods (FMCG): These are long lifecycle products such as office supplies, batteries, canned groceries or health and beauty aids with highly predictable sales patterns and responsive supply sources.
• Highly variable goods: These are short lifecycle products such as fashion apparel, seasonal and promoted items that require more sophistication to accurately predict sales. They are often long lead-time items imported from overseas.

For the basics/FMCG goods, retailers tend toward more use of full automation, as defined in the DPA spectrum. The process revolves around ongoing category management processes that tie all activities to goals that are set on the basis of market trends and financial objectives. In the basics/FMCG merchandising life cycle, the process starts with detailed category reviews followed by the assortment planning that leverages intelligent clustering (based on data mining) to identify material store clusters that warrant unique assortments. Through this process, the same insight used to segment customers and drive marketing activities is applied to product decisions. 

For each store cluster, an integrated assortment and space planning solution is used to optimize store layouts, determine the optimal assortment for the available space and then deliver store-specific planograms that illustrate exactly how the product should be displayed. Goods at each store are automatically priced – and re-priced – based on the latest consumer demand, inventory and optimized promotional plans. A fully automated replenishment system handles ordering, for both stores and central distribution centers. Replenishment is typically complemented by a sophisticated inventory optimization solution to determine the DC and store service levels needed to maximize productivity while allowing retailers to have just the right amount of stock on hand.

For highly variable products such as fashion apparel, the application of DPA tends toward the automated analytical support side of the spectrum. During the preseason planning process, retailers execute sophisticated forecasting, data mining and optimization routines to seed plans and optimize assortments. Once the applications are properly configured, these analyses are generated automatically and provided to planners via a solution workflow that is tailored to the planning process. Although the main focus here is on the automated analytical support portion of the DPA spectrum, the trend is toward increased automation. For example, the latest assortment planning solutions now offer sophisticated “recommended plan” functionality that automatically seeds the assortment plan with a recommended category product range for each store cluster. Extensive exception alerting further drives planning process accuracy and efficiency.

Once in season, when sales history for even the fastest fashion items is available, higher levels of DPA are becoming the standard. Promotion optimization enables the automated merchandising of media vehicles with products and offers that will best achieve traffic, revenue and profit objectives. With allocation and replenishment optimization solutions, each store gets the right number of units. Fully automated revenue optimization solutions trigger the selection of profit-maximizing clearance prices at the store SKU level.

Beyond SKUs and planograms: Taking DPA to the next level
The consumer relationship and merchandising examples are just two areas where leading retailers are moving toward DPA. Today’s advanced solutions extend DPA to other processes that reach into the store and across the supply chain. For example, advanced forecasting improves automated labor scheduling. Automated planning processes can improve communication with vendors. One vertically integrated retailer uses DPA to signal changes to its factories. This breadth warrants a cross-functional approach, making the CIO’s role ever more strategic. As one of the most senior executives with a true cross-functional perspective, effective CIOs play a critical role as a corporate change agent, encouraging the adoption of DPA across the enterprise.

The potential benefits are game-changing with hundreds of millions of dollars in gross margin improvements. The rest of this publication goes deeper into analytically enabled decision process automation from the perspectives of different key executives and includes numerous case studies that illustrate how retailers are delighting customers and delivering significant shareholder value with DPA.