This is the third in our series about the retail industry’s challenges and opportunities in relation to Supply Chain Integration. The first introduced you to the overall landscape of supply chain touchpoints and challenges of “doing it right.” The second focused on processes retailers undergo to bring “the right product(s)” to market.
In this blog we’ll survey processes which help you determine “the right quantity.”
Often, best-of-breed solutions addressing these processes are isolated information silos within the enterprise. With the advent of digital commerce, each of these processes has taken on real-time urgency because of the enterprise-wide need to know current inventory positions.
Let’s survey these twelve supply chain touchpoints to identify the opportunities and challenges of data integration.
The quantity of available inventory is among the most important and most dynamic measures for a 21st century retailer. Yet, if you are like most retailers, you have yet to make this measure reliably accurate. Worse, you are very likely to have multiple versions buried in the various siloed systems that we’ll now discuss. One of the biggest opportunities for integrated retailers is to provide a single trusted source for available inventory. With accurate availability, you sell more, fulfill more productively, and make better use of your supply chain resources. The way forward is a combination of data integration, technology, and internal processes. The data integration project scope must include any transactional system that manipulates on-hand inventory at the local, distribution center, and supplier levels. Many retailers are now using radio frequency tags at the item, carton, or container levels. The internal processes include a variety of compliance and physical inventory procedures.
Assortment Planning lies at the intersection of product and quantity touchpoints. When your merchants and planners decide the depth of an assortment, they are committing to inventory levels throughout the product selling cycle. When they select the breadth, they are deciding the product mix, or variety. In the days of brick-and-mortar, Assortment Plans were static and memorialized in a siloed system. Now in the age of digital commerce, they must be constantly updated to reflect local demand, competition, and local fulfillment. Local assortments must be rebalanced when they become too broad, too narrow, too deep, too shallow, broken, too heavy with high- or low-priced goods, or missing key items. This means that data integration strategies must transform the assortment plans into dynamically updated enterprise assets.
For decades, Computers have assisted space planners in laying out their physical stores. So many things must be considered: lighting, flow, security, stock rooms, fixtures, signage, and shelves. Suppliers frequently weigh in with their views on how to display their line. The output of each is the pictorial representation showing the local assortment’s variety, depth and the positioning of key items. Space planning software needs the seamless integration of extensive product information to truly optimize space: pricing, packaging, physical dimensions, sales velocity, status in the assortment, competitive positioning, etc. Also vital is the limitations and capacities of store fixtures. Now with the robust shopping information available, it would be advisable to dynamically integrate the space plans with what can be gleaned about local demand. Good space plans break quickly when local assortments become sparse, out of balance, too broad, or too narrow. Many chains now want to integrate space plans with local photographs to identify anomalies to trigger corrective action when space plans get out of synch with the in-store reality.
In a simpler retail world, suppliers shipped their retail orders for immediate distribution to their physical stores. It was rare to hold back a reserve at the distribution center. Now, for both retailers and their suppliers, supply chain applications are grappling with the thorny problem of how much merchandise to allocate to each channel. Wise retailers are holding back in order to be more responsive to consumer demand. Many strategies have emerged ranging from buy on-line pick up in store (BOPIS), pooled inventory, vendor fulfillment, 3rd party fulfillment, and distribution center hold back. We see evidence of powerful solutions entering the market that need abundant source data to do their work. Near real-time integration is essential to tap into these resources.
Receiving and Quality Control.
When merchandise arrives, two bad things can distort the quest for the right Quantity: quantity discrepancies and quality issues. The supplier may ship different quantities than were ordered. Second, there may be quality issues that dramatically alter the available quantity. Most retailers rely on an EDI-enabled receiving process that captures this data and integrates to the ERP. But EDI integration can be tricky. Faulty translation must be detected and resolved quickly to avoid disrupting the entire distribution process. And in this omni-channel world, receiving data may be often directed to several destinations. Quality issues, when detected early, can forestall countless downstream problems. One of the tests of a well-integrated retailer is to signal to multiple systems when defective merchandise must be removed from availability.
Across the retail spectrum, demand forecasting is becoming more critical in meeting the needs of today’s shopper. We see great activity here, but little strategic direction. Retailers and suppliers are frequently duplicating efforts and basing their forecasts on entirely different assumptions. We see retailers trying to base their forecasts mindlessly on prior years without regard to recent trends, lost sales, or channel conflict. We see redundant forecasting within a single organization, one based on top-down methodology, the other bottoms-up. However, retailers are tackling this, with or without their supply chain partners. The requirements are: tremendous computing resources, volumes of inventory and sales data, consumer trends, and, if available, information from external sources such as weather, social media, competition, etc. Data integration is at the heart of any successful effort.
Pack Size Optimization.
When wearing apparel and shoes are packed in size runs, the quantities packed for each size should conform to the local demand at the package’s destination. If you get this right, your distribution costs decrease because of the economies of scale when you ship packages instead of individual items. Suppliers and retailers often share this responsibility but often with imperfect data and outdated assumptions. And shipping in size packs, usually means ordering, receiving and warehousing in size packs. To do it well, you must track the fast-changing needs at the local level and remove the noise from on-line orders. Data integration is a must.
Apparel and shoe merchants face an enormous challenge in maintaining the right size quantities at each selling locations and channel. This is not only a challenge at the item store level, but across any number of merchandise segmentation schemes. To do this well, robust product information must be coupled with near real-time data regarding sales and returns, available inventory, and supply chain expectations. Often the demand forecast is involved. For retailers that ship in size packs, that too is a consideration. Even the most capable software tool is fundamentally useless without extensive data integration.
A great many retailers and suppliers use specialized software to optimally allocate merchandise across a range of selling destinations. This has always been a data integration challenge, but with unified commerce, allocation must now align to the digital supply chain. In the event of shortage, which channels get priority? How can you remove the false positives from on-line customer purchases such on line returns or in-store fulfillment of on-line orders? How much merchandise should be held back? All this requires a new look at the data integration requirements of allocation software.
Specialized solutions for basic stock replenishment have also played a key role for many retailers and their suppliers. Unified commerce compels you to rethink this capability in much the same way as we describe for Allocation. In digital commerce, replenishment calculations are derived from inventory availability, and not on hand.
If you are like many integrated retailers who are also wholesalers and manufacturers, your great advantage is in knowing in detail what, where, when, and how many. But with great supply chain integration, all retailers can access the systems of their most significant suppliers. The Purchase Order should really be a comprehensive window in this activity. With this level of integration, you as a retailer can define when in the production cycle important supplemental information should be provided to the supplier. For example, for an apparel order here are the possible points of intersection assuming the initial order is a commitment for a minimum of a fabric.
Here are five decision points where retailer and supplier can progressively engage, driven by tight data integration:
1. Selection of color range and quantity
2. Selection of styles to be cut from the fabric
3. Shipment dates
4. Selection of sizes
5. Store quantities by size and color.
We’ve now taken you through the twelve isolated processes that help retailers get the RIGHT QUANTITY to the right location. In our survey supply chain touchpoints in the digital world, we’ve now taken you through the RIGHT PRODUCT and QUANTITY. Next up is the RIGHT PLACE.