5 Crucial Ways to Manage Seasonal Supply Chains with Analytics in Retail Organizations


Empty shelves or website stockouts will likely greet shoppers across the globe during the 2021 holiday season. It’s an apt supply chain storm of increased demand and severely constrained supply and labor. The pent-up market from the pandemic is leading to an increase in online and in-store orders. At the same time, Covid-19-related restrictions, combined with container shortages, labor and driver shortages, railroad bottlenecks, and port congestion have restricted supply like never before. Retailers’ inventories are 30-year low, and toy making companies are urging customers to shop months early for holiday takeaways. Shipping costs have enhanced by over 300 per cent compared to Jan 2020. Numerous ships are waiting to dock at Southern California ports. 73 container ships were anchored off California by the end of September, waiting for a berth. U.S. President Joe Biden announced on Oct. 9 that the L.A port will operate 24×7 to clear the backlog, however, even that’s not going to be partly enough as there is no end in sight for any of these issues.

  • More than 20% of supply chain managers plan to decrease the number of SKUs in their product portfolio, but they are not sure of the overall rationalization strategy.
  • More than 45% of supply chain executives want multi-source materials and expand their supplier base but lack an expansion plan.
  • More than 40% of supply chain executives aim to maintain a higher inventory level for critical SKUs and reduce stockout scenarios but have no visibility.

How can Retail firms deal with these unavoidable supply chain issues in the short term?

Interestingly, Retail organizations that turn to supply chain analytics will have a real benefit this season and exceeding. Now is the right time for organizations to bring in analytics and data science to address these problems, irrespective of their data journey in this moving landscape. In most cases, organizations have a better chance to succeed if they select the right partner to assist them with data science and analytics initiatives.

Here are five steps Retail companies can take in the immediate short term to deal with these ongoing challenges.

1. Simplify product portfolio

Retail organizations can decrease complexity within the supply chain by reducing product variations or discontinuing less profitable or high complexity SKUs. This involves three simple steps:

SKU classification: Classifying SKUs by stockout possibility score (SPS). SPS is evaluated at an SKU/store (or warehouse) level and depends on:

  • Whether the product is sourced locally or not
  • Predicting suppliers’ performance (based on past performance concerning demand)
  • Suppliers’ risk score (financial, operational, geopolitical, number of suppliers)
  • Present inventory levels compared to forecasted demand (days of supply)

SKU segmentation: Segmenting SKUs relies on profit Vs the stockout possibility scorecard. Evaluate the profit considering increased transportation and labor costs.

SKU rationalization: Desist SKUs in the high SPS and low-profit segments. Keep a watch on the SKUs with high yielding profits and high SPS scores, then take instant steps to decrease the SPS score of these SKUs.

2. Source raw material dynamically

Building a dynamic sourcing plan that optimizes orders over the network in every planning cycle after observing the supplier’s performance scorecard and demand signals. Rather than adjusting the number of shipments from every supplier, this configuration allows organizations to decrease costs and minimize the risk while providing timely shipping of orders.

3. Optimize pricing to shape demand

During supply disruption, channels can adjust pricing to curb demand while maintaining/gaining revenue. When there are supply constraints, a retail firm may use one or many to impact the market. In the case of long-term supply chain disruption, raising list costs is highly noted. With EDV pricing, you must consider channel coherency, price gaps compared to the critical competition, organizational role within the retailer price guidelines, category, and their impact on customer demand. Additionally, retailers should look for ways to shift customer demand from the most to the least impacted products within their category portfolio. The quickest action a retail firm can take for short-term challenges is to move their upcoming promotional plans to curb high volumes of demand. There’s a risk that households will switch their spending to top-notch brands; but, this risk is decreased during supply-chain issues since it is typically an industry-wide problem.

4. Adopt on-shelf availability and out-of-stock alerts

An automated alert system can pre-empt products that are out of stock based on actual inventory levels and expected sell-out trends in the upcoming days and weeks. Based on these alerts, organizations should increase POs well in advance, replenishing stock before inventory runs out. ML can raise alerts for misplaced, damaged, and phantom inventory within stores and include a mechanism to directly alert the store task force.

5. Build an intelligent allocation strategy

Finally, savvy companies should distribute inventory in distribution centers and fulfillment centers based on trends, which can be gauged through a precise and accurate demand-sensing exercise done at the SKU level. Allocating higher inventory in the hot spots or high-demand clusters and maintaining healthy stock levels elsewhere.

Accelerator-based ML solutions can assist retail organizations take these steps and more, money, energy, and saving time. ML algorithms working together with employees can assist organizations across the world navigate ongoing supply chain issues while delighting their consumers, treating their employees well, and delivering on their promises.

Final Thoughts

The pandemic has forced retail executives to mount urgent efforts to adapt their supply chains, whether by revising their purchase orders and merchandising plans or by reallocating all kinds of resources — working capital, inventory, employees, transport capacity — to where they are needed most. Therefore, effective, data-driven supply chain planning is more crucial than ever in the age of expanding seasonal supply chains and networks. Presently, companies have an opportunity to use this challenging time to explore where investments are needed, evolve the supply chain analytics function, and reposition the companies to better support business growth once economies rebound.

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