With the second swing of economic slowdown – retailers are the frontrunners for experiencing the recessionary effects. While many retailers were hit unguarded in 2008, retail leadership has seen similar waters not so long ago. Is there a way out? With very less capital available, how will retailers enhance their offerings and continue to grow in these times? Is is possible with the help of technology? These are the questiones we’re trying to answer with this Winning with Pre-Season Planning whitepaper.
Many organised retailers, more so in emerging economies, expand rapidly. In the process of expansion – as the supply chain grows, it becomes more complex. Retailers lose track of the most important piece – ‘Store Allocation’. The opportunities lost at each individual store of a retail chain aggregate, into huge losses at a chain level. Therefore, it becomes pivotal that the answer to retail supply chain issues lies in successfully meeting demand without erring into either over stocking or high stockout rate.
Matching supply with demand is a primary supply chain challenge for any retailers. While, excess suply leads to excssive markdowns or salvage, inadequate service levels dissatisfies customers. The retail industry demands accurate and efficient delivery of goods.
Technologically, store level allocation solutions tap into the demand indicators available at the point of sale and couple them with historical data to predict accurate store level allocations. Moderns solutions not only compute initial store leve allocation but also improve the accuracy of predictions with time through a built in machine learning error measurement and minimization mechanism through sensitivity analysis.
The planning process is conducted at various levels in the following dimensions:
- Product: item, style, sub-class, department, division, channel, company
- Location: store, district, region, division, chain, channel
- Time: week, month, quarter, season, year
At these intersections of these dimensions variables such as sales, inventory on hand, receipts, markdowns, gross margin, turn, etc. In this whitepaper we’d be using Sell-Thru, Gross Margin, Avg. Price and Buy Units as measures for season planning.
Most retailers take these high level plans down to lower levels of detail. Key item planning, store planning and the addition of unit planning for both inventory and demand is sometimes factored to support the buy(ordering) and allocation needs of a specific cathegory of products. And hence, in this attempt of how Merchandise Financial Planning could be used for a better pre-season planning substituting the use of in-season ‘Band-Aid’ solutions like Markdown Optimization is shown with this item example.
If you would like to learn about the different scenarios we worked out, download the whitepaper below.