Even in today’s technology savvy world the challenge of ensuring a product is in-stock for consumers to consider for purchase remains one of the retailers and their trading partners’ biggest challenge.
Depending on how easy consumer demand is to predict for a product category (some are more predictable than others), we have seen retailers and their vendors with missed sales opportunities of up to 40%.
In addition to the missed sales opportunities damaging both the retailers and their vendor’s sales and margin, the out of stock product also leads to creating a level of dissatisfaction with the consumer. If items are unavailable often enough it may actually lead to a consumer deciding to switch their retailer of preference. The vendor is also impacted by their products not being in stock. Depending on the strength of their brands, the consumer may choose to switch products (as opposed to retailer switch) when their product is unavailable, and if satisfied with the alternative, it may lead to the consumer brand switching permanently.
So in this world of electronic order processing using a store sales and inventory data to manage store inventory and forecast future demand, why is it that so many retailers and their suppliers are still challenged with out-of-stocks?
1. Data Daily – Many inventory management solutions use weekly sales and inventory snapshots to create the model stock (ideal inventory level for a SKU at store level based on estimate future demand). The use of weekly data to determine the inventory requirements for a SKU at store level is flawed for many reasons.
- a) The most complex and accurate forecasting solutions in the world still struggle to provide accurate consumer demand at the most atomic level (SKU/store). The beauty of refreshing sales and inventory data on a daily basis is that the model stock for the store/SKU can be updated daily thereby providing a more accurate snapshot of any daily inventory requirements.
- b) It doesn’t allow for a business to run a replenishment order more than once a week.
- c) It doesn’t allow for an inventory management system to review important SKUs (typically new product lines or promotional campaign items) on a daily basis using the most recent daily sales and inventory levels at store.
- d) Running analysis on ISP on a weekly basis provides false information to management on the true inventory position. The weekly analysis of ISP does not take into account the daily fluctuations of ISP.
2. Rigid ERP Systems – Although there are many benefits of running an enterprise and rigid ERP solution, managing inventory across diverse product categories with differing life cycles and decay curves is not one of them. ERP solutions typically are designed to manage inventory for product categories that are easy to predict. When faced with product categories with short life cycles or seasonal activities, they typically are ineffective.
3. Time-poor buying and planning teams – today’s modern retailer runs a very lean buying team. The buyers and planners have responsibility of sales and gp, trading terms, marketing funds, promotional management, range management and overall inventory levels. When challenged with an ineffective ERP and/or legacy system they will attempt to managing inventory using a spreadsheet solution. A time poor buying and planning team will manage the high velocity SKUs and campaign SKUs without having the time to manage other SKUs. The outcome being out of stocks for second tier SKUs that, when consolidated, equate to a significant missed sales opportunity.
4. Unsatisfactory Fulfilment rates – the best consumer demand solutions cannot account for vendors having inadequate demand planning solutions. There are many distributors and/or manufacturers today who have underperforming demand planning solutions that contribute to fulfilment rates as low as 50%. These unsatisfactory fulfilment rates are typically the result of poor data and/or science being employed to create demand plans.
The V Net service model creates an inventory management process that solves all the current “out-of-stock” challenges faced by retailers and their trading partners.
1. Daily Data – Our consumer demand forecasts utilise daily data ensuring the most up to date “model stock” information (at store/SKU level) when running replenishment order processes.
2. Customised Algorithms – Unlike “one size fits all” ERP solutions, the V Inventory module creates consumer demand forecasts utilising algorithms that are fit for purpose. The consumer demand curves created by the V Inventory module suits the nuances of the respective product category.
3. V Net Inventory Specialists – Our team leverage the “science” within the V Inventory module and create a process that ensures both the retailer and vendor receive new line and promotional campaign allocations, along with replenishment orders in a timely manner, eliminating the risk of out of stocks due to time poor executives focusing on other priorities.
4. Fulfilment Rates – The V CPFR module ensures that a vendors demand planning process including a consumer demand forecast by SKU that is built from atomic level (store / SKU). The CPFR forecast process links the weekly demand forecast to the actual replenishment orders created by V Inventory on a weekly basis. The outcome being 95+ fulfilment rates.
By solving the challenges mentioned above V Net deliver an in stock position of 98%, thereby maximizing the sales opportunity for both retailer and their trading partners.