Critical Steps to Forecasting Replenishment for Demand Planning

Forecasting replenishment correctly and following standardized inventory replenishment processes continues to deliver significant returns to retailers, wholesalers, and manufacturers. For the retailer/ wholesaler/ manufacturer ready to move away from legacy technologies, there are huge opportunities that cost 50-90% less than legacy systems. A forecast accuracy in the 90% range we know delivers a significant shareholder value increase of 15% or more.

Several documented events support these claims (click a link): a retailer achieved a 25% inventory reduction and a 3% same store sales increase in 90 days, the sales and inventory trend continued going forward (press release), Dr. Mentzer’s 3 page story concerning a collection of businesses that delivered an average 15% shareholder value increase via forecast accuracy improvements which directly impacted forecasting replenishment, and The Home Depot Chairman and CEO, Frank Blake, specifically stated in the 2011Q4 earnings briefing that supply chain investments continued to provide significant benefits including increased turns and same store sales.

Our supply chain investments continued to deliver benefits for the business, improving our in-stock rate and asset efficiency as we again improved inventory turns this year. As of the end of 2011, we handled approximately 70% of our cost of goods sold through central distribution in
the US. This compares to approximately 25% four years ago.

Key data Sources for Forecasting Replenishment

Forecasting replenishment requires performance indicators for reorder point, order up to amount, forecast accuracy, service level attained and automated/ configurable alerts and exception management to deliver significant returns for businesses. Data points needed for forecasting replenishment include: demand forecast, demand forecast error, Service level goal, lead time, optimized supplier order cycle (days between reorders), product order cycle, and supplier minimum pick quantity. To learn more about the forecasting replenishment performance indicators and data sources, including how they work together, visit this link: inventory replenishment

Key data Sources for Inventory Replenishment Processes

Some data sources needed for the inventory replenishment process but are not part of forecasting replenishment include: company rounding rules, supplier min to ship size, and shelf life. Each of these data points and some additional data points like inventory carrying cost should be used for inventory optimization. The inventory optimization software should deliver the optimized supplier order cycle which is the key contributor to days of shelf stock maintained, a key factor for accurate demand plans and purchase projections. To learn more about order cycle optimization via inventory optimization processes, visit this link: inventory optimization

Forecasting Replenishment and Demand Planning the Budget

Some people argue that building the demand plan and budget should happen before forecasting replenishment; perhaps this is old school methodology. We believe the budget is part of demand planning that should follow AFTER an initial Forecasting Replenishment process for your business. A root issue with many demand planning processes today is the acceptance of inaccurate forecasts. A study of planners revealed that 90% change the number their forecast system delivers. Additional research shows that most forecasting systems have a base technology that is old and dated, contributing to the inaccuracy. Worse, some companies use products like Excel for demand forecasting and aggregation. Since many people believe poor forecasting is inevitable and human intervention is the solution, it makes sense to build a plan and then run forecasting. Think about CPFR (collaborative planning, forecasting and replenishment) – note how planning is before forecasting.

The results of plan first and then forecast can be seen in the inventory replenishment process we have seen at numerous companies.

Buy for the non-replenishment plan first to account for promotions, ads, and events.
Use the balance of the plan money for replenishment.
If sales do not meet plan then cut receipts – often replenishment is the first cut.

The double impact of this decision is lost sales for non-replenished and then lost sales for replenished. Having worked in retail/ wholesale for more than 15 years, I can say with certainty that this is a very common set of events. Today, many businesses fail to realize the double loss they create.

Build Demand Planning with Replenishment Forecasting Projections

Assuming a your business has accurate demand forecasting (contact us for a free consult), then forecasting replenishment should be step 1. Demand Planning for the changes in the business like new product, replacement products, promotions and events would be step 2. Finally, forecasting replenishment again where promotions and events are planned in step 2 to complete the circle.

Replenishment Forecasting 1st then build Demand Plans

Demand Forecast each product/ location (include future events and promotions)
Calculate inventory optimization to determine average on hand inventory
Project sales, inventory level, open purchase order, and new purchase orders.
Use data to build demand plans
Where ‘new’ promotions and events are added- recalculate steps 1-3

Confidence in the demand forecasting accuracy when forecasting replenishment and even non replenishment products would encourage the ideas presented today. With an 85 or 90% forecast accuracy, your business processes would embrace the idea of forecasting replenishment first and use the forecasting projections as the starting point for the demand planning. Most Demand Planning tools and software today focus on the planning and not demand forecasting accuracy. The good news is that companies can buy software today that does take advantage of hardware and software improvements to deliver solid, dependable, and accurate Demand Forecasting. These new Demand Forecasting software solutions are making it much easier for accurately forecasting replenishment and non- replenishment products in your business. You can run forecasting projections to use in your Demand Planning and ‘Tighten the Links in Your Chain™.’

Are your ready to ‘Tighten the Links in Your Supply Chain?™’

We are here and ready to help. Contact us for a free consultation about your forecast accuracy and inventory management opportunities. You can also request a demo and see how things can really start to improve in your business in 90 days.

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Stuart D

Stuart Dunkin is a strategic visionary who leads by calling on his broad range of experience as a former retail executive as well as a consultant for top retailers and for the E3/JDA software company. He founded Data Profits to solve a real-world problem plaguing retailers today – the disjointed relationship between supply chain data, people and business goals. He has experienced first-hand the challenges and frustrations that occur when decisions are made based on wrong data, which often leads to the wrong actions being taken with crippling results like overstock, out-of-stock, and increased working capital.
Stuart graduated from Auburn University, with bachelor of science in business administration.