As a consultant, I get asked this question a variety of times. Why should we improve forecast accuracy? What is it worth to us? What is the business case to spending money to improve the process and implement some expensive demand planning software?

There is value in this for sure – the evidence comes from the fact that year-after-year companies continue to hire more demand planners and invest millions of dollars in putting together processes and software packages. Now to dissect this, let us look at the Service-Cost Balance model that we preach in our workshops.

Improving the demand forecast directly gets to two things that are important to companies:

1. Increasing the top-line – Improve customer fulfillment and delivery and increase the level of Sales. Nothing works like reputation or service performance. People flock to your company products and services if they are satisfied with what you offer. The converse will be painful – bad news spread like wild fire.

2. Improve the bottom-line through process efficiency – Optimize inventories by trimming the level of inventories, cutting obsolescence and producing just enough to meet your demand.

3. Eliminate process costs – Expediting, over-time that may otherwise be required to fulfill volatile and unpredicted customer demand.

Now if we want to quantify the benefits from forecast accuracy, it is difficult to quantify the first item. What is our lost sales? What is the effect of one point reduction in fill rates? Did it cause lost sales? Did we lose a customer?

It is a little easier to look at the savings in inventory through improvements in forecast accuracy.

At any time, your inventory level is comprised of Safety Stock to meet demand and supply uncertainties and the inventory needed

**But your average inventory = Safety Stock + Lead time demand or (order quantity if you are using the min-max method to deploy).**

We can find a relationship between the amount of safety stock you can decrease for each percent point reduction in Forecast Error, since forecast error figures directly in the Safety Stock calculation.

**Safety Stock = Forecast Error * Service Level Quotient * Square Root (Lead Time)**

From simple calculus, the effect of one unit reduction in Forecast Error is just the product of Service Level Constant * Sqrt (Lead-time). So at 98% service level with a lead time of say two months, the effect of one unit reduction in Forecast Error is 2.90 Units.

What is the impact of a % point reduction in MAPE? The answer depends on the level of your current forecast quality.

However, the relationship of inventory reduction to your current MAPE Level is not linear. The calculation on the reduction in inventory is a function of your current level of forecasting. This determines the quantity of inventory reduced for each percent point improvement in Forecast error.

**If you are at 50% MAPE on average currently, the reduction would be 2% of inventories for each point improvement in forecast error. ** IF you are at 25% MAPE currently, the improvement will be 4% for each point reduction.

This is actually a conservative estimate since it considers only the safety stock component of the total inventory.

If your forecast is an over-estimate of the Lead time demand, then you carry additional inventory not accounted for in the above calculation. This will also introduce obsolescence risk.

So a lower bound is to just use the reduction in safety stock but being aware that a better forecast will also allow you to deploy better to the lead time demand. Better forecast can also help you reduce production and logistics costs such as over-time and expediting costs.

So if you have $200MM in inventory and let us assume that 25% of that total is safety stock then you have $50MM in safety stock.

A reduction of 10 point MAPE will result in a reduction of $10MM in safety stock. 10 point MAPE reduciton =20% reduction in Safety Stock or $10MM assuming currently your average MAPE is 50%.

Again this does not consider any reductions in the inventory carried to cover lead time demand (particularly due to forecast bias) or obsolescence that results from unsold inventory. Obsolescence is a bigger risk since you lose all of the inventory investment.

Next question is what does the reduction of $10MM in inventory really mean to you? This completely depends on the inventory carrying cost for your company.

Inventory carrying cost can be any where between 12% to 40% per year. So in financial terms, a $10MM reduction in inventory could result in bottom line improvement of $1.2MM (at 12% carrying cost) to $4MM.

Now we are talking real dollars……………..

Let us try to save some of those costs by bettering the demand plans!

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