This document proposes a key performance indicator (KPI) for evaluating forecast accuracy that takes into account multiple factors. A KPI is calculated as a weighted average of four indicators: forecast accuracy, customer fill rate, excess inventory, and inventory turnover. Each indicator is rated on a scale and given an importance weight. The KPI is then calculated using a formula that averages the weighted ratings. This provides a more holistic view than only looking at raw forecast accuracy. An example calculation shows a scenario where the KPI evaluates as "excellent" while forecast accuracy alone would be "concerning." Considering multiple factors gives a fuller picture of forecast and business performance.

1. B Y Q I M I A O H U
DESIGNING KPI FOR
FORECAST ACCURACY

2. PROBLEM
• Sometimes upper management will decide to solely use
planners’ forecast accuracy at lagN (forecast as of N months
ago; N usually depends on production lead time) as indicator
to evaluate a planner’s performance.
• However, there are many other factors impacting accuracy.
For example, warehouse capacity, customer credit hold, shift
of retailers’ open to buy $ from future or past months, out of
stock, or even catastrophic events (i.e. Hurricane Harvey in
2017)…etc.
• Often time, single lag of accuracy does not provide all the
business insights, thus is only fragmented in terms of diagnosing
a business’ overall well being.

3. 4 THINGS THAT IMPACT THE PROBLEM
• Traditional way of calculating forecast accuracy is
using the formula:
Error=(Actual-Forecast)/Actual
Accuracy=1-Error
• The four direct results of a good forecast accuracy
are
• High forecast accuracy (the higher the better)
• High customer fill rate (the higher the better)
• Minimal excess inventory (the lower the better)
• High inventory turnover (the higher the better)

4. INDICATORS WITH RATINGS
Indicator1--A Forecast Accuracy 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Indicator2--F Customer Fill Rate 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Indicator3--E Excess Inventory
Indicator4--T Inventory Turnover
Remark #1, #2 & #4, the higher the better
#3, the lower the better
Dark and Light Oranges are corporate average
Red represents poor performance
Green represents excellent performance
High (=0)
Medium
High (=0.5)
Medium
Low (=0.75)
Medium
Low (=0.5)
Medium
High (=0.75)Low (=0)
Low (=1)
High (=1)

5. FORMULA FOR KPI
Importance (Weight)
Indicator1--A Forecast Accuracy 30% ->Impacts #2, #3 & cash outflows
Indicator2--F Customer Fill Rate 30% -> Directly impacts financial performance
Indicator3--E Excess Inventory 30% -> Directly impacts financial performance
Indicator4--T Inventory Turnover 10% ->Measures how fast a company can generate cash
100%
30%
A
30%
F
30%
E
10%
T
KPI
• KPI is a weighted average subtotal of all 4 indicators
• The % weight of importance alters as business priorities shifted

6. HOW TO MEASURE THE KPI & METRIC
This KPI can be measured by a numeric %, which is a weighted
subtotal of all 4 indicators. The higher the final % indicates a
more satisfactory result from forecast accuracy
100%
Idealism-will
never happen
in reality
90%
Excellent 80%
70%
Acceptable 60%
50%
To be
Concerned 40%
30%
Big Trouble
20%
10%

7. KPI CALCULATION EXAMPLE
30% X
48%
30% X
99%
30% X
0.75
10% X
0.75
74.1%
Forecast
Accuracy (A) 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Customer Fill
Rate (F) 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Excess
Inventory (E)
Inventory
Turnover (T)
High (=0)
Medium High
(=0.5)
Medium Low
(=0.75) Low (=1)
Low (=0) Medium Low (=0.5)
Medium High
(=0.75) High (=1)
48%
99%
.75
.75

8. CONCLUSION
At 74.1%, KPI is within the range of “Excellent”, versus
if only looking at pure forecast accuracy 48%,
business would be evaluated as “to be concerned”.
100%
Idealism-will
never happen
in reality
90%
Excellent 80%
70%
Acceptable 60%
50%
To be
Concerned 40%
30%
Big Trouble
20%
10%
74.1%
48%