median cycle time shrinking to just six hours. It’s not much
of a stretch to conclude that the “dock to stock” improvement (which presumably helped ensure product was available to be picked) contributed to the impressive gains seen
in both internal and total order cycle times.
WHERE ARE THE POINTS OF PAIN?
Of course, every coin has its flip side, and this year’s survey
was no exception. Just as performance against several of the
metrics showed noteworthy improvement over the previous year, performance in other areas deteriorated.
Exhibit 3 identifies the major points of pain—the metrics that saw the biggest performance declines. It’s worth
noting that three of the five “pain points” centered on
internal operations, notably the pick and pack functions.
Although we can only speculate as to the cause, one possibility is that the typical order profile has changed, with
orders getting larger. If so, that might explain why performance dropped against those particular metrics, which
focus largely on speed.
It’s also worth pointing out that in some cases, performance slippage may not be a bad thing. Take the “honeycomb
percentage” metric, which showed the biggest drop in performance relative to last year’s survey.
Like “average warehouse capacity” and “peak warehouse
capacity” (whose performance declined as well), “honey-
comb percentage” is a measure of how fully space is being
used within the warehouse or DC. And while it might
appear that the objective here would be to get as close to
100 percent as possible, that’s not necessarily the case. In
fact, research has shown that the ideal “average warehouse
capacity used” number may be closer to 80 percent, because
it gives facilities the flexibility to respond quickly to chang-
ing economic conditions.
About the authors: Karl Manrodt is a professor at Georgia
Southern University. Joseph Tillman is senior researcher
and consultant for Supply Chain Visions. Kate Vitasek is
founder of Supply Chain Visions.
The authors welcome readers’ comments, suggestions,
and insights into the research and their own use of metrics.
They can be reached by e-mail: Karl Manrodt at
kmanrodt@georgiasouthern.edu, Joseph Tillman at
joseph_tillman@SCVisions.com, and Kate Vitasek at
Kate@SCVisions.com.
EXHIBIT 2
Going up! Where DC performance improved
Metric
Internal order cycle time
Dock-to-stock cycle time
Pallets picked and shipped per person hour
Supplier orders received per hour
Total order cycle time
Days on hand – raw materials
Distribution costs as a of sales
Major opportunity
> 36 hours
> 18. 7 hours
< 7 per hour
< 1. 5 orders
> 72 hours
> 66 days
> 10.2%
Typical
>= 8 and < 23. 4 hours
>= 4 and < 8. 2 hours
>= 14. 5 and < 20 per hour
>= 3 and < 5 orders
>= 15 and < 48 hours
>= 29 and < 45 days
>= 3. 3 and < 6%
Best in class Median 2011 Median 2010
< 2. 2 hours 12 hours 24 hours
< 2 hours 6 hours 9. 1 hours
>= 26. 5 per hour 18. 5 pallets 15 pallets
>= 10 orders 4 orders 3 orders
< 4. 5 hours 36 hours 48 hours
< 15 days 30 days 39 days
< 1.7% 4% 5%
Note: Survey responses have been divided into quintiles to make it easier for companies to see where they stand in comparison with other warehouses and DCs. For example, the “best in class” category represents the
top 20 percent of respondents, while “major opportunity” represents the lowest 20 percent of respondents—or those who have the most to gain from performance improvements.
EXHIBIT 3
Points of pain: Where DC performance declined
Metric
Honeycomb
Orders picked and shipped per hour
Lines picked and shipped per hour
Cases picked and shipped per hour
Days on hand – finished-goods inventory
Major opportunity
< 14%
< 2 orders
< 13. 6 lines
< 34. 8 cases
> 75.2 days
Typical
>= 39 and < 69.8%
>= 4. 2 and < 9. 5 orders
>= 25 and < 40. 6 lines
>= 85.2 and < 144 cases
>= 30 and < 45 days
Best in class
>= 85%
>= 29. 8 orders
>= 77.4 lines
>= 280 cases
< 14. 4 days
Median 2011 Median 2010
50% 72%
6 orders 8. 5 orders
30 lines 36.0 lines
120 cases 142.5 cases
36. 7 days 32 days
Note: Survey responses have been divided into quintiles to make it easier for companies to see where they stand in comparison with other warehouses and DCs. For example, the “best in class” category represents the
top 20 percent of respondents, while “major opportunity” represents the lowest 20 percent of respondents—or those who have the most to gain from performance improvements.
