IN THE PAST YEAR, TENS OF THOUSANDS OF WORDS HAVE
been written about “big data” and how to manage it. The fact of the
matter is that big data is simply a new term for an old condition.
Almost from the first day that technology became widely used in
managing the supply chain, we’ve had more data than we could
use. Rather than spending time and resources trying to manage
what we don’t need, I think it might be interesting to try to reduce
the amount of data to that which we really can use effectively. This
could be particularly important in managing the performance of
logistics service providers (LSPs), where in too many cases, outsourcers will become so enamored of data that
they measure far more than they need to.
In 1610, Galileo Galilei said, “We must mea-
sure what can be measured, and make measur-
able what cannot be measured.” (Over the years,
this statement has evolved into the more direct,
oft-quoted axiom, “You cannot manage what
you cannot measure.”) But today, some 400 years
later, many supply chain managers still struggle
with the application of that premise. Different
companies will have different criteria for mea-
suring their LSPs’ performance. For example,
a pharmaceutical client would be much more
concerned about batch controls and error rates than an appliance
manufacturer would. But four basic rules should apply over all
industries and providers:
b The first axiom is the tried and true, “You can’t manage what
you can’t measure.” This is particularly valid for outsourced oper-
ations. If you do not know how the provider is performing against
agreed-upon standards and benchmarks, it will be impossible to
evaluate not only its performance, but the client’s own customer
service.
b Make measurable what cannot be measured. The task here will
be to identify activities in discrete segments against which you can
establish measurable and achievable standards. A common mis-
take is to establish standards that are so vague they are absolutely
meaningless. This creates additional work for both parties. Once
the activities have been identified, then their importance can be
determined.
b Measure only what is important and actionable. This is the area
where a lot of big data is generated. It also often leads to “report
abuse.” Some managers will become so fascinated with the reports
BY CLIFFORD F. LYNCH fastlane
How much is too much?
themselves that they will insist on measur-
ing trivia. If it doesn’t have an impact on the
operation or the operation’s cost, efficiency, or
customer service, forget it. While every compa-
ny has its unique needs, in a typical warehouse
operation, the measurement of eight to 10 basic
areas should be sufficient. Examples of these are
productivity, order-fill rate, on-time perfor-
mance, inventory variations, order cycle time,
line-item accuracy, number of orders handled,
and space utilization. You
really don’t need to know
how many orders were load-
ed at Door 5 by employees
wearing blue shirts.
b Measurement must be bal-
anced. Too many measure-
ments can bury the opera-
tion in details and lead to
friction between the parties.
Too few or too general evalu-
ations make the performance
difficult to manage. Timing
should be balanced as well. There is no need to
measure everything every day.
Certainly, as our technology continues to
improve, we will learn more about our supply
chains, i.e., generate more and “bigger” data,
and the information no doubt will be helpful.
The phrase “Information is power” probably
has been quoted on millions of occasions; but
in my mind, the real power lies in being able to
take the information and use it effectively. This
includes rejecting the information you don’t
need to manage your activities.
Clifford F. Lynch is principal of C.F. Lynch & Associates, a provider
of logistics management advisory services, and author of Logistics
Outsourcing – A Management Guide and co-author of The Role of
Transportation in the Supply Chain. He can be reached at cliff@
cflynch.com.
