| Supply Chain
Management
Return on invested capital (ROIC)
is often a primary business consideration. A key driver
of ROIC is inventory. Indeed, inventory is a key
consideration in managing the overall supply chain.
Given uncertainty in both supply and demand, statistical
methods are important in managing inventory levels and
improving supply chain performance. This can be done in
several ways. Statistical methods are used to size the
buffers in multi-node supply chains so as to carry the
least amount of inventory to attain desired
responsiveness goals. Target inventory levels are
computed based on statistical theory so that alternative
methods of replenishing the supply chain can be
evaluated. Responsiveness can often be attained through
a combination of capacity and inventory. Statistical
methods aid the evaluation of the tradeoffs. The
product portfolio can be evaluated in terms of gross
return on inventory (GROI). GROI measures a product’s
(or product portfolio’s) contribution margin after taxes
relative to the inventory investment. Often there are
products which are much better at attaining high GROI
than others. Knowing the difference is important in
improving profitability. Finally, statistical methods
are used to affect product design. Design for supply
chain is an important consideration in developing
products that will tend to have high GROI.
A couple of references on
this topic come from a long-time colleague at Agilent
Technologies.
Kruger, G.A., “A
Statistician Looks at Supply Chain Management”,
Quality Progress, 2004.
Kruger, G.A., “The Supply
Chain Approach to Planning and Procurement Management”,
Hewlett-Packard Journal, February 1997.
|
