1 Introduction
An approach that can treat different product instances in a special way based on their specific characteristics
and needs has been argued to bring special benefits both in manufacturing and in supply chain industrial
contexts [1]. Focussing on supply chain and logistics operations, the impact of such a product intelligence
approach [1, 2] has been recently under consideration in a number of different areas such as road-based logis-
tics [3], intermodal transportation [4] and production logistics [5]. In this paper, we discuss its applicability
and potential benefits in another area of logistics operations, other than transportation-related ones |the
operations run in warehouses.
Due to the rapidly changing preferences of customers, orders received by warehouse companies (espe-
cially third-party-logistics ones) increasingly exhibit special characteristics, such as smaller order size, higher
product variety, request of shorter response time, and request for changes after the order has been initially
created and placed [6]. This means that although the traditional performance targets for warehouse services
(e.g. warehouse utilisation, tighter inventory control) still remain, in today's environment, they are subject to
the specic, special needs of dierent customers. This is particularly true in third-party-logistics warehouses
that manage a high variety of products and a big number of individual customers. Here, the operations are
required to become more customer-oriented and more responsive to requests with dierent characteristics
and needs in an ecient manner.
In this paper we aim to demonstrate the way the product intelligence paradigm can respond to the above
challenges by studying its future application in a third-party-logistics warehouse company. After reviewing
the current situation in warehouse management systems in Section 2, we discuss the opportunities for the
adoption of intelligent products in warehouse operations and their potential applications in Section 3. We
present our scoping case study along with two specific application examples in Section 4 before concluding
with our findings.