The volume, variety and velocity of business and supply chain data are increasing dramatically. At the same time, improved technologies, such as artificial intelligence and machine learning, are already on the horizon. Ernst & Young has recently published an interesting report, titled Digital Supply Chain: It’s All About That Data. The authors make one thing very clear: “Companies must act now to focus, simplify and standardize big data through an enterprise data management strategy.” If companies fail to do so, the authors argue, “technology will drive increasing data cost, complexity and inefficiency; companies will be unable to benefit from advanced analytics like machine learning; and they will be unprepared for the next wave of data growth triggered by new technologies like IoT and blockchain.” In other words, companies fail to be successful unless they become masters of their supply chain data. Maybe business schools should increase the proportion of IT knowledge in their SCM curricula?
The following Google Ngram Viewer graph shows the frequency of the terms “supply chain”, “logistics” and “procurement” in books published between 1975 and 2008. It turns out that the use of the term “supply chain” accelerated in the late 1990s and overtook “logistics” in 2007. We can only speculate about the current use, as Google’s database ends in 2008.
We certainly all agree: Trust between supply chain partners has a lot of benefits. However, in their forthcoming study of trust in the buyer–supplier relationship, Villena and her co-authors argue that there is a “duality of trust”: Trust has benefits but it can also become dysfunctional if it is excessive. The results of their study show “that trust follows an inverted-U shape with performance”, i.e., at a certain point the negative effects offset the benefits of trust and performance declines. The authors also show that “[t]rust’s negative effects are more severe for those buyers that are highly dependent and operate in stable markets”. But why could trust ever be harmful? Well, trust might create “blind faith” into a supplier when the buyer is too optimistic. Another explanation could be that buyers might avoid tensions with suppliers that they otherwise trust – even if they observe declining performance. Trust can also increase reliance and unnecessary obligations that constrain the buyer.
Villena, V.H., Choi, T.Y., & Revilla, E. (in press). Revisiting Interorganizational Trust: Is More Always Better or Could More Be Worse? Journal of Management
What are the upcoming SCM trends? Firstly, in our recent research about “hot topics” in SCM, sustainability topped the list. Indeed, 2016 has, most probably, been Earth’s hottest year on record. Ask yourself: “What will be my contribution to revolutionize our business models and create truly sustainable supply chains?” Secondly, 2017 could become the year for supply chain managers, as an increasing number of companies realize that SCM belongs in the C-suite – and that this can make a difference! Another example is Lego, the toy maker, which has recently appointed a supply chain expert to become new CEO. Companies seem to understand that SCM is not just another name for logistics; it rather creates the smile of value creation. Finally, machine learning and artificial intelligence have recently made an astonishing leap forward. Not much imagination is needed to realize that this development is about to “disrupt” decision making in SCM. Why not let machines select your suppliers? Have a good new year!
Our new article, titled Accounting for External Turbulence of Logistics Organizations via Performance Measurement Systems (Supply Chain Management: An International Journal, Vol. 21, No. 6), is out now. It deals with the interface of supply chain risk management – a “hot topic” in SCM research – and performance measurement systems (PMS). The article was co-authored by Andreas Bühler, Carl Marcus Wallenburg and me. We address two research objectives: First, we focus on the outcome of PMS design for turbulence: We argue “that accounting for external turbulence via metrics in PMS design is beneficial for logistics organizations and show to what extent it increases organizational resilience and the [performance] of the companies”. Second, we focuses on the antecedents of PMS design for turbulence: We demonstrate “that the approach which the upper management of an organization has toward how to use the PMS in general will strongly impact the extent to which an organization incorporates risk metrics into its PMS”.
Bühler, A., Wallenburg, C.M., & Wieland, A. (2016). Accounting for External Turbulence of Logistics Organizations via Performance Measurement Systems. Supply Chain Management: An International Journal, 21 (6), 694-708 DOI: 10.1108/SCM-02-2016-0040
If you do not have access to the article, the accepted author manuscript can be downloaded for free at Copenhagen Business School’s Research@CBS platform (click on the document in the green box there).
The Council of Supply Chain Management Professional’s Academic Research Symposium (ARS) (formerly: Educators’ Conference) has earned a prominent reputation with many academics, as it is an excellent opportunity to meet colleagues and share new research for discussion and feedback. The ARS is proudly considered the premier event for research in supply chain management and logistics (SCML), and is an open event created to bring scholars from all disciplines into the SCML discussion. As a member of the Conference Committee, I would like to draw your attention to the Call for Papers of the 2017 CSCMP Academic Research Symposium, which will be held in Atlanta, GA, U.S. next year. The 2017 symposium will embrace research from all areas of business connected to SCML. The Conference Committee is excited to facilitate an event that will examine the past, present, and future innovations that continue to advance the discipline. Please find this and other CfPs on the right side of this blog.
You should all read this interesting article: Approaching the Conceptual Leap in Qualitative Research by Klag & Langley (2013), which is useful for researchers who build theory from qualitative data. Its central message is “that the abductive process is constructed through the synthesis of opposites that [the authors] suggest will be manifested over time in a form of ‘bricolage’.” The authors use four dialectic tensions: deliberation—serendipity, engagement—detachment, knowing—not knowing, social connection—self-expression. One of the poles of each dialectic has a disciplining character, the other pole has a liberating influence: On the one hand, overemphasizing the disciplining poles “may result in becoming ‘bogged down’ in contrived frameworks (deliberation), obsessive coding (engagement), cognitive inertia (knowing) or collective orthodoxy (social connection)”. On the other hand, overemphasizing the liberating poles “can also be unproductive as researchers wait for lightning to strike (serendipity), forget the richness and nuances of their data (detachment), reinvent the wheel (not knowing) or drift off into groundless personal reflection (self-expression)”.
Klag, M., & Langley, A. (2013). Approaching the Conceptual Leap in Qualitative Research. International Journal of Management Reviews, 15 (2), 149-166 DOI: 10.1111/j.1468-2370.2012.00349.x