Three crucial steps to accelerating returns from your transportation management system spend

Johnny Ivanyi and Vivek Chhaochharia
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Johnny Ivanyi: Bayer Crop Science, St Louis Headquarters, USA
Vivek Chhaochharia: Ernst & Young, USA

Journal of Supply Chain Management, Logistics and Procurement, 2025, vol. 7, issue 4, 350-357

Abstract: Global supply chain disruption shows no signs of slowing down. In recent years, international organisations such as Bayer Crop Science have juggled cost instability, distribution bottlenecks, escalating fuel costs and other macro factors that are buffeting global logistics. To stay in front of these challenges and deliver exceptional customer service, Bayer initiated a worldwide digital transformation. Primarily intended to transition to a state-of-the-art transportation management system (TMS), Bayer deployed Blue Yonder’s TMS across more than 65 countries, replacing disparate tools, outdated legacy systems and manual processes forced to manage an increasingly complex logistics network. While the initial transformation saw a 3–5 per cent improvement in overall transportation spend, a 7 per cent increase in asset utilisation, a decrease in environmental impacts and a major cultural change, Bayer transportation leaders realised that the expected return on investment (ROI) was not being sustained over time as inevitable changes to the supply chain occurred. As a result, Bayer leadership sought the input and guidance of Ernst & Young LLP (EY), a veteran of numerous global digital transformations with deep experience in the complications, rigours and demands of volatile supply chains. Together, Bayer and EY teams built a framework leveraging three strategies to drive greater ROI for Bayer and any other supply chain operator seeking improved efficiencies. This paper details the strategies and approach taken. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.

Keywords: logistics digitalisation; transportation management; warehouse management; digital transformation; supply chain volatility; artificial intelligence; machine learning; supply chain autonomy (search for similar items in EconPapers)
JEL-codes: L23 M11 (search for similar items in EconPapers)
Date: 2025
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