Digital Supply Chain-Leveraging innovative technology is essential in any modern supply chain. Indeed, to succeed in the modern industry, supply chain digitalisation is a key ingredient. Due to the way customer demands change, companies must use digital technology to be lean and agile or run the risk of being left behind by competitors.
Stefan Gstettner, Partner & Associate Director in the Frankfurt office of BCG, is an experienced supply chain professional. As part of his role, he exclusively focuses on advising clients in end-to-end supply chain management. Supply Chain Digital speaks with Gstettner to uncover more about the affect supply chain digitalisation is having on the industry.
How would you describe Boston Consulting Group? What differentiates it?
We have a fascinating and to a large extent, unique blend of people, capabilities and insights. This becomes evident while working on large and complex transformations. Beyond the table stakes that every consulting company provides, we deploy an exceptionally diverse and strong set of people with unique capabilities (e.g. data scientists, change management experts, deep topic experts, IT architecture experts). For me, the biggest differentiator is that we are able to collaborate and form powerful teams with these diverse individuals. That’s how real impact can be unfolded – individual excellence in a complex, connected situation does not bring as much value as a well-formed team. And finally, I feel it’s always inspiring and fun for our clients to work with us.
With digital transformation having such a major impact on the supply chain industry, how vital has AI and machine learning become to businesses?
The most surprising aspect of SCM is that the word “digital supply chain management” is still around. It could have become the “new normal” already and we should achieve a consensus that no supply chain is “non-digital” anymore. This means AI and ML as enabling technologies are an integral part of operating supply chains. I cannot imagine any supply chain without these capabilities anymore. Practically, of course, there are still several hurdles. Not only are the capabilities to run AI and ML in supply chains difficult to acquire and to retain in the organisation, but the areas where they are applied (take demand sensing as an example) also need to be carefully embedded in the overall processes and connected to the other elements in the supply chain.