Digital technology is rapidly transforming business processes, communication processes, and customer activities—disrupting and destabilising markets, but also enabling the creation of new ones. (Forbes Insights Team, 2018). This module looks at the “state-of-the-art” in analytics capabilities and how they drive supply chains, from marketing to sourcing. We will look at every type of disruptive and transformational analytics technology in an end-to-end supply chain. This includes information technology, process and product technologies, Blockchains, 3-D printing, and every analytics driven technology relevant to supply chains. We will evaluate what makes them work, learn to question the assumptions behind the algorithms, learn to appreciate and comprehend the data that drives them, and consider the trade-offs decision makers have to make when using them.
Companies from IBM to UPS to Amazon have succeeded by not only using the right analytical tools - but by knowing which questions to ask with their analytics algorithms, and how to make the right decisions at the right time. These tech giants also understand that the key to success is not just using analytics to solve individual problems, but to have a connected analytically driven supply chain.
We will look at how leading organizations use analytics to meet their strategic objectives, provide value to the business, and make decisions. The module will heavily focus on industry best practices. An integrative approach to technology is critical if technology is going to drive supply chains that are efficient, effective, and that provide a sustainable competitive advantage.
PART I: “Big” Data Driven Supply Chain Management
• How and why analytics has become a game changer for supply chain management.• A connected system – the uniqueness of analyzing supply chains.• Data overload - The barriers to becoming a supply chain analytics organisation
PART II: Impact on Supply Chain Levers
• Big Data’s impact on the supply chain lever “Sell” (Marketing). Addressing relevant/latest analytics applications such as; micro-segmentation, price optimisation, and location-based marketing. • Big Data’s impact on the supply chain lever “Make” (Operations). Addressing relevant/latest analytics applications such as; optimizing inventory and digital factories. • Big Data’s impact on the supply chain lever “Move” (Logistics). Addressing relevant/latest analytics applications such as; perfect-order delivery, optimising transport routes, and the functionality of autonomous vehicles. • Big Data’s impact on the supply chain lever “Buy” (Sourcing). Addressing relevant/latest analytics applications such as; developing supplier scorecards, risk measurement, automating routine purchases, and optimising supplier bundles.
PART III: A Framework for Implementation
• Develop a roadmap to lead to supply chain digital transformation.• Develop an S&OP model using analytical skillsets already gained during the course to showcase supply chain analytics in action.
This highly interactive course will use textbook material, written and video cases, video clips, experiential exercises, and a hands-on project. We want to learn supply chain analytics in practice, how it is used, what questions to ask, and to “talk to talk.”
|Module Content & Assessment