As competition heats up to meet consumer fulfillment expectations, the analyst community has worked to define a supply chain model that can dynamically and rapidly respond to changing market needs, sometimes called "Response Networks". Gartner calls their version “Respond Planning”. Supply Chain Insights (Lora Cecere’s firm) calls it “Networks of Networks”. And Bob Ferrari of Ferrari Consulting has coined the term “Digitally Enabled Response Networks”.
While there are some similar concepts among the three, in a recent report Bob Ferrari has laid out a specific architecture for this paradigm and offers three working examples of organizations from the healthcare, internet retail and beverage industries. Here is how Ferrari describes it.
The response network model begins with a dynamic and profitable assortment at the Point of Sale (POS). The downstream assortment is fed by a responsive system able to continually and seamlessly synchronize the network to meet customer expectations across multiple retail channels, either online or combined with a physical retail presence.
This approach reflects a convergence of supply chain planning and execution for synchronized action and response. It requires shifting from a product-centric to a more customer-centric omnichannel fulfillment process because the customers’ demand intentions become the trigger for the network response, adjustments, or alternative actions. Managing the supply network cannot be viewed solely as a cost-driven activity, but rather an integral part of orchestrating fulfillment needs in the channel of most convenience for customers.
A Digitally Enabled Response Network at Costa Express
Here are some of the key attributes of a response network (much of it taken directly from the report):
- A move from supply-driven or purely demand-driven, to a service-level driven supply chain fulfillment support capability. Rather than the supply network determining the parameters of customer fulfillment capabilities, the supply network is configured and enabled to respond to the different service level needs, channels and fulfillment parameters preferred by customers.
- A strong vision of what dynamic customer response needs to be among fulfillment channels, including the data and information needed to make more timely, predictive and informed decisions relative to executing required service levels.
- The connecting of upstream product demand sensing with downstream network planning and execution response supported by a singular streaming information and decision-support capability. The continuously updated streaming of data and information moves beyond individual software applications and becomes available to the planning and response systems for multiple business partners.
- The integration and synchronization of individual and collective supply chains into a singular virtual response network, anchored in a data and information-rich environment with predictive decision-making tools and capabilities. It leverages IoT, Manufacturing 4.0, predictive analytics or other AI-based decision-making technologies to manage end-to-end network synchronization, risks, and unplanned exceptions.
- Technology that can support item-level planning granularity and scale to the data and information volumes needed for supporting dynamic replenishment networks. More advanced technology to provide automated decision-making and user-friendly and well understood depictions of information.
- Transformational projects, including the process, people and change management strategies to support a phased transition.
The Ferrari study delves much deeper into these concepts, including three detailed industry examples, common learning themes and key takeaways.