By Dr. Sanjoy Paul, Prof. Hau Lee and Mahesh Veerina
In this series, we put different tracking approaches on a common foundation and categorize them into that we refer to as hard and soft attribute-based tracking. Then we argue why both hard and soft attribute-based tracking are important and how one complements the other, leading to near-optimal visibility. In this blog post, we describe the supply chain as a large workflow of interlinked processes and discuss soft and hard handoffs in attribute-based tracking. For more on this topic read the whitepaper A Holistic Approach to Supply Chain Visibility.
Figure 1: Supply Chain is a gigantic workflow of interlinked processes
Conceptually, every functional process, such as the Supplier process, Inbound Logistics process, Factory process, Warehouse process, Outbound Logistics process and Distribution Center process, consists of several activities (steps) as shown above in Figure 1. The activities in each functional process can be divided into three parts:
Inbound Edge is the first activity and Outbound Edge is the last activity. The rest of the activities are clumped into the Core. Specifically, if we take the Supplier process, it consists of the following steps – Requisition, Approval, Purchase Order, Shipping. Here, Requisition is the Inbound Edge and Shipping is the Outbound Edge, while Approval and Purchase Order are lumped into the Core.
For the next function of Inbound Logistics, the steps are: Contacted, Scheduled, Loaded and Delivered. Contacted is the Inbound Edge and Delivered is the Outbound Edge while Scheduled and Loaded are clumped into the Core as shown in Figure 2. The rationale for introducing the terms “Inbound Edge” and “Outbound Edge” is to show the “Triggering” of actions from an upstream functional process (say Supplier Process) to an adjacent downstream functional process (Inbound Logistics Process) and so on along the supply chain as functional boundaries are crossed and a change of stakeholders takes effect.
Figure 2: Activities (steps) within specific functional processes in a Supply Chain
The Outbound Edge of an upstream function feeds into the Inbound Edge of a downstream function. In this example, the Shipping activity of Supplier Process triggers the Contacted activity of Inbound Logistics Process, meaning that as soon as the Supplier is ready to ship, the Inbound Logistics needs to be contacted for scheduling the pickup. While each functional process has a micro-level workflow linking the steps, there is a macro-level workflow interconnecting the functional processes from upstream all the way to downstream.
Hard attribute-based tracking identifies the arrival and presence at a functional process. In other words, the macro-level workflow can be tracked based on hard attributes. Soft attribute-based tracking identifies the transition from one step to another within a functional process. Thus, micro-level workflow can be tracked based on soft attributes.
Once we have a mechanism for tracking both hard and soft attributes in real time, gathering the relevant data at the appropriate level of granularity, and superimposing them on to the digital models of the various entities in the supply chain, we can essentially create a digital twin of the supply chain, visualize the performance at different levels of granularity in real time, and perform real-time what-if analysis for making smart decisions for risk mitigation and/or improved operations and planning.
Inefficiencies happen in two main areas: (1) transition from one step to another within a function and (2) transition between functions. We call the first type of transition “soft handoff” and the second type of transition “hard handoff.” Since soft handoffs are within a given functional entity (or an organization), they can be handled with escalations within the hierarchy of the organization if the delay in the soft handoff is detected. However, hard handoffs happen across organizations and hence, they need different modes of intervention rather than an escalation within the organizational boundary.
Soft handoffs can be handled and streamlined by soft attribute-based tracking. Every handoff has a “from” state and a “to” state as the workflow is executed. When a “from” state is reached, if a notification is sent to the stakeholder of the “to” state proactively, inefficiency in the system can be reduced.
For example, when “Purchase Order” is approved in the Supplier Process (refer to Figure 2), a notification can be sent to “Shipping” so that “Shipping” is triggered without any delay. In case “Shipping” is not triggered within a pre-specified time, a second notification or alert can be sent to the stakeholder of “Shipping” or even escalated up the hierarchy. If and when soft handoff is within an organization, the enterprise-wide messaging system of the organization can be used for this purpose. However, it is possible that the soft handoff happens across organizations or companies. In fact, we need to pay more attention when soft handoffs cross organizational or company boundaries. Blind spots are exactly there if we do not track the “soft” attributes.
Hard-attribute based tracking can detect when hard handoffs happen but when the expected handoff does not happen, it cannot determine why it did not happen. As an example, when say, raw material is “Loaded” on the delivery truck of 3PL (refer to Figure 2), sensor-based tracking can detect it, but if Loading does not happen, hard-attribute based tracking cannot determine why it did not happen and hence cannot help take appropriate action to make it happen. However, soft attribute-based tracking, by virtue of more granular tracking, would know exactly at what step the workflow got stuck and by messaging the right stakeholder, can make the process move.
Coming back to the same example, the moment “Shipping” is done in the Supplier process (as detected by the soft attribute-based tracking), if a notification is proactively sent to the right stakeholder of the 3PL for “Contacted” state (refer to Figure 2) as well as to the corresponding stakeholder of the Supplier organization, it is highly likely that the stakeholder will take the appropriate steps assigned to him/her, and help move the process, thereby reducing or eliminating delay. Note that this is an example of soft handoff across organizational boundaries.
One difference between a Hard and Soft handoff is that for the former, messaging must be done across organizations, while for the latter, the messaging needs to be done within an organization (except in the rare cases of cross-organization soft handoffs).
Cross-organizational messaging requires a common messaging platform for the upstream (Supplier) and downstream (3PL) organizations involved in the Hard handoff. That may not always exist. In that case, it may make sense to notify the right stakeholder of the upstream organization (Supplier) using enterprise-wide messaging so that the upstream organization can follow through with the downstream organization (3PL) in case the downstream organization does not execute the respective step in time. In the context of the example being discussed, if 3PL does not respond in time, the stakeholder from the Supplier can follow through with the stakeholder of the 3PL in order to avoid delays. The same process can be followed between the 3PL and the Factory; between the Factory and the Warehouse; between the Warehouse and the Outgoing 3PL; and between the Outgoing 3PL and the Distribution Center during Hard handoffs, making the end-to-end process streamlined, thereby reducing inefficiency dramatically and improving the overall experience of various stakeholders in the supply chain.
In summary, every function of the supply chain involves following process, and the entire supply chain can be thought of as a gigantic workflow of interlinked processes. There are inefficiencies that can occur in both soft and hard handoffs, and we discussed how these handoffs can be handled and streamlined through attribute-based tracking. In our next and final blog post in this series, we explore how you can use AI and machine learning analytics to further improve efficiencies in your supply chain.
Dr. Sanjoy Paul is an innovator, disruptive entrepreneur, and an industry-recognized expert in AI & IoT.
Prof. Hau Lee is a Professor at Stanford University Graduate School of Business and Co-Director of the Value Chain Initiative.
Mahesh Veerina is a seasoned Silicon Valley entrepreneur, technology executive and investor and is the President and CEO of Cloudleaf.
All blog posts in this series:
Learn how implementing both hard and soft attribute-based tracking is key to achieving near optimal visibility and an efficient and highly profitable supply chain.