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 explore how the Visibility Index is computed, and discuss the benefits of tracking both hard and soft attributes. For more on this topic read the whitepaper A Holistic Approach to Supply Chain Visibility.
In the previous blog post, we illustrated how “blind spots” can be eliminated in the supply chain and the progress in Value can be observed clearly if both the hard and soft attributes are tracked. That is, when soft attributes are tracked and are complemented with the tracking of hard attributes, the movement of Value can be clearly observed as it changes progressively.
Figure 1: Value Diagram when both Hard and Soft Attributes are tracked
Once we have the accurate depiction of the visibility of soft and hard attributes, we can compute what is called the Visibility Index (VI). The Visibility Index is a metric that helps an enterprise to precisely understand the level of their maturity in tracking not only the flow of materials and finished goods, but also the progress in the execution of business processes in their supply chain. It helps an enterprise appreciate the gaps from an agile decision-making perspective and infer the steps needed to improve their overall business performance. Furthermore, it will help them benchmark themselves against the competition and adopt best practices. Last but not least, visibility is a means to the end, meaning better visibility will enable enterprises to plan better and make faster decisions, helping them to close the gap between planning and execution, and thus giving them a competitive edge in the industry. A supply chain that is able to merge planning and execution cycles is what we refer to as the Next Generation Supply Chain (NGSC).
The Visibility Index will vary from company to company based on the granularity of visibility of the various hard and soft attributes. We define Visibility Index VI as a vector:
where X represents Hard attribute-based visibility, Y represents Soft attribute-based visibility.
where Xi represents the visibility at step i along the X-axis in Figure 4 where i =0 through 6 corresponds to a through g and N (the number of entities in the supply chain) = 7
where Yi represents the visibility at step i along the Y-axis in Figure 4 where i =0 through 6 corresponds to a’ through g’ and N (the number of entities in the supply chain) = 7
Figure 2: Visibility Index (VI) for Example Cases
Figure 2 depicts the Visibility Index (VI) as a two-dimensional plot, where the X-axis represents the value of Hard attribute-based visibility, while the Y-axis represents the value of Soft attribute-based visibility. VI will always fall in the square region bounded by (1, 1). Vectors A (1, 0), B (0, 1) and C (1, 1) represent the three extreme cases corresponding to full hard-attribute & zero soft-attribute visibility, full soft-attribute & zero hard-attribute visibility and full hard-attribute & full soft-attribute visibility respectively as shown above. Vector D is an example of an enterprise whose hard attribute-based visibility is on the higher side (0.75), while soft attribute-based visibility is on the lower side (0.2). On the other hand, Vector E is an example of an enterprise whose soft attribute-based visibility is on the higher side (0.6), while hard attribute-based visibility is on the lower side (0.15).
Enterprises can be categorized into four basic quadrants based on their Visibility Index as shown in Figure 3: (1) Basic, (2) Grounded, (3) Granular and (4) Advanced. Basic indicates relative immaturity in both the hard and soft attribute-based visibility. Grounded refers to more emphasis on sensor-based tracking, leading to higher visibility on the hard attribute side with less emphasis on tracking business processes, leading to lower visibility on the soft attribute side. On the other hand, Granular refers to more emphasis on business process tracking, leading to higher visibility on the soft attribute side with less emphasis on sensor-based tracking, leading to lower visibility on the hard attribute side. When an enterprise has a balanced emphasis on both hard and soft attribute-based tracking, it belongs to the Advanced category. The goal of every enterprise should be to be in the top-right quadrant – the Advanced category. To emphasize extreme behavior, we have carved out an appropriate sub-quadrant within each quadrant.
Figure 3: Visibility Index (VI) Categories
If we superimpose the example cases on the above diagram, they look like the one shown in Figure 4, where A & D belong to “Very Grounded” category, E belongs to “Granular” category, B belongs to “Very Granular” category and C belongs to the “Very Advanced” category as expected, based on the visibility numbers for hard and soft attributes for the respective cases.
Figure 4: Visibility Index (VI) Categories for the Example Cases
Hard attribute-based tracking provides the ground truth as the sensors gather the information from the raw materials/components and finished goods in real time. The ground truth consists of a variety of real-time data that help answer important business questions like:
There are many such business questions that can be answered with full certainly, but only if hard attributes are tracked.
Visibility of soft attributes provides additional granularity to visibility and helps the stakeholders become more agile in their decision making. For example, think of a situation where the raw materials/components are visibly present at the Supplier (as indicated by the location sensors – hard attribute tracking) but have not yet been handed over to Logistics by the Supplier (otherwise, the location sensor would have indicated the presence of raw materials/components on the delivery truck – again known from hard attribute tracking). At this stage, until the raw materials/components are handed over to Logistics, there will be no change of state as far as hard attribute-based tracking is concerned. Potentially, the system could be in this state for a non-deterministic amount of time, creating the impression of raw materials being lost (from information visibility perspective) in a black hole. Naturally, it will not be clear whom to contact to make the system progress and not get stuck. This is the drawback of pure hard attribute-based visibility. Specifically, if soft attributes are not tracked, it would not be clear if the Supplier is waiting for “approval” from the ordering entity or for reception of the “purchase order” or for the workers to “pick, pack and load” the supplies onto the truck. To make it worse, it is not clear whom to contact to resolve the issue – should it be the person responsible for “approval” or should it be the person raising the “purchase order” or should it be the worker who “picks, packs and loads” the supplies on the truck? Thus, the lack of soft attribute-based visibility leads to higher delay and lower efficiency, not to mention stakeholder dissatisfaction. However, if soft attributes are tracked, it becomes clear that if the delay is because the purchase order (PO) has not been received by the Supplier, the person responsible for issuing the PO can be contacted and the issue can be resolved in a timely and targeted manner. Similarly, if the worker responsible for pick, pack and load is not present, his supervisor can be contacted and alternative arrangements can be made to pick, pack and load the supplies on to the truck as soon as the PO is received. This eliminates the inefficiency that leads to higher delay.
This argument holds at every stage of the supply chain. For example, if the supplies are ready to be handed over to 3PL (3rd Party Logistics) but not done, the supplies will naturally not arrive at the factory. Without tracking soft attributes, it will not be clear if the 3PL have been contacted or even if they have been contacted, if the 3PL have scheduled a pickup or if there has been a delay in loading the truck. Note that the responsibility for contacting 3PL lies with someone at the Supplier side, while the responsibility for scheduling a pickup lies with someone at the 3PL, and the responsibility for loading supplies on to the truck lies with the union workers. Hence, in order to solve the problem, it is absolutely essential to know where the situation is via soft attribute tracking and then take a targeted action to resolve the issue on time.
The main point here is that the tracking of soft attributes enables faster detection of the problem, quicker identification of the cause and faster resolution of the problem, leading to higher efficiency, improved throughput, lower delay and higher stakeholder satisfaction. Moreover, soft attribute tracking enables a better and more accurate computation of ETA and as a result, the resources for subsequent stages of the workflow can be lined up just in time, thereby reducing, if not eliminating, any wait time leading to maximization of efficiency and higher stakeholder satisfaction.
In summary, there are numerous benefits to tracking both soft and hard attributes of the supply chain, such as faster detection of the problem, quicker identification of the cause, and faster resolution of the problem. In our next blog post, “The Benefits of Tracking Both Soft and Hard Attributes,” we describe the supply chain as a large workflow of interlinked processes and discuss soft and hard handoffs in attribute-based tracking.
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.