Supporting Supply Chain Agility: Simple Concepts, Complex Technology
Complex factors such as concurrency, intelligent alerts and the use of downstream data eventually increase the agility of supply chain control towers. Forbes reveals how such technologies are ensuring the simplest solutions through the best outcomes.
Supply chain control towers have come of age. The concepts that allow modern control towers to support agility are easy to describe. The technology that empowers these concepts are quite complex.
To support supply chain agility a control tower needs to do the following:
- Provide near real-time visibility to inventory, shipments, and risks.
- Provide support for concurrent planning. Organizations have different plans for supply and demand planning. They have different types of plans for long range, intermediate, and near-term planning. With concurrent planning, these plans are connected. A change in manufacturing scheduling, for example, ripples up to the integrated business plan. Changes in short-term demand forecasts get highlighted in the supply plans.
- The system needs to be intuitive. Let’s take the example of a “hot load.” The trick is to identify what is “news” and what is “noise.” Perhaps a truck is late, but it contains product where a company has plenty of stock. On the other hand, an ocean container might come in early but contain products that are in a low stock position. So, the system needs to tell users which to receive first.
- Supply chain applications need to make more accurate forecasts. Downstream data increases forecasting accuracy, particularly for near-term forecasts. Forecasting accuracy and estimated times of arrivals are improved when machine learning technologies are applied.
- The systems need to be easy to use so that planners can easily run scenarios to understand how best to mitigate exception situations.
- The solutions need to support internal and external collaboration, playbooks, and war rooms. Not all problems can be solved using math. Collaboration with diverse stakeholders is often necessary. If certain types of exceptions occur on a regular basis, a playbook can be built to help automate these recurring problems.
Technology Needs to be Complex So that Solutions Can Be Simple
I am not going to go through each of those bullet items and describe the complexity. That would be overkill. But I will describe the complexity around just one of these areas – getting near real-time visibility to shipments, inventory, and risks.
The ability to support better visibility is based on using application programming interfaces (APIs) rather than relying on EDI, emails, portals, and phone calls. Because many large companies use many different business and supply chain applications across different business units and regions, the integration problem is significant. Companies may need to use data lakes and technologies that help to harmonize the data from the different applications.
A data lake consumes all the critical data from the different applications. Significant work is required to generate a harmonized data layer. The critical master data for supply chain management includes objects like sales orders, shipments, inventory, and lanes. Different business systems can define all the fields associated with these forms of master data differently. When implementing this, a company needs to ask their business users what data points they needed for each of these master data objects. It does not matter what various business systems, like SAP, thinks a “purchase order” is. A harmonized definition of “purchase order” is crated based on what is needed to support the control tower.
Then these objects need to work together to create a time phased view into what inventory will be available at what locations. To understand the current inventory position, a company takes their initial stock position and then calculates how that inventory position is changed by things like quality inspections, purchase orders, production orders, and intercompany demand.
The improved visibility to shipments was based on federal regulations requiring truckers to electronically track their hours of service. Suppliers like FourKites or Descartes MacroPoint provide near real-time visibility based on API integration to truck carriers’ GPS enabled electronic logging devices or by getting small carriers to agree to use smartphone applications that support tracking.
The solutions that provide real-time visibility to supply chain risks are fascinating. These solutions work by continuously monitoring a wide variety of risks, identified based on monitoring hundreds of thousand online and social media sources, and then linking those risks to a map they have created of their customer’s end-to-end multi-tier supply chain.
The other things supporting agility – concurrency, intelligent alerts, the use of downstream data, and so forth – all have their own complexities. But the basic point is this, we have dreamed about having robust supply chain control towers that can provide control that is analogous to what airport control towers or war rooms provide. Until the last few years, the technology did not support this. But finally, the technology has caught up to the vision. Companies are using these solutions to great effect. The early adopters have been rewarded with a greatly enhanced ability to respond intelligently to the COVID-19 Pandemic.