Preview – Most IBP cycles around the world are based on a 20-year-old process definition supported by 20-year-old planning concepts. This traditional IBP is not set up for a fast-changing world, where speed of decision making confers a competitive advantage. Intelligent automation will change this. In a series of short blogs, I will discuss the transition of traditional IBP towards a more intelligent IBP. In this blog: The Rise of Autonomous
Automating the supply chain
Automation has been happening for hundreds of years. It has long been focused on improving productivity of boring, repetitive, or dangerous human activities. We now have automated production facilities, warehouses, and transport in our physical supply chain. One of the early examples was this beautiful 1913 Ford Model T production line.
After physical labor, the next step is to automate the knowledge worker, either supporting or automating their cognitive tasks. It will help the knowledge worker plan, simulate, decide, and act if required. It will do so at a higher speed, larger scale, greater consistency, and precision, and with more endurance than any human is ever capable of.
One of the holy grails of supply chain management will arrive when we combine both. Digitized physical assets, combined with a digital twin of the knowledge worker, can foresee, or detect and react faster to change.
According to the book Intelligent Automation, 42% of work can be automated, 32% of work can be augmented and 26% of work can be eliminated. These numbers account for 84% of the workforce. Supply chain planners in traditional IBP will not escape this evolution.
Visualizing the future of planning
Supply chain planners are still mostly supported by Wave 1 systems (ERP) and Wave 2 systems (APS) in order to perform their tasks. Autonomous planning can’t be achieved by these systems. We’ll see the rise of Wave 3 systems, or systems of intelligence, which will provide intelligent automation that replaces the human planning process as well as cognitive automation that augments a planner’s decision making with predictions, insights, and recommendations.
In this 2019 Foresight article, I highlight 8 elements required for autonomous planning. Miss one of them and it won’t be possible. Autonomous planning is no easy feat but must be possible. If NASA can drive an autonomous robot on Mars and SpaceX can land rocket boosters vertically back on earth, autonomous planning must be possible right? You can argue the speed at which this will happen, but denying it seems either ignorant or arrogant.
Alain Perrot, a 30-year-old IBP veteran, who foresees a full symbiosis between human and machine across all planning horizons, noted; “In 10 years’ time from now, we need to visualize what machines can do.”
Visualizing this future, we can assume Intelligent automation will lead to more Intelligent IBP, with at least the following features:
- Data gathering, cleansing, master data and planning parameter maintenance will be automated.
- Descriptive and diagnostics analytics will be automated and made available at all times for IBP stakeholders.
- Planning processes are largely digitized and automated with the help of a digital twin
- Decisions in the S&OE horizon (highly frequent/lower value) will be largely automated
- Intelligent automation will identify variations and gaps to plan and automatically action these up to a defined threshold. Above that threshold it provides recommendations to be decided upon by humans.
- Increased agility for strategic decisions versus the long (4-6 weeks) traditional sequential IBP planning and decision cycle
- Human and machine decisions will be digitized in order to learn from them
This is good news for supply chain planners. Not only will they get a more effective IBP. They will get a much more interesting and engaging job.
The human remains central
The machine will not overtake the human. The machine will still require human guidance. Kasparov’s law dictates that the combination of ordinary humans and ordinary machines using the right processes can lead to superior performance, even triumphing over human genius or powerful computers alone.
Furthermore, Moravec’s Paradox, indicates that machines and humans have complementary strengths. Because of this, the human stays central, and the focus will shift to human-machine collaboration.
The rise of automation will liberate planners from the boring tasks and gives time back to be more human again, but at the same time, will require a new skill set. More about that, in the next blog