Companies, that utilize the digital capabilities of Supply Chain planning, will be much more resilient, better equipped to handle challenges and compete more effectively. What does that mean in practical terms? Learn more in this blogpost.
Imagine if you were a company who had a bidet for sale these days. Yes, those that you put up next to the toilet. Apparently, many people are changing their buying behavior as demand has increased significantly. And of course, producers of bidet’s have a hard time following the spike in demand. On the other hand, people’s stock of toilet paper have probably hit the maximum. Manufacturers of toilet paper may experience a slightly lower demand in the coming time.
What is the point here? Firstly, it is not the first time that Global Supply Chains have experienced a disruption and it will probably not be the last time either. But how do you actually prepare for the next ” disruption ” or for some companies – an obvious opportunity to sell more.
Traditional Supply Chain planning is based on old thinking
Supply chain planning is still, in many companies, based on a 60 year old paradigm. It assumes, that you predict demand and then massage it into the rest of your supply chain. The premise for doing this is, that you are able to create a precise plan that you can execute. But in that, there is one challenge: the lack of being resilient and uncertainty of whether the plan can be kept at all.
In the military the terminology “no plan survives first contact with the enemy ” is used. The same goes for the Supply Chain. It is difficult to predict uncertainties. Uncertainties like what future demand looks like, whether deliveries are on time etc. are difficult to estimate. Some companies try to compensate by working with security stocks.
Create a resilient planning model
What can you do instead? Our suggestion is that you start working with the resiliency in the way you do your planning, in other words create a resilient planning model. What do we mean by that?
The technologies (cloud-based) should be utilized to a greater extent. Also, you should start working with the planning mindset of the company. This means, practically speaking, that you should work with scenario planning (several scenarios at once) and work with your forecasting accuracy. You can work with your forecasting accuracy by automatically taking into account, as examples, seasonal fluctuations, weather, order sizes and the impact of campaigns. Machine learning combined with human fine-tuning can help improve the demand model over time.
Work with a “Digital Twin”
Another initiative would be to create a physical supply chain and align decisions across the supply chain by working with a “digital twin ” i.e. a digital model of your current Supply Chain. With the digital model of the supply chain you will be able to simulate, how resilient your Supply Chain will be facing a certain variation and uncertainty. It will be possible to test how the Supply Chain will react under different scenarios.
It is not possible to guard 100% for the unknown unknown. What you can do is to invest in a planning model and technology that has already incorporated advanced algorithms that are based on a delivery performance towards the markets and at the product level. Technologies that also consider the company’s financial goals such as minimizing working capital, maximizing margins and reducing the risk of an obsolete inventory. It’s about having the technology that constantly helps in making these trade-off decisions.
Companies, that try to plan in the “normal” way will have big challenges in the future. On the other hand, companies that utilize the digital capabilities including automation, advanced algorithms and machine learning will be much better equipped to handle the challenges and compete more effectively.
Alis Sindbjerg Hemmingsen is a Thought Leader at Optilon. She has more than 25 years of experience within the Supply Chain field. Optilon has a long track record helping companies achieve competitive advantages by improving Supply Chain performance. Learn more about Optilon here.