With many of its clients in Europe worried about the impact on their supply chains, Zhou, sheds some light on how manufacturers and retailers can do more to mitigate risks and avoid too much disruption.
The impacts on Chinese businesses
The impact of the coronavirus has been huge to Chinese business. According to official data, Chinese exports in January and February fell by 17.2% compared with the same period last year.
For one of FuturMaster’s beverage customers, sales in February were down 80% compared to last year. For a fashion client, it was only able to achieve about 30% of like-for-like sales thanks mainly to online, which has remained relatively resilient.
There still remains a lot of trepidation around consumer demand. Short-term demand from end-consumers has fallen sharply. And due to so many people being quarantined at home, the geographical distribution of demand has also changed. A lot of demand shifts online.
“During times of such uncertainty, every company needs to make simulations on how demand may evolve and if and how they can satisfy this demand based on their production and warehouse capacity,” said Zhou.
“You also need to closely monitor which transportation routes are cut, or how many workers will be unable to show up at various sites due to lockdown. For many companies in China, the problems were compounded because they don’t have the technologies to support these simulations; so they’re unable to anticipated demand and supply by looking at multiple scenarios.”
On food shortages and empty shelves
Panic buying – where many UK supermarkets have already seen empty shelves from people buying bottled water, hand sanitisers and toilet rolls – and further stock-piling is likely to test suppliers to the limit. Food and manufacturing companies in Europe face many challenges from the impacts of the coronavirus.
However, sourcing materials may not be the biggest problem on the supply side. Companies are also seeing reductions in their production and warehousing capacities due to labour shortages: for instance, when one worker tests positive, the whole team has to be put into quarantine.
Moving products around can turn out to be an issue as well, especially when transportation routes are affected due to border closures. According to a recent McKinsey report, trucking capacity to ship goods from factories to ports in China is at around 60-80% of normal capacity, with goods facing delays of around 8-10 days on their journey to ports.
“During the crisis, companies need to produce more with reduced resources. This is made possible by optimising the production by reducing set-up times. Manufacturers also need to produce more efficiently: having updated demand planning data allows you to produce only what is most in demand and profitable,” Zhou said.
“Anticipating ahead – by doing simulations – enables companies to be better prepared. Being able to react in an agile and efficient way is vital for coping with any crisis situations.”
Case study: Bottled water supplier, China
China consumes more bottled water than anywhere else in the world: around 25 billion gallons a year, according to the IBWA trade association, which accounts for more than a quarter of the world’s volume. And yet, one of the largest suppliers of bottled water to China has been able to avoid severe stock shortages thanks to using sophisticated supply chain planning technology to help the company anticipate and respond quickly to the emergency.
The company has numerous factories it can call upon to change capacity whenever and wherever necessary, based on forecasting of demand and supply capacity. It was also able to determine which were the most important products to prioritise, by taking into account the stock on hand in each warehouse and the available production and distribution capacities.
As it happens, most factories in China were already scheduled to close for a week over the Chinese new year, at a time when many coronavirus cases were threatening to bring Wuhan (where the Covid-19 virus outbreak started) to a standstill. However, shortly before, a team of planners were already busy gearing up and preparing for various possible closures after hearing more and more news of lockdowns in different areas. So it looked at the areas likely to be most affected and where else it could produce, and at what capacity.
The supply chain team learned about the traffic restrictions in various places, using the FuturMaster system to make an updated plan for the supply network. It regularly collected information from local managers to understand and build a picture of where and how many workers were most likely to be available at any given time. It ran simulation after simulation. It came up with a plan A, a plan B, C, and so on. This foresight and planning meant that it was less likely to be taken by surprise and resulted in continued supplies to almost everywhere.
The bottled water company was able to endure the turmoil largely thanks to FuturMaster’s supply chain planning technology and sufficient preparations to allow it to model various different scenarios and come up with the best solutions. For instance, by shifting production capacity to different locations and planning ahead for change, it was able to supply enough goods to cope with factory closures and offset transportation problems elsewhere.
“Everything that seems normal everyday becomes totally impossible. For many businesses, you might need to find another logistics network. You have to focus on where’s the best factory that you can produce in and look closely at costs and feasibility. All the normal variables that supply chain planners use on an everyday basis become uncertain and questionable. But you can act with foresight to mitigate risk.
“In times of panic – and against a backdrop of empty shelves – some digital technology can be used to avoid a crisis. Digital technology can help make better decisions afterwards and prioritise things whenever there’s a choice to be made,” added Zhou.
AI and machine learning
“In times of extreme uncertainty and volatility in demand, digital technology can certainly make sense of a multitude of data, quickly and optimally. This requires a supply chain planning tool that’s highly flexible and data-driven. Ideally, you need to be able to manage as many variables as possible to get more accurate forecasts on demand and optimise the supply accordingly. It’s something that would normally take days to do manually. And a machine is often much better than humans at crunching numbers and making decisions from wades of information.”
