The valuable impact of sharing data in times of scarcity

What are the root causes of this scarcity economy?

“We see scarcity taking several forms: there is a lack of raw materials, a shortage of employees and scarce logistics resources, like containers . This is caused by a few factors, the COVID-19 pandemic is the main one. Computer chips are scarce because demand for certain products, like cars, decreased at the beginning of the pandemic. But this was only temporary. The economy recovered, so demand increased. In parallel, COVID-19 measures led to a strong boost in digitalization, resulting in a demand boom for computer chips. But chip manufacturers cannot accelerate that easy. We need more high-tech and this need will only explode in the future. The same thing is happening with special metals.”

“Besides the scarcity in raw materials, there is a personnel shortage. With COVID-19, the demand for personnel increased strongly in some domains, and decreased enormously in others. These heavy fluctuations, combined with the illness, quarantine rules and high work pressure, created an enormous impact in the availability of employees.”

“Scarcity also feeds on emotion. Uncertainty and volatility lead to stress and pressure, with scarcity as the end result.”

“For example, we analyzed team sizes at nursing wards (during a pre-COVID period) with fluctuating demand and employee availability. We showed that the periods where the team size was too big was about equal to the periods where the team size was comparably too small. However, the negative feeling and the impact of personnel scarcity was not fully compensated by the positive feeling they had when there were enough personnel. As a result, an overall feeling of scarcity remained.”

What are some of the possible solutions?

“A traditional method to create robust supply chains is using buffers and safety stocks. But if raw materials are scarce, this is not possible. In addition, in industries like high-tech, where continuous re-engineering takes place, buffered components and semi-finished products can easily become outdated.”

“In this complex and continuously changing world, data can guide us. First, create transparency when it comes to scarce resources and elements. What are the available buffers, their characteristics, and dependencies, and how do they relate to end products? Then, answer questions about the expected demand. For example, apply AI/ML to find out what the possible bottlenecks could be, based on historical data. Which slack or shortage can we expect when demand or products change?”

“In this complex and continuously changing world, data can guide us. First, create transparency when it comes to scarce resources and elements.”

“Insights based on data are crucial. Transparency helps you steer the business based on facts and figures. Consider a company in the semiconductor industry, producing expensive lithographic machines. This company sends production plans frequently to its suppliers, so that they can fulfill the required demand. The production plan is stable, but this might not be the case at the component level. As a result, a small configuration change might imply that a certain component is not available, causing production bottlenecks. If the company had access to their suppliers' buffer and capacity data, bottlenecks could be identified earlier in the supply chain. This would allow them to consider alternatives. If their suppliers were to share this information upfront, they can get more clarity for their production schedule and identify where they can be flexible.”

The most important element is to strengthen the relationship between partners in the supply chain. In the literature this is called anti-fragile . When there is pressure on the chain, the chain becomes stronger. In essence, concepts like Lean and Supply Chain Collaboration are based on continuously analyzing and improving the situation. For example, at Zara, purchasing, design, production and logistics teams make decisions together. All the relevant information from stores is shared directly with the entire chain. Every incident is recognized as a learning moment, to make the chain stronger and better.”

“For data to be shared, clear agreements are necessary. Companies must also have the willingness and trust to share data. ”

“This is a service-oriented rather than a dominant way of thinking. In a large scientific study on supply chain collaboration, this social and psychological aspect was mentioned as an important success factor .”

“Next to this, the right legal agreements and technology are required. Blockchain can be a good enabler. There have been successful data sharing applications that use blockchain in the financial sector, and strong opportunities within the logistics area . For instance, Walmart is working on blockchain pilots to enhance their supply chain transparency and track their goods more efficiently.”

“Finally, it can be beneficial to have a neutral party as the orchestrator that collects and shares the data. In the current platform economy, more initiatives in various sectors are popping up. For example, Cantena-X is an alliance between large German car producers and their suppliers. This alliance has set standards for sharing data, which are also used by smaller suppliers. Similar initiatives are taking place in the Netherlands with iShare. In all these initiatives, it is important to define which data must be shared, and how it can be used for better and joint planning decisions across the supply chain. Before involving many parties, the lesson learned here is to start and act small. In the high-tech industries, which are extremely strong in industrial engineering, I am convinced that there are opportunities to collaborate further in the logistics domain.“

What is your opinion about scarcity in personnel and personnel rostering?

“There is a huge peak in logistics vacancies, even employment agencies in this industry are struggling to find people. Creating good schedules has become challenging, since complexity has increased considerably. You have more laws governing working hours, volatility in demand and required resources, and individual employee preferences that are constantly changing. On the flip side, technology has advanced. It’s now possible to predict the required capacity, balance the need and shave peaks, and create employee-centered rosters instead of cyclical rosters. This can be done by applying optimization and AI/ML, while respecting individual employee preferences. Employee satisfaction goes up when you enable them to exchange shifts and provide personalized information. Moreover, when you share data and centralize roster scheduling over departments, you can create more efficient schedules. Flex pools can be used to balance different department needs, before contacting employment agencies.To further increase employee satisfaction, other HR aspects, like education and career planning, are relevant. But applying the right tooling and techniques to create healthy and efficient rosters is already a big win.”

Will scarcity last or will it end?

“Scarcity is here to stay in logistics and many domains, like raw materials and personnel. Collecting and sharing data using a lean and agile approach offers great opportunities. You can create more efficient schedules and plans, and easily consider alternatives. For employees, it also improves satisfaction. In the supply chain, bottlenecks in resources and raw materials can be identified at an earlier stage. So, you can identify ways to avoid them. But, to share data effectively, you need transparency, good leadership and trust. “