Finding hotspots in cold chain logistics by using Design Thinking

You probably don’t think about it, but products and materials that have gone through a temperature-controlled logistics process are something we deal with every day. A cold chain, so to speak.

Cold chain logistics is a complex operation. It involves stringent planning, careful monitoring, and speedy execution without compromising on product quality and safety. Meanwhile, it is hugely dependent on unpredictable variables, with the human being as the biggest risk factor. According to one study on cold chain failure points, 90% of the occurrences are due to human error, with most of the errors happening during handling.

For this reason, many leading companies in industries such as retail, agriculture, and life sciences struggle with getting the processes optimized and lack a well-defined cold chain distribution strategy. Moreover, trends like globalization, increasing focus on product quality, and stricter regulations put upward pressure on the need for efficiency, transparency, and integrity in these cold chains.

So how do we go about these business challenges at Capgemini?

We leverage our Design Thinking capabilities at the SAP Innovation Center to get to a solution that creates value for end users. The benefits of this approach are:

• End users and their needs are at the core of the process and solution
• By using Design Thinking, we leverage collective expertise in a collaborative way
• Ample testing allows us to learn from failure and adjust quickly.

To get a more in-depth look into how Capgemini uses Design Thinking to help our customers begin or expand their SAP Leonardo journey, see this article as well.

In this case, we used the Design Thinking methodology to explore, discover, design, and prototype a set of services and applications that enable cold chain quality managers to make better decisions. By carrying out user research and synthesis, we made sure we were creating a solution that end users will love using.

What really helped us during the Design Thinking process were the constant feedback cycles with users and SMEs to make sure we were doing the right things. Moreover, the earlier in the process you find elements that “do not work so well,” the easier it is to change them.

Through the discover and design phases we found that most quality problems are due to poor handling of the goods. These problems are most frequently discovered at goods receipt. That’s why we opted for real-time monitoring of temperature conditions by utilizing the SAP Cloud Platform and its Internet of Things capabilities.

Furthermore, the solution focuses on shipment preparation, modal choice, route assessments, temperature monitoring, and quality decision assistance. The latter is realized by analyzing vast amounts of data and feeding it to a machine learning model.