While supply chain visibility has gained attention in the last years, temperature management has been relevant for the last decades. In our blog series, we describe the why, how and what of an integration between the two and the benefits one can gain from that. In this second blog post, we will look at the HOW.
Supply Chain Visibility is often translated as “having all the data”. But having all the data and not being able to use, analyse, prepare, share, or bring them into a relevant context, will not result in any benefits. Visibility data should therefore be aligned to consequently increase quality and efficiency in temperature management.
The following figure highlights three layers that need to be considered in order to realize this vision: Data collection is at the foundation. From here, the single pieces need to be connected into a context. On top we describe how control on the supply chain will be executed.
Let’s take a closer look at each layer:
For collecting the data, we include the easily accessible application systems used by your own supply chain. In addition, we extend the collecting to external services, and to the huge amount of data provided by sensors. It is also possible to include an unlimited number of partners, including the partners’ partners and so on.
Here, the challenge is to collect the data from various sources, technologies, formats, or standards. In a first approach, it should be clarified which data are essential for the defined objective. Later it will be necessary to establish a service that enables us to provide connectivity routinely over all sources and to couple those to further sources.
As long as data points are not connected to each other, the huge amount of data alone does not provide value.
Connecting data can be done in a very direct way, for example by receiving a tracking number for an outbound parcel once it has been created to follow the handling up to the parcel’s delivery.
And connecting data can also be done in a more complex and proactive way. Think of a large pop festival being announced. If a standard route uses the motorway in that region, you will better plan a different route on that specific day. You would need an earlier departure to compensate the detour and the warehouse would need to plan an earlier commissioning compared to their usual routine. So, you would react on news that on first sight does not seem of importance for your business, long before any congestions are reported in the traffic news.
If you think of the huge amount of data, connections will not always be as easy. So, on the one hand it should be very clearly defined, which data should be put in which context to fulfil your informational requirements. On the other hand, your technology toolset should have some powerful options for analytics, machine learning, artificial intelligence and further. Once you have the data, you would like to use them in every possible way.
Controlling is the highest and most value-adding level of our activity flow. Here, we earn the benefits of realizing the integration of temperature management with supply chain visibility. Knowing if and where you currently lack control or what causes this lack, helps you to use the additional insights in the correct manner.
First of all, you may describe exceptions which occur from time to time, like the outage of a truck. You may describe some rules, how to react once an exception is detected. In some scenarios this would lead to more automation, like an automated triggered tendering process.
Also, preventive actions can be established that are triggered by real-time data or simulations. A machine learning algorithm would help you to understand the most effective reaction from similar situations in the past and the applied reactions.
Artificial intelligence may even be used to predict a situation from recognizing patterns upfront. Preventive actions, such as re-routing trucks on Friday afternoon would help to avoid situations, like being stuck in commuter traffic. On a tactical level, platforms would ensure direct access to all data for the automation of routine processes or the continuous planning and optimization.
Therefore, the distinct approach chosen for integrating temperature management with visibility is a two-way process: top-down, translating a vision into a concept for the three described layers, which results in concrete action fields for the individual requirements. Bottom-up, collecting the corresponding data, connecting them to obtain better insights, and use them for improving control of the supply chain.
To find out more about WHAT action will integrate temperature management with supply chain visibility, read our third part.