Data is king in our digital world, and the Connected Supply Chain Cockpit harnesses your data so that you can predict the future with greater certainty: what customers will order and when; how much inventory is needed and where; as well as the timing of maintenance and replacement parts. It also means more transparency and massive savings by reducing the time spent on retrieving information. Through technology and data, you finally have more control over your supply chain from beginning to end.
Supply Chains in Real Time Save Time and Money
A tarpaulin truck is carrying humidity-sensitive goods to your production site. Schedule and quantity deviations are identified and revealed at an early stage based on real-time data transmitted by Bluetooth Low Energy devices that accompany the goods. The devices are paired with the relevant delivery data so that further analyses can be executed, and these devices also transmit conditions such as humidity, temperature and light to an onboarding unit. The onboarding unit – found in newly produced trucks and easily installed on older ones – transfers this information to the cloud where the data is interlinked with other data and becomes part of the analysis for estimating arrival time (ETA) based on traffic and weather conditions. It can recalculate stock coverage and initiate counter measures if the stock coverage drops under a certain defined threshold. Also, as the devices record conditions, it would identify humidity in the tarpaulin truck as it drove through rain. As the tarpaulin truck is carrying humidity-sensitive goods, the freight may be affected and not useable, which would have negative consequences for the planned production. Reordering would take several days. The Connected Supply Chain Cockpit identifies the possible reduction in the quality of the goods that will arrive and initiates a new purchase order as soon as the threshold for humidity is exceeded. The early reorder through the connected supply chain drastically reduces the time for the provision of goods in the needed quality.
Furthermore, based on GPS information that is also transmitted when the devices are paired with the delivery, the localization of the goods can be identified. As an example, with the definition of geo fences around a plant, subsequent tasks can be initiated: when the truck is 80 kilometers from its destination, all registration documents can be generated and electronically transmitted to the driver. Considering truck drivers often do not speak the local language, the registration and instruction documents can be provided in the driver’s language, reducing waiting time for the driver.
Advantages of a connected supply chain:
A Digital Twin of Your Supply Chain
Big Data, cloud-based platforms and in-memory processing allow data handling and modelling for a one-to-one copy of an entire supply chain: the digital twin is born. The digital twin is based on operational data and reflects all the specifics of a supply chain. As the system is fed by ERP data, it is always up to date and simulations can be run without simplifications. Comparisons and benchmarks between actual and what-if scenarios are possible on the fly. You benefit from several features:
A Use Case From Chemicals – Cost Cutting in Supply Chains
A major chemical manufacturer was questioning its national distribution strategy. Two business units were operating separate distribution networks in one country. Products and clients were different. How to assess the benefit of merging? The digital twin brought both business units together in one virtual supply chain. Data of daily transport and handling operations were simulated and optimized and as a result, capacity was found sufficient even in a merged and downsized distribution network. The simulation pointed out a two-digit percentage savings potential. Implementation realized the feasibility and savings.
A Use Case From Chemicals – Cost to Serve
A global chemical manufacturer was keen to understand the correlation between order pattern, supply frequencies and supply costs per customer/product. With the help of a digital twin, these multiple dimensions were brought into one model. Simulations showed the cause for cost peaks driven by order pattern. As correlation was obvious and the impact on costs and carbon footprint was transparent, the chemical manufacturer was able to convince his customer to change his order behavior. It was a win-win at its best.
A Use Case From Life Sciences – Carbon Accounting
A large multinational life sciences company used the digital twin approach to reflect the carbon emissions for its fully outsourced transport operations. Interfaces provided ERP data at the transaction level. The ERP data was validated and gaps were closed automatically by applying business rules so that an end-to-end transparency was achieved. Carbon data is now updated and available daily – carbon accounting at its best.