By Bart De Muynck, chief industry officer with project44
As if the last three years weren’t disruptive enough, 2023 will continue to bring more challenges. With supply-chain challenges, there will be new and different costs to consider. Socioeconomic challenges, like inflation, will continue to impact raw-material costs. Labor costs will escalate as workers demand salary increases to cope with the cost-of-living crisis. Geopolitical factors will continue to pressure global economies. Experts are warning about the social and economic impacts of extreme weather events. In addition, there will be more changes to regulatory requirements with scrutiny on sustainability reporting.
As more disruptions affect supply chains, one thing is certain: tomorrow will be nothing like yesterday nor will yesterday’s data be any indication to what next week will bring. Hence, companies need to switch from using historical data to real-time data if they want to plan and execute their supply chains efficiently and attain resilience and agility. Only after relying on the real-time data will companies achieve the velocity they need to stay competitive in their industries.
Superior data leads to efficiency
High-quality data from the entire connected network was previously missing; people had to make educated guesses. Now we have data feeds from supply-chain-visibility platforms in real time with high data quality powered by AI and Ml. This, in turn, replaces “guesses” with informed decisions based on the right data. Where real-time data provided by visibility platforms started with showing where assets were at any time, it quickly evolved to predicting ETAs of the asset with high accuracy.
The value of the real-time data is found in creating more efficient and more automated workflows. As data is evolving from being used for historical reporting to predicting, prescribing and automating, the quality of the data becomes more important and hence the need for AI to clean, normalize and augment the data and even use generative AI to create data points.
Real-time decision making
The value of real-time data has gone beyond transportation as we’ve extended first-mile and last-mile tracking capabilities. However, it does not stop there. The data isn’t just valuable on the execution side of the supply chain, it is being shared with transportation-management systems (TMS) for more accurate and real-time supply-chain execution planning. Real-time data informs supply-chain control towers that combine it with data from other sources, like warehouse-inventory data or order-management systems, to create actions based on broad supply-chain insights. This insight helps companies go from simple linear supply-chain execution to real-time supply-chain decision execution.
More recently, we have identified the value that real-time visibility data provides to upstream planning systems for sales and operations execution (S&OE), retail forecasting or demand planning. As historic data is no longer enough to predict the future, real-time data and predictive data from visibility platforms is needed for high accuracy of supply-chain planning and driving accurate supply-chain execution.
Supply-chain management applications are like cars, comparable to high-performing sports cars with loads of horsepower. However, even the top performing car still needs a reliable fuel source. Data is the most reliable fuel we have to maintain a sound supply chain. The purer the fuel (meaning the higher the quality of the data), the better the cars perform. Formula 1, for example, has transitioned from a sport about the best car and the best driver to relying heavily on real-time data to forecast the best strategy planning to win a race, often by a fraction of a second.
The supply chain requires strong partnerships between visibility platforms and supply-chain planning providers to maintain unified solutions, data and applications, all to power the high velocity supply chains of the future.
