Machine Learning has proven to be one of the strategic technologies for the wide and complete analysis of data, greatly improving forecast accuracy. Excellence in Supply Chain management requires smart optimisation of millions of decisions.
By combining Machine Learning software + experts, your company gains access to the most advanced forecasting technology, and thanks to the experts, your company gains access to expertise and dedication to your team using their programmatic capabilities to take into account all of your Supply Chain constraints: container shipments, minimum order quantities, shelf space capacity, all your historical data, ordering or manufacturing constraints, all economic drivers, combining business process analysis, training, and software to give you real-time visibility into performance, the ability to track compliance, making the best possible decisions based on your ROI (return on investment). The whole process requires full robotisation so that it can be operated at any scale, freeing up the company’s teams from routine tasks.
For inventory technology to be truly effective, it must be autonomous. Machine Learning increases efficiencies by automating existing processes including automated data collection, workflow automation, schedule prioritisation, alerts, performance management, and integration with existing systems. It adapts to the complexity of your operations, easily scaling from a single location to enterprise wide.
Each Machine Learning software has its own characteristics: some deliver better forecasting using probabilistic forecasting technique to drive better outcomes; some others require deeper math, using open source database techniques; others are autonomous advanced yard and warehouse management systems to gain visibility, like autonomous drones which manage operations more efficiently, or perform a particular mission, such as scanning the inventory in a certain rack area. Using vision and mapping software drone guide itself around the warehouse safely, delivers scalable cloud-based solutions through extensive Internet of Things (IoT) sensor network that includes GPS and cellular technologies to capture and share real-time information via web. Some Machine Learning use the Internet of Things (IoT), and Blockchain with open source database technique to track patterns and trace products.
You can import all the relevant data into your Machine Learning account in just a few clicks; files can be uploaded through the web or through other protocols to handle very large quantities of files in various formats, or even scale up to extremely large retail networks if needed. You can build a complete Supply Chain where all the knowledge is auto-maintained and only needs human intervention occasionally.
What to look for an efficient Learning Machine: First, meet with your team to define the quality and compliance requirements of your service delivery operations and how this integrate in your organisation as a whole. Then, design and deliver training to your team on the topic of quality control and surveillance, and finally, customise service delivery compliance software, empowering your management team to schedule, approve, monitor, and report on every aspect of quality assess.
Summing up: Data maintenance can be a difficulty and is blocking many companies from getting the full ROI out of their S&OP. Machine Learning and Predictive Analytics in general are already bringing a lot to S&OP via software and will probably bring even more benefits in the future.
Dave Food