Use Case Library

Companies who monitor (in real time) tactical and strategic change to identify gaps and discover market opportunities will maintain or increase their competitive edge. Operations managers and senior executives use control towers to get visibility in supply chain operations. By collecting and combining data from a growing number of new information sources like IoT, GPS, and electronic logging devices companies get an additional layer of intelligence across their operations, and across enterprises. Information on production processes, stock levels, shipment and orders can now be tracked to a new level of detail, enabling supply chains to optimize contingency plans by monitoring disruptions, evaluating the impact towards the plan, and acting in real time. Incorporating this type of new data streams into traditional track and trace, S&OP, or supply chain monitoring activities is not straightforward; organizations are looking into data science to open up new options to produce meaningful outputs and to use that output for improved risk mitigating strategies and operational processes to boost their performance when reacting to unexpected disruptions or market opportunities. 99% of the data used in control towers to monitor supply chain information consists of time series data streams. This information can be used in AI/ML to evaluate future behavior, calculate the impact on performance, and act accordingly. Evaluating the potential performance improvement from the introduction of AI/ML with the goal to adapt your operational scripts is not an easy task. Defining the right AI/ML strategy, what ML approach to use, how to train and configure your models and then deciding how to deploy them tends to be a timely and costly project. And then there is also the enormous number of potential uses, scenarios, and configurations of supply chain networks to take in account. Once you choose, configure and deploy your models, you will need to continuously monitor your setup for performance (accuracy) deterioration due to changes in the data sources, changes in supply chain and logistics networks, changes of business models, and last, but not least, the dynamics of your business and industry. Typically, this is covered by having a department of specialists who maintain and optimize these configurations and deployments.

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