With multiple departments in various functions contributing to the success of a business’ supply chain, it can be a time-consuming and arduous task to diagnose problems when something breaks in the process. Information provided by each player may be fragmented and biased by the individuals obtaining the information, and piecing together an answer from these sources may take valuable time that could have been spent fixing the problem. After weeks of effort, the problem may have already passed, or identifying the root cause may not actually guide any action toward improving the process for the problem identified or future problems like it.
An automated root cause analysis system brings several advantages that will help an organization detect issues early and address problem areas in the supply chain efficiently. We consolidate data to standardize this process across the organization, minimizing function-specific bias. We then use advanced analytics tools such as machine learning, business logic driven algorithms, and deep learning to pinpoint root causes of failures. We communicate these insights through intuitive reporting and visualization tools, putting real-time (or near real-time) findings at the business user’s fingertips with the appropriate technology stack.
Opex Analytics has provided solutions for measuring and tracking end to end performance, allowing companies to detect and diagnose performance issues early enough to guide action and adjust for problematic instances. Automating frees up the resources that would have been used to diagnose problems so that this bandwidth can be used to address and fix the problem instead.