- Data Analytics executive Eskigun flags supply chain optimisation driven by IBM Cloud Pak for Data.
- IBM uses virtual conference to launch new Cloud Pak and Watson capabilities.
IBM’s Cloud Pak for Data solution is being used to optimise the T‑Mobile US (TMUS) supply chain, according to Erdem Eskigun, the operator’s Director of Supply Chain Data Analytics & Operations Research. Eskigun highlighted the deployment as part of IBM’s first ever all‑virtual Think Digital conference.
Three new capabilities were launched by TMUS, building on existing functions of three IBM solutions: Cloud Pak for Data; Cloud Pak for Automation; and Watson Assistant. Eskigun flagged that TMUS was using the former to ensure a “more responsive and agile supply chain, while saving costs and delivering superior customer service”. The data and artificial intelligence (AI) platform is bringing together disparate databases from across TMUS to better optimise operations. “Now, we can go from idea inception to delivery to business users much quicker”, Eskigun added.
IBM and Deutsche Telekom (DT) have worked “side by side” at the former’s Watson IoT Centre in Munich, where DT set up a “Telekom IoT innovation space” in January 2018. There have also been hints at future tech moves with Watson AI from Telekom Innovation Laboratories (Deutsche Telekomwatch, #70 and #89).
AIOps on RedHat OpenShift
IBM also used the May 2020 Think Digital conference to launch Watson AIOps, a new AI build on Red Hat OpenShift, capable of running across any cloud and primed for integration with a large ecosystem of partners. T‑Systems has in recent years extended its AppAgile enterprise platform‑as‑a‑service offering on the same OpenShift platform, and its implementation of Lenovo’s Open Cloud Automation solution is OpenShift compatible (Deutsche Telekomwatch, #65 and #93).
Watson AIOps is pegged as a solution to make chief information officers’ increasingly complicated jobs easier, by enabling automation of IT infrastructure in a bid to reduce costs and increase resilience to service disruptions. Specifically, the technology detects and diagnoses IT anomalies in real time, enabling teams to respond quickly.