Client
Our US-based client, an Elevator Company, is the world's leading company for vertical transportation systems, principally focusing on elevators and escalators.
Our US-based client, an Elevator Company, is the world's leading company for vertical transportation systems, principally focusing on elevators and escalators.
The client has a vast portfolio of two million + elevators and escalators units across geographies, which helps move more than two billion people every day. The objective of the company was to bring value to their end customers by providing -
In addition, the various personas lacked real-time view of data and necessary insights that will help them in their day-to-day operations. The challenges could be listed as:
LTM partnered with an elevator company in new ways to create new outcomes. LTM addressed the need for a disruptive business model for the client, with connected elevator solution. The solution provides real-time status of the unit, data insights and complete visibility of elevator portfolio.
LTM was involved in the development of IoT solution using Microsoft Azure platform. The data stream generated was operationalized into actionable insights with the help of analytics, predictive models and machine learning algorithms
More than 200,000+ connected elevators monitored by end of 2020 across the US, EMEA, China and Asia Pacific.
This solution aimed at keeping the field technicians a step ahead in monitoring the health of an elevator and predict the need of maintenance to reduce frequent failures and avoid unnecessary maintenance visits. The cloud-based advanced analytics solution leveraged the use of sensor data, service data, alarm and events to predict unfavorable incidents for proactive response and faster resolutions.
Democratization of the IoT data enabled the stakeholders to take decisions and not depend on the experts or technician visit all the time. Making customer service representative aware of the elevator operational status, helped avoided dispatch of technicians on false alarms. This resulted in saving service call cost by avoiding unnecessary truck rolls and saving the technician’s time. Additional service calls were eliminated by predictive maintenance. Improvements in remote intervention and remote troubleshooting further reduced the visits and thus improve efficiency.