LIA Co-pilot Description
It usually takes a day to an entire week between a KPI going bad, it getting tracked and actioned. Meanwhile, the end-customer experience is adversely impacted. As the customer expectations move towards the world of quicker commerce, the organisations also require a real time service operations management tool.
An engine would monitor pre-defined KPIs against thresholds for all operating objects: rider, hubs, and vehicles. Whenever the KPIs falls out of bounds, an alert should be triggered to the corresponding individual or his manager. These also include machine learning based tracking of leading indicators to predict foreseeable operational challenges.
The engine would also automatically close the alerts once the KPI is back inside bounds. An intuitive incident management UI would enable easy tracking of open alerts and communication within teams.
Key benefits:
Faster issue resolution, enabled by instant problem identification and seamless communication
Unlock management bandwidth, driven by the shift to “management by exception”
Exhaustive KPI tracking of all operating objects, without subjective bias or chances of misses
An engine would monitor pre-defined KPIs against thresholds for all operating objects: rider, hubs, and vehicles. Whenever the KPIs falls out of bounds, an alert should be triggered to the corresponding individual or his manager. These also include machine learning based tracking of leading indicators to predict foreseeable operational challenges.
The engine would also automatically close the alerts once the KPI is back inside bounds. An intuitive incident management UI would enable easy tracking of open alerts and communication within teams.
Key benefits:
Faster issue resolution, enabled by instant problem identification and seamless communication
Unlock management bandwidth, driven by the shift to “management by exception”
Exhaustive KPI tracking of all operating objects, without subjective bias or chances of misses
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