General context

This project is named after Uptime, a lift maintenance company that prides itself on predictive maintenance. Each lift, no matter the manufacturer or the model, has a great amount of sensors for monitoring the state of the lift at all times (going from simple information like “the doors opened at 3:35PM on floor 6” all the way to minute details about components malfunctioning or any anomaly of the sort). All that information is relayed to the motherboard of the lift for later consultation by a lift maintenance engineer.

Normally, a lift maintenance engineer comes to the site of a broken down lift, accesses that stored info and figures out the next steps from there. Uptime however has developed a connected device, plugged at all times into the lift’s motherboard and connected to a 4G antenna, that allows lift engineers to access that data and know what is going on with a lift from their smartphone without having to physically move there to check.

This allows lift maintenance engineers to optimise their breakdown interventions. Or even better: through pattern detection algorithms, possible breakdowns can be detected before they can happen and be prevented.

After developing that device and successfully using it for their own maintenance operation, uptime started renting their technology to other lift maintenance SMBs, in order to democratise predictive maintenance.

Problem assessment

After an extensive amount of user research and field study to understand how lift maintenance SMBs work in terms of process, what pain points they face in their field of work and what’s important to them, one feedback was clear: communication with their clients (co-owners associations, facility managers etc..) needed much improvement.

With no real time data on the status of their fleet of lifts, customer support agents are unable to help clients on the short term, and most of the activity reporting is done manually in the most tedious way.

Through uptime’s IoT device, most of that key information can be proactively transmitted to end clients, give customer support agents the tools they need to answer their client’s questions efficiently, and activity reporting can be automated.

Definition

Any solution to this problem should be aimed at two profiles:

SMB employees who need to:

• Check information relating to the IoT device and their fleet’s status

• Automatically generate activity reports for their clients using IoT device data

• Manage notifications sent to their clients through SMS and email (what kind and at which frequency)

• Manage users (end client accounts)

End clients who need to:

• Know what’s currently ongoing with their lift(s) in terms of maintenance activity

• Know exactly what’s been done during past maintenance interventions and visits

• Know when the next routine visit is planned

• Download activity reports

• Manage notifications received through SMS and email (what kind and at which frequency)

• Browse through quotes and bills

• Check information relating to the IoT device

The chosen solution to answer these needs is a platform that encompasses all this data to make it accessible to both profiles. After mandatory steps of defining the structure of the platform through brainstorming and card sorting workshops with our own stakeholders as well as lift maintenance SMBs (our clients), and after many iterations of wireframing what would be the ideal version of that interface and testing it, the result was the following.

This platform is the fruit of many different phases of testing and iterating over a couple months. The final result as showcased above was first story mapped, and got developed gradually from barebone essential features all the way to its final version.