Is Your Call Center Turnover Rate High?

We talk to a lot of call center agents, and their job is stressful. Statistics bear this out, as Call Center attrition rates are among the highest of virtually all professions. Attrition rates are averaging anywhere from 30-45% annually, depending on what study you read.

RevTwo AI can help mitigate against high attrition rates in the call center. How? Some examples:

Problem #1: Agents spend an inordinate amount of time just trying to initially understand the customer’s problem. When a call comes in, how much time do your agents spend trying to figure out the status of the machine, what its software version is, when was the last PM, etc? In the meantime, the customer is down and frustration is building.

Solution: RevTwo AI gets data from the product and/or the operator, and can automatically assess this information in seconds and communicate it to the agent. This frees up the agent to spend more of their time on tasks that have an impact on the customer. Making customers happy motivates agents to do better.

Continue reading “Is Your Call Center Turnover Rate High?”

Why not AI instead of an IoT Platform?

Many OEM’s are struggling with IoT. From my perspective, if you have more than 25% of your devices connected to the Internet and under management, you are doing quite well compared to everyone else.

In addition, OEM’s have come to an IoT crossroads today. Many are faced with the challenge of migrating from their current IoT platform, which they’ve been using for years, to another one.  Others are earlier in their journey and are trying to make sense of the number and disparate quality of other IoT platforms that are out there.

Continue reading “Why not AI instead of an IoT Platform?”

There are many different ways to utilize RevTwo’s AI. Even if your device isn’t connected. Even if you can’t access a smartphone.

We just finished our first experience with exhibiting at Field Service USA. It was a great experience and we met a lot of companies interested in our technology.

We showed a demo at our booth of one of the ways to use our AI. For an unconnected device, we install a special script which creates a dynamic QR code showing the status of the device at any point in time. We call this an “Issue Fingerprint”. When there’s a service event, the user selects a function on the device that displays the QR code, then scans the code with a mobile device and submits it to the AI in the cloud, which returns a root cause and solution to the mobile device. You can see a simple demo of how this works here.

Continue reading “There are many different ways to utilize RevTwo’s AI. Even if your device isn’t connected. Even if you can’t access a smartphone.”

Are You Still Having to Look at Log Files?

I was talking to a customer last week about the workflows they use when a customer contacts the support organization for service.

The most common workflow I see is something like this: customer calls the help desk, the agent asks a bunch of questions, and if they can’t resolve the issue then the agent gets a specialist or an engineer involved. They may open a remote access session to connect to the device (IF it’s connected…) If the problem still can’t be resolved, then they dispatch a field service engineer to the customer. While onsite, the engineer either triages and resolves the issue on their own or they talk to their own help desk to help get things sorted out.

This particular customer said “we don’t necessarily do that. If the help desk can’t resolve the issue, then we ask the customer to send us a set of log files for us to analyze.” Then if they can identify an issue through the examination of these files, they dispatch the engineer.

Going through log files is time-consuming and complicated. You have to look at the files sent to you by the customer when there’s an issue and then you have to compare those files with other log files that represent a healthy machine.

Continue reading “Are You Still Having to Look at Log Files?”

Takeaways from Field Service Medical

Last week I attended this annual event where there were approximately 100 field service executives from medical device companies.  The event was 2 ½ days long and included interactive sessions on everything from remote service to retaining service techs (a bigger issue than you’d think!).

From my perspective, these were the main IoT topics that dominated the event and my thoughts on them:

Continue reading “Takeaways from Field Service Medical”

ATTENTION RADIOLOGISTS: AI Is Not Going To Replace You Anytime Soon

I read this article in IoT World about connected health trends to keep an eye on for 2019. It talks about use cases for AI such as wearables, patient dashboards, surgical robots. It talks about some VS guy who a few years ago said that AI can do 80% of what doctors can do and that radiologists would be obsolete by 2022!

The overall progress of AI adoption in healthcare has been really slow. It seems to me that so many companies are trying to develop AI solutions for applications and use cases that are just too complicated or rely on an ecosystem of other technologies to make them happen.

We need to stick to the basics. No tech project or initiative will be successful unless there’s a business case to drive it. And in healthcare, the obvious business case for AI starts where IoT did: service and support.

Companies trying to deploy an IoT technology so they can remotely support their devices in the field are certainly still facing challenges today. More and more of their end users, particularly overseas, are resisting their attempts to connect to their devices on their network because of security concerns. But the business case for remote service and support still is strong.  Reducing downtime, reducing 2nd service calls, improving MTTR and FTF rates still translate right to the bottom line for OEM’s and their customers.

Continue reading “ATTENTION RADIOLOGISTS: AI Is Not Going To Replace You Anytime Soon”