Cutting operational costs with remote monitoring

In our last article on the value of trending data for performance prediction, we talked about how automated remote monitoring works to provide real-time and historical data that can be mined to determine trends in performance and insights into the future health and longevity of battery installations.

Here, we’ll focus on how that trending data results in a strong ROI for remote monitoring systems by cutting operational costs in three main areas: decreased maintenance costs, increased battery life span, and proactive treatment of potential issues.


Decreased maintenance costs

While installing even an affordable remote automated monitoring system like PBT’s remote battery monitoring system (BMS) is more of an initial investment than the quarterly readings that are traditionally performed when battery installations are manually tested, many remote systems pay for themselves in under two years.

Additionally, the availability of consistent, accurate data eliminates wasting resources on unnecessary maintenance, providing a pathway for more strategic and efficient allocation of funds.

Increased battery life span

When battery installations are continually and accurately monitored, two things happen that help maximize life span. First, insights garnered from trending data decrease unnecessary testing which can, in itself, be intrusive and negatively impact battery capacity immediately following testing and even overall life span.

Second, the trending data that is collected via automated remote monitoring allows for early detection and remedy of potential problems. Sometimes this means preserving the life of healthy batteries in a string by replacing single faulty batteries as they are discovered; in other instances it may involve the third main cost-saving attribute of automated remote monitoring: proactive treatment of potential issues.

Proactive treatment of potential issues

Perhaps the greatest value of trending data is that it allows organizations to be proactive instead of reactive. Instead of responding to a failure once it occurs—including handling the financial fallout of interrupted operations—organizations utilizing automated remote monitoring systems gain the insights needed to catch issues either before they occur or in their beginning stages.

When trending data indicates an issue is likely to take place, proper action can be taken to avert it so that operations continue seamlessly and efficiently. Trending data also positions organizations to troubleshoot, identifying any issues that do occur in their nascent stages rather than waiting for the next quarterly manual test, by which point the problem could have had months to worsen.

The value of trending data in predicting and helping mitigate the risk of the disruption to critical operations caused by battery failure coupled with automated remote monitoring systems’ versatility, scalability, and affordability makes them a sound financial choice for organizations across a range of industries, paying for themselves in a matter of months and cutting costs along the way.

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