We’re told that understanding our data is the key to a more productive workforce, more efficient resource management and faster/more accurate warnings when something is awry in operations. That’s true—to an extent.

Before we can really benefit from the massive streams of data being unleashed in our systems every hour of every day, we have to define exactly which conditions we want to better manage, and implement targeted systems that make it possible. Cities and large organizations are generally swimming in unstructured data that can make it difficult to find the answers they need, when they need them. Developing systems to measure key performance indicators (KPIs) within data can help to design better alert settings and improve productivity.

Cities and organizations both have a very clear need for incredibly fast and accurate alert settings that will inform key team members when the system has been physically compromised. For cities, implementing alert settings and streamlined operations that can warn constituents and prepare infrastructure for an incoming natural disaster is imperative. For example, cities can customize a KPI measurement approach to develop a tornado warning system that automatically applies a rating based on the Fujita Tornado Intensity Scale and instantly sends out clear, actionable alerts for how and where to prepare people and (if possible) protect vital infrastructure like water systems.

For private-sector businesses, the needs for alert settings are generally less dire, and more related to being able to make decisions that improve efficiency and productivity. A multilayered resource measurement system Element Blue installed at the Desert Mountain golf community in Arizona uses alert settings that tell course managers when temperature and moisture measurements in the system are out of range (in the “red zone” for KPIs). Being able to see those alerts and act quickly to correct the conditions saves course managers incredible amounts of time, energy and money repairing and replacing the greens that their business depends on.

So, all you have to do is define the KPIs you want your system to monitor, and then get it up and running, right? Unfortunately, that day is still a ways off. Monitoring KPIs within natural resources such as water or soil can be challenging due to their inherent complexity.

Water alone has conditions like salinity and bacteria that need to be constantly monitored, and the data that results can be difficult for a non-expert to understand. Before implementing a water-monitoring system and expecting alert settings to streamline your operations, take the time to really pinpoint definitions of what you need to identity and how that information needs to be presented to team members who will ultimately be in charge of making decisions based on that information.

After you have defined the conditions you need to develop alert settings for, consider moving toward instrumentation—specifically, the use of highly sophisticated sensors — for data collection. If at all possible, start by measuring several seasons of data to define what is “normal” for your system. Sensors are incredibly accurate at measuring KPIs, and can automatically move your organization toward a path of greater productivity and more efficient operations.

The key here is to work with a company like Element Blue that can develop a system to simplify the data coming from the sensors so your team members don’t need to be experts to understand when KPIs are being reached. For example, at Desert Mountain, you don’t have to be an agronomist to understand that you need to leave the sprinkler system on longer because the soil is dry.

The long-term financial savings associated with good management practices and avoiding expensive repairs make the cost of a system with accurate alert settings a worthwhile investment.

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