Last week I wrote about realizing the value of geospatial technology. This requires understanding the ultimate problems our technology will be used to solve for consumers and building action oriented technology to make solving these problems easier for operators.

This week I’ll dig into what building action oriented technology means and what’s required to produce it so we can improve the adoption and profitability of our technology. 

Because value is ultimately realized by people taking action in the physical world to produce positive outcomes, action oriented geospatial technology must be:

  • Meaningful to the people operating it
  • Reliable, and
  • Easy to integrate into physical workflows

While a concert of systems is essential for producing action oriented technology that works for people, in this blog I will focus on how data is the cornerstone of each of these action oriented pillars. Specifically, relevant contextualized data, persistently accurate data, and real time multimodal data. 

Let’s get started with how relevant contextualized data makes technology truly meaningful for those using it to accomplish a job. 

Relevant Contextualized Data is What Makes Technology Meaningful for Users

If given the choice between:

  • an annotated hard copy of final site plans printed this morning or an 
  • an app with a great user interface, AR capabilities, and access to every raw draft of every project plan on or offline… except the one finalized late last night, 

the team responsible for effectuating the plan will pick the hard copy. Every. Single. Time. 

What matters most to the people responsible for doing the work is access to the specific information they need to get the job done. Providing access to relevant contextualized data is vital to developing meaningful action oriented technology. 

Don’t get me wrong, user interface and offline access are important too, and I’ll get to them below, but if the data behind the technology isn’t relevant or contextualized, the technology is little more than an impediment to taking value creating action. 

Relevant contextualized geospatial data is directly applicable and meaningful to the task at hand. In many cases it is recent, if not real time, providing a representation of the physical world capable of informing the actions necessary to produce value in it. Moreover, it is presented and organized in a manner that aligns with the needs of those responsible for acting upon it, including critical context beyond mere raw information. 

This could mean annotated high resolution imagery, story maps conveying change over time, parcel data with easement setbacks, or a simple pin dropped at a location. It all depends on the user and context! And that’s the key.

For example, an Equipment Operator will need access to different data in a different format than a Network Planner. While the Operator may want to zoom out to evaluate the potential impact to the network of shutting off a valve before digging, they will spend most of their time focused on where they need to dig, what they are digging for, and what they need to avoid to prevent damage and hazards. Relevant and contextualized for them will be a picture of what’s under the ground in the specific location they’re working, setbacks, project plans, and other data informing where they need to dig to get their job done to spec. This data must be as recent as possible to ensure the work order is executed efficiently.

On the other hand, the Network Planner will engage larger amounts of data in a more systemic and analytical manner. While there will be a high degree of overlap of the data used to complete each of their jobs, these roles have vastly different workflows and priorities. The Network Planner may not need the most recent information on the specific network component the Operator is digging to fix, because the network design will remain the same. But they do need the most recent zoning and parcel data to ensure cost effective and compliance network designs. 

Thus, developing meaningful geospatial technology is not just about doing cool things with sensors and complex analytical software. It’s about understanding the people who will ultimately use it along the entire value chain so we can acquire and present data that is relevant and contextualized for them. Doing so will improve the adoption and operationalization of solutions driven by geospatial data only so long as the technology is reliable. 

Reliability Stems from Persistently Accurate High Quality Data

It is a feat in and of itself to build an app or platform that works as expected every time someone opens it up to operate it. Whether you’re online or offline, working across time zones, or performing complex spatial joins, it works. This is what many think of as reliable.

This is not what I’m talking about when I say reliable. 

It’s one thing for technology to work as you expect, and another entirely to RELY on it to take action. Reliability to me requires persistently accurate high quality data

While “high quality” is relative to the problem to be solved and the budget available to do so, persistently accurate is less squishy. “Persistently accurate data” consistently reflects the real-world information it represents, without significant fluctuations or errors, irrespective of changing conditions or circumstances making it a dependable resource for decision-making and operational processes. 

Consider a city’s emergency response system. To first responders,”reliable” doesn’t merely mean that the emergency response application opens without a glitch when a call comes in. It means when a call for help is made, they are empowered by technology to act quickly and effectively with the confidence that the data guiding their decisions is accurate.

Imagine a situation where a caller reports a fire emergency at a specific address. The reliability of the emergency response system is not determined solely by its ability to connect the caller with the fire department, but also by its capacity to deliver real-time, persistently accurate geospatial data to the closest engine capable of responding. From up-to-date information about the building’s layout and the location of fire hydrants, to nearby road closures and even real-time weather conditions, persistently accurate data is critical to rapid and effective decision making. Without such persistently accurate data, the response could be delayed, and lives and property put at risk.

When dealing with emergencies and high stakes situations, every second counts. Having access to persistently accurate data ensures that those responsible for acting can make informed decisions rapidly. They don’t need to waste time verifying the accuracy of the information they receive, as they can rely on the data provided. Moreover, if data doesn’t consistently reflect real world conditions, the consequences can be severe. For instance, if the data inaccurately shows a fire hydrant where there isn’t one, firefighters may face a dire situation when they arrive at the scene unprepared.

Persistently accurate data is the linchpin of reliability. It enables rapid and effective decision making aligned with conditions in the real world so users can take value creating action. 

Thus, achieving greater market penetration with our geospatial technology is not just about building functional applications, it’s about fueling them with dependable, persistently accurate data. While this is especially critical in scenarios where lives and safety are on the line, the principle holds true across various domains, from urban planning and environmental monitoring, to land development, energy production, and augmented reality experiences. To build truly reliable systems, we must prioritize persistently accurate high quality data alongside functional features and user interfaces. 

Achieving this level of reliability so our technology can be fully action oriented and operational depends on the seamless integration of various data sources. 

Integrating Spatial Products Seamlessly Into Physical Workflows Requires Real Time Data Gathering from Multimodal Sensors

Today, operators must remove themselves from the physical tasks they’re ultimately responsible for performing to analyze, edit, and input data on digital devices. Have you ever tried to do this on a hot summer day when you’re wearing gloves or sweat drips onto the screen of your mobile device? I have. It can be incredibly difficult, frustrating, and downright dangerous.

Meaningful and reliable technology is excellent, but to be truly action oriented, geospatial technology must seamlessly integrate with physical workflows. AR and VR technology is rapidly evolving to make this a reality and will require real time data gathered from multimodal sensors to drive true business value.  

Seamless integration means eliminating the need for operators to interrupt their tasks to analyze or input data manually. Instead, their technology should proactively gather, process, and present information in real-time, ensuring continuous and efficient workflow. This will require multimodal sensors such as high resolution imaging, LiDAR, GPS, WiFi, radar, thermal, etc. depending on the use case.  

Picture a large-scale construction project, where a construction manager is tasked with ensuring the project stays on track while maintaining a safe work environment. The site is dynamic, with heavy machinery in motion, contractors on-site, material being dropped off and hauled away, and tight schedules to meet. Real-time data gathering and processing is crucial to managing this complexity effectively with technology.

On-site sensors must be deployed to track equipment locations and performance, evaluating the built product relative to spec, and preventing safety hazards. Simultaneously, weather stations provide real-time weather updates and satellites inform not only development progress but also the location of materials critical to staying on track. This multifaceted data stream converges into the construction manager’s interface, offering a comprehensive view of the site’s status without the need to interrupt work or increase risk by stepping into harm’s way.

By integrating data from various sensors, the construction manager can optimize resource allocation. Rerouting equipment based on real-time data, minimizing downtime and improving productivity. Moreover, real-time data enables proactive decisions. If a sudden storm is detected they can adjust work schedules or implement safety measures, reducing potential risks, delays, and budget overruns. Seamless data integration also facilitates communication among project stakeholders without distracting from productive operations. Progress reports and as builts complete with highly accurate measurements are shared in real time with contractors, owners, and suppliers, ensuring everyone is on the same page and aligned with project goals.

For geospatial technology to be truly action oriented, integrating spatial products into physical workflows is not a luxury but a necessity. The ability to gather and harmonize data from diverse sensors in real-time is critical to empowering operators to navigate dynamic challenges, make informed decisions, and keep projects safe, on schedule and within budget without being distracted from their physical tasks.

Conclusion

For most of its history the geospatial industry has built awesome products for technical people. Yet, the future of our industry depends on the awesome convergence of technology enabling action oriented geospatial products capable of seamless integration in operational workflows. While there is a host of supporting hardware and software tech necessary to support such integration, relevant, contextualized, persistently accurate, real time, multimodal data is critical to developing meaningful and reliable geospatial technology. 

Thanks for reading! Sign up for my email list to keep following along!

Or if you want to know how you can start, or improve your data acquisition and production, find some time to talk with this link!