Location analytics is nothing new. In fact, business groups and analysts have been able to use most tools to overlay various visualizations on geographic maps for some time. The constraint for business users, however, is that many tools are restricted to maps provided by the tool comprising countries, or states, or street maps, but usually leveraging standard map tiles only. Applying spatial data with a heat map either requires another tool, plugin, or some coding to get it going—certainly out of scope for the standard business user.
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There is a need to take business user spatial analytics a step further. There are many use cases that require a custom map that would never be provided by the analytics tool vendor, nor a mapping tile provider (for example, Google or OpenStreetMap). These custom maps represent something unique to the organization and have no relevance to other businesses. The simplest example of such a map is the floor plan of your business, whether it’s a hospital, school, casino, or a retail floorplan like the graphic below.
How you've laid out your space may be based on your experience in the industry and best practices, or you may have just inherited it that way. You might even have tweaked the layout based on pain points you’ve experienced—like moving a particular shelving unit because it was obstructing natural foot traffic around the checkout area. But this is a reactive approach to a problem that has already manifested itself and potentially had a financial impact, like when customers walk out of your store because the over congestion at checkout creates an unacceptable wait time. How can store layout and planning be more strategic? How can you improve the physical layout of your space to be more optimized, comfortable, or lucrative?
Oracle Analytics provides the ability to load your own custom map layer. In the retail example above, that would be the supermarket’s floor map. After capturing data of people’s movement through the store via Internet of Things (IoT) devices like Wi-Fi, Bluetooth beacons, or cameras, we can plot time spent at each point in the store as an overlaid heat map shown in the graphics below. This displays the lowest traffic areas in blue with high traffic areas in red tracked over time.
It becomes very clear that our store is quite busy during the breakfast rush and is relatively sparse after lunch. Also, some aisles appear consistently busier than others. Both of these findings lead us to actionable insights. For example, we should consider a different checkout area layout so that we can ensure better social distancing during those busy periods. Also, consistently busy aisles with popular products should be more evenly distributed throughout the rest of the store. This is not only to promote better health and safety for customers and staff, but dead areas in stores aren’t generating revenue.
Location analytics technology is more important than ever during the COVID-19 pandemic. Social distancing is forcing retailers, gyms, and restaurants to think differently about their physical layouts as they try to run the business as optimally as possible within mandated guidelines. For retail, it’s about optimizing your floor layout for directional foot traffic and ensuring that usually congested areas are reconfigured for social distancing. Gyms need to position equipment at safe distances and track how individuals’ workout habits have them moving around and between machines at different times. Restaurants have moved to outdoor dining but need to position tables correctly to allow patrons and wait staff to be safe during service. Mapping the foot traffic of people through your space over time quickly highlights areas that become overcrowded and require some modification to your process to ensure better distancing and movement through that space.
From a healthcare worker, I heard a real-life story about how floorspace analytics had positive impacts not only for safety but for the hospital’s finances as well. On a hospital floor, a project was started to analyze nurse foot traffic on an average day. Optimizing the layout of the nurses’ station and routes for regular rounds can have significant positive impacts. Monitoring nurses’ movements throughout the day led to changes and creating new walking routes, previously blocked by desks, that effectively saved nurses time getting from point A to point B. That in itself was a win; however, there was another big unexpected benefit. Due to the previous long walking rounds, nurses tended to carry more medications for multiple patients to not have to extend their walking by continually returning to the pharmacy. As such, medications would be mislaid during those trips. With the new optimized layout, nurses only had to carry what was required for that specific trip and the unexpected result was a significant reduction in lost medications.
This type of spatial analytics isn’t new. Some tools just require special plugins or coding or IT to build out those graphics. Like most of these tools, Oracle has it’s own Spatial Studio for more advanced analysts with more demanding spatial requirements. For standard business users, however, Oracle Analytics enables the creation of compelling spatial visualizations that are as simple as building a pie chart. Spatial visualizations that expose patterns and trends that are otherwise impossible to see with other visualization types help spark new insights and drive process improvements across industries, businesses, and organizations.