Part 5 of 5 >> Use your map to be the central tool when deciding how your service locations are performing, where you need to add locations and more.
Let’s bring back our plain, bubbles and icons visualization we showed you at the beginning of this series and see how much value is waiting to be unlocked, shall we?
Here’s what you need to know about this map:
And here’s what this customer of ours was trying to do:
Their goal was to evaluate their hospital network and develop a plan for their network strategy based on:
We will start our analysis with by taking a look at who is going to which hospital. To do that, we’ll use a spider plot (also known as a flow chart) to see which patients visited each hospital.
Now just in this first view, we start to see some interesting things. This visualization shows a lot of people going past two other hospitals in network to visit Clinicas Mi Doctor. The data compells us to take action and uncover the reason why.
Another thing we can see just by looking at the map is that there are a variety of patients that came to a hospital site for multiple visits.
By using custom popups, we can click on each patient bubble and see data that is within our Qlik dataset. There were two things that the customer discovered from this analysis:
INSIGHT #1 >> A handful of patients went to one location and had to leave and go to a different location to get the service they needed.
ACTION >> Answering questions such as: How can we make it easier for our patients so they only have to travel to one site? Do we need to offer more services at more locations?
INSIGHT #2 >> There are patients going to various sites in a short time period.
ACTION >> Answering questions such as: Could this be a drug user? Could this be someone committing fraud? This was not the goal of the dashboard, but our customer was able to unintentionally identify some of these fraudulence issues and misuse of the system and put a stop to it.
Let’s say you have a company objective and goal to have all your patients within two miles of your hospital (or your store, your restaurant, etc.). We can simply turn on radial plots to see which patients are outside of the target radius.
It’s now easy to visually see that we need another hospital in the northern region to service a handful of patients. We can also compare the visualization above with a heat map to find the location that has the highest density of patients.
Ideally we’ll want to place a hospital in the middle of the northern hotspot. But we can also look to see if a clinic outside our network already exists. To do this, we simply do a google search within QlikMaps to see if there are any clinics in the area. Once we pull in this layer of data from google, we can interact with that on the map like it was our own data to see if it helps achieve our goals.
Finally, we can also pull in data from outside our data source to evaluate the demographics of territories as a separate layer on the map. In this example below, we pulled in open data from the US census to see the median age of the area.
You are now equipped with data-driven reasons to pitch a new location to your boss because you can show with data:
Features Used: radial plots, spider plots, heat maps, search functionality, ESRI integration
Shown in QlikMaps for QlikView
Part 2: Spot A Problem – Take Instant Action
(Instead of jumping from app to app, you can centralize your work flow to your map. Yes… we just rhymed there.)
Part 4: Crime Analysis
(You may not be tracking criminals, but all businesses can use the functions they’re using to visaulize data changes)
You can watch the full webinar to see all the features in action and get tips from QlikMaps product architect, Patrick Vinton OR you can check out these blog posts that will spark your creativity for how to use location analytics to get buisness value.
To thrive with your data, your people, processes, and technology must all be data-focused. This may sound daunting, but we can help you get there. Sign up to meet with one of our analytics experts who will review your data struggles and help map out steps to achieve data-driven decision making.