I have a Corvette that I like to work on for fun and relaxation. It gives me an excuse to learn something new and an opportunity to hone my troubleshooting skills. It can be a fun way to spend a few hours on a weekend.
A few weekends ago I was looking for a few parts for a small project. This was spur of the moment and really didn’t need to be done now (as the car will be stored soon for the winter). I found the parts I needed from a single company, but then something strange happened.
This website had my address, knew the two parts that I wanted, but failed to make the process easy and almost lost a sale. I needed to manually check five different store locations to see if they had both parts. In this case two of the five did. One store was about 5 miles from my house and the other about 20 miles away.
Just think how helpful it would have been for this website to use the data available (i.e., inventory and locations) and present me with the two options or better yet default me to the closest store and note the other store as an option. Using spatial features this would be extremely easy to implement. It’s the equivalent to the “Easy Button” that one office supply uses in their commercials.
Now, take this example one step further. The website makes things quick and easy, leaving me with a very pleasant shopping experience. It could then recommend related items (it did, but by that time I had wasted more time than necessary and was questioning whether or not I should start that project that day). The website could have also created a simple package offer to try to increase my shopping cart value.
All simple things that would generate more money through increased sales and larger sales. It would seem that this would be very easy to justify from both a business and technical perspective, assuming the company is even aware of this issue.
I frequently tell my team that, “People buy easy.” Help them understand what they need to accomplish their goals, price it fairly, demonstrate the value, and they make the rest of the sales process easy to complete. This makes happy customers and leads to referrals. It just makes good business sense to do this.
So, while geospatial technology might not be the solution to all problems, this is a specific use case where it would. The power of computing systems and applications today is that there is so much that can be done so fast, often for reasonably low investment costs in technology. But the first step getting there is to ask yourself, “How could we be making this process easier for our customers?”
A little extra effort and insight can have a huge payoff.
In an earlier post I mentioned that one of the big benefits of geospatial technology is its ability to show connections between complex and often disparate data sets. As you work with Big Data you tend to see the value of these multi-layered and often multi-dimensional perspectives of a trend or event. While that can lead to incredible results, it can also lead to spurious correlations of data.
First, let me state that I am not a Data Scientist or Statistician, and there are definitely people far more expert on this topic than myself. But, if you are like the majority of companies out there experimenting with geospatial and big data it is likely that your company doesn’t have these experts on-staff. So, a little awareness, understanding, and caution can go a long way in this type of scenario.
Before we dig into that more, let’s think about what your goal is. Do you want to be able to identify and understand a particular trend (reinforcing actions and/or behavior), or do you want to understand what triggers a specific event (initiating a specific behavior). Both are important, but they are both different. My personal focus has been on identification of trends so that you can leverage or exploit them for commercial gain. While that may sound a big ominous, it is really what business is all about.
There is a common saying that goes, “Correlation does not imply causation.” A common example is that for a large fire you may see a large number of fire trucks. There is a correlation, but it does not imply that fire trucks cause fires. Now, extending this analogy, let’s assume that in a major city the probability of multi-tenant buildings starting on fire is relatively high. Since they are a big city, it is likely that most of those apartments or condos have WiFi hotspots. A spurious correlation would be to imply that WiFi hotspots cause fires.
As you can see, there is definitely potential to misunderstand the results of correlated data. More logical analysis would lead you to see the relationships between the type of building (multi-tenant residential housing) and technology (WiFi) or income (middle-class or higher). Taking the next step to understand the findings, rather than accepting them at face value, is very important.
Once you have what looks to be an interesting correlation there are many fun and interesting things you can do to validate, refine, or refute your hypothesis. It is likely that even without high-caliber data experts and specialists you will be able to identify correlations and trends that can provide you and your company with a competitive advantage. Don’t let the potential complexity become an excuse for not getting started, because as you can see above it is possible to gain insight and create value with a little effort and simple analysis.
Two years ago I was assigned some of the product management and product marketing work for a new version of a database product we were releasing. To me this was the trifecta of bad fortune. I didn’t mind product marketing but knew it took a lot of work to do it well. I didn’t feel that product management was a real challenge (I was so wrong here), and I really didn’t want to have anything to do with maps.
Boy, was I wrong in so many ways. I didn’t realize that real product management was just as much work as product marketing. And, I learned that spatial was far more than just maps. It was quite an eye-opening experience for me; one that turned out to be very valuable as well.
First, let me start by saying that I now have a huge appreciation for Cartography. I never realized how complex mapmaking really is, and how there just as much art as there is science (a lot like programming). Maps can be so much more than just simple drawings.
I had a great teacher when it came to geospatial – Tyler Mitchell (@spatialguru). He showed me the power of overlaying tabular business data with common spatial data (addresses, zip / postal codes, coordinates) and presenting the “conglomeration of data” in layers that made things easier to understand. People buy easy, so that is good in my book.
The more I thought about this technology – simple points, lines, and area combined with powerful functions, the more I began to think about other uses. I realized that you could use it to correlate very different data sets and graphically show relationships that would otherwise extremely difficult to make.
Think about having access to population data, demographic data, business and housing data, crime data, health / disease data, etc. Now, think about a simple and easy to use graphical dashboard that lets you overlay as many of those data sets as you wanted. Within seconds you see very specific clusters of data that is correlated geographically. Some data may only be granular to a zip code or city, but other data will allow you to identify patterns down to specific streets and neighborhoods. Just think of how something so simple can help you make decisions that are so much better. The interesting thing is how few businesses are really taking advantage of this cost-effective technology.
If that wasn’t enough, just think about location aware applications, the proliferation of smart devices that completely lend themselves to so many helpful and lucrative mobile applications. Even more than that, they make those devices more helpful and user friendly. Just think about how easy it is to find the nearest Indian restaurant when the thought of curry for lunch hits you. And these things are just the tip of the iceberg.
What a lucky day it was for me when I was assigned this work that I did not want. Little did I know that it would change the way that I think about so many things. That’s just the way things work out sometimes.