A lot has been written on Business Intelligence and Information Technology. Using data analysis in the decision-making process is common for most medium to large organizations. Organizations are also doing a better job of eliminating silos of data and streamlining the capture and sharing of data throughout the organization. I personally love to see it when organizations become more efficient just by organizing their data and improving their workflows. Conversely it drives me crazy every time I go to the doctor and they ask me to fill out the same information over and over. They even duplicate the data they are asking for over multiple pages! Now the last time I was there they had iPads with a couple of fields already filled in. Now that’s making progress, but something tells me we still aren’t quite there in the health care sector. The real estate industry has historically been a laggard in information technology. This is surprising since when you think about it, real estate is an industry that operates on information inefficiencies. If you have even purchased or leased real estate, then you know what I mean. Think of all the data you must gather to complete a real estate transaction. Who has the advantage here? Someone that works in real estate everyday like an agent or landlord, or a small business owner leasing a space for the first time?
I recently watched an Apple event online where they introduced all the new products. This usually happens in the fall and they live stream these events to get as much press attention as possible. There was something very interesting that I noticed at the beginning of the presentation. They showed the location of the building where the event was taking place and mentioned the name of the venue and city that it’s located in. Now Apple is very meticulous about these presentations and I wondered why they did this. I think they did this because they designed the presentation to have the core elements of a story. People remember stories better than facts. Stories take place in settings; and settings depend on location. I think the location of the building being in San Francisco also helped to reinforce the Apple brand. When you think of adjectives to describe Apple and San Francisco, many of the same words come up: Cool, Beautiful, Expensive, and Diverse. Location brings context to your story. Think of a picture of the Grand Canyon with a dusty winding trail in the middle of the summer. Now think of a picture of Times Square, New York in the winter at dusk. Each place has a group of unique data characteristics based on its location. Now this is all great for a book or a movie, what does this have to do with business data?
Business organizations are trying to solve problems every day to become more successful. Often when these problems involve data sets that contain the aspect of location; groups either skip or get bogged down into how to include location in the analysis. Obstacles can include lack of data and software, or simply the lack of knowledge of the options for integrating location analytics into your organization’s enterprise workflow. This book is designed to prepare you to recognize and take advantage of situations where you and your organization can become more successful through the use of location analytics.
Geographic Information Systems (GIS) are the foundation for location analytics. GIS consists of layers of spatial data that are overlaid to perform analysis and/or data visualization. Dr. Roger Tomlinson (1933–2014) is generally recognized as the “father of GIS.” He developed the first GIS for use by the Canada Land Inventory in the early 1960s during which time he was working as a photo interpreter for Spartan Air Services in Canada. When tasked with identifying the best location for a tree plantation in Kenya, Tomlinson worked with computers to find a solution. He went on to sell this solution to the Canada Land Inventory who assisted the government with land use and land planning. His GIS methods greatly improved the accuracy and efficiency of working on land use projects at the time.
Location analytics is simply the analysis of location data displayed in order to communicate a specific measured result. This analysis can be done on a small scale such as—“What are the demographics of my stores that have the best sales?” Or it can be done on a large scale such as—“Which parcels in a specific state have the best soils and necessary slope for a new large-scale farming project?” Increasingly these projects and platforms are moving from a single analyst or group of power users to enterprise systems that are used by many people in the organization. As these enterprise systems grow so does the complexity of integrating these projects. Having good data to work with makes a huge difference in accuracy of the project, as well as in the time it takes to deliver a completed project.
Paul Amos, previously the Managing Director of the Wharton GIS Research Laboratory at the University of Pennsylvania and with over 18 years of experience with GIS and real estate, defines location analytics as “the study of variables that are pertinent to the success or failure of a real estate location.” And Mr. Amos goes onto say
On an individual level, people use location analytics for where they choose to live. In addition to their preference for the type of dwelling (e.g., Condo, single-family, rent vs. own, etc.), they may consider factors near where they are locating such as access to parks or cultural attractions, school district quality, crime and taxes. Commercial businesses use location analytics to identify concentrations of customers that would most likely purchase their products. They may also be interested in knowing the location of complimentary and competitor locations, traffic patterns and site characteristics. Industrial firms may use location analytics to identify areas with qualified employees based on the company’s human resource needs along with logistics options to move their goods from the industrial facility to the locations where the products are sold. Firms that can take advantage of new and unique databases can gain a competitive advantage with location analytics. I’ve seen growing availability of international demographic databases which can certainly help a multi-national company with their location analytics needs. The precision of these databases is not as detailed to small geographic regions like census block groups in the US or postal codes in Canada. I’m sure these databases will continue to be enhanced and much like a real imagery was 10 years ago, these data will become more commonplace and inexpensive as the adoption rate increases.
The Shopping Center Group, headquartered in Atlanta, GA, has been using location analytics for a while now to find the best locations for various retailers. Working with retailers and landlords alike, The Shopping Center Group is in the business of making the most of location data. As Director of Innovation and Technology at The Shopping Center Group, Gregg Katz says that
I can tell you that what we have learned is that to truly work with, and understand, location analytics you need to understand the movement of the consumer: what is the true trade area of a location, where are people traveling from to get to a location (home/work/other), what times of day does a location get the most visits. Does a retailer want to cannibalize because the net result is better than the current situation? We have concluded that location analytics is a combination of demographics, psychographics (consumer behavior) and understanding movement. Combine this with local market knowledge and you have a winning formula.
Gregg goes on to say
Understanding holes in the market, cannibalization, trends, and so on. As with Landlords, I will again reiterate that all of this information cannot be looked at in a silo. It must be combined with a local market understanding based on “boots on the ground” research. Information is only useful if you use the right information and accurate information. Just because a computer says “it is” does not mean it has taken everything into consideration. Examples include roadwork, retail shifts because of new developments, and so on. That is most often not reflected in location analytics from a data perspective. Location analytics does a good job of showing you what is but does not factor in what’s next without adding a formulaic/algorithmic approach to it and even that can be hit or miss and take years and a lot of money to perfect.
Whatever the size or scale of the project, there are several elements that are key to perform this analysis. GIS software is at the heart of performing and displaying location analytics projects. GIS requires spatial analysis software, location data, and computer hardware to run and share the analysis. The results of this analysis include various outputs such as a map, table, report, interactive web-map, and/or an interactive web-based dashboard that includes any combination of these elements. There are many options when it comes to GIS software and data; the key is pick the software and data that best fits your organization’s goals for the project as well the budget limitations. Keep in mind that sometimes a “point in time” solution might solve an immediate need but does not provide an ongoing long-term solution.
Market and Markets, a leading market research and consulting firm, has determined that the location analytics market is estimated to grow from $6.83 billion in 2014 to $11.84 billion in 2019, at a Compound Annual Growth Rate (CAGR) of 11.6 percent from 2014 to 2019.1 And they go onto say that
In terms of regions, North America is expected to be the biggest market in terms of revenue contribution, while emerging economies such as Middle East and Africa (MEA), Latin America (LA), and Asia-Pacific (APAC) are expected to experience increased market traction with high CAGRs, in the due course.