My Take on Data Analytics in Recreation
Over the past 4 months, I have started working towards my Masters of Business Administration, and this past semester I learned all about data analysis and with that, I learned why it is important, how it evolved, how to use it, and about the ethics behind using it. As part of this class, we were asked to write about our perspective on data analysis and for this assignment, I really want to dive into how this is used in recreation. I have chosen recreation because I am striving to be in the Outdoor Recreation field and want to know how I can use data analysis in the future and why people in the outdoor industry should care about data analysis. From what I have found There are many people in the outdoor industry using data analysis and most of these people are not the large-scale decision-makers but the day-to-day operations staff.
To understand why data is important and how you understand it you need to know where your data comes from and who is collecting your data. Below is a chart from the National Recreation and Parks Association which displays how different parks are collecting data
Based on this chart majority of the data collected by parks is done by the Survey of Residents which is done by creating a survey and distributing it throughout the surrounding residents in order to make a conclusion. Next, we see both people counting users and automated counters this is good because you can see how much use you are getting which can be compared to past or future results or even results on a different day to see what days are most popular. Then there are customer engagement tools that collect information shared by their users. Lastly, there are market research resources which while is not collecting data about one specific location or program can be used to give you a greater understanding of who can be attracted to what is being offered and give you a better idea on how to promote what you are offering.
A lot of the people who think that data analytics is important is the day-to-day operations side of an organization Compared to the higher-up decision-makers. Below is a graph from the National Recreation and Park Association which is comparing the operational side of recreation to the Mayor or County Executives.
As you can see from the graph While 52% of Operational Decision Makers believe data is important only 38% of Executive Decision Makers have that same belief. While this may seem like a shock to most people that the Executive level holds less of a priority regarding data one thing, we must look at is why. During this course, one thing which I have learned is that while Executives may seem to hold less of a priority on data, they usually actually do value it except they just don’t understand it enough to fully value how it is done. This is because the Executive level tends to understand the data less, causing them to not fully see the value of the data or how it can be used as a benefit. On the flip side if we look at the Operations side these are the people who are seeing the data in the day to day operations and can see where different data is coming from giving them more insight into what they are looking at
To help the Executive level understand the data more some organizations will have the Executive level get some training or experience in that specific area or bring in a subject specialist in order to help interpret what the data means and where different data is coming from so that they can get the initial background to the data. those who are analyzing the data can also make different charts with labels and visual representations such as the one showing the difference in value on data to present to the Executive level to try to create a comprehensive view on what the data is representing. Analysts can also create dashboards that will allow more data to be shown and filtered in one place to show a large scale of what is happening all in one place. Lastly, analysts can also run different scenarios within the data in order to show what can be done to fix certain problems or what would happen based on different decisions.
Some of the top ways the Outdoor Recreation Industry can use data can be seen by the chart below. This chart from the National Recreation and Parks Association shows how Facility Usage and Program Performance are where data is valued the most.
This is interesting to see because most people struggle to think about how you can use data in the outdoors besides usage data and demographics as in these areas you can get clear numeric values to use which you can get clear answers to what is performing the best. Program performance can value an exponential amount using data analysis in a multitude of ways. To start you can collect different data as to what areas of a program are working which will be able to tell you what you need to do. This is one of the ways which people would probably go to first as you get a clear answer, but you can also use things like surveys with write-in answers to get data on keywords. This can be implemented if you are running trips which last all day and under improvements, the word lunch is on 75% of the results you can pretty much infer that people are interested in you providing lunch and may even pay more if you do.
One of the largest ways data can be used by the outdoor industry is by looking at land use and seeing what is being used and if it is being used in the best way that it can be whether that being in an efficient or sustainable way. This data can be used by localities and states to see what they can improve and show what options they have. This can also help with zoning laws to make sure that they give enough land designated to different areas so that the land is being used the best that it can be. This data can also be turned into different graphs or even databases like this one. (https://www.nd.gov/gis/apps/Download/?clipping=Full&coord=ND83-SF&format=SHAPE&layers=NDHUB.STATEPARKS) This website is a database which shows different ways for which land is being used in North Dakota. Things like this can allow people like executives as well as everyday people to understand data as well as use data to make connections with their own life and see why they should care about the specific data. Many resources like this one allow people to export the data which is being used to create it so that you can see what went into making that visual. This also allows people and other analysts to take the data and run different scenarios with it to see what could happen if different things were moved, floods occurred, natural disasters happened, and more. An example of this could be the location of different hospitals and EMS stations to ensure no one is further than 30 minutes from an EMS station or hospital. By using data and running different scenarios you can see how long it would take to get from a location to a hospital making it easier to see if the goal was met. You could also use data to see where the best location would be for a new EMS station.
While data analysis is an important tool it is important for those who are collecting and analyzing the data to make it as clear and understandable as possible in order to let people who are not seeing where the data is coming from understanding what they are looking at and what the significance of it is. It is also important to look at what you are collecting in your data and how it is being collected to ensure that the data backs up what you are analyzing. Data is also not only about specific numbers and yes and no results but a multitude of different aspects. Data can also be represented in several different ways in order to show and project different things. Two of the most common ways for data to be represented are in charts as well as dashboards which allow viewers to have a visual representation of what they are looking at and what the significance is. Data can be used for a multitude of problems and can be beneficial in almost any situation if applied properly.
Thank you for taking the time to read my paper about data analysis in outdoor recreation and if you are interested in learning more you can visit the NRPA website for all the charts used in this paper.
Sources
National Recreation and Park Association. Using Data at Park and Recreation Agencies, National Recreation and Park Association, 2016,www.nrpa.org/contentassets/f768428a39aa4035ae55b2aaff372617/data-analysis-park-and-recreation.pdf.
