On Monday’s episode we covered a number of issues surrounding data and the data profession as it applies to Social Entrepreneurship. However, all these problems overlook the most important issue for the utilization of data for social enterprises, namely having any data to analyze.
On today’s episode we talk about the importance of knowing your data intimately before being able to garner any meaningful insights. For the Social Entrepreneur this may entail going out into the field and collecting it in person!
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Music for the show: Foolish Game / God Don’t Work On Commission by spinmeister (c) copyright 2014 Licensed under a Creative Commons Attribution (3.0) license. http://dig.ccmixter.org/files/spinmeister/46822 Ft: Snowflake
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Welcome to data couture. Hi, I’m your host Jordan, on today’s data bytes, we’re going to be following up on Monday’s episode, namely the interview between Jordan and Brian Jefferson on various issues surrounding data and the data profession when it is applied to social entrepreneurship. And so in that interview, something that came up was an interesting one. Namely, a lot of social entrepreneurs aren’t necessarily data professionals. And so with that, and with the ever increasing demands of using data to solve all the world’s problems, the question is, where does fledgling social social entrepreneur even start, and clearly, I have problems with the word entrepreneur, and apparently even social, that being that there are lots of resources that I mentioned in Monday’s episode, including various websites, various projects, various groups that are trying to get the data scientists, the data professionals connected up with the social entrepreneurs.
And of course, there are all sorts of apps and tools and systems that one can employ with just a little bit of money in the scheme of things in order to collect the data, normalize the data, clean the data, and then pump that out into meaningful results. Now, that is certainly an option for various people going down this path, but it doesn’t really speak to another issue that we have, namely, how to get the data in the first place. It might seem easy if your particular organization is focused on problems, say in the United States, or in Europe, or in Australia, or any other country that does a very good job of keeping track of and measuring various results about the population. But let’s say that even in these countries or any other country around the world, for that matter, let’s you’re focused on a problem that doesn’t necessarily have any sort of statistics, or any sort of good data sets available. What’s one to do?
How How does one even pitch this idea to any sort of investor any sort of interested party or person to get the funding necessary to go then enact change? That’s a real problem is well before any of the actual technical pieces any of the data manipulation, transposition, visualization, or any of the predictive parts? Right? This is a very basic question. And it’s an interesting one, and it’s one that I think we would do well to solve. And frankly, the best answer that I have is to become like the social scientists become like, the psychologists literally collecting data out in the field, become a true scientist, as you are an entrepreneur, because at the end of the day, what does your organization have to say?
What it like? What, like, what do your suggestions for how to change the world? Why does that matter? Well, it’s because you have very, very solid data and very solid data collection practices underlying them. And so quite literally, if there’s a problem that you see, or you’ve heard about, or whatever the case may be, that has caused you to want to start this particular social business, well go out into the field and start taking measurements. And once you start taking measurements over time, hopefully you’ll find a group of like minded individuals who will also share similar passion until your data set will grow and grow and grow. And really, that’s the best way to collect data. That’s the most meaningful data. That’s the richest data.
And maybe this sounds obvious to most, but at the end of the day, really the skill that a data analyst or data engineer data scientist has the most important one is knowing their data. And what better, what better way to know the data than to have collected it yourself or have been down in the trenches and see where the data itself is collected. Of course, this doesn’t just apply to me new startup and a new social business that’s coming up on the block. That’s exciting. This applies to every business every single data professional, my ideas, like for example, and my particular credit union, it’s great to have all the data. And it’s great to understand what fields mean and what various variables or facts have in common.
But at the end of the day, if you don’t know what your frontline staffs doing, how they’re actually collecting the data and how they’re collecting the data is speaking to your members or the members and customers are going through the various online channels, if you don’t understand that moment, that unique piece of contact between the data collector, and the member customer, trusting their data with us, then you don’t truly know your data. same can be said for any organization that relies on data from customers, which let’s face it, that’s basically every industry. Now for the social entrepreneur, once you have this rich data set in hand, and by that time, you’ll have a very deep understanding of exactly what the problem is, what the variables are, that go into collecting those bits of data, whether or not you’re looking at super fine grained, like the most basic type of data, you can get about a particular problem or you’re looking at aggregated data, you’re looking at higher level of data that builds upon other pieces of data.
Then when you go into these various data aggregators, you’d speak to them or you get these various tool sets from third party vendors, you’ll be in a significantly stronger position to actually say something with your data. And we can say something with your data that is meaningful, and that has true underlying value that you know, deeply. Well, you’re probably not going to fold because you do know the problem, you know it down to the very basic one and zero of the data you’ve collected. Now, for anyone who has a different idea about maybe how social entrepreneurs should go about collecting their data, and I’d love to hear it, leave a comment below. Be sure to subscribe and I will talk to you soon.
That’s it for the show. Thank you for listening. And if you liked what you’ve heard, then consider leaving a comment or like down below. Stay up to date on everything data couture, be sure to follow us on Twitter at data couture pod. consider becoming a email@example.com forward slash data couture music for the podcast. It’s called foolish game. God don’t work on commission by the artist spin Meister used under a Creative Commons Attribution 3.0 license, writing editing. Production of the podcast is by your host, Jordan bohall