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/data-culture/
Transcription
Episode 2.
This is using the whole whale, a podcast that brings you stories of data and technology in the nonprofit world. my name is george weiner, your host and the chief whaler of wholewhale.com, thanks for joining us.
George: Hello this is name is George Weiner, your host, its march 7th, in new york, don’t worry it’s still cold here, although daylight savings is coming. Today I want to talk about the idea of data culture. Data culture is a topic that we spend a lot of time thinking about at wholewhale. the idea is essentially is how the cultures within our organization need to adapt, so that we can maximize and use the data that we have. When were talking about data, I think it’s really interesting to take the long view and really understand at a macro level what’s going on.
So, why not to the beginning, 30,000 bce* we have the first cro-magnon man, not too much going on there, not too much big data, 32000 bce* we have mesopotamia and the first written word, it takes us a little while to write something down that could be saved and recorded. and then in 1968 we have the first beginnings of the internet, officially calling it the internet where they defined the term in 1995.
Let’s think now, just over the past decade, just the last ten years, the amount of data, and by data I mean not just personal information, but recorded words really. Just in the last decade we have got more saved and created, stored by human kind, than in the past 30,000 years*, and so what does that mean as a culture in a general sense, also in a smaller sense to an organization, where everything we are doing is recorded, and our ability to understand what’s being done by our users, and the people that are important to our organization, is now available. its overwhelming really. And, the only way you can truly maximize it, is you can’t put baby in the corner, you can’t put data in the corner, and just rely on one person. Kindof like a hero data analyst, if you’re so lucky to have one, to go off there into the corner, interpret it and bring us back from up on high, the information.
So, in a loose structure, we would like to recommend, when you’re thinking about what does a data culture look like, within your organization. To define it, data culture is: an organization that looks asks what does the data say, and then acts on the results, even when convention or tradition may disagree. It is using the analytic process to leverage relevant insights from Big-data, and transform the way business is done internally and externally, the culture depends on staff on all levels, to measure outcomes, act based on available data, and build on existing knowledge overtime. There are three components to the data culture: people, process, and product. So balancing together, starting with people, we think is the most important, if you think as an equation, this is 40-50%. We need to be giving staff access to the data they need, with holding regular meetings, they’re establishing proper structure internally. People who have been in the job roles for a while, may not have the necessary analytic skills, so there’s also an element of training, and understanding that we have to invest in the training resources so that our people have the ability to understand what they’re looking at and then make changes as a result. The processes inside, setting measurable goals, communicating the right data internally is helping us with the physical act, of how we are interacting and improving our organization methodically by using data. And then finally, the product side, actually the smallest component, but sometimes I think we get obsessed with this, if only we had the right tool to come in here and show me a chart, all of our answers would be solved, and we’d finally understand what’s going on. The product at whole whale we really leverage a lot is google analytics, free web tracking tool that gives us tremendous insight on web behavior. There are of course others, optimize, which will help you test, then use the data available from your site, to increase your insights. But again we don’t like getting too focused on product as the solution, and subscribe to some sort of solutionism, if only we had the right toy we’d have the solution.
So, we’ve got this rough model, it’s important to say any culture in an organization, and we know this probably from experience, is largely dictated from the top management. And so one of the biggest killers is the “Hippo”. Now if you’re not familiar with this term, I’m excited to tell you, the hippo is an acronym, is the highest paid person in your organization. And when this person is somebody, who puts the blinders up, leads from the gut, and just trust me I’m right , don’t look at data I’ve been doing this for years, we’ve got an issue. Because ultimately you’re not going to be in an environment where the best possible answers are going to be tested and evaluated when possible based on the data. This is not to say that having a leader that has got vision is something that is going to stop a data culture, quite the contrary…
Think about the 1962, JFK moon speech. Where he basically says, within the next decade we are going to put a man on the moon. That is tremendous vision. Notice though if you go back and look at the speech, he does not go on to say we are going to use this type of rocket fuel, this type of aluminum alloy what have you, to build the ship, he does not go on to say how nasa is going to figure this out. but he sets the direction, and gives that type of vision, and sets the goal really.
jfk moon speech follows…
And that is a perfect example of how we can be interacting with leaders that bring us vision, but not necessarily the minutia of execution, where data is really great on saying, “hey I know you want to go north but the compass, and all other available data say were going east, if we correct the course, we will get there faster.” and I like this as a balance thinking of data as a compass, informing the direction we go, not as a benevolent dictator, that tells us everything we should ever know. Don’t worry there’s still room for human thought there.
So that is the concept for today, thinking about data culture. We’ll be talking a lot more about it, and looking for examples out there to make this real, but it is certainly a process and something that we like to think a lot about.
This has been using the whole whale, the podcast. For more information about the topics covered in todays show, please check out wholewhale.com and consider following us on twitter @wholewhale. And thanks for joining us.
*(The earliest known remains of Cro-Magnon-like humans are radiocarbon dated to 43-45,000 years before present that have been discovered in Italy[2] and Britain,[3] with the remains found of those that reached the European Russian Arctic 40,000 years ago.[4][5]
*Mesopotamia is the site of the earliest developments of the Neolithic Revolution from around 10,000 BC.)
