All I have heard over the last 5 years is how “Data is the new ____”.
From “Data is the new oil” to “new fabric” to any other fancy analogy the author could come up with. Now, there’s nothing wrong with it. Analogies help us understand a concept and remember the concept later. My daughter told me the other day, the “best way to learn something is to teach it” and that’s why “remembering” the analogy is key. Whenever, you are trying to relay the concept to someone else, and you use that analogy, it makes the whole process of learning, remembering and teaching it later a whole lot easier.
Back to the topic (Why do I digress so much?) – So, everyone’s talking about Data.
If “Data” is so important for our organizations and is one of our strategic resources, why are we struggling so much to “monetize” this data? (I don’t mean monetizing the “data” in the sense of re-packaging what we have collected and then sell it, I simply mean “Why can’t we put our Data to good use”?)
Why do we still have just a handful of people who understand what data analysis means and then we have swaths of people who don’t? These very few people who say “Data is my job” are serving about 10-100x many others who say “I need Data to do my job”. The current model isn’t sustainable and we need to bridge that gap.
Bridge what gap?
You might ask, “Aren’t we all supposed to be doing a specific function? Isn’t it a bad idea for all of us to Data Analysis? We all have specialized skills to do something specific, right?”
Right. However, there is something different going on here.
Let’s go back in time. Go way, way back in time. Yes, back when we were probably referring to each other by making some weird clicks in our mouths to garner attention. Until, we realized that we can make a lot of different clicks and sounds and more importantly, differentiate those sounds and give each one of those sounds some meaning. Yes, I am talking about the birth of language.
We were all able to get along with sounds and sign language, yes? That worked until we figured out that it didn’t. Now, the “Homo erectus” realized that we had a power that other animals didn’t.
That was the power of language. And, they put that to great use.
And, that’s sort of what I am hoping we start doing a bit more. We can all Speak Data fluently once we learn the language. We are not all expected to do our own Data Analysis. But, I think we should all know our basics.
Why do we need to do that? Let’s dig in a bit more.
We have these two sides of our selves here. We have the side that wants to protect our Data. We are teaching the values of what owning our Data means. There are conversations going in many households (I know they are happening at our household) what you do when click “Like” and how that “Like” is monetized (in the traditional sense). As individuals, we feel that we are entitled to the privacy of our Data and the consent to using my data and my information should not taken for granted
Yet, at the same time, when we go to our professional organizations, we start talking about the power of algorithms and ask analytics teams why we can’t use Telemetry to gain deeper understanding of our customers.
You see the irony and the conflict here?
We might have a conflict in our brains about how we feel about the use and misuse of Data.
I believe we can bridge that gap to an extent by creating a culture of understanding Data better. I believe we need to bridge that gap for all generations. We need to talk about Data with our kids and we should be able to talk about Data with our parents. For that, we are going to understand some common concepts around Data, not just as an analyst or a Sales leader but as a father and a son. So, we can have a deeper conversation about such topics in our personal lives.
That’s the sort of culture that I hope we create
Now, creating a culture is easier said than done. Creating a culture is NOT a job. Not for one person, not for a team of individuals. It is something where you can lead with some principles to foster a community where culture is created organically. You probably have heard this before I will cite it again here, when you look at culture, you have to think of a culture as a bio-organism, the parts work together to support the function of the whole. (something, I just learnt is called functionalism in cultural anthropology, an approach established by Bronislaw Malinowski).
So, how can one person starting thinking about influencing a culture? It will take time and it will happen with the help of many others. This isn’t just one of those enablement efforts or a directive wherein, if the higher ups in the organization start talking about Data Culture and mandating us to attend courses on Data Culture and sit in trainings that we will have a better “Data Culture” next year.
This is more of how your household evolves over time. You all do what you are supposed to do together. But, you find certain ways of doing something seem easier and more comforting and satisfying that other ways. For one family, it may kneading dough by hand is more satisfying even if it takes longer. Longer time in kitchen means more connection if you are in the kitchen together with your family. For other families, a Breville might come to the rescue and that’s completely fine.
Over time, though, your family will have certain beliefs and values that you will establish that make sense for you. The important part about that establishing of beliefs is the debate that must occur.
Debate is vital and serves as the lifeblood for Data Culture to grow and evolve.
The debate / discussions and arguments about what we should and shouldn’t do is what provides our culture stronger roots. That’s sort of what we need to aspire to do at our organizations.
I hope this inspires you as a organization leader to be a cultural leader. You want to make better decisions using better Insights from your data? Then, let’s remember some of the basic rules to evolve our understanding of Data and thus, our Data Culture
A. We have to be able to all “Speak Data” and that starts with establishing the language of Data. This depth of your “Data Language” maybe different than other organizations’ language. And that’s, okay. Over time, each one of our languages will evolve
B. The second concept of this evolution will be tied directly to our ablity to debate about data. Just looking at data and dashboards isn’t enough, we need to question what we see and its interpretation. We need to be able challenge ourselves and other about what we see coming in our Data
C. Prepared to be challenged by not just what we see in your data but also the different interpretation of it. The cognitive diversity that your team provides to the interpretation is a boon and let’s learn to recognize that
Of course, evolutions didn’t happen over months or over years. So, if you are worried about the timespan it might take for your organizations to evolve. Our “Homo Sapiens” brains are unbelievable at understanding new concepts. Given our own rapid transformation in understanding the Data that we have (given the explosion of data storage) over last 2 decades, I am not too worried about our abilities to make sense of it from hereon. I am only worried about us not putting in the effort.
I will follow up with some posts about how specifically we can start implementing some of our ideas to evolve our “Data Culture” and improving our “Data Literacy”. Follow me as we go on this journey together.
For now,
Let’s start with the ABC. We will get to “Z” together one day.
