What I came away with most of all was just how on board Qlik is with driving global data literacy. I had the pleasure of sitting in Jordan's workshop on Sunday with about 40 others. It was a small group which allowed us to ask direct questions and get amazing feedback from Jordan. I think I walked out of there with a hundred different ideas of how our company can expand data literacy.
Another highlight for me personally was listening to Alan Schwarz both on the Data Literacy Panel on Tuesday and then his discussion about journalism on Wednesday. His quote, "Numbers don't lie. Words do." will stick with me for a long time. I think everyone in that session would have gladly listened to him present for another hour after it ended. It was that good.
I agree 100% with the earlier comments about needing to be clear on the benefits to the business - but I also believe the best way to seek the investment of others is to demonstrate that you’re also investing in yourself. It doesn’t have to be a monetary investment: think about enrolling in some free, online training modules - or subscribing to data literacy podcasts and newsletters.
Show your manager that you’re serious, that you can apply some of the learnings you’ve picked up through your own development - look for opportunities to learn “on the job” from someone who is more familiar or more comfortable with data - your enthusiasm and commitment to your own personal development will go a long way!
I'd start with the business benefit. You have to sell it to him or her in terms that person can understand. How will this training benefit them and or the business-at-large. Get that conversation in place, and the training should be an easy sell. :)
In my opinion best and more effetive is to get from high level managements clear objetives and marks to achieve and then to commiy jointly also indivuduals involved on data project. First is needed a really commitment from high level management people!
A culture change takes time and continous efforts to keep momentum and ensure its sustainability in a dynamic work place. Therefore, creating a strong Data Culture should always be the "end goal" even though definitions and content of the concept may change. And as I see it, strategic and tactical initiatives within BI adoption and data literacy are enablers or building blocks in a company's journey towards a stronger data culture.
But of course they are all interconnected.
I also believe it's how we think about data. Data is information. All industries are driven by data, but I think the ones who see themselves as data driven are simply asking themselves more questions about their business and they are using data to help find answers. For example, a Retailer could simply ask, "How much am I selling?" That's using data. But what if they used data to help them answer questions like: "What should I be selling?" "Why is that item selling or not?" "Who is buying?" "Are there things about my buyers I didn't know, but if I did would help me find more buyers like them?"
When looking at data literacy inside of a company's culture, I think it's important to ask questions like: How well does this organization support curiosity? Do we make time for people to learn new skills? Are we okay if we try something and it fails?
Because you can have BI skills, you can understand that data is a critical part of the equation, you can even speak data, but if the human side is missing I don't believe you'll have the success you really want.
To me, so much about data literacy is being willing to ask questions and knowing that data can help you find the answers. It's just starting there. Even simple questions like is priority A or priority B more important can change mindsets. For example, in product development we are starting to analyze things like revenue opportunity, revenue loss, user satisfaction, user efficiency, people cost to build, and technology cost to build for each new feature we choose to develop. By analyzing real data combined with deep business understanding, we can start to make our case for our priorities. In order to do this, we have to pause, take a breath and give ourselves time to be curious, to find the sources of data that will help us, and to take a chance and get it wrong. But we are definitely shifting the conversation.
For those of us toiling in the mines of building data literacy, it can be easy to overlook a key pillar for a data culture: executive leadership. "The only thing of real importance that leaders do is to create and manage culture. If you do not manage culture, it manages you, and you may not even be aware of the extent to which this is happening." (Edgar Schein, MIT Sloan School of Management).
If you're building a data culture, it is both fair and necessary to expect senior leadership to articulate the importance of data fluency, set expectations for data-driven decisions, model the kind of behaviors they expect, and invest in training.
As a parent, I'd argue that the modeling of behavior may be most important. For example, when the executive team makes decisions, do they explicitly use data? When they present organization-wide updates, do they do a good job of communicating and visualizing this data? Do they translate strategies into specific measures that are well communicated? These are the types of things that can help everyone see how they should be incorporating data into their activities.
i think the culture is a byproduct of data literacy, and BI adoption.... you cant force a culture change, its needs to be organic....but you can help set the stage through easy to use BI Tools and data advocates throughout the business....using these forums, it helps build a safe place to learn and grow provided the company leadership is supportive.
Critical thinking and curiosity are the starting gates for data literacy and a great place to start! A grass-roots initiative can be as simple as asking “what data did you use to make this decision?”.
Often we look straight to training programs and strategies when really - at the heart of it - data literacy is simply reading, writing and comprehending data, so every single opportunity we get to weave data into our thinking and decision-making is an opportunity we should treasure!
In your day-to-day activities, start asking “what does the data tell us?”, “how is this measured?”, “where does the data come from?”