The data driven and data informed culture

The data driven and data informed culture

Episode 004

What does a data culture mean? And is there a difference between Data-driven vs. Data-informed?

What does a data culture mean? And is there a difference between Data-driven vs. Data-informed?

An organization that uses data in their decision-making process. From the highest executive to the summer intern.

Sound far-fetched? It shouldn’t! Most organizations are on their own journey towards using data to drive significant value for their customers and shareholders.

But many organizations aren’t there yet. And that can be frustrating. Building a data-informed culture doesn’t happen overnight, but it does lead to great results.

In this episode of Data Able, we talk about the Data-driven culture, and the Data-informed culture. Mostly semantics, the difference is in the level of maturity the organization has with using data. Ideally, every business line is comfortable with combining their deep industry expertise with their data and insights that lead to the best decisions and outcomes possible.

Until next week!

Thanks and Happy Listening!


 
 

The exciting future of self service analytics

The exciting future of self service analytics

Episode 003

The future of self-service analytics is bright, but could things like AI help analysts do their jobs even better?

The future of self-service analytics is bright, but could things like AI help analysts do their jobs even better?

Self service analytics isn’t going away anytime soon. In fact, we think it’s only become more prevalent!

Why is this? Well for starters, there’s more data than ever before! And our BI, Analytics and Data Science teams just simply can’t (and shouldn’t) keep up with the demand. This is a great problem to have, but will require shifts in the traditional analyst paradigm.

Leaders are finally starting see the value in their data, and in order to get them what they need, we need to move faster, getting the RIGHT data, in the RIGHT hands, at the RIGHT time.

So what about Artificial Intelligence? Is it going to eliminate the need for analysts, data science, etc.? The short answer is no… but it IS going to require that the consumers of this information are capable of a baseline understanding of how data works, how math works, and how to communicate what’s being created.

We hope you enjoy this episode. Until next week!

Thanks and Happy Listening!


 
 

Twin Cities Meetups Are Creating a Data Culture

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This month the Twin Cities hosted Startup Week. One of the many great sessions was about the history of data visualization, delivered by Matt Dubay on behalf of the Twin Cities Data Visualization Group (TC Data Viz) (of which I’m an organizer). There was an amazing level of engagement and energy in the room and for the topic. As a side-note, I encourage you to check out the TC Data Viz group if you haven’t already. It’s a place where all are welcome - beginner or advanced - technical or business users – and our tools are agnostic, whether open source or proprietary software. We provide a fun and creative space to share ways to display data in our businesses and communities.

One of the main themes discussed during the session was around data literacy. One astute person noted that IT and self-service BI cannot drive the destiny of data literacy within organizations. Instead, it needs to be something solved by the business users themselves. Only then will self-service BI truly succeed. I couldn't agree more! Data fluency is an upcoming challenge that business leaders, managers, and individuals need to make time for, if they’re going to create data-savvy organizations.

In related news, the September 2018 McKinsey Quarterly published an article entitled "Why data culture matters". The whole article is great and highly recommended, but one key insight I want to touch on was that “Data culture is decision culture". The takeaway here is that organizations shouldn’t "… approach data analysis as a cool 'science experiment' or an exercise in amassing data for data's sake. The fundamental objective in collecting, analyzing, and deploying data is to make better decisions". One other thing I want to touch on is their call for the “democratization of data" and its importance in a data culture. From the article: “… get data in front of people and they get excited. But building cool experiments or imposing tools top-down doesn't cut it. To create a competitive advantage, stimulate demand for data from the grass roots." 

Certainly, executive buy-in is important for resource allocation and overarching strategy, but executives don't make most decisions. Organizations succeed by the many decisions each employee, contractor, and customer make each day. Empowering and encouraging those stakeholders to get excited about data whether it is educational opportunities, competitions, data-for-good initiatives, or other ways to help invigorate and empower data culture at the grassroots level is essential.

So a little homework this week:

  • Executive: Identify a way to empower and encourage your organization to support a grassroots-level data culture. What change can you support and encourage at the grassroots level so that everyone not only wants data but needs data to survive?

  • Managers: Identify a way you can empower and encourage your team to support a grassroots-level data culture. What new decisions can you or your team harness new or existing data to make better decisions than you had before? 

  • Experienced contributors: Identify how you can better use data to make better decisions and even demand data that had not been used before to make decisions? Further, how you can you help support newer contributors in this effort? 

  • New contributors: Provide a fresh insight on how your organization can better encourage using data in roles. Your fresh perspective has a distinct advantage of seeing what could be as your are not encumbered by what is or was.

Now go and do your part changing the data culture at your organization!


BEYOND THE DATA IS ON A MISSION

We help high-performing individuals become champions for a more data-driven approach in their organization. We believe that data science is only part of the equation.

Getting value out of data requires building a culture that starts with YOU, is supported by executives, and trickles down to every front-line specialist in your organization.


 
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Is it time for everyone to be data literate?

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Is it time for everyone to be data literate?

Episode 002

Data literacy is a fast-growing topic. But what is it? And why should organizations care?

Data literacy is a fast-growing topic. But what is it? And why should organizations care?

So what is this new concept we’re hearing a lot about these days? Data Fluency or Data Literacy is getting a lot of buzz right now. What is it and why should i care?

We describe it as: Framing problems, applying data, making data-informed decisions, and being able to communicate with data (through storytelling, or data visualization).

Another key aspect of a good data user that isn’t taught in textbooks or online coding classes? Empathy. The ability of the data user to understand the needs of her audience, craft the right narrative and deliver the right answer to the right person at the right time. You may even consider putting empathy in your job descriptions going forward!

So is data literacy only for analysts and data scientists? Absolutely not! We think product teams can benefit from using data. We think HR teams, Finance teams, Operations teams, Sales teams and Marketing teams can all benefit from data literacy. It’s a tool in your toolbelt to help you become a better marketer, finance leader, or product owner.

We would be remiss if we didn’t share a few of our favorite resources for further study. First, there’s Cole Nussbaumer’s fantastic blog Storytelling with Data. We also love Kate Strachnyi’s Story by Data blog. And check out Jane Crofts’ company, Data to the People who are building data literacy assessments for organizations all over the world!

Thanks and Happy Listening!