The 10 Habits of Data-Driven Teams

Being a data-driven organization takes more than the latest technology and quality data. It’s more than just running one-off data literacy training.

It’s about building daily habits to drive change with data.

So, what are the habits of truly data-driven teams?

We turned to some of the best in the data & analytics community to find out. Discover the 10 habits that data-driven teams and their leaders live by every day — allowing them to deliver real results, drive change, and hit goals faster.

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Introduction

Word on the street is that being data-driven is important. In fact, most companies today strive for a data-driven culture. It enables better decisions, increases agility, and ultimately leads to more positive business outcomes. The list goes on.

Data is the new gold, and organizations are increasingly recognizing how its practical, everyday uses can add significant value to their business. Take Netflix, Google, and Coca Cola for example.

Netflix is transforming the entertainment industry right before our eyes by harnessing data to profit off of our television and movie tastes.

Google collects insights from their people analytics to understand how to “build a better boss” and improve their workplace culture year after year.

Coca Cola leverages the power of data to serve users more personalized advertisements — increasing their click through rate by 4x.

There are really two types of “data-driven companies” — the type represented by Netflix, Google, and Coca Cola and those who are simply “masquerading” as data-driven.

So, what is it that sets them apart?

Being a data-driven organization takes more than the latest technology and quality data. Like other aspects of digital transformation, it requires transforming your culture into one that embraces data-driven decision-making and all of the everyday processes involved. 

It’s more than just running one-off data literacy training. It’s about building daily habits to drive change with data. 

So, what are the habits of truly data-driven teams? We turned to some of the best in the data & analytics community to find out. Discover the 10 habits that data-driven teams and their leaders live by every day — allowing them to deliver real results, drive change, and hit goals faster.

Table of Contents

Habit 1: Know When to Trust Your Gut vs The Data | Wendy Batchelder, Chief Data Officer at VMware

Habit 2: Harness Data Storytelling | Brent Dykes, Author, Founder, and Chief Data Storyteller at AnalyticsHero, LLC

Habit 3: Maintain Operational Excellence | Brandee Sanders, VP of Marketing at Motive Retail

Habit 4: Cultivate a Culture of Experimentation | Talin Koutnouyan, VP of Marketing at Influential

Habit 5: Build a Feedback Loop on Trust | Justin Breaux, Social Media Producer and Digital Analyst at Argonne National Laboratory

Habit 6: Speak the Language of Data | Jordan Morrow, Head of Data, Design, and Management Skills at Pluralsight

Habit 7: Conquer the Last Mile of Analytics | Kate Strachnyi, Founder of DATAcated

Habit 8: Start with the Story | David Ciommo, Data Visualization Principal at Humana

Habit 9: Measure What You Wish to Improve | Juan Riojas, Chief Information Officer at Rackspace

Habit 10: Know Your North Star Metric | Cassidy Shield, SVP of Sales & Marketing at Narrative Science

Habit 1: Know When to Trust Your Gut vs The Data | Wendy Batchelder, Chief Data Officer at VMware

Are you making key decisions based on data or are you making them based on gut instinct or experience? 

“My favorite is when you put data in front of someone and it’s very compelling or very obvious what the decision should be made and then someone dismisses it and says, No, I’m going to follow my gut. Well, is that the pizza you had for lunch or is that really your experience? How do you distill that?”

As a person, you only know so much. Data will help you see things that you wouldn’t normally see. It can help you tell a story that you maybe didn’t know existed. It’s a great way to check and challenge yourself when you’re trying to do something that is complicated or impactful. 

You don’t need data for every little decision, but if you’re making big decisions that are going to require a big change — spend time with the data. 

Gut instinct and data are often seen in opposition to one another. But the truth is, effective decision-making doesn’t have to be an either-or proposition. We need both data and gut instincts to make better business decisions.

About the Data Changemaker:

Wendy Batchelder serves as the Chief Data Officer of VMware and is responsible for the company’s business insights, analytics solutions and delivering excellence in data management across the company. She directs planning and implementation of enterprise information systems to foster innovation that creates competitive advantage, enhances the customer experience, improves service quality, supports business development, improves cost effectiveness, and leads to greater productivity and efficiency.

Wendy has spent over 15 years in leadership roles at a variety of global companies spanning various industries. Prior to her role at VMware, she held various leadership roles at Wells Fargo, including Head of Enterprise Master & Reference Data and Head of the Corporate Risk Data Office. 

Habit 2: Harness Data Storytelling | Brent Dykes, Author / Founder / Chief Data Storyteller at AnalyticsHero, LLC

So, you have done it. Your tracking is in place, your data is clean, modeled and easily available. All the information is at your fingertips. 

The next question is whether your colleagues in different departments and teams can make any sense of it. Ideally, the information empowers them to make data-driven decisions. However, we know without context and meaning, the numbers alone will not lead anywhere. This is where good data storytelling comes in.

Data storytelling is a structured approach for communicating data insights, and it involves a combination of three key elements: data, visuals, and narrative.

“When narrative is coupled with data, it helps to explain to your audience what’s happening in the data and why a particular insight is important. Ample context and commentary are often needed to fully appreciate an insight. When visuals are applied to data, they can enlighten the audience to insights that they wouldn’t see without charts or graphs. Finally, when narrative and visuals are merged together, they can engage or even entertain an audience. When you combine the right visuals and narrative with the right data, you have a data story that can influence and drive change.”

Leaders can no longer rely on just data analysts or data scientists to access and interpret analytics. Team members in all parts of the organization — sales, marketing, operations and others — require some data storytelling capacities to ensure internal decision-makers can turn new insights into improved business performance.

About the Data Changemaker:

Brent Dykes is the Founder & Chief Data Storytelling at AnalyticsHero, LLC and Author of Effective Data Storytelling: How to Drive Change with Data, Narrative, and Visuals. Brent has more than 15 years of enterprise analytics experience at Omniture, Adobe, and Domo. His passion for data strategy and data storytelling comes from consulting with many industry leaders including Nike, Microsoft, Sony, and Comcast. He is a regular Forbes contributor and has written more than 35 articles on different data-related topics. In 2016, Brent received the Most Influential Industry Contributor Award from the Digital Analytics Association (DAA). He is a popular speaker at conferences such as Strata, Web Summit, Shop.org, Adtech, Pubcon, RISE, Crunch, and Adobe Summit. Brent holds an MBA from Brigham Young University and a BBA in marketing from Simon Fraser University.

Habit 3: Maintain Operational Excellence | Brandee Sanders, VP of Marketing at Motive Retail

Operation excellence is the backbone of any data-driven team and transparency is the key to driving & achieving that level of excellence.

“Without transparency, no one knows what’s going on. Things become opaque. They get stuck in the Goliath legacy mindsets of  “we’ve always done it that way.” And “We’ve always done it that way” doesn’t scale.”

Operational excellence is about creating repeatable, transparent, and easy-to-scale processes. It’s about creating environments where everything is on the table and everyone knows their swim lanes. It’s about never having to ask, “What is marketing working on? What is the data team working on?”.

How do you achieve this level of transparency?

You can adopt a project management tool like Basecamp or Trello (depending on the size of your organization) to create templatization & clear swim lanes of ownership.

This becomes a place where people can come in and very easily see at a glance — What is this project? Who owns it? What does it do? What stage is it in? What does it mean for my particular role?

With this approach, there’s no mystery. No smoke and mirrors. Everyone knows what everyone’s working on.

“That’s a huge paradigm shift for some of the Goliath because they’re very legacy. So the mindset is to hide and work in silos, but silos are prohibitive to innovation.”

About the Data Changemaker:

Brandee Sanders is VP of Marketing at Motive Retail. She is an award-winning Digital Nomad, Vice President, and Marketing Technologist at the intersection of creative and commerce specializing in data-driven, quantifiable results.

An avid world traveler, she’s managed a wide spectrum of projects for a variety of clients, from Silicon Valley startups to Emmy award-nominated film studios and Fortune 500 companies. She’s collaborated with Inc. Magazine featured entrepreneurs, TED Talks educators, Gartner Magic Quadrant leaders, and innovators from all over the world, in roles ranging from directing digital marketing, e-commerce, blogging, content, advertising, and full scale multimedia production, to social media, website launches, PPC and SEO.

Habit 4: Cultivate a Culture of Experimentation | Talin Koutnouyan, VP of Marketing at Influential

If there’s one thing that will suck the life out of any data-driven team, it’s failing to overcome organizational resistance to experimentation. Sadly, it’s an all-too-familiar story.

“It’s rare to come across a company that has a true experimentation culture. Most of them are in positions where their goal is to produce results. With that focus on business objectives, it’s easy to skip steps in the experimentation process.”

Experiments must be disciplined, organizationally aligned, supported by an infrastructure, and culturally embraced. In other words, running experiments should be as normal as running the numbers. But, how do you get there?

There needs to be a commitment to the process and an adherence to certain types of skills — skills that align with the following personas:

  1. Be a scientist – Get really prescriptive with the types of questions that you’re asking. Form really specific and measurable hypotheses that you can easily translate into a test.
  2. Be a statistician – Collect and connect the dots.
  3. Be an engineer – When you’re planning for an experiment, it can look really great on paper. However, when you reach execution and you’re running ads on Facebook, Instagram, LinkedIn — you’re going to come across specific hurdles from a tracking perspective. It’s your job to find the best solutions.
  4. Be a politician – Understand that there’s going to be multiple stakeholders at any point and different perspectives on what is important. Be ready to manage that conflict and fight for stakeholder buy-in.

Think about experimentation as a necessary third data set that truly makes your organization data-driven. It enables you to directly connect the what and the why, providing you with a more complete picture of your business. 

About the Data Changemaker:

Talin Koutnouyan is the VP of Marketing at Influential and has worked with globally-recognized companies and organizations such as PricewaterhouseCoopers, NASA’s Jet Propulsion Laboratory, the National Science Foundation, Time Magazine, and hundreds of Fortune 500 brands.

She is a data science, AI, machine learning, and behavioral science expert. She leverages these tools along with relevant data sets to help organizations identify strategic insights, emerging trends, new markets they should enter, and roadmaps for acquiring and retaining high lifetime-value consumers.

Habit 5: Build a Feedback Loop on Trust | Justin Breaux, Social Media Producer and Digital Analyst at Argonne National Laboratory

When you start out on a new team, you may not know what data your leadership wants.

By maintaining consistent reporting, you can test & iterate on what you think the most important metrics or KPIs are to them.

It can take a while to get aligned. It can take a while for the analysts themselves to be able to find out how to translate information in a format that leadership sees value in and can immediately recognize over time.

The key is to create a feedback loop where you’re consistently capturing feedback and refining your reports. But how do you actually build that feedback loop?

“It’s always about the relationships. The quality of the relationships will determine the trust your colleagues have in you to do your job. That feedback loop comes as a result of that trust.”

Engaging in regular conversations with your colleagues or clients is also key to understanding their needs and building that loop. You can use these questions to start that conversation:

  1. What business questions are you seeking to be answered?
  2. Who will use this data? Who are the key stakeholders?
  3. What’s the easiest way for you to receive the data?
  4. What actions will be taken on the data?
  5. What do you expect to learn?
  6. What questions do you have about the content and its performance?
  7. What questions might the intended audience have about the analysis?
  8. How should these questions be prioritized?

About the Data Changemaker:

Justin Breaux is a Social Media Producer and Digital Analyst at Argonne National Laboratory. At a time when government agencies are just beginning to understand the value of measuring communication efforts, Justin has been collecting, analyzing and communicating out this information to his leadership for over three years.

As a social media manager and digital analyst, Justin has single-handedly built Argonne National Laboratory’s data collection and reporting system. A consummate networker, he meets regularly with individuals throughout the laboratory and at partner organizations to identify goals and communication challenges to develop strategic plans that meld the latest in communication tactics with the organization’s goals.

Habit 6: Speak the Language of Data | Jordan Morrow, Head of Data, Design, and Management Skills at Pluralsight

Data literacy. It seems that everyone is talking about it today. CDOs position literacy among their top priorities and for many organizations, it is one of the most pressing needs.

The teams who are comfortable using data, speaking about it, and finding insight in it will inevitably come out on top — especially those who leverage the four levels of analytics: descriptive, diagnostic, predictive, and prescriptive.

Level 1: Descriptive

Imagine you’re sick. You’re waiting in the doctor’s office. The doctor comes in and looks at you, says, “You are sick,” leaves the room never to come back. How many people would go back to that doctor? What that doctor just did was descriptive analytics. Other words for this are data visualizations, dashboards, reporting, KPIs.

Level 2: Diagnostic

You go back to the doctor. Now imagine the doctor says, “You are sick and here is why.” You’ve discovered the why. Data literacy seeks to truly help individuals get good at diagnostic analytics.

Level 3: Predictive

The doctor’s going to say, “I predict you take this medicine, you get bed rest, you do this, you do that, you’ll overcome it.” Sometimes you’re not right and that is one of those things that people need to understand about data and analytics. Not every prediction is going to come true. That’s not the point of predicting something.

Level 4: Prescriptive

This is where we’re getting really advanced. It’s similar to predictive, but in prescriptive, your data and analytics will be telling you what you should be doing. It will prescribe it for you.

“That’s the thing that we need to realize —data is just data. It just sits there. You need the four levels of analytics to bring value to it.”

About the Data Changemaker:

Jordan Morrow is on a mission to close the data skills gap and establish a data-centric culture by bringing data literacy to the masses. He’s passionate about delivering a human touch to a world of numbers and gets the greatest satisfaction when he can help people see and understand the power that data analytics can bring to their careers, their businesses, and their personal lives.

Currently, Jordan leads Pluralsight’s data and design/management across various channels. The program is designed to help people learn and improve their data capabilities and gain an understanding of how to effectively use these skills to handle the large amounts of data found in modern organizations.

Habit 7: Conquer the Last Mile of Analytics | Kate Strachnyi, Founder of DATAcated

Getting the right data to the right people at the right time is always easier said than done. This is the challenge of the last mile of data analytics.

“If you can’t deliver it, if you can’t get it across that last mile — you have not run the full marathon. You’re just running for no reason. You don’t get the medal. You don’t get the reward.”

You’ve collected and prepared all of the data. The last mile is how you inspire action and change. How do you present your insights in a way that resonates and tells your audience what to do next?

Data storytelling can be your tool to cross the finish line. 

With data storytelling, you don’t start with the data. You start with a business problem or a question. You need to think about the type of data you can collect and how you will explore, analyze, and visualize it. You need to think about your audience and what they care about most. What are the 2-3 questions they’ll have as soon as they see your data story? Then, you need to craft a narrative that addresses those questions and incites action. 

Only then will all of your “training” and preparation be worth it.

About the Data Changemaker:

Kate Strachnyi is the Founder of DATAcated, a company that delivers LinkedIn content strategy for companies focused on innovation in artificial intelligence (AI), machine learning (ML), and data science. She is also the Founder of DATAcated Academy where she delivers on-demand and live training on data visualization and storytelling.

Kate is a LinkedIn Top Voice in Data Science & Analytics (2018 & 2019). She also hosts the DATAcated Conference — a virtual conference that brings together expert speakers along with thousands of participants in the data & analytics community.

Habit 8: Start with the Story | David Ciommo, Data Visualization Principal at Humana

There are a lot of bad dashboards out there.

And they’re typically created using one of these two approaches:

  1. You have data. You bring it into a BI platform. You throw some charts and graphs on it. You make changes throughout and then finally call it a data story or a dashboard.
  2. You have a tool and you’re really only specialized in one tool or platform. You go get the data but struggle trying to get the data into the platform because it’s limiting for one reason or another. Or, you don’t really know what you’re doing.

And after all of that work, you never actually come up with a story. It’s just a statistical report. It’s a glorified Excel spreadsheet. We’re not slowing down enough and thinking about what we are actually doing or why we’re doing it. We need to start with the story.

“Forget about the data for a moment. Forget about the tool that you’re using. Just start with the story. What are you trying to say? It’s no different than writing a screenplay or a book. Who is my audience? 

Ask the important who, what, why, when, where, and how questions around the information. Then, you go look at your data to see if it supports that story. If you don’t have enough data to tell the story — go get that data.”

Get ahead of the questions. Help your audience understand the “so what,” not just the numbers. Ask yourself: Why should someone care about my findings? How does this information impact them?

Most people actually don’t want to look at data. They just want to know what it means for them and what they should do next.

About the Data Changemaker:

David Ciommo is the Data Visualization Principal at Humana. A trained illustrator, David began his career in graphic design at Discovery Communications where he played a key role in the branding and creative development for the Discovery Kids Channel and Animal Planet Channel. Many years later, his career pivoted to data visualization & storytelling despite having no previous data & analytics background. 

At Humana, David founded the Visualization Center of Excellence, an internal site created to share style guides, tip sheets, and other resources around data storytelling and data literacy. His overarching goal is to combine purposeful human-centered design principles with first class data visualizations in an effort to provide meaningful insights and tangible actionable opportunities to the leadership at Humana.

Habit 9: Measure What You Wish to Improve | Juan Riojas, Chief Information Officer at Rackspace

Quite simply, what gets measured gets done. Think about it. If you can’t measure something, you can’t understand it. If you can’t understand it, you can’t control it. If you can’t control it, you can’t improve it.

Measure what you wish to improve. Build your action plan and make it visible.

“I’m a firm believer when you measure it, you improve. When you can put stuff out there and everybody can go in and see it, I think it’s really rallying people around one common goal.”

When you make metrics & goals visible to everyone, you’re able to rally people around one common goal. When you identify demonstrable actions that are driving a metric, people can begin to see how their work impacts the numbers.

Everybody feels like they can really contribute to it. How do I reach that outcome or result? There’s commitment. And that’s what makes a team successful.

It isn’t a novel recipe — it’s really just working as one team.

About the Data Changemaker:

Juan Riojas is the Chief Information Officer at Rackspace. As Chief Information Officer, Juan is responsible for enterprise-wide data strategy, management, and analytics to meet the need of the business through time to insight. Prior to Rackspace, Juan worked for Informatica building their inaugural Data Office and has held various executive leadership roles at Gogo, Dell, and Accenture.

He is a visionary leader with extensive expertise in global logistics, advanced analytics, and cloud transformations. Juan has been recognized for being a highly motivated, innovative and a results oriented leader with a proven track record of providing clear, practical, and creative approaches to delivering successful results.

Habit 10: Know Your North Star Metric | Cassidy Shield, SVP of Sales & Marketing at Narrative Science

Changing an organization’s culture to be data-driven is hard. It can be difficult to know where to start. Here are a few steps you can take to make data a bigger part of our decision-making process: 

  1. Choose your north star metric

Tie this metric to a strategic initiative of the company – it needs to matter broadly. 

  1. Take accountability for that metric

The true test isn’t patting yourself on the back when all is well; it’s what your team does when failing. Make the mental shift from the metric justifying your work to the metric driving your work. 

  1. Make it visible

Ensure everyone knows this is the metric you are focused on driving and why. When the metric is discussed in all-hands, your team discusses it. If you have a KPI dashboard in your company, it’s clear who is accountable to that metric and answers questions about it. This step makes it real for your team – peer pressure can be a beautiful thing.

  1. Become the expert

“Wait – one metric? Our business is more complicated, and this would never work.”  

Wrong. The beauty of a single metric is that you begin to focus on what drives this metric and what does this metric drive? The Inputs and Outputs. You break down the leading indicators and figure out how to impact those metrics to impact your metric. You look at how your metric impacts the overall business and adjust the definition necessary to drive performance.

It’s not really one metric; it’s building a systems-thinking approach for your organization.

  1. Overlay human judgment

I’m not saying to blindly let a metric drive what you do and who you are. However, without structured thinking and the discipline data provides – humans are too susceptible to cognitive bias. Use the above to reduce uncertainty, and your judgment will be that much better. The combination of data and experience is what makes for good decision-making.

About the Data Changemaker:

Cassidy Shield is the SVP of Sales and Marketing at Narrative Science. With over 20+ years of experience in the field, Cassidy has led multiple marketing teams spanning brand management, digital marketing, product marketing, customer marketing, corporate communications, market research, and end-user experience. He’s re-positioned companies for future growth, built marketing functions from the ground up, and expanded brands globally.

Cassidy is also the host of the Leading with Data Podcast where he leads conversations with D&A leaders about digital & cultural transformations and driving change with data.

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