Tips for Developing a Data-Driven Team Mindset

Creating a data-driven culture doesn’t happen overnight — it’s something you have to build 𝐢𝐧𝐭𝐞𝐧𝐭𝐢𝐨𝐧𝐚𝐥𝐥𝐲. After my last post, I got a lot of questions about practical tips we can take to create that culture within our organizations. So here's 4 actionable steps you can take starting today 👇 🔑 Provide easy access to data This is the simplest one. People need to be able to interact with something to see its value. At the very least, have a dashboard for important KPIs that is accessible to everyone in the company. Take the time to design it so it's intuitive and easy to understand (more on data UX later). I've also seen companies use Slackbots as an effective way to push weekly updates to relevant channels. 📚 Encourage data literacy Data without any context is just numbers. Make it easy for everyone to understand what each chart or value means. When in doubt over-communicate and explain exactly the definition behind everything in detail. This can be tooltips, a text FAQ at the bottom of your dashboard, or even a full-blown wiki. Just make sure it's easy to consume and not buried. When you get more advanced, you can offer internal training sessions or office hours. These venues can enable people to ask more specific questions relevant to their job, and even get some hands-on training with how to manipulate data. 🧑🔬 Make data core to the decision-making process As your team is deciding on the next initiative to focus on, bring data to help make your case. And push others to back up their ideas with data. Approach it by discussing a trend or unique segment that might indicate an opportunity. Create a hypothesis for why this data looks this way and what it means. If you can then project how these numbers would change based on your initiative, that's even better. 🎊 Celebrate data-driven wins After you're using data to inform your decisions, use it to help tell a story about new initiatives. Show the broader organization how data-driven decisions lead to success. The more people see data being used successfully, the more value they will see in it and want to join in themselves. When data becomes part of your company’s DNA, it empowers every team to make smarter decisions, innovate faster, and drive growth. What things have you tried to evangelize the importance of data within your organizations? Let me know in the comments!

Spend time teaching your team to think with #data! 📊 It’s one of the best investments you’ll make as a #founder. Here’s how I’ve approached it with my team: Focus on purpose. Before diving into data, we always start with one question: “What are we trying to answer?” For example, when optimizing #GoogleAds campaigns, we ask, “Which keywords drive the most #conversions?” If we see unqualified #leads, we ask, “Is it the ad creative, the audience, or the landing page misaligned?” From there, we tweak the ad copy, adjust the #target audience, or refine the #valueproposition on the landing page. Train them to dig deeper. Not all data is created equal. So, train your team to filter noise, spot patterns, and align insights with goals. For example: Low email open rates? Run A/B tests on subject lines to identify what resonates. Low email click-through rates? Evaluate #CTA placement, wording, and design. Encourage curiosity. I set aside time for the team to ask “What if?” and test ideas, fostering an exploration environment. Foster curiosity with “What if?” scenarios and hypothesis testing. For example: We asked, “What if we target high-LTV customers for #AmazonAds?” It led to a big boost in click-through rates and revenue. Noticing high bounce rates, we added a downloadable resource. Adding it improved time-on-site and lowered the bounce rate significantly. Connect insights to action. Data is useless if you don’t act on it. Teach your team to turn insights into next steps immediately. For example: We noticed tools demo segments from our #webinars were the most engaging. By posting those clips on #socialmedia, we saw a significant increase in audience engagement. Build confidence through practice. For many, data analysis can feel overwhelming. To help, we’ve started regular “data sessions,” where team members present their findings from recent campaigns, like a #Facebook ad experiment. What steps are you taking to help your team think with data?

One of the earliest things I did as a new people leader was create tenets with my team. Tenets are the principles that guide how we work and make decisions every day. They’re not fixed rules. They’re what we believe works best right now. They guide our choices today, but if we find a better way tomorrow, we update them. Looking back, I believe creating tenets as one of the first things we did mattered because we were all feeling a little uncertain with changes happening on our team. Creating tenets gave us something to hold onto. It was a way to bring us together and ground us in what the future could look like together. We started with conversations about what mattered to us, what we wanted to stand for, and how we’d make decisions quickly. Here's a look at the tenets from my very first team. I actually still follow all of these now! 1️⃣ We advocate We advocate for our learners and believe that effective learning design begins with understanding and championing their needs. 2️⃣ We consult We consult to find the right solution for our customers. We ask thorough, thought-provoking questions to deliver complete, integrated, and cross-functional solutions. When learning isn’t the right solution, we offer appropriate alternatives. 3️⃣ We build for reusability We build for reusability and scale. Whenever possible, we leverage what already exists and avoid reinventing the wheel. 4️⃣ We pursue meaningful measurement We relentlessly pursue meaningful measurement. We use data-driven practices and strive to achieve optimal financial, operational, and experiential outcomes. 5️⃣ We iterate and invent We iterate and invent based on data to drive our improvements. We refuse to be blocked by what has or has not worked in the past. 6️⃣ We invest in our own learning We are invested in our own learning as much as our customers’ and don’t back down from solutions that require growth of our skills or knowledge. Those tenets became our team's anchor. Through change, competing priorities, and big ideas, they reminded us who we were as a team and how we wanted to show up in our work. What tenets guide your team or what’s one tenet you’d add to your team today? #learninganddevelopment #instructionaldesign #leadership #teambuilding #culture #futureofwork #elearning

Last week, I posted about data strategies’ tendency to focus on the data itself, overlooking the (data-driven) decisioning process itself. All it not lost. First, it is appropriate that the majority of the focus remains on the supply of high-quality #data relative to the perceived demand for it through the lenses of specific use cases. But there is an opportunity to complement this by addressing the decisioning process itself. 7 initiatives you can consider: 1) Create a structured decision-making framework that integrates data into the strategic decision-making process. This is a reusable framework that can be used to explain in a variety of scenarios how decisions can be made. Intuition is not immediately a bad thing, but the framework raises awareness about its limitations, and the role of data to overcome them. 2) Equip leaders with the skills to interpret and use data effectively in strategic contexts. This can include offering training programs focusing on data literacy, decision-making biases, hypothesis development, and data #analytics techniques tailored for strategic planning. A light version could be an on-demand training. 3) Improve your #MI systems and dashboards to provide real-time, relevant, and easily interpretable data for strategic decision-makers. If data is to play a supporting role to intuition in a number of important scenarios, then at least that data should be available and reliable. 4) Encourage a #dataculture, including in the top executive tier. This is the most important and all-encompassing recommendation, but at the same time the least tactical and tangible. Promote the use of data in strategic discussions, celebrate data-driven successes, and create forums for sharing best practices. 5) Integrate #datascientists within strategic planning teams. Explore options to assign them to work directly with executives on strategic initiatives, providing data analysis, modeling, and interpretation services as part of the decision-making process. 6) Make decisioning a formal pillar of your #datastrategy alongside common existing ones like data architecture, data quality, and metadata management. Develop initiatives and goals focused on improving decision-making processes, including training, tools, and metrics. 7) Conduct strategic data reviews to evaluate how effectively data was used. Avoid being overly critical of the decision-makers; the goal is to refine the process, not question the decisions themselves. Consider what data could have been sought at the time to validate or challenge the decision. Both data and intuition have roles to play in strategic decision-making. No leap in data or #AI will change that. The goal is to balance the two, which requires investment in the decision-making process to complement the existing focus on the data itself. Full POV ➡️ https://lnkd.in/e3F-R6V7

I thought tools were the key to data success. But tools never fixed the real problem: For years, I chased the latest stack, governance model, or dashboard tool. But the real reason data teams struggle? → Limiting beliefs Here are 5 mindset shifts that changed everything for me: 1. From victim to owner: Stop blaming “bad data culture.” Start delivering business outcomes. 2. From perfect to pragmatic: Progress > perfection. MVPs win. 3. From control to enablement: Build for usability, not control. 4. From tech stacks to products: Relentless focus on stakeholder problems. 5. From reporting to value: Quantify impact. Build like a business unit. These shifts aren’t obvious. Some are painful. But they are necessary. I learned them the hard way - over a career that spanned marketing, data engineering, global leadership, and product. You don’t have to. Yesterday, I shared how to break free from the mindset traps holding your data team back with 3,000+ data leaders. 👉 Read the full story here: https://lnkd.in/gPs72pGV ♻️ Repost if you’re tired of building dashboards no one uses.