How to Drive Action Using Data Insights

Using Data to Drive Strategy: To lead with confidence and achieve sustainable growth, businesses must lean into data-driven decision-making. When harnessed correctly, data illuminates what’s working, uncovers untapped opportunities, and de-risks strategic choices. But using data to drive strategy isn’t about collecting every data point — it’s about asking the right questions and translating insights into action. Here’s how to make informed decisions using data as your strategic compass. 1. Start with Strategic Questions, Not Just Data: Too many teams gather data without a clear purpose. Flip the script. Begin with your business goals: What are we trying to achieve? What’s blocking growth? What do we need to understand to move forward? Align your data efforts around key decisions, not the other way around. 2. Define the Right KPIs: Key Performance Indicators (KPIs) should reflect both your objectives and your customer's journey. Well-defined KPIs serve as the dashboard for strategic navigation, ensuring you're not just busy but moving in the right direction. 3. Bring Together the Right Data Sources Strategic insights often live at the intersection of multiple data sets: Website analytics reveal user behavior. CRM data shows pipeline health and customer trends. Social listening exposes brand sentiment. Financial data validates profitability and ROI. Connecting these sources creates a full-funnel view that supports smarter, cross-functional decision-making. 4. Use Data to Pressure-Test Assumptions Even seasoned leaders can fall into the trap of confirmation bias. Let data challenge your assumptions. Think a campaign is performing? Dive into attribution metrics. Believe one channel drives more qualified leads? A/B test it. Feel your product positioning is clear? Review bounce rates and session times. Letting data “speak truth to power” leads to more objective, resilient strategies. 5. Visualize and Socialize Insights Data only becomes powerful when it drives alignment. Use dashboards, heatmaps, and story-driven visuals to communicate insights clearly and inspire action. Make data accessible across departments so strategy becomes a shared mission, not a siloed exercise. 6. Balance Data with Human Judgment Data informs. Leaders decide. While metrics provide clarity, real-world experience, context, and intuition still matter. Use data to sharpen instincts, not replace them. The best strategic decisions blend insight with empathy, analytics with agility. 7. Build a Culture of Curiosity Making data-driven decisions isn’t a one-time event — it’s a mindset. Encourage teams to ask questions, test hypotheses, and treat failure as learning. When curiosity is rewarded and insight is valued, strategy becomes dynamic and future-forward. Informed decisions aren't just more accurate — they’re more powerful. By embedding data into the fabric of your strategy, you empower your organization to move faster, think smarter, and grow with greater confidence.

I watched a junior analyst present a finding that could have saved her company $2M a year. The room went silent. Everyone nodded. The CEO said, "Great work." Then they moved to the next agenda item. Six months later, nothing had changed. She never presented data again without a recommendation. Here's what she learned. You know this routine: You run the numbers. You build the dashboard. You present the report. And then… you wait. You wait for "decision-makers" to decide. That's where your role ends, right? Except you've probably watched it happen: You uncover a critical trend. Everyone nods. They call it "important" and "insightful." Then the meeting ends. The Slack thread goes quiet. The dashboard gets bookmarked and forgotten. No action. No change. No impact. Your best work, dead on arrival. Here's why: Data doesn't move the world. People do. And the person best equipped to guide the decision? Often, it's you. But somewhere along the way, we convinced ourselves that our job is to inform, not to influence. The next time you're in that room, try changing the script. Instead of stopping at: ✔ "Here's what the data shows" Go three steps further: ✅ "Here's what it means for our strategy" ✅ "Here's what I recommend we do next" ✅ "Here's the risk if we don't act" Watch what happens. The room shifts. Questions get sharper. The energy changes. You're no longer just reporting findings—you're guiding decisions. Leaders respect clarity. Teams value direction. And your insight finally has a fighting chance to become impact. Your role isn't to drop numbers on the table and disappear. You're not a human calculator. You're not a chart factory. You are: A strategist who sees patterns others miss A problem-solver who connects dots across departments. A driver of action who turns "interesting" into "essential" Your voice might be the single difference between another forgotten dashboard and a real-world change that actually matters. So the next time you're tempted to hold back because "my job is just to present the data"— Stop. Your work doesn't end at insight. It ends at impact. And impact requires you to speak up, lean in, and guide the room toward what the data is screaming at them to do. Have you ever held back a recommendation because you thought it wasn't your place to say it? What happened? Did someone else eventually make the call, or did the insight just... disappear? I'd love to hear your story.

📌 The True ROI of Business Intelligence Every company wants to be data-driven. They invest in modern data stacks, hire analysts, launch dashboards. And then… nothing really changes. Decisions are still made based on gut. Insights are acknowledged but not acted on. Dashboards are checked but not really used. Here’s the truth no one wants to admit: Being “data-driven” doesn’t mean collecting data. It means consistently taking better actions because of it. And that’s where most companies fall short. The real ROI of data analytics doesn’t happen when the report is delivered. It happens when a business process improves because of it. Let’s break it down with some examples to better understand my point: 1) A churn report doesn’t create value. → But an ops team that launches a new retention workflow based on that report? That’s ROI. 2) A marketing dashboard doesn’t grow revenue. → But reallocating ad spend based on performance patterns? That’s ROI. 3) A sales funnel visualization doesn’t close deals. → But identifying and removing a drop-off bottleneck? That’s definitely ROI. Do you see my point? So the question now becomes: How do you ensure your analytics actually lead to action? Here’s a playbook I would recommend: 1️⃣ 𝐓𝐢𝐞 𝐄𝐯𝐞𝐫𝐲 𝐈𝐧𝐬𝐢𝐠𝐡𝐭 𝐭𝐨 𝐚 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 Before you publish a report, ask yourself: “What is someone supposed to do with this?” If the answer isn’t obvious, the insight isn’t useful yet. Make it actionable and not just interesting. 2️⃣ 𝐀𝐬𝐬𝐢𝐠𝐧 𝐎𝐰𝐧𝐞𝐫𝐬𝐡𝐢𝐩 If a KPI has no owner, it has no future. → Every critical metric should have a name next to it. Not to blame, but to empower. Because action requires accountability. This is the easiest way to make people adopt your dashboards. 3️⃣ 𝐌𝐚𝐤𝐞 𝐭𝐡𝐞 𝐍𝐞𝐱𝐭 𝐒𝐭𝐞𝐩 𝐂𝐥𝐞𝐚𝐫 Your dashboard isn’t an outcome. It’s a means to make better decisions. And you should definitely make it easy for your end user. → Schedule recurring check-ins for feedback → Create a simple action log linked to KPIs → Use alerts to notify the right person when a critical KPI changes Most organizations don’t fail because they don’t have insights. They fail because they don’t have systems for what happens next. The bottom line is: A lot of companies say they want to be data-driven. But in practice? If your BI initiative doesn’t lead to action, it’s not complete. The ROI of analytics lives in the next step. Design everything you build to make that step easier, clearer, and faster. #BusinessIntelligence #DataAnalytics

As analysts, uncovering valuable insights is just the first step. The real magic happens when those insights drive action and results. Here’s how I approach turning analytics into decisions that matter: 1️⃣ Start with the End in Mind Always tie your analysis to a business objective. Whether it's increasing user retention, reducing churn, or improving operational efficiency, knowing the "why" behind your data ensures your insights are actionable. 2️⃣ Frame the Narrative Insights are only as powerful as the story behind them. Craft a narrative that’s: Clear - Avoid technical jargon; explain what’s happening and why. Concise - Highlight the key takeaways in a few bullet points or visuals. Compelling - Use data visualizations or analogies to make your insights memorable. 3️⃣ Collaborate Early and Often Actionable insights often require buy-in from multiple stakeholders. Engage key decision-makers, product managers, and engineers early in the process to align on priorities and understand constraints. 4️⃣ Provide Recommendations Data alone doesn’t drive action—recommendations do. Pair every insight with a clear next step, such as: A/B test this feature for higher engagement. Adjust pricing strategy to improve conversion rates. Focus marketing efforts on underpenetrated customer segments. 5️⃣ Quantify Impact Leverage forecasts or historical comparisons to show the potential upside of acting on your recommendations. For example, “Implementing X could increase revenue by 10% over the next quarter.” 6️⃣ Follow Through Action doesn’t end with delivering insights. Stay involved: Monitor implementation progress. Measure outcomes against your forecasts. Share success stories or lessons learned. 7️⃣ Build a Culture of Action Encourage data-driven decision-making across your organization. Host workshops, create dashboards, or share case studies of how analytics has driven impact. Insights are powerful, but actionable insights are transformative. What steps do you take to ensure your analytics drive real-world change? #data #dataanalytics #datainaction

𝗙𝗿𝗼𝗺 𝗥𝗼𝘄𝘀 𝘁𝗼 𝗥𝗲𝘃𝗲𝗻𝘂𝗲: 𝗗𝗮𝘁𝗮 𝗶𝗻 𝗧𝗵𝗿𝗲𝗲 𝗔𝗰𝘁𝘀 Most enterprises don’t fail at collecting data. They fail at turning it into impact. Confusion between data sets, data models, and data products is one of the biggest hidden taxes on transformation programs. Let’s break it down. 𝗧𝗵𝗲 𝗜𝗻𝗴𝗿𝗲𝗱𝗶𝗲𝗻𝘁𝘀, 𝗥𝗲𝗰𝗶𝗽𝗲, 𝗮𝗻𝗱 𝗦𝗮𝘂𝗰𝗲 𝗼𝗳 𝗗𝗮𝘁𝗮 Data Set (The Ingredient): Rows, columns, logs, and transactions. They provide visibility but are meaningless without context. Data Model (The Recipe): Structures data into meaning - predicting churn, segmenting customers, optimizing supply chains. Intelligence, but abstract unless operationalized. Data Product (The Sauce): What users consume - a pricing dashboard, fraud detection tool, or recommendation engine. It drives action by solving business problems. Taking an example of revenue growth management - The data set has outlet details, shipments, price lists, and promotions. The model translates this into elasticity curves, promo effectiveness, and pack architecture. The product delivers actionable guidance: which packs to push, discounts to drop, promotions to double down on. 𝗜𝗻𝘀𝗶𝗴𝗵𝘁 𝟭: 𝗢𝘄𝗻𝗲𝗿𝘀𝗵𝗶𝗽 𝗨𝗻𝗹𝗼𝗰𝗸𝘀 𝗜𝗺𝗽𝗮𝗰𝘁 Data products need dedicated owners like product managers who bridge business and technical teams. They validate use cases, ensure business alignment, and champion adoption. Ownership accelerates decisions and keeps products impactful. 𝗜𝗻𝘀𝗶𝗴𝗵𝘁 𝟮: 𝗕𝘂𝗶𝗹𝗱 𝗮 𝗣𝗿𝗼𝗱𝘂𝗰𝗲𝗿-𝗖𝗼𝗻𝘀𝘂𝗺𝗲𝗿 𝗠𝗼𝗱𝗲𝗹 Treat data products like commercial offerings. Producers focus on quality, documentation, and compliance; consumers discover and use products independently. Catalogs, self-service tools, and governance enable delivery at business velocity without sacrificing standards. 𝗜𝗻𝘀𝗶𝗴𝗵𝘁 𝟯: 𝗖𝗿𝗼𝘀𝘀-𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗧𝗲𝗮𝗺𝘀 𝗳𝗼𝗿 𝗩𝗲𝗹𝗼𝗰𝗶𝘁𝘆 Components like models, platforms, and APIs often sit in siloed teams. Leading companies form cross-functional teams that own data products end-to-end, reducing friction, accelerating innovation, and balancing enterprise consistency with business agility. 𝗧𝗵𝗲 𝗧𝗿𝘂𝗲 𝗨𝗻𝗹𝗼𝗰𝗸 When raw data, robust models, impactful products, and analytics align, data stops being a cost center and becomes a growth engine. What’s your view? Does your organization clearly differentiate between data sets, models, products, and analytics? Where are the biggest gaps or opportunities today? #DataStrategy #DataProducts #AI #Analytics #Transformation

If your CX Program simply consists of surveys, it's like trying to understand the whole movie by watching a single frame. You have to integrate data, insights, and actions if you want to understand how the movie ends, and ultimately be able to write the sequel. But integrating multiple customer signals isn't easy. In fact, it can be overwhelming. I know because I successfully did this in the past, and counsel clients on it today. So, here's a 5-step plan on how to ensure that the integration of diverse customer signals remains insightful and not overwhelming: 1. Set Clear Objectives: Define specific goals for what you want to achieve. Having clear objectives helps in filtering relevant data from the noise. While your goals may be as simple as understanding behavior, think about these objectives in an outcome-based way. For example, 'Reduce Call Volume' or some other business metric is important to consider here. 2. Segment Data Thoughtfully: Break down data into manageable categories based on customer demographics, behavior, or interaction type. This helps in analyzing specific aspects of the customer journey without getting lost in the vastness of data. 3. Prioritize Data Based on Relevance: Not all data is equally important. Based on Step 1, prioritize based on what’s most relevant to your business goals. For example, this might involve focusing more on behavioral data vs demographic data, depending on objectives. 4. Use Smart Data Aggregation Tools: Invest in advanced data aggregation platforms that can collect, sort, and analyze data from various sources. These tools use AI and machine learning to identify patterns and key insights, reducing the noise and complexity. 5. Regular Reviews and Adjustments: Continuously monitor and review the data integration process. Be ready to adjust strategies, tools, or objectives as needed to keep the data manageable and insightful. This isn't a "set-it-and-forget-it" strategy! How are you thinking about integrating data and insights in order to drive meaningful change in your business? Hit me up if you want to chat about it. #customerexperience #data #insights #surveys #ceo #coo #ai

Everyone in healthcare wants to prove ROI. But the real challenge is the disconnect between data and action. Organizations are producing more analytics than ever. But insights alone don’t drive value. They have to be connected to real decisions, interventions, and measurement. That’s where things often break down. Teams are stitching together disconnected datasets, vendor programs, and internal workflows. The result is predictable: slow action, unclear ownership, and outcomes that are nearly impossible to attribute back to any one effort. But attribution shouldn’t be the fight. If the goal is healthier members and more efficient operations, then success should be shared. What matters is whether the combined effort moves the needle. The organizations seeing real ROI are the ones connecting the full chain: better insights → clearer actions → measurable outcomes → continuous improvement. When those pieces work together, value becomes visible—not because one dataset or program "deserves credit,” but because the system is finally aligned to deliver results.

Leaders, here’s a reality check! A data-driven future isn’t just about systems and strategies—it’s about people. Your success depends on: → Connecting people to your vision → Empowering them with the tools and skills to succeed → Leading with a focus on collaboration and inclusivity Data may drive decisions, but it’s the people that unlock its full potential. As you scale your organization, don’t overlook the human connections that turn data into meaningful impact. When your people grow, your organization thrives.     Want to harness the full potential of data? Want to drive smarter decisions and stronger organizations?   Start by building an inclusive data infrastructure where everyone can:   • Access data • Act on data • Align with data   Here's how:   1. Engage Individuals Show the value of data in decision-making.   2. Educate Teams Teach them how to leverage data to meet their goals.   3. Enable Infrastructure Connect systems, drive governance, foster literacy.   4. Promote Transparency Ensure data is open and accessible.   5. Encourage Collaboration Create a culture where data is shared and used collectively.   6. Support Continuous Learning Offer training and resources to build data skills.   7. Lead by Example Use data-driven insights in your leadership.   With these steps, you can transform your organization. Or enhance the data culture you already have.   It's not just good for your people. It's good for your community, too.   Data matters. Make it count.   P.S. Want to chat about keynotes? DM me “KEYNOTE”

🚨 The data community has been chasing the wrong metric. We’ve spent years perfecting analytics: building data warehouses, lakehouses, scalable data pipelines, beautiful dashboards. We have convinced ourselves that faster insights = bigger impact. But insight alone doesn’t change outcomes.  Action does. In the past few months, I’ve had the opportunity to step out of my own data bubble and work closer with operations. I’ve realized we need to rethink how data teams create impact.  I’ve come to see three stop-and-starts that our community needs to embrace: 1️⃣ Stop doing just analytics. Start building feedback loops from analytics to operations. Insights that don’t drive action are wasted potential. It’s time to connect the dots. Connect analytics to workflows. Automate decisions. Partner with business lines to close the loop between data and impact. 2️⃣ Stop focusing only on BI semantic layers. Start building your enterprise ontology. BI Semantic layers are great, but they mostly serve analytic tools. Go deeper: model how your enterprise truly works. We need to create a map that connects customers, products, suppliers, vendors, risk, and outcomes. That’s where intelligence becomes actionable. 3️⃣ Stop staying in the data bubble. Start co-designing goals and OKRs with operations. Data can’t shape outcomes if it’s detached from them. Sit with the people who own the results. Define shared goals and OKRs. Make data a co-pilot in decisions, not a post-mortem observer. If you don’t know what the top level objectives of your company are... then that is where you should start! I truly believe that the data community must move from “faster time to insight” to “insights that drive action and outcomes.” 💭 How are you closing the loop between data & analytics and operations in your org?

Data doesn’t drive action. People do. But most data teams forget this crucial truth: There’s a massive gap between having data and creating value. And the only way to close that gap is: action. Action can look like this: → Sending customer lifetime value to Google Ads → Sending churn scores to your email tool → Sending a next-best offer to Hubspot These moves can drive real impact. But here’s the catch: You need buy-in to make them happen. And buy-in doesn’t magically appear. It’s earned: through storytelling. But even storytelling isn’t enough. Before you craft the story, you need to understand the user: → What do they care about? → What are their goals? → What are their fears? Only then can you tell a story that resonates, wins trust, and leads to action. Christian Sassano shared a brilliant framework yesterday: Data ➡️ Story ➡️ Buy-in ➡️ Action ➡️ Value I’d just add one step before all of that: Understanding the User. Data ➡️ User ➡️ Story ➡️ Buy-in ➡️ Action ➡️ Value What’s helped you get stakeholder buy-in? Want actionable tips on how to build great relationships with stakeholders and drive value in the AI-age? Join 1500+ subscribers who read my free newsletter here: https://lnkd.in/gVTdbXXE