Assessing the Strength of Your Data Strategy

What is #dataculture really made of? To move beyond vague slogans, we are breaking it down into four practical, observable dimensions. This framework is what we use to assess where organizations stand and where to start when trying to strengthen #data culture. 🧠 Mindsets & Beliefs The internalized values and assumptions people hold about data and its role in their work: > Employees believe that data is a shared asset and a critical enabler of their success. > People trust data and feel responsible for maintaining its integrity. >Curiosity and experimentation with data are encouraged and celebrated. 🏢 2. Organizational Norms The shared practices, expectations, and structures that support a consistent and collaborative approach to data: > Leadership uses data in communication and decisions. > KPIs and definitions are standardized and shared across teams to drive alignment. > Collaboration between business, technology, and data teams is trusted, fluid, and ongoing. 👥 3. Individual & Team Behaviors The everyday habits and interactions through which people demonstrate ownership and fluency with data: > Teams proactively involve analysts and data experts when solving problems. > Team members respectfully challenge each other using data and logic. > Teams operate with an awareness of the externalities of their data, proactively helping others access or understand data when needed. 🔁 4. Decision-Making Systems & Processes The formal and informal mechanisms through which data is applied to improve decision quality and organizational learning. > Data is actively used to ground decisions at all levels. > Intuition is respected, but at appropriate times tested against evidence. > Key decisions are tracked and revisited to assess outcomes and refine approaches. If your company is trying to get more value from its data but something isn’t clicking, this framework can help pinpoint where to focus.

Steps the CFO can take to ensure the data strategy isn't just a static plan but a dynamic tool for success - keeping it aligned with the business goals and continually optimized for maximum impact 👇 A successful data strategy hinges on two vital practices: setting clear Key Performance Indicators (KPIs) and fostering a culture of constant improvement and iteration. 📌 Setting the Right KPIs KPIs are your navigation tools in the sea of data. They are measurable values that give you a clear picture of how effectively your data strategy is being implemented. Choosing the right KPIs is crucial, as they should reflect and support your broader business objectives. For instance, you might measure: 1️⃣ Data Quality: How accurate and consistent is your data? 2️⃣ Data Accessibility: How easily can your team access the data they need? 3️⃣ Data Utilization: Are you effectively using data to inform decisions? 4️⃣ Data Security: How well are your data security protocols performing? These KPIs will differ based on your specific goals and the nature of your business, but tracking them consistently will help pinpoint areas for improvement and guide your strategic decisions. 📌 Cultivating Continuous Improvement Your data strategy should be a living, breathing entity, evolving with your business. This means regularly evaluating its effectiveness and making necessary tweaks. Creating a culture that values continuous feedback and collaboration is key routinely engaging with various stakeholders, collecting their inputs, and acting on them will keep your strategy responsive and relevant. Stay on the cutting edge of data management trends and innovations. Participate in industry forums, attend workshops, and network with peers to keep your strategy fresh and forward-thinking. Remember, your data strategy is a journey, not a destination. By attentively monitoring your KPIs and embedding a culture of perpetual growth and refinement, you can ensure your data strategy remains a robust, impactful part of your business operations. Connect with me and the eCapital Advisors team, and let's turn your data strategy into your strategic advantage. 🔽 🔽 🔽 👋 Hi, I'm Lisa. Thanks for checking out my Post!   Here is what you can do next ⬇️   ➕ Follow me for more FP&A insights    🔔 Hit the bell on my profile to be notified when I post   💬 Share your ideas or insights in the comments ♻ Inform others in your network via a Share or Repost #digitaltransformation #finance #business #technology #cfo

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.

We can't be friends... ...if your data strategy = picking data tools. That’s not a strategy. That’s a shopping spree. Yet I still see “data strategy” decks that are 80% vendor logos and 20% vibes: - “We’ll use dbt for transformation” - “Snowflake is our single source of truth” - “Looker for self-serve” Cool. And? - Linda from Marketing is still downloading all your dashboards to Excel - CEO Lisa still emails you every weekend why revenue numbers don't add up - And your Engineer Luis is still spending 80% of his time hot-fixing bugs Here’s a truth most people avoid: If your org is confused, misaligned, or drowning in dashboards… no tool is going to fix that. A real data strategy starts with clarity: - What's our company vision and mission? - What business objectives will get us there? - Who is driving these business objectives? - What's their key struggle to get there? - How do our data products empower them? Answer those well and your tool choices become obvious. Skip those and you’ll keep mistaking motion for progress. 📉 Tech stacks don’t drive business outcomes. 🧠 People, context, and clear thinking do. ♻️ Repost if you've ever seen a "data strategy" doc that was just a modern art collage of logos → Follow me, Sebastian, for daily insights on building impactful data teams in the AI-era.