How to Build a BI and Analytics Strategy

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.

Too many teams accept data chaos as normal. But we’ve seen companies like Autodesk, Nasdaq, Porto, and North take a different path - eliminating silos, reducing wasted effort, and unlocking real business value. Here’s the playbook they’ve used to break down silos and build a scalable data strategy: 1️⃣ Empower domain teams - but with a strong foundation. A central data group ensures governance while teams take ownership of their data. 2️⃣ Create a clear governance structure. When ownership, documentation, and accountability are defined, teams stop duplicating work. 3️⃣ Standardize data practices. Naming conventions, documentation, and validation eliminate confusion and prevent teams from second-guessing reports. 4️⃣ Build a unified discovery layer. A single “Google for your data” ensures teams can find, understand, and use the right datasets instantly. 5️⃣ Automate governance. Policies aren’t just guidelines - they’re enforced in real-time, reducing manual effort and ensuring compliance at scale. 6️⃣ Integrate tools and workflows. When governance, discovery, and collaboration work together, data flows instead of getting stuck in silos. We’ve seen this shift transform how teams work with data - eliminating friction, increasing trust, and making data truly operational. So if your team still spends more time searching for data than analyzing it, what’s stopping you from changing that?

Recently, in one of our meetings, someone pitched an incredibly innovative idea. It was bold, creative, and backed by the latest tech. We were all impressed. But as the conversation evolved, it became clear that while the idea was brilliant, it didn’t solve any real problem. This isn’t rare. In the world of tech, we often get caught up in building cool. What we really need is to build useful. The real challenge isn’t just creating advanced technology, it’s ensuring that the people it’s built for can actually use it to drive outcomes. This is the gap between building and using, Between production and consumption . At MathCo, we’ve learned (sometimes the hard way) that success lies not just in building powerful solutions, but in making sure they are adopted, understood, and embedded into everyday decisions. So how do we bridge this gap? * Start with the decision, not the data. Understand how decisions are made before building anything. * Define value in business terms. Establish specific business metrics that demonstrate value upfront. * Think about the whole solution. Build the technology, processes, and change management as one integrated system. * Build adoption into the analytics. Make it easy to use. Create solutions that fit into how people already work. * Design for iteration. Create feedback mechanisms that improve both the analytics and its application over time. It’s not the features, but the fit that matters most. What's your experience? Has your organization successfully bridged this gap between analytics and adoption? #TechThatWorks #InnovationWithPurpose #OwnYourIntelligence #EnterpriseAI #AdoptionFirst

The unprecedented proliferation of data stands as a testament to human ingenuity and technological advancement. Every digital interaction, every transaction, and every online footprint contributes to this ever-growing ocean of data. The value embedded within this data is immense, capable of transforming industries, optimizing operations, and unlocking new avenues for growth. However, the true potential of data lies not just in its accumulation but in our ability to convert it into meaningful information and, subsequently, actionable insights. The challenge, therefore, is not in collecting more data but in understanding and interacting with it effectively. For companies looking to harness this potential, the key lies in asking the right questions. Here are three pieces of advice to guide your journey in leveraging data effectively: 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲 𝟏: 𝐄𝐬𝐭𝐚𝐛𝐥𝐢𝐬𝐡 𝐆𝐨𝐚𝐥-𝐎𝐫𝐢𝐞𝐧𝐭𝐞𝐝 𝐐𝐮𝐞𝐫𝐢𝐞𝐬 • Tactic 1: Define specific, measurable objectives for each data analysis project. For instance, rather than a broad goal like "increase sales," aim for "identify factors that can increase sales in the 18-25 age group by 10% in the next quarter." • Tactic 2: Regularly review and adjust these objectives based on changing business needs and market trends to ensure your data queries remain relevant and targeted. 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲 𝟐: 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞 𝐂𝐫𝐨𝐬𝐬-𝐃𝐞𝐩𝐚𝐫𝐭𝐦𝐞𝐧𝐭𝐚𝐥 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬 • Tactic 1: Conduct regular interdepartmental meetings where different teams can present their data findings and insights. This practice encourages a holistic view of data and generates multifaceted questions. • Tactic 2: Implement a shared analytics platform where data from various departments can be accessed and analyzed collectively, facilitating a more comprehensive understanding of the business. 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲 𝟑: 𝐀𝐩𝐩𝐥𝐲 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 • Tactic 1: Utilize machine learning models to analyze current and historical data to predict future trends and behaviors. For example, use customer purchase history to forecast future buying patterns. • Tactic 2: Regularly update and refine your predictive models with new data, and use these models to generate specific, forward-looking questions that can guide business strategy. By adopting these strategies and tactics, companies can move beyond the surface level of data interpretation and dive into deeper, more meaningful analytics. It's about transforming data from a static resource into a dynamic tool for future growth and innovation. ******************************************** • Follow #JeffWinterInsights to stay current on Industry 4.0 and other cool tech trends • Ring the 🔔 for notifications!

If you're building a data career, mastering the art of measurement planning can be one of the most effective ways to differentiate yourself from your peers. Companies need people who are thinking about this every time they launch a new initiative. If you can develop strong skills here, it can be your ticket to getting involved earlier on, in more projects, and to becoming seen as a true strategic partner in your organization. Here's what you should focus on... 1. Think Business First -> Resist the urge to dive straight into the data. -> Understand how critical this project is to the business. -> Ask what the key goals for the initiative are. -> What are the most important questions you'll answer? 2. Know Your Audience -> Who is driving the project? Is this the primary audience? -> What are the goals and incentives of key stakeholders? -> What data can you provide that will help them? -> What types of info may inspire them to take action? 3. Define the Key Performance Indicators (KPIs) -> For the goals identified, translate them to metrics -> Prioritize metrics based on importance to stakeholders -> Go a layer deeper, and think about KPI driving levers -> How do you picture optimizing the businesses KPIs? 4. Identify the Data Sources You'll Need -> Where will you get each data point you need? -> Who owns or manages each existing data source? -> Are the data sources available real-time? -> Are there gaps in existing data? How do you fill them? -> How can you automate or streamline reporting? If you can follow this framework, you should be able to break down any project and build a measurement plan that will help your organization identify goals, understand outcomes, and optimize performance to drive the business to new heights. We've got a free guide that goes deeper on this, called 'How to Build a Measurement' plan. CHECK IT OUT: --> https://bit.ly/3eaXGmq @ Data Pros - what else would you add here? #data #analytics #businessintelligence #measurement #planningforsuccess