Article
    by Jukka Kostiainen, Value Architect, Nortal Finland

    Moving the data discussion from the engine room to the boardroom

    The secrets of successful C suite leaders.

    Service

    Data and AI

    Industry

    Industry Manufacturing

    Today, the industrial companies that thrive are those that shift from hindsight to foresight, leveraging real-time data and AI to spot potential disruptions early, enhance energy efficiency, and allocate resources where they’re needed most – before bottlenecks occur. Real-time data is no longer just a technical detail, but a boardroom priority: the catalyst for AI innovation and a key driver of both resilience and long‑term competitive strength.

    As a CEO or C‑level executive, the question isn’t whether to invest in your company’s data foundation, but how to lead the organization to become truly data-driven. To excel, one must champion data-driven decision-making at every level – from the engine room to the boardroom. In this article, we share best practices learned from executive leaders setting the benchmark among our customers. These insights may resonate with any leader tasked with putting data at the center of their company’s business.

    The executive leaders’ role in data: bridging strategy and execution

    In our previous article, “Real-time data + real AI = real solutions to factory floor problems,” we explained why combining real-time data with AI-powered analytics is a game-changer for industrial companies. Together, real-time data and AI unlock transformative efficiencies by turning yesterday’s reports into actionable foresight: from optimizing logistics to preventing costly equipment failures. These are business opportunities that directly impact company’s profitability and competitiveness.

    While working with clients on data foundations and the shift to real-time data and analytics, we’ve noticed several common patterns among successful executive leaders. These patterns reveal what makes a data strategy succeed – and they might surprise you. Here are four things that set the most effective leaders apart. Next, we will take a closer look at each of these elements and unpack what they mean in practice.

    #1 Start with why and how data pays off

    In working with organizations across industries, one consistent lesson is that successful data-driven transformation begins with clarity of purpose rather than technology. The leaders that excel in data‑driven transformation create a data and technology vision rooted in business strategy. If your strategy centers on margin protection, sustainability, or customer experience, data initiatives must align with those priorities. This alignment ensures every euro invested supports the business, not just technology modernization.

    Digitalization should be treated as a strategic asset. Like any asset, it requires disciplined investment and must ultimately generate shareholder value. A strong business case for a data foundation is invaluable yet often overlooked. Too often, the focus is on implementation and capabilities, while the assessment of value creation, especially long-term profitability, is neglected.

    If an organization lacks a standardized investment evaluation model, the minimum requirement should be to calculate the return on investment (ROI) for the data foundation. ROI is an intuitive and straightforward measure of investment efficiency, but it comes with clear limitations. It ignores cash flow timing, can be misleading for long-term initiatives, and does not reflect absolute value creation.

    Net Present Value (NPV) offers a more robust basis for decision-making. By considering the timing of cash flows and the cost of capital, NPV directly aligns with shareholder value creation. However, NPV is also more complex and sensitive to assumptions about future cash flows and discount rates.

    Many organizations struggle to clarify the opportunities within data foundations. That’s why we work closely with business owners to calculate returns and uncover hidden costs before making technology decisions. The value of a strong data foundation and data-driven business typically falls into three categories:

    A) Growth: Structured, real-time data unlocks new revenue streams and innovative business models.

    B) Risk mitigation: Up-to-date, synchronized data supports compliance and strengthens resilience.

    C) Efficiency: A modern, fit-for-purpose technology foundation harmonizes technology architecture and reduces costs associated with legacy systems.

    The executive leaders who succeed in data‑driven transformation invest time and effort in communicating the data vision and business case — anchored in the company’s strategy — in ways that inspire the entire leadership team. Data-driven transformation isn’t confined to a single function; it changes how the whole company operates and requires commitment from all members of the leadership team.

    Just as it is crucial for executive leaders to engage and commit the leadership team, it is equally important to keep the board of directors informed about the data transformation. Building a competitive business strategy is a core responsibility of the board, so they must understand how data supports strategic priorities. In these discussions, leaders are better equipped when they have a solid, grounded business case to support their data-driven rationale.

    #2 Draw the use case roadmap and rigorously monitor progress

    Once the vision is clear and backed by robust numbers from the business case, the executive leaders who succeed in data‑driven transformation ensure their teams have a strong grasp of the most compelling use cases for the data platform. As we noted in our previous article, generative AI can sometimes seem like a hammer seeking nails. However, the most valuable industrial use cases for data and AI often emerge in areas like machine learning and other real-time analytics applications.

    As the world transitions from digital to post-digital, our methods of measuring success must also evolve. While traditional long-term metrics like ROI and NPV remain vital for assessing digital investments, they are fundamentally lagging indicators – reflecting past outcomes. A post-digital mindset requires looking ahead, not behind. To manage and optimize value creation in real time, organizations need to break down high-level KPIs and deeply understand how value is generated throughout the operation, down to the shop floor. This approach enables timely course corrections and more informed decision-making. Teams can then use these insights to refine their roadmap, nurture value, and scale successful practices into enterprise-wide capabilities.

    One of our customers’ executives exemplifies this shift by monitoring energy consumption and costs in real time to track the day-to-day evolution of the profitability of digital investments. At the shop-floor level, KPIs become even more concrete, for example, measuring the percentage of time optimized setpoints are applied in the production process. These operational indicators provide early signals of digital solutions adoption and whether their value potential is being realized.

    This is the essence of post-digital leadership: not just deploying technology, but orchestrating value. It is also at the heart of how we can support industrial leaders. We combine deep technological expertise with a strong understanding of industrial processes and business models, enabling organizations to connect strategic financial outcomes with operational execution and real-time performance management.

    Discover how we can help you leverage Microsoft Fabric for real-time, compliant data

    #3 Technology pilots come first, scale follows later

    Technology should enter the conversation only after the vision and expected outcomes are clearly defined. Ultimately, the goal is not to buy tools, but to enable capabilities that deliver business value. When the entire leadership team is aligned on the vision, the business case, and the initial use cases, selecting the right technology stack is based on facts, not beliefs.

    Modern platforms like Microsoft Fabric enable organizations to unify operational and analytical data, generate real-time insights, and scale across the enterprise. However, even the best technology will fail without a pragmatic, stepwise approach. In our experience, the most successful organizations begin with a few high-impact pilots, run them in short cycles, and measure and communicate results. They then use the learnings to refine their technical architecture and integrations, organizational capabilities, processes, and their operating model before scaling. This approach reduces risk and accelerates time-to-value.

    #4 Empower your people to power the transformation

    Technology alone does not transform a business – people do. Change management is often underestimated, yet it is the single most significant factor in realizing value. Organizations must be prepared to use data in decision-making. Executive leaders who excel in data‑driven transformation recognize the need to train teams, redefine roles, and embed new routines, and allocate the time and resources required to put them into practice. Preparing the organization for the transformation also means fostering a culture that shifts from reactive firefighting to proactive planning. Without this investment in people, even the most advanced solutions will underperform.

    Real-time data and data-driven transformation are no longer optional – they are the foundation for resilience and growth in modern industrial environments. Executive leaders and teams that succeed don’t treat data as an IT upgrade but as a strategic asset. They start with vision, build a solid business case, and lead their people – at both the operational and board levels – through change with confidence. The question isn’t if you’ll transform, but how fast and how far you’ll go.

    man holding tool sparks flying
    man holding tool sparks flying
    man holding tool sparks flying
    man holding tool sparks flying
    man holding tool sparks flying

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