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Data-Driven, from Hype to Reality: How to Truly Become an Innovative Company

Kirey Group


    Despite the increasing corporate spending on data management and analysis (+18% in Italy in 2023), few companies can truly be called Data Driven. According to the Data Quality 2023 Study by SD Times, only about 16% of companies are, while other studies place this figure around 20%.

    Data as the Engine of Corporate Growth

    The path to becoming a data-driven company is long and complex. Firstly, not all companies interpret the concept similarly; some believe that a simple decision support system for major strategic decisions is enough to make a company an example of data-centricity. But this is not the case.

    Borrowing from AWS's definition, a data-driven company is an organization that uses data as the engine for its growth. Data drives decision-making processes and is made available to stimulate innovation and create value for customers. An interesting aspect of this definition is that, besides recognizing data as a central asset, it does not restrict it to decision-making alone. In a data-driven company, data improves internal and external processes and relationships, and can also identify opportunities for innovation and the development of new products, services, and even business models.

    Why is it so Complex to be Guided by Data?

    Given the breadth of the phenomenon, adopting a data-centric paradigm is anything but simple. Integrating data—or rather the information derived from it—into decisions, processes, and relationships often implies a systemic transformation that not all companies have undertaken, and very few have completed.

    According to many operators and analysts, creating the so-called data culture is the main challenge. As the Harvard Business Review stated, "the biggest obstacles to creating data-driven companies are not technical, but cultural." This stems from the ubiquitous resistance to change and the depth of the transformation, which replaces established mechanisms, intuitive approaches, and experience-based methods with a truly analytical method that requires a dedicated mindset to be embraced. Being data-driven involves "a sort of ‘humility’ in recognizing that data knows more than we do,” and such an evolution can only be gradual and very progressive.

    While not representing the main concern, the technical challenge should not be underestimated. Until recently, companies interpreted their data only transactionally, confining it to silos unsuitable for supporting complex analysis activities. The significant evolution of recent years, which has completely redefined architectures, structures, and data management and analysis methodologies, was driven by the need to make companies increasingly data-driven regardless of their initial maturity and the complexity of their information ecosystem. One problem companies do not have, and never will, is the quantity of data at their disposal.

    The Path to Becoming a Data-Driven Company: 4 Essential Steps

    The transition to a data-centric model does not follow a predefined path, and it is up to each organization to identify the best route based on its business model, initial digital maturity, and the complexity of its organizational and informational ecosystem. Some companies focus on developing internal skills, others invest in innovative technologies, and still others review their processes with the aim of optimizing them through data use.

    Regardless of the starting point, the key to building an effective data-driven strategy is to adopt an integrated approach, ensuring that technological, cultural, and organizational evolution proceed hand in hand.

    1. Developing an Evidence-Based Culture

    The cultural evidence-based approach is the cornerstone of this model as it shifts the focus of decision-making from individual intuition to rigorous data analysis.

    The first step in this direction is the active commitment of top management, who must support the transformation with concrete actions and take responsibility for the change. Organizationally, data centrality is achieved by promoting a collaborative approach between technical and business skills, and by integrating data and analytics into every functional unit of the company.

    2. Findable, Accessible, Interoperable, and Reusable Data

    In a dedicated analysis, MIT highlights the key characteristics data must have to support a data-driven company: they must be findable, accessible, interoperable, and reusable.

    Although these characteristics may seem obvious in a company that bases its business on the ability to analyze and value information, often the starting point is very distant and requires intense effort to bridge the gap. For example, ensuring that all corporate data is easily findable on demand requires the implementation of modern data management architectures that cover the entire organization, integrate sources of both structured and unstructured data, and have complete and descriptive metadata that facilitate searching.

    3. Data Democratization

    Data democratization is a concept analogous to accessibility in the previous paragraph, but not limited to the technical component.

    In a modern company, every decision should be data-supported, not only those of a strategic and systemic nature. For this to happen, data must be accessible throughout the organization, and all users must have analysis skills (data literacy) proportionate to their needs. Data democratization is one of the main challenges of modern companies because it involves cultural, technical, organizational, and competency components.

    4. Continuous Experimentation and Adoption of New Technologies

    A modern company bases its competitiveness on exploiting data potential and must therefore be ready to experiment and quickly adopt new methodologies and solutions, without fearing to question traditional approaches. For example, consider the acceleration that AI has experienced in recent years: every day, increasingly sophisticated approaches, models, and algorithms are developed to extract value from data, automate processes, predict trends, and generate new insights.

    Staying Competitive in Challenging Markets

    The data-centric modernization path is certainly complex and intricate. However, it is also the only winning path for organizations that want to preserve and potentially enhance their competitiveness in markets full of agile and innovative players, who are born data-driven and have innovation and continuous change in their DNA.

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