Connecting The Dots: Communicating The Value Of Data
Bringing together industry expertise and academic insights to discuss how leaders can effectively communicate the importance of data across all levels of the organisation, getting buy-in from every part of the business. Corndel invited leading HR, L&D, data professionals and business leaders from enterprise organisations, offering a unique space to discuss and connect with peers facing similar challenges and sharing best practices.
Dr Mark Kennedy, Director of the Data Science Institute at Imperial College London and a prominent figure in the data science community, ‘connects the dots’ at our roundtable event by drawing a compelling analogy between the urgent need to develop effective data leadership and the concept of fitness, specifically data leadership fitness. Just as physical fitness demands a balance of strength, flexibility, and endurance, so does leadership in this data-driven world (Harvard Business Publishing Corporate Learning).
Developing leadership fitness requires finding the balance between thriving today and tomorrow, a strong vision for the future, the flexibility to adapt to immediate needs, and the endurance to stay committed over time. Keeping a slow and steady pace forward will build true resilience and growth across organisational capabilities. Dr. Kennedy shares that becoming fit, whether physical or data-driven, is a journey. It doesn’t matter where you start—whether you’re about to buy your first pair of running shoes or already running marathons. The key is simply to begin.
"Can machines think?"
In the early 1950s, Alan Turing, a brilliant mathematician, posed a question that set the stage for a revolution in artificial intelligence (AI): “Can machines think?” His proposal, known as the Turing Test, was an imitation game where a machine’s ability to exhibit human-like intelligence would be tested through text-based conversations. This groundbreaking idea planted the seeds for what we now call AI.
Turing’s vision was ahead of its time. However, as AI evolved, the limitations of the Turing Test became apparent. AI dramatically transformed from early imitative AI to sophisticated substantive AI capable of learning and adapting, continuing with generative AI, which creates new content and drives innovation across industries, and additive AI, which enhances human capabilities by introducing new tasks and opportunities. These rapid advancements suggest AI will play a critical role in shaping our future, highlighting the importance of effective data management as organisations become capable of tasks that Turing could only dream of.
We now operate in an expanding dataverse, brimming with data from countless sources. As we delegate tasks to machines, we must have the necessary human and technical skills to provide correct inputs that directly impact the outputs these systems generate. Mastering this dynamic between humans and machines is essential for data leadership.
Challenges in data science: Navigating the new frontier
Dr Kennedy outlines three significant challenges for organisations and data science:
Fundamentals of data science: With the rapid advancement in technology and sensing capabilities, understanding the fundamentals of data science is more critical than ever. Leaders must grasp the basics to make informed decisions about effectively leveraging data.
Model variety: The diversity of AI models can be overwhelming. It’s crucial to distinguish between genuine expertise and those who lack substance. True experts can explain complex concepts in simple terms, avoiding the obfuscation often seen in discussions about AI.
Evolving standards: The standards for good data science are constantly evolving. Staying ahead of these changes requires continuous learning and adaptation to remain competitive.
Building data assets and organisational capabilities: The foundation of success
In this expanding AI and dataverse, organisations must focus on building robust data assets and enhancing their organisational capabilities. Data assets include the vast amounts of information generated and collected by businesses, which can be transformed into actionable insights. However, possessing data alone is not enough; the ability to analyse, interpret, and apply this data effectively drives competitive advantage.
Drawing from Dr. Mark Kennedy’s advice and roundtable discussions, several key insights and strategies for building these capabilities emerged:
Infrastructure: Organisations must have the proper infrastructure to securely collect, store, and manage data. This includes investing in advanced analytics platforms and tools that enable seamless data integration and processing. Those in attendance recognised they needed greater data expertise to ask the right questions of data professionals to guide their infrastructure investments effectively.
Data-driven culture: Creating a strong data culture is essential. Across all of our roundtables, we heard that “data storytelling”, “insight building”, and “data literacy” continue to be growth areas, revealing that leaders should focus on encouraging collaboration across departments, breaking down silos, and promoting data literacy at all levels. Employees must be empowered to use data in their decision-making processes, supported by ongoing training and development programmes. Leaders noted the importance of presenting data-led recommendations simply.
Leadership and collaboration: Dr. Kennedy emphasised that effective data leadership must champion the use of data, demonstrating its value through clear, impactful use cases. Effective communication between tech leads and people leads is crucial to break down silos and drive strategy. Our roundtables echoed this, where participants highlighted the need for data project leads who can bridge the gap between IT and business units.
Utilising AI: The roundtable discussions revealed a general positivity towards AI’s potential to streamline processes and improve jobs, with leaders keen to understand how best to use AI. Leaders also recognised the ethical and practical challenges of AI implementation, ensuring that AI-driven growth aligns with organisational values.
Skills gaps and training: Many roundtables were aware of skills gaps within their teams, often relying heavily on basic tools like Excel. To bridge these gaps, custom solutions and targeted training are necessary. Empowering employees to “connect the dots” by self-servicing their analytics and making informed decisions without relying solely on data analysts is crucial. Leaders should ensure that their teams are equipped with the latest knowledge and skills in data and AI, fostering a culture of continuous learning and adaptation.
Top-down support: Embedding a data-driven culture requires top-down support. Participants of the roundtables believe it is crucial to create roles like Chief Data Officer (CDO) and Chief People Officer (CPO) to legitimise the use of work time for upskilling in data and AI. Creating these roles also ensures that data governance and ethical considerations are integral to an organisation’s data strategy.
Dr. Kennedy encapsulated these insights perfectly: “Building data assets, organisational capabilities, and collaborative relationships are essential. There’s no easy way to get fit and, likewise, no shortcut to successful data leadership. You need to go through all the steps.”
James Kelly, CEO and Co-Founder of Corndel
As James Kelly, CEO and Co-Founder of Corndel, aptly described: “The magic ingredient for us is when the people skills, data skills, and tech skills come together at an intersection of skills. We’re convinced that this intersection—where diverse thinking, data, human skills, and technology come together—is what’s going to make organisations successful.”
The path forward: Building data leadership fitness
An explosion of technology powered by data and AI is fundamentally changing how we live, work, and relate to one another, driving unprecedented transformations across industries all across the globe. Organisations that harness the power of data and AI will lead this wave of innovation, creating new business models and enhancing the quality of life globally.
A GenAI era demands a new type of leadership to steer organisations through great change and ambiguity. Building data leadership fitness will involve more than technical know-how. It requires innately human skills, like collaborative relationships, storytelling, stakeholder management, and making a persuasive case for data-driven initiatives. Developing this intersection of skills will ensure that all parts of the organisation work together to maximise the potential of data and AI.
The journey from Turing’s imitation game to today’s sophisticated AI systems is a testament to humanity’s pursuit of growth, making data leadership fitness more critical than ever before. Leaders can confidently steer their organisations through digital transformation by balancing vision, flexibility, and endurance and building robust data assets and organisational capabilities. The key is to take the next step, however modest, and keep moving forward. Slow and steady progress will build the resilience needed to thrive in a complex, ever-changing environment.
