The dark side of the moon: the human touch in the age of data

"The dark side of the moon" is one of Pink Floyd's most famous songs and a monumental success in music history. It’s also a fitting expression for something hidden from view but still significant.

It is a powerful metaphor for the often-overlooked role of people in data strategy, often neglected but essential for success since its influence can make or break the effectiveness of every initiative. This encompasses both the human element itself and its active and passive interactions with data strategy – i.e. how people influence its evolution and how they are impacted by it.

People's opinions, preferences, biases, choices and actions can generate negative effects - like roadblocks, course changes, obstacles and friction - or positive ones like innovation, alignment and smoother implementation. This space includes those directly involved in the design or leadership of transformation processes and those who experience the effects to varying degrees of separation.

These aspects often remain overshadowed by more visible and immediate factors. However, if they are treated superficially, sidelined or ignored - viewed as marginal, out of scope, or irrelevant - they can lead to deficiencies, inefficiencies or failures in data strategy and beyond!

In this article, I will discuss the essential elements of a data strategy that places the human element at its core. The insights shared here come from my personal experience as a data strategy advisor at Quantyca - Data at Core , where I’ve led many initiatives in this field. I also draw on the book "Humanizing Data Strategy" by Tiankai Feng , which offers many valuable insights and aims to make the human aspect more practical and help data professionals apply it effectively in their own organization.

Let’s start by briefly explaining the goal of a data strategy.

Why data strategy should matter to you

If I had to come up with a riddle, I'd say:

“Everyone talks about it, many try, some reap the benefits, few truly understand it and no one finds it easy”.

Some wise guy might reply with "marriage!" or "being an entrepreneur!" - valid answers, perhaps, but here we’re talking about data strategy.

Let's take a closer look at what it’s about. On the first pages of Tiankai Feng's book, he shares one of the best definitions of Data Strategy I've come across:

“Data strategy is a long-term plan that defines the people, processes, and technologies to create, process, and use data to intentionally drive value in a meaningful, secure, and transparent way.”

I think this definition captures and explains everything effectively, so I’ll start here to break down its meaning - step by step.

It is a long-term plan

Given its impact, it’s not something typically wrapped up quickly. It usually spans months or even years, depending on the scope, complexity of the organization and ambition of the project. However, it's important to note that a sound data strategy doesn’t aim to build the pyramids – i.e. projects that start but never seem to end. Instead, it sets medium- to long-term goals and proceeds with an incremental and iterative approach, executing various initiatives based on priority.

It encompasses the entire organization

It closes the loop between people, processes and technologies. This necessitates a detailed analysis through interviews and deep dives, as understanding these aspects is crucial to grasp the starting point, goals, constraints, solutions and possible paths. The relevance and complexity of these three dimensions - people, processes, and technologies - can vary greatly across organizations making it crucial to approach them without stereotypes and avoid a "one-size-fits-all" method.

It covers the entire data lifecycle

It addresses every stage of data management, from the initial creation and collection of raw data to its processing, distribution, analysis and consumption. A robust data strategy ensures that each step in the lifecycle is aligned with the organization's goals and that data flows smoothly and efficiently through the pipeline. It also specifies how data governance, security and compliance are managed throughout the lifecycle. Moreover, the strategy must be adaptable to changes, whether they are semantic adjustments, technological advancements or shifts in business objectives, and should promote continuous improvement in how data is handled and leveraged. A mature data strategy not only maximizes the value derived from data but also ensures that data assets are managed sustainably over time.

Intentionally drives value

This particularly resonated with me and touches on a critical point for many organizations: a data strategy is a plan and, as such, should serve to achieve a goal. For organizations, the goal is to create value - and especially in today’s world - this is achieved mostly through data. For instance, we’re saying that data should produce value not by chance but because it’s designed to do so: it’s fit-for-purpose. This implies also that nobody should waste time and resources on useless data, which also implies that people must evaluate clearly in advance what data is needed and why. This goes somewhat against what has been preached over the past decade with the rise of data lakes and the philosophy of "load all the data you like and decide later what to do with it" - pure madness.

Acts in a meaningful, secure, and transparent way

This refers to the essential characteristics that data must have. For completeness and clarity, I’d extend this list to include the attributes of the “data as a product” concept, coined in the Data Mesh paradigm. A data product should be DATSIS: Discoverable, Addressable, Trustworthy, Self-describing, Interoperable and Secure. Pretty self-describing, I guess.

At this point, if everything is clear, you should ask yourselves whether you're doing it right or why you haven’t started yet!

The H Factor

Just as in the popular TV show where musical talents with a special vocation are discovered, in data strategy identifying key players and leveraging the human factor is crucial for success.

Right from the first page of his book, Tiankai hits the mark by highlighting a fundamental aspect:

“We try to be analytical, reasonable, and fact-based (‘data driven’), but the truth is that we’re all emotional, irrational, and unpredictable.”

I couldn't agree more. I'm a computer engineer, so I'm used to being associated with the stereotype of someone who deals with software or hardware, not people - unfortunately, not without some truth to it.

Often, due to our work and background, we find ourselves dealing with deterministic tools, numbers, formulas, models and algorithms. But these elements are merely pieces of the puzzle - it's people who move them and even justify their existence.

People are the ones who define the physical expression of data by establishing its model, or who set the logical steps and frequency at which a flow operates, they decide what reports are needed and what they should contain. All these "materials" produced are useful only as long as there are people who decide they are - this is why treating data as a product stands out.

The more collaborative and cohesive people are, the more agreements, touchpoints and shared understandings can be reached. However, disagreements can also occur, leading individuals to work independently. While rules are inherently followed by applications and processes, humans who disagree find ways to circumvent or change them, otherwise they resist by opposing those enforcing the constraints.

Everything people do can influence the outcome of an initiative - whether it’s their behavior, relationships, growth aspirations or resistance to change. We have a peculiarity, a "bad habit" so to speak: unlike digital assets, we aren’t "simple" entities that can be perfectly captured in static documentation or, to put it elegantly, a data contract. We are complex beings: we have personal goals, preferences, mindsets, experience, gaps and emotions - all of this on an individual level. Furthermore, we are social animals born to interface and interact with each other, adding more dynamism to our complexity.

An initiative can fail because someone opposes it simply due to disagreement with the person proposing it - at the expense of both, as the cause is overshadowed by self-interest. Others may resist change because they like their comfort zone. Teams that are tightly bonded may resist being reorganized or divided into different groups, thus potentially obstructing progress. In short, the human element implicitly adds multiple complex factors.

Despite the well-known trio of processes, people and technology, it’s people who are truly the central pivot around which the other two aspects revolve. Processes are designed and governed by people, and technologies are chosen, implemented and monitored by people. Therefore, people are the zero point. If this aspect is well-managed, the other two will naturally follow suit – not for nothing, but let’s avoid deferring the biggest issues until the end.

When it comes to people in organization, sooner or later you have to confront the reality of the great divide between business and IT. Does it sound familiar?

"IT's none of your BUSINESS"

If I had to sum up the relationship between IT and Business in one phrase, this would be it:

“IT's none of your BUSINESS”

I think this phrase perfectly encapsulates the feeling of miscommunication and mutual misunderstanding that plagues the interaction between these two worlds.

On one side, we have the IT professionals, usually seen as wizards who speak in a language of acronyms and code. They usually see the business folks as dreamers who don't understand the complexities of technology.

On the other side, we have the business decision-makers, the strategists who thrive on vision and big-picture thinking. They speak in terms of ROI, market share and customer satisfaction. To them, IT is a black box that should just work. They often see the techies as narrow-minded geeks who can't see beyond their screens.

Each group goes about its affairs, often viewing the other as an obstacle rather than a partner. Collaboration is rare, typically only when required and when it does happen, it's usually fraught with frustration and confusion. The IT team rolls their eyes at yet another "urgent" request that makes no technical sense, while the business team sighs in exasperation at the latest "incomprehensible" tech stuff. Each side sticks to its own domain and the gap between them widens.

The irony is that both sides need each other to succeed, but the communication barrier remains a?big?challenge. This phenomenon can be described as “the other side syndrome”: people should stop looking at differences but instead focus on common goals and final value.

One of the most powerful messages in Tiankai’s book is the concept of co-creation - the process by which both sides actively contribute to generating value and creating something new. This approach goes beyond the traditional view of data teams as a service desk - where you request something, and they deliver it - or the self-service model, where one side provides all the necessary tools, leaving the other to figure it out on their own. Whether you use a service or self-service, there will always be a dissatisfied party wanting more. To ease this conflict, both sides must take responsibility and cooperate, aiming not for my goal versus yours, but a shared one.

The issue is current and the gap exists. How do we address it?

Mind the gap

The gap between business and technical roles, aside from the clear division of corporate roles is an implicit result of the professional paths each person chooses to follow. It's natural for individuals to develop skills that are most relevant to their area. Organizations often encourage this expertise, while leaving it up to each person to broaden their skills outside their boundary - typically referred to as soft skills. However, this term is somewhat misleading, as these skills are increasingly crucial for success, helping individuals stand out and achieve more. It's wrong to label them as soft when they are fundamental, and it's equally wrong to push them to the background, expecting individuals to decide how to develop them in their personal time. While some companies may offer ad-hoc activities to address specific gaps, these efforts often fall short of truly fostering growth in these areas. I believe a crucial first step toward synergy is investing proactively and directly in “soft” skills.

Many successful individuals have cross-functional skills - both technical and business related. They can engage with both types of stakeholders and navigate discussions across both domains, making them highly valuable. However, there's a paradox: our education system, starting from elementary school, provides both technical and theoretical components. It focuses more on breadth than depth, offering a basic understanding across subjects. As we progress to high school and beyond, we choose paths - technical, humanistic, managerial or theoretical - and specialize (eventually, in our professional lives, we hope to apply this specialized knowledge). This specialization often leads to challenges in communicating and collaborating with those who speak a different "language" or have complementary skills. As we advance in knowledge, we risk becoming disconnected if we don’t take the necessary measures.

This isn’t a new problem; many companies invest significant time in team-building activities, cross-functional training and establishing communities of practice. While every organization needs deep experts in various areas, there's an equal need for individuals who are balanced between technical and functional aspects. If this duality doesn't exist within a single person, teams should at least aim to balance members with different strengths and ensure they work closely together.

Having expertise is gratifying for the individual and crucial for the organization, but it’s also about being able to interact effectively with others. If you’re an expert but can't communicate or collaborate well, what good is that expertise? This issue of interfacing applies both ways - a business expert speaking their own language and a technical expert speaking theirs.

Organizations should invest in promoting data literacy so that everyone, whether they work directly with data or not, understands key aspects of the data lifecycle to improve cooperation and proactive management. Similarly, technical experts should develop a solid understanding of business fundamentals - by investing in business acumen - to facilitate relationships and operations.

Assuming we’re on the right path to aligning business and IT, how can we ensure we consider all aspects of the human dimension?

The missing ingredient

Despite each organization having its unique traits and the human dimension not being governable by models and algorithms, there are key elements to consider and common mistakes to avoid. Drawing on experiences from similar contexts can provide valuable insights and possible solutions.

Often, attention to human factors is only given when dealing with rights, minorities, sensitive data and strict security policies. In other cases, particularly in traditional contexts with fewer regulatory constraints, data strategy initiatives tend to focus on data and technology aspects while the human dimension is dismissed with a summary of key stakeholders to engage, a review of the organizational chart and the definition of the target team structure.

It’s not uncommon for organizations to delegate the management of relationships and employee development solely to HR or to view communication as a marketing responsibility. Such approaches undermine transformation processes by hindering collaboration and cross-functional integration.

For delicate operations like change management, it's crucial not just to manage but to lead. This applies to all key figures involved, not just main sponsors or stakeholders. People should be engaged and inspired to participate actively, only then can a data strategy become a natural process with contributions from everyone.

These aspects, while they might seem peripheral, are actually central to a modern data strategy. Conway’s Law is clear: if an organizational structure and data architecture are incompatible, the organizational structure will prevail. I think this applies beyond architectural or topological considerations to attitudes, behaviors and relationships.

In his book, Tiankai presents a framework based on his professional experiences that addresses human-related issues. I’ve found his focus areas and insights relevant and eye-opening. To dig into the human aspect of data strategy, he suggests focusing on Competence, Collaboration, Communication, Creativity and Conscience. Let me quickly summarize these aspects and why I see value in them.

Competence

Ensuring that everyone in the organization has the right skills is essential. However, there’s often debate over what this actually means: how much should technical staff understand about business processes? And to what extent should business professionals dig into data operations?

This area is critical for effectively managing and adapting to change. One of the main challenges in the change process is the fear of not having, or being able to develop, the necessary skills. Some resources may be reluctant to embrace new skills, preferring to rely on the expertise they’ve accumulated over years in now-obsolete frameworks.

When it comes to skill distribution, the synergy between data and business knowledge is vital for a successful data strategy. Another critical aspect is finding the right balance between in-house and outsourced resources.

Competence is not just about theoretical knowledge but also the ability to apply that theory in practice. Regular training and a modular organizational structure are key to fostering ongoing skill development and adaptability. Incentives and the establishment of communities of practice also play a crucial role.

In the data field, developing expertise is challenging due to the wide scope and the constantly changing tools and practices. It’s foundational to have a plan, determine roles and associated skills and define individual development paths. Collaboration with HR is essential to ensure that employees receive the support and development opportunities they need to build both their competence and confidence. People must feel capable of handling their responsibilities, which can be nurtured through supportive training and a positive work environment.

Collaboration

Competence without collaboration limits the ability to scale and eventually caps the potential for value creation. Collaboration involves working within a team, across different teams within the same functional area and between different functional areas. Some of these dynamics are embedded in the team topologies used but others require cultivating an environment that encourages interaction and cross-pollination. This can be achieved for example through the creation of communities of practice, meetups, academies and team-building days.

Collaboration also means sharing goals, taking responsibility and providing shared workspaces and tools. It’s important to integrate this aspects into professional development, alongside skill growth, by setting objectives and incentives tied to collaborative efforts.

Collaboration is built on trust and the most natural collaborations arise at the intersection of common problems where both parties have a shared interest. It’s easier to start this way and then grow a relationship that has already proven successful: start small, then expand. Also keep in mind that Measures Of Success (MOS) are crucial for demonstrating results and securing the necessary buy-in for new initiatives.

Communication

This is one of the most underrated aspects today, yet it's crucial for enabling collaboration, gathering feedback and refining.

Creating a stakeholder map that distinguishes roles as active/passive and detractors/promoters is invaluable but just a starting point. It helps identify where to focus efforts and how best to engage different stakeholders.

A key factor for the success of any initiative is focusing on value creation for individuals, not just for the business. Many people might not see the benefits or may even doubt how their role could evolve, leading to reluctance or, worse, hostility. Therefore, it's essential to map business objectives to individual goals and plan effective communication to bring everyone on board.

Creativity

Stopping here would lead to flat, top-down initiatives that are passively received. Instead, it's important to foster creativity within the organization by creating an environment that encourages new ideas, open dialogue, experimentation and continuous improvement.

Creativity develops when there is investment in mindset, practice and consistency. This can be achieved by encouraging interactions between teams and expanding the pool of contributors.

Conscience

Awareness is essential for distinguishing what is right or wrong, or - for navigating the gray areas - for what is more sustainable, respectful and resilient. Making a solution sustainable isn't just about costs for the organization (whether running or maintenance), but also about environmental impact.

Human judgment and critical thinking are the cornerstones of sound decision-making while ensuring diversity, equity and inclusion.

My 2c

Tiankai’s work provides a deep reflection on the core human aspects we encounter daily in our work. I recommend this book to all data professionals embarking on a data strategy journey or undergoing organizational transformation.

What stood out most to me was the book's focus on aspects often overlooked or ignored in organizations, or perhaps addressed only too late, leading to inefficiencies and issues.

I was struck by Tiankai's idea of applying Ikigai to prioritize initiatives finding the perfect balance between excitement, feasibility, resources and strategic alignment.

If I may, I would add to the framework another dimension: Emotion or - as I’d call it to keep with the theme of "C's" - Connection.

While it may seem transversal to the other dimensions we've discussed - especially collaboration and creativity - I believe it’s a critical aspect that deserves recognition on its own, particularly when we focus on the human element.

On one hand, it’s what distinguishes us as humans, on the other, understanding what moves people emotionally is key to identifying weaknesses or powerful levers in your strategy. When we are emotionally engaged, we tap into extra energy and become more involved.

Emotion enriches both ourselves and those around us, leaving a lasting impact.

To strengthen this aspect and fully harness its potential, you can:

• promote emotional intelligence - by training leaders and employees to recognize and manage their own emotions and those of others. This improves communication and reduces conflicts
• create an active listening environment - by encouraging an environment where people feel heard and understood. This increases the sense of belonging and?reduces?stress

Transforming frustration into determination can drive the team to explore new paths, while channeling constructive criticism into continuous improvement projects strengthens team cohesion. Similarly, passion and enthusiasm can be directed towards creative initiatives, fostering a dynamic and proactive work environment.

Emotions should be acknowledged, understood, and channeled for the benefit of both the organization and the individual. They should also be tested by encouraging people to step out of their comfort zones, fostering personal growth and improvement while enhancing the?organization

Final thoughts

Why this sensitivity to the human dimension, you might ask?

It stems from both professional and personal maturity, as well as practical experiences over the years. I've realized how crucial these aspects are and how they shouldn't be underestimated.

If there's one regret in my career, it's starting too late to focus on these elements, having spent much of my time on technical and technological aspects - loving to do it. However, there's always an opportunity to improve through further study, learning and engaging with others.

Too many times professionals label issues as "cultural" or "organizational" recognizing gaps but failing to offer actionable solutions. While defining the optimal team structure is important, other crucial aspects are left to HR and marketing, neglecting the essential human dimension.

You certainly don't need to be a philanthropist or an anthropologist to understand and feel yours these topics and definitely many of the aspects mentioned are not new to most of us. However, this shouldn't stop us from discussing them and promoting its values or neglecting their value.

Talking with others, being empathetic, connecting to a worthy cause and promoting its values are crucial. We are too used to talking about technical issues and should lift our eyes from the paper or monitor in front of us, observe those around us, understand what drives others, and learn how to relate better?with?everyone.

Naturally, here we are discussing data strategy and its relationship with the human dimension. However, many of the thoughts made can extend beyond the scope of strategy in general, impacting the overall health of an organization and its business.

Too often positive outcomes arise by chance due to exceptional individuals rather than from structured goals and clear responsibilities. The human dimension needs a proactive plan for the aspects mentioned above (Competence, Collaboration, Communication, Creativity, Conscience - and Connection if I’ve convinced you).

Every organization is unique, and human dynamics add layers of complexity. That’s why your data strategy must tackle these challenges directly to be truly effective: people are the backbone of data strategy.