Digital transformation is a wild ride. It’s full of ambitious goals, high expectations, and big promises.
But here’s the challenge: You must think long-term while proving results today. That’s a tough balancing act!
If you focus too much on the future, people lose patience. They need to see progress. But if you chase only quick wins, you risk patching problems without making real change.
Great leaders master both.
They understand that transformation is a marathon, not a sprint, and they know that momentum is everything. They practise strategic patience, moving with urgency while keeping their eyes on the bigger picture.
True transformation isn’t an overnight success story. Sure, you can roll out new tech, automate a few processes, or migrate systems to the cloud in a few months. But fundamentally changing how a company thinks and operates? That takes years!
This is just a snippet from a longer piece originally published on Human & Digital on Substack. If you’d like to read the full post, go there.
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Most leaders would describe themselves as change-makers. They talk about transformation, innovation, and driving progress. But in reality, many simply manage what already exists — keeping things efficient, organised, and stable.
There’s nothing wrong with stability. Organisations need it. But leadership isn’t just about maintaining order.
The real difference between a manager and a builder is this: Managers optimise, while builders create!
In a world of constant disruption, businesses don’t just need leadership that keeps things running smoothly — they need leadership that builds.
Managers focus on today, Builders shape tomorrow!
This is just a snippet from a longer piece originally published on Human & Digital on Substack. If you’d like to read the full post, go there.
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I you think the only way to become a CIO is by climbing the IT ladder, think again!
The whole CIO game has changed — like, massively!
It’s not just about managing servers and software anymore. These days, a CIO has to actually drive business growth, make (internal) customers’ lives easier, and, honestly, make sure tech is worth the money instead of just burning through budgets.
That’s why Account Executives (AEs) might be some of the best candidates for the job. They know how to listen and talk to customers, influence the right people, and make sure whatever solution they’re selling actually makes sense for the business. And if that’s not basically the whole point of being a great CIO, then what is?
This is just part of the article — I shared the full version on Substack. If you’re curious and want the complete picture, you can find it on Human & Digital.
Businesses love to talk about agility. The ability to move fast, pivot quickly, and outpace competitors has become the gold standard for success. But what happens when speed isn’t enough? What if the next disruption isn’t just a curveball but a complete shift in the game itself?
Real resilience — the kind that keeps businesses afloat and thriving — goes beyond agility. It’s about adaptability.
It’s about building a company that doesn’t just react to change but absorbs it, reshapes itself, and emerges stronger.
Most leaders think they’re ready for disruption because they have a strategy, a digital roadmap, or an agile framework. They’ve implemented cloud solutions, adopted DevOps, or embraced remote work. But these are just tools. Having a fire extinguisher doesn’t mean you’re prepared for an earthquake.
Take the businesses that raced to digitise during the pandemic. Some adapted, integrating digital channels into their long-term models. Others simply moved online as fast as possible — only to struggle when the next shift came.
The difference? One was focused on resilience, the other on reaction speed.
Agility and adaptability are often used interchangeably, but they’re different.
Agile businesses react. Adaptable businesses evolve!
Consider the companies that thrived after major disruptions — not just by pivoting but by fundamentally rethinking their approach.
Agility might get you through the first wave of a crisis, but adaptability ensures you survive the second, third, and beyond.
True adaptability isn’t just about mindset — it’s about how a business is structured, its decisions, and how technology is used.
Why Tech Alone Won’t Fix Your Problems
Every major shift — economic downturns, regulatory changes, tech disruptions — creates winners and losers. The winners aren’t always the biggest or the fastest; they’re the ones that adapt best.
The lesson? Short-term survival tactics won’t save you when the next shift comes. Long-term adaptability will.
So how do you move beyond agility and build real resilience?
Disruption isn’t a question of “if” but “when.”
When the next shift happens — whether it’s economic, technological, or something entirely unforeseen — your business will either react or adapt.
Which will it be?
Thanks for reading!
This post was originally published on Human & Digital on Substack. If you enjoyed it, consider subscribing for more insights on leadership, strategy, and transformation.
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It happens all the time! A company invests in the latest tech, expecting a game-changer — faster processes, better decisions, and everything finally running like a dream.
But give it a few months… and reality hits!
Workflows are still messy, teams are struggling to keep up, and customers? They don’t seem to care.
So what went wrong? Wasn’t this supposed to fix everything?
Here’s the thing — tech isn’t magic. It’s just a tool. And like any tool, it’s only as good as the people using it.
This is just a snippet from a longer piece originally published on Human & Digital on Substack. If you’d like to read the full post, go there.
You know that moment when a big strategy is announced? The slides are polished, the vision is clear, and the leadership team is pumped. Everyone leaves the room (or the Teams call) nodding along, thinking, "Yeah, this makes sense. Let’s do it."
Then… nothing really happens!
Not right away, at least. At first, people are busy. Then, other tasks emerge. And before you know it, a few months have passed, and the big strategy is sitting on a shelf, collecting dust.
So what went wrong?
Most of the time, it’s not the strategy itself. It’s what happens — or, more often, what doesn’t happen — after the strategy is approved.
And the real issue? It’s not process, or tools, or dashboards. It’s people.
No strategy fails all at once. It unravels in small, almost invisible ways: a meeting where no one asks questions, a task force that never really gets off the ground, or a team that assumes the “big picture stuff” doesn’t really apply to them.
Here’s how it usually plays out:
This one’s classic. A new strategy rolls out, but day-to-day work doesn’t stop. People still have deadlines, projects, and fires to put out. So, without meaning to, they push the strategy aside — just for now.
And “just for now” turns into six months later, when someone finally asks, Hey, what happened to that thing we were all supposed to be doing?
Strategy gets announced at the top, and everyone assumes it’ll “trickle down.” Except that’s not how real work happens. If no one’s clearly responsible for driving execution, then everyone assumes someone else is.
Leadership assumes teams will figure it out.
Teams assume managers will guide them.
Managers are waiting for more direction from leadership.
And the cycle repeats.
On paper, the strategy was solid. But then the market changed. Customers acted differently than expected. Internal systems weren’t quite ready. Teams ran into roadblocks no one saw coming.
Instead of adjusting, people hesitate. They don’t want to be the ones who say, Uh, this isn’t working as planned. So they either struggle to make the original plan fit — or just quietly stop pushing forward.
People are busy and working hard, but are they working on the right things? Hard to say!
Many strategies get stuck in “ongoing” mode, with no clear progress markers. If teams don’t know what success looks like, they default to what’s familiar. They keep doing what they’ve always done because at least that feels productive.
Companies love trying to fix execution with more processes. More tracking. More reports. More check-ins.
But the truth is, execution isn’t about more process — it’s about better alignment. It’s about making sure people:
And the biggest mistake? Assuming that once you’ve said the strategy, people automatically get it.
They don’t. People need to hear it, talk about it, question it, and see how it applies to them. That takes time!
If your team can’t sum up the strategy without looking at a slide deck, it’s not clear enough.
Keep simplifying until anyone can say: Here’s what we’re doing, and here’s why it matters.
No plan survives first contact with reality. If teams feel locked into a strategy that doesn’t fit their daily work, they won’t engage with it.
Give them room to adapt while still keeping the direction clear.
If following the strategy feels separate from people’s “real work,” it won’t happen.
It should be integrated into the way teams already operate — not regarded as an additional project.
And not just in theory!
Name real people — individuals, not departments — who are responsible for keeping the strategy moving.
If ownership is vague, execution will be too!
A strategy doesn’t succeed because it was approved. It succeeds because people actually do it. And that doesn’t happen in a single meeting or a big email rollout.
It happens in everyday decisions. In small, practical steps. In conversations where people connect the dots between their work and the bigger picture.
At the end of the day, the best strategies don’t live in PowerPoints. They live in actions!
Thanks for reading!
This post was originally published on Human & Digital on Substack. If you enjoyed it, consider subscribing for more insights on leadership, strategy, and transformation.
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When organisations invest in new technology, there’s often a sense of excitement — and high expectations. Leaders anticipate streamlined processes, empowered teams, and delighted customers. Yet, these initiatives are often under-deliverable, falling short of the expected transformation. So, what’s going on here?
In my experience, when technology underperforms, it’s rarely because of the tool itself. More often, it’s about how the technology is implemented and the expectations placed on it. This value gap forms when technology isn’t closely tied to business goals or when companies overlook the cultural and behavioural shifts that need to accompany it. However, this gap can be avoided with a few critical adjustments in approach.
One of the biggest reasons tech initiatives fail is a lack of alignment with the organisation’s objectives. I’ve seen companies adopt technology with a vague idea of “boosting productivity” or “improving customer service” without fully considering how the tool serves a specific, measurable business goal. When this happens, teams lose focus because there’s no clear marker for success. Technology initiatives work best when anchored to specific, shared objectives that teams can rally around and measure against.
I can’t emphasise enough how often user needs are overlooked in tech projects. We tend to assume that a new tool will naturally improve workflows, but adoption will lag if the people using it don’t find it helpful or intuitive. It’s that simple! The most successful tech projects I’ve seen start with deep user involvement — interviews, testing, and inviting their input on specific features. It’s worth the effort because people are far more likely to adopt technology that feels made for them.
Let’s be honest — change management often gets pushed to the bottom of the priority list in tech projects. Many leaders assume the technology will sell itself. However, tech changes disrupt routines, and people need support to understand how it fits into their daily work. I’ve seen projects stall simply because people lacked the necessary training or context. A well-structured change management approach — such as clear communication, hands-on workshops, and continuous access to support resources — can make all the difference in helping employees embrace new tools.
Far too many companies launch technology with high expectations but little follow-through on measurement. It’s like setting out on a trip with no map or destination in mind. Setting up metrics and feedback loops right from the start creates a clear picture of the technology’s impact and highlights areas for improvement. It’s not about perfection from day one but about making adjustments based on honest feedback.
To ensure technology delivers on its promise, leaders need to think of it as more than just a tool rollout. In my experience, successful initiatives are ones that treat tech as part of a broader strategy, combining alignment, user engagement, and feedback. Here are a few steps to get there:
Align with Clear Business Goals
Start every tech project by defining what success looks like. This goes beyond buzzwords and gets specific. For instance, if you’re investing in automation, target an outcome like “reduce processing time by 30%.” This clear objective becomes a rallying point that keeps teams focused and helps everyone understand how the tool contributes to larger goals.
Integrate User-Centred Design
Engage end users from day one. This isn’t about token feedback but about genuinely listening to their needs and building around them. When users feel like a tech solution has been designed with their challenges in mind, they’re far more likely to adopt it. I’ve seen this pay off repeatedly: involving users leads to a smoother rollout and a tool that truly fits into their workflow.
Strengthen Change Management
Don’t skimp on change management. Provide not just a training session but an entire support structure. Think of it as a gradual adoption curve, with ongoing workshops, clear channels for questions, and maybe even champions within teams who can offer guidance. The more support people have, the more likely they are to adopt the new technology.
Establish Metrics and Feedback Loops
Set measurable success criteria and schedule regular feedback sessions. For example, measure usage rates, productivity boosts, or user satisfaction. The point is to stay adaptable — based on real feedback, you can make early adjustments and increase the project’s chances of long-term success.
Technology alone won’t deliver transformative value. The organisations that succeed are those that approach tech initiatives as part of a balanced strategy that includes people, processes, and a purpose aligned with business goals. By prioritising user needs, investing in change management, and staying open to feedback, companies can close the value gap and achieve the desired results. After all, technology is only as powerful as the strategy and people behind it.
Digital transformation (DX) isn’t just about adopting the latest tech; it’s about using that tech to achieve strategic objectives that drive real value for your organisation. Yet, without a structured roadmap aligned with business goals, DX initiatives can quickly lose direction, leading to wasted resources and disappointing outcomes. Here’s a guide to crafting a digital transformation roadmap that keeps your tech investments focused on what matters most — your business goals.
Before choosing tools or technologies, clarify your business vision. What specific outcomes are you aiming for? Aligning digital initiatives with your strategic objectives sets a clear direction, whether it’s enhancing customer experience, improving operational efficiency, or entering new markets. This step is often overlooked in the excitement of transformation, but it’s essential for giving purpose to every digital initiative.
Digital transformation is not an IT project; it’s an organisational evolution. Successful DX requires input from various departments, including operations, finance, HR, marketing, and, of course, IT. To create an effective roadmap, identify these key stakeholders early and involve them in decision-making. This collaborative approach builds diverse perspectives and creates buy-in, which will help you avoid resistance later on.
Engage each stakeholder by showing how the DX goals align with their departmental objectives. For example, you could highlight how automation might help the HR team streamline recruitment or how data analytics could help finance identify cost-saving opportunities. Gaining this commitment early on ensures DX initiatives are embraced rather than resisted.
Next, it’s critical to evaluate where your organisation stands today in terms of digital maturity. Take stock of your current technology stack, data infrastructure, skills, and processes. An honest assessment reveals where your organisation is strong, where you have critical gaps, and what might need to change to achieve your goals.
For instance, a manufacturing firm might realise that while it has advanced machinery, it lacks the data integration needed to gain real-time insights into production efficiency. Recognising this can prioritise data integration as an early step in the transformation process. This baseline assessment also helps identify “quick wins” — immediate, high-impact improvements that can build early momentum.
A successful DX roadmap includes clear, measurable milestones to track progress. Set these milestones according to your transformation phases: digital adoption, process optimisation, data integration, and so on. Begin by prioritising initiatives that deliver visible impact or address critical gaps identified in your maturity assessment.
For example, a retailer might first focus on implementing a data analytics platform to better understand customer buying habits before investing in an omnichannel marketing system. By taking on one high-impact project at a time, you avoid overwhelming the team and increase your chances of success. Starting with “quick wins” also demonstrates tangible progress to stakeholders, which builds trust and keeps the momentum going.
To make your roadmap a reality, dedicate resources and establish governance structures that keep projects on track. Digital transformation needs time, budget, skilled personnel, and strategic oversight. This means carefully planning your resources, defining project teams, and establishing clear lines of accountability.
Set up a governance framework that includes decision-making structures, progress reporting, and performance measurement. Regular check-ins and transparent reporting keep stakeholders informed and projects aligned with organisational goals. If you’re implementing machine learning to improve customer targeting, for instance, periodic reviews can help ensure the model delivers accurate insights and is ethically applied. Strong governance lets you adapt quickly without losing sight of your objectives.
Once initiatives are underway, maintain focus on execution, monitoring, and adaptation. Digital transformation isn’t a one-time project; it’s an ongoing journey that requires regular course corrections. Track progress against your milestones and gather feedback from both internal teams and external customers to refine your roadmap as needed.
Business conditions and market dynamics change, so be ready to pivot if necessary. For instance, a sudden shift in consumer demand may lead a retailer to accelerate e-commerce transformation. An agile approach allows you to keep transformation efforts aligned with shifting priorities, making your organisation more responsive to both opportunities and challenges.
Your digital transformation roadmap should be a living document that grows and adapts with your business. Regularly revisit your business goals, assess your progress, and adjust your approach to ensure DX continues to deliver real value. The most successful organisations use their roadmap as a guide — not a strict plan — allowing them to make strategic pivots that create lasting impact.
By focusing on business objectives, securing stakeholder buy-in, assessing capabilities, setting priorities, and maintaining flexibility, you can build a DX roadmap that not only transforms your tech stack but also drives sustainable growth and meaningful business outcomes.
Dataspaces are now a hot topic in Europe! Data is a predominant factor for the advancement of society, and dataspaces have collected attention from individuals, businesses, and governments who have recognised their impact and significance on the data economy. Although dataspaces can be confusing at first, especially for those unfamiliar with them, they are essential for the EU data economy’s progress and success.
The European Commission (EC) plays a key role in enabling the data economy, and dataspaces are at the core of a future defined by a competitive and innovative data-driven market. With this vision in mind, the European Commission has set an ambitious objective of establishing a Common European data space.
The Common European Data Space is more than an initiative; it is a strategic plan! What is its goal? It’s about bringing EU Member States closer together by ensuring data flows freely and securely across borders. The result? A wealthy digital society in which data is the primary driver of economic growth.
But here’s a fascinating twist — the aim is to accomplish all this while allowing the people and companies who create data to stay in control. It is about creating a secure and welcoming environment for everyone to contribute and benefit from shared data.
The basis of this concept is that it will affect how we all leverage and exchange data on a global scale. Dataspaces fit nicely with the EC’s ambitious aim by preserving data control in the hands of those who create it while establishing a platform optimised for responsible sharing.
The EC’s ambition goes beyond mere catching up; it is to be the world leader in establishing responsible data sharing for everybody! The EC has the potential to influence how we engage with data, grow our economies, and generate new ideas. All while ensuring that your personal or corporate data rights remain protected in today’s digital landscape. It’s like the EC saying, “Hey, let’s lead the charge in making data work for everyone, everywhere!”
Think of a vast digital world where data from different places, in various forms, all come together. That’s what dataspaces are like — a lively, interconnected universe where data flows. They act as digital bridges that effortlessly connect different data sources, breaking down the usual barriers that keep data separate.
Dataspaces are intentionally designed to incorporate data in all forms, regardless of format or location. By providing a unified ecosystem, dataspaces offer a consistent solution for different data species, including structured data stored in databases, unstructured data found in documents, and real-time data collected from sensors. As a result, dataspaces serve as an inclusive and adaptable environment for all forms of data.
A data space can be seen as a data integration concept which does not require common database schemas and physical data integration but is rather based on distributed data stores and integration on an “as needed” basis on a semantic level. Abstracted from this technical definition, a data space can be defined as a federated data ecosystem within a certain application domain and based on shared policies and rules.
- Design Principles for Data Spaces
Picture this: you can easily access, analyse, and collaborate on data from different places without dealing with the complex problem caused by the data being everywhere or figuring out where it’s located in advance. Well, that’s where Dataspaces comes in!
Have you ever considered how a country’s use of data is linked to its economic success? This correlation is quite significant! Having a data-driven economy can boost a country’s economic growth. Think of dataspaces as the real heroes here because they let data move freely across borders. Consider this: Businesses can grow and expand into new markets more efficiently, and startups can get their hands on the valuable data they need to succeed.
But the influence of dataspaces extends beyond economic growth alone. They also play a vital role in driving societal progress through innovation. By breaking down barriers between sources, formats, and locations, dataspaces provide easier data access. This accessibility enables corporations, researchers, and governments to leverage data for study, development, and decision-making. In essence, dataspaces is a platform for data integration, improving access to information and encouraging innovation.
As previously described, dataspaces have immense potential, but recognising their geopolitical relevance is paramount. The United States has been the dominating player in the global data landscape, and companies like Google, Facebook, and Amazon have made significant data-driven advancements thanks to the large volume of data they have accumulated. Also, thanks to its vast population and growing IT industry, China has emerged as a key player in the data economy. Using domestic data, companies like Alibaba, Tencent, and Baidu have expanded their global footprint and positioned China as a relevant player in the data domain while reducing dependence on US-based businesses.
Recognising the need to catch up in the data race is only the beginning for the European Union (EU); however, one major obstacle is the fragmentation of the European digital market. The EU comprises multiple countries with diverse languages, cultures, and regulations, making the creation of a unified data ecosystem challenging. This fragmentation contributed to the lack of large-scale tech companies capable of competing with their U.S. and Chinese counterparts.
The EU’s data strategy must evolve to bridge this gap and compete effectively with the United States and China. This transformation involves cultivating innovation-friendly environments, supporting the growth of tech startups and scale-ups, and streamlining regulations to encourage data-driven-powered enterprises. As the EU progresses toward its vision of a Common European Data Space, embracing dataspaces as integral components, it must prioritise cross-border data flows while ensuring robust data protection mechanisms.
Imagine if data from various sources could collaborate seamlessly, transcending data boundaries while maintaining data control. Dataspaces can be inherently complex, but three essential components are crucial: federation, interoperability, and data sovereignty.
A federated data space is a dynamic and decentralised infrastructure that nurtures trust in ecosystem data sharing. Unlike centralised data systems, where everything is consolidated in one place, a federated data space adheres to agreed-upon principles that emphasise collaboration. Think of it as harmonising a symphony of diverse data sources, each with unique traits and locations.
The beauty of a federated data space lies in its capacity to dismantle traditional data silos. Data from diverse sources and formats becomes accessible and shareable without needing a one-size-fits-all data warehouse. Instead, data remains where it’s born, and those responsible for it retain control. This decentralised approach respects data ownership and allows adaptability and scalability.
Data interoperability is a key concept for dataspaces since it enables seamless data flow within and between dataspaces. This means that interoperability goes beyond a dataspace; it extends across them, creating a network of dataspaces. This interconnectedness ensures that the advantages of interoperability are spread throughout the data ecosystem, amplifying its possibilities.
Data interoperability acts as a catalyst within dataspaces by increasing accessibility and simplifying data integration. This simplification reduces the time and resources needed to transform data into an asset. Think of ontologies as translators in the world of dataspaces! These structured vocabularies carefully define how data should be understood, bridging the gap in understanding for all participants, whether they are providing or using the data.
And the need for interoperability between dataspaces? Imagine a world where healthcare, agriculture and energy sectors collaborate seamlessly, sharing data to inspire innovation and tackle complex challenges. This captivating vision aligns perfectly with the European Commission’s commitment to sector dataspaces. These specialised spaces are intelligently designed to break down barriers that once separated different domains by leveraging interoperability as the key that unlocks all their potential.
Data sovereignty is a core concept in a federated data space. It refers to the notion that individuals and organisations have ownership over the data they create and manage, perfectly aligned with the decentralised structure of a federated data space. Beyond ownership, data sovereignty also plays an essential role in increasing trust within the data community, ensuring that data sharing is built upon mutually agreed-upon terms that promote transparent and responsible data usage.
This principle respects the fundamental rights of data creators, granting them the ultimate authority over how their data is employed and shared. Yet, data sovereignty offers more than just control. It champions the freedom to adapt and expand within the data ecosystem, enabling individuals and organisations to tailor their data resources as circumstances determine.
In the world of federated data spaces, data sovereignty isn’t an afterthought; it’s a guiding beacon. It empowers stakeholders to maintain control, adapt to evolving needs, and collaborate within a decentralised and trustworthy data-sharing environment. Ultimately, it’s all about safeguarding data as a valuable asset that benefits everyone involved.
Dataspaces represent the dynamic and interconnected landscapes where the future of data unfolds. Picture it as the bustling heart of a European data digital revolution. In this vision, Europe stands at the forefront, imagining a world where data flows freely, fostering economic growth and igniting a spark of innovation while safeguarding the fundamental concept of data sovereignty.
The commitment of the European Commission to forge a Common European Data Space is more than just a strategic move — it’s a bold, forward-looking vision. It’s not merely about catching up with the global pace of data sharing; it’s about leading the charge with a commitment to responsible data sharing that empowers individuals and organisations alike. In this landscape, dataspaces transcend borders, embracing the potential for increased collaboration across regions, governments, and organisations to weave a harmonious global data ecosystem.
Dataspaces introduce elements that magnify their importance. Think of it as harmonising the diverse melodies of data sources; the Federation breaks down the traditional data silos and champions data autonomy. Meanwhile, Interoperability serves as a catalyst, simplifying the intricate art of data integration and making data more accessible to all. It’s akin to the master key unlocking doors to transformative potential within and between Dataspaces. Lastly, Data Sovereignty emerges as the guardian, ensuring control, adaptability, and collaboration remain the guiding principles within this decentralised and trust-rich data-sharing environment.
As we step into the era of Dataspaces, we embark on a path congested with exciting opportunities. It’s more than just data — it’s about the remarkable power of data employed responsibly to paint a brighter digital future. In Dataspaces, the data landscape undergoes a metamorphosis, and it will be exciting to witness such a transformation and its contribution to the economic growth and prosperity of the European Union.
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I led a research project on customs and supply chains a few years ago. During a presentation, I introduced the concept of personalisation and emphasised the importance of tailoring solutions to meet the unique needs of individuals working in the same organisation. At the time, I received a mix of excitement with sceptical looks. Fast forward to today, personalisation is no longer a new concept. Companies like Amazon and Netflix have successfully implemented customised experiences for their consumers. However, a disparity remains between personalised consumer-facing applications and our organisations’ often uniform nature of internal applications. But what are the reasons behind this discrepancy? Can we enable personalised experiences within organisational settings?
Historically, products were crafted primarily to emphasise their fundamental functions. Organisations endeavoured to produce efficient, dependable, user-friendly products to satisfy consumer demands. Nevertheless, with the emergence of technology and the ascent of interconnected digital ecosystems, the role of products has broadened beyond their intrinsic abilities.
Products are no longer just vessels for delivering functionality or generating revenue. They have evolved into powerful conduits that create enormous amounts of data, providing new customer experiences.
Data has emerged as the lifeblood of modern product development. Every interaction, click, and engagement with a product generates valuable information that can be analysed and used to provide personalised experiences to customers. This shift towards data-driven product development signifies a significant turning point where the accumulation and utilisation of data have become indispensable to meet customers’ evolving needs.
By harnessing the power of data-driven insights, companies can gain a deeper understanding of their customer’s preferences, behaviours, and needs. This newfound knowledge enables the creation of personalised experiences that resonate with each individual, enhancing customer satisfaction and engagement. Whether recommending relevant products, curating customised content, or anticipating future needs, data drives these transformative customer experiences.
To harness the power of data-driven insights, companies leverage data to inform product development decisions, identify trends, and optimise features to meet customer expectations. Advanced analytics techniques such as predictive analytics enable companies to anticipate customer needs, personalise recommendations, and deliver proactive solutions.
As companies shift from mass production to customisation, they can tailor products and experiences to meet individual customers’ unique preferences and requirements. Companies can offer personalised recommendations, suggestions, and content by analysing customer data, enhancing customer satisfaction.
This data revolution in product development has far-reaching implications. It empowers companies to move beyond a one-size-fits-all approach and create products and experiences attuned to individual customer preferences.
Consumer-facing platforms like Amazon and Netflix have emerged as pioneers in delivering personalised content and experiences to their users. These platforms have harnessed the power of data-driven strategies to curate customised recommendations and create a tailored experience for each individual.
Amazon’s recommendation engine uses a variety of factors to suggest products to users, including purchase history, browsing behaviour, and demographic information. This results in a more personalised shopping experience and increases the chances of discovering relevant products. On the other hand, Netflix has a sophisticated recommendation system that analyses a user’s viewing history, ratings, and preferences to suggest TV shows and movies tailored to their tastes. This personalisation strategy leads to increased engagement and satisfaction.
Recommendation engines rely on collaborative and content-based filtering techniques to generate personalised suggestions. Collaborative filtering compares user behaviours and preferences with similar users to identify patterns and make recommendations. Meanwhile, content-based filtering analyses the attributes and characteristics of products or content to generate suggestions based on a user’s past interactions and preferences. Hybrid approaches that combine both techniques are also commonly used.
Behind the scenes, data collection and analysis are crucial for customisation. Platforms collect vast amounts of data from various sources, including user interactions, preferences, ratings, and feedback. This data forms the foundation for generating personalised recommendations. Advanced machine learning algorithms are then employed to process and analyse the collected data. These algorithms identify patterns, correlations, and user preferences, enabling platforms to deliver highly targeted and personalised experiences.
While consumer-facing platforms have embraced personalised experiences and tailored recommendations, a paradox of sameness in organisational applications often exists. Internal applications within organisations typically exhibit a uniform nature, providing the same kind of data and user experience for all users. Verifying individual needs through multiple data points would be the ideal way to personalise the application’s experience instead of relying on a generic approach that may not suit everyone. This discrepancy can be attributed to several factors, including the challenges of implementing personalisation at an enterprise level and the potential benefits that personalised experiences can bring to organisations.
Organisational applications are often designed to prioritise standardisation and efficiency, ensuring that workflows are streamlined and consistent across departments. However, this approach can result in a one-size-fits-all approach with little focus on individual needs. Compounding this concern is the vast amount of data organisations must contend with, making it challenging to present personalised information in a relevant and manageable way.
The COVID-19 pandemic has led to a significant increase in remote work, resulting in a notable growth in the development of Digital Workplace applications. These applications now gather data from cloud-based collaborative systems and aim to provide a personalised experience that caters to the unique requirements of diverse users. However, it is essential to note that while progress has been made, personalisation’s full potential has not yet been realised due to information silos in various systems.
Consolidating data from various systems and departments to create a unified view of the user can be difficult. Furthermore, accessing and analysing sensitive employee data raises concerns about privacy, data protection, and compliance. Implementing personalised experiences across a large, diverse organisation with various user roles, functions, and preferences can also be complex and resource-intensive.
Despite these challenges, personalised experiences can offer significant benefits within organisations. By providing employees with tailored information, tools, and workflows, personalised experiences can enhance productivity and efficiency. Personalisation can also foster a sense of value and individuality, increasing employee engagement, satisfaction, and retention. Personalised applications can facilitate knowledge sharing, collaboration, and targeted communication, improving teamwork and information dissemination.
To enable personalised experiences, user-centric design is critical. Employees should be placed at the centre of application design, focusing on their specific needs, roles, and preferences. Segmentation and role-based personalisation can also tailor application interfaces, content, and functionalities to specific user segments. Contextual relevance is another important factor, using contextual information such as user location, time of day, or current tasks to deliver relevant and timely information.
We are now at the forefront of the era of personalised experiences, where products have become conduits for data-driven insights that shape customer interactions. This paradigm shift in product development goes beyond mere functionality and revenue generation. It recognises the transformative potential of data in creating tailored customer experiences and fostering more profound connections.
By harnessing the power of data-driven insights, companies can unlock new levels of personalisation and meet individual customer needs more effectively. Consumer-facing platforms like Amazon and Netflix have pioneered the art of personalised content and recommendations, leveraging advanced recommendation engines to deliver tailored experiences to their users.
However, a disparity often exists between personalised consumer-facing platforms and internal applications within organisations. The challenges of implementing personalisation at an enterprise level, such as data integration, privacy concerns, and scalability, have hindered organisations’ adoption of personalised experiences. Despite these barriers, the potential benefits of personalised experiences in organisational settings are significant, including enhanced productivity, employee engagement, and knowledge sharing.
To enable personalised experiences within organisations, addressing factors like data integration challenges, privacy and data security concerns, and resource limitations is crucial. User-centric design, segmentation, and role-based personalisation can help create tailored internal applications catering to employees’ needs and preferences.
As we embrace the possibilities of personalised experiences, organisations must prioritise transparency, consent, and compliance with privacy regulations. By doing so, they can instil trust in employees and ensure that their data is protected while delivering meaningful, personalised experiences.
Looking ahead, the future holds exciting trends and possibilities in personalised experiences. Advancements in artificial intelligence, machine learning, and data analytics will further refine personalisation capabilities. We can expect more sophisticated recommendation engines, hyper-personalisation based on individual contexts, and seamless integration of personalised experiences across various organisational applications.
In conclusion, the era of personalised experiences has arrived, and the role of data in product development has transformed significantly. By embracing data-driven insights, overcoming barriers, and implementing effective strategies, organisations can unlock the transformative potential of personalised experiences.
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The Personalisation Paradox: Balancing Efficiency and Individuality in Corporate Applications was originally published in DataDrivenInvestor on Medium, where people are continuing the conversation by highlighting and responding to this story.