Category: Knowledge article
Operating within dynamic business ecosystems has become the norm. But do you remain part of someone else’s network, or should you build your own? Lauri Koop chose the latter. As former CEO of DPG Media Online Services and of Aimwel – a company that automates marketing campaigns for the recruitment sector – he decided not to follow the dominance of the American tech giants and instead built a successful advertising ecosystem himself.
Originally from Finland and Estonia, Koop worked for German media giant Axel Springer and Monster before joining DPG Media. “I had the privilege of working for major companies, which naturally places you in ecosystems of significant scale and influence.” As a senior executive in the advertising and media industry, he frequently dealt with some of the largest and most powerful companies in the world.
Today, American tech giants like Google, X, and Meta dominate the headlines. But interesting developments are also taking place closer to home. “Northern Europe, where I come from, leads Europe in IPOs. Stockholm alone has more than Germany, the Netherlands, and France combined. Estonia produces six to seven times more unicorns (startups valued at over a billion dollars) per capita than the European average.”
Why is this relevant? Because networked collaboration is the key to overcoming the huge disadvantage Nordic companies face. Estonia only has 1.3 million inhabitants. Like other Scandinavian countries, the domestic market is small. “If you have an idea or ambition in that environment, you’re forced to think internationally from day one. From the start, you consider your role in the broader ecosystem you aim to be part of.”
In a time when more people, systems, and businesses are digitally connected than ever, your focus can’t just be on the product or service you offer. The value you create for consumers, end users, and all other ecosystem participants becomes fundamental.
The Role of Technology
“Technology is at the heart of how modern ecosystems serve customers,” Lauri Koop continues. “And every major company either wants or already has its own ecosystem.” He cites Uber with Uber Eats, Airbnb offering insurance and other services, and Spotify with its podcasts. Amazon’s ecosystem spans Alexa, Prime, Payments, Music, the AWS cloud, and services in healthcare, marketing, and logistics.
The benefits of ecosystems are broad. They unlock new revenue streams and business models, accelerate tech adoption, lower costs, and improve efficiency. And perhaps most importantly: they give their owners power and control. “Once you have or are an ecosystem, others can’t just push you aside. Five of the world’s seven largest companies are either digital ecosystems or own one.” Even Nvidia is pivoting from GPU/chipmaking to building AI Robotics Ecosystem – an ecosystem with massively larger revenue opportunity than only providing the chips that power AI platforms.
“It’s also clear that the Americans have mastered this dynamic. Europe, so far, has not kept pace. China may catch up in time. We must admit: the U.S. is doing something right here.” Still, Koop believes it’s essential to consider your own position and opportunities. He shares three examples from his own experience: an SEO ecosystem, an app store, and an alternative advertising platform.
Flywheels for Growth
First, an observation. “In the U.S., just 16 major media companies dominate Google’s top organic (non-paid) search results. That is because they host a vast amount of highly authoritative, search-optimized content. They also own many web domains that extensively interlink. For example, Hearst’s Cosmopolitan links to sister brand Marie Claire.”
This makes it nearly impossible for an ordinary company to break through. To claim and maintain that kind of presence in Europe, Koop quickly formed centralized search engine optimization (SEO) teams at each media group he joined, essentially copying the American playbook. “Media groups that build internal SEO ecosystems can gain a significant competitive edge by leveraging all their resources effectively,” he says.
They can also use targeted content and affiliate partnerships to continuously match supply and demand for people, products, and services. Koop introduced an app store for publishers where third parties could offer their own developed apps. “For example, a widget that offers insurance options on automotive websites, or one that links clothing, shoes, and accessories in images directly to stores selling them. This too creates a flywheel effect – as success grows, so do both widgets and advertisers.”
Advertising Ecosystem
Finally, there is the paid advertising market, where Google plays a dominant intermediary role between advertisers and media companies. Ads from companies like Albert Heijn or MediaMarkt often appear on platforms like DPG, Mediahuis, and Talpa – typically through Google and a web of supporting players: media agencies, analytics providers, data vendors, social platforms, and so on. “All those middlemen together take about half of every advertising euro. Plus, they set the rules, and their services keep getting more expensive.”
This is why it makes sense for media companies to take control. “At DPG Media, we have around 100 brands. In principle, we only need one user consent to carry out commercial actions, giving us a strong position in our own local market. By developing our own ad tech, we were able to work directly with advertisers and agencies.”
According to Koop, this is how several ‘local heroes’ are emerging: ecosystem-style platforms like Funda.nl and Bol.com, which are successful on their own terms. “Even though their market values are no match for the American giants, you can still build a local ecosystem that delivers real value.” Open ecosystems tend to be more successful, he adds, because they offer more value to the end user.
Clearing the Way for Impact
A few key takeaways for anyone looking to claim a leading role in a digital ecosystem: understand what your users want and how you can deliver value. Don’t do what’s easy or comfortable – always act strategically. Work with the right strategic network partners. Clear the path for impact. Building value in one area may mean making sacrifices in another.
“You need a strong team to make all this happen,” Lauri Koop concludes. “Made up of people with an open mindset, able to think beyond existing business models and build something new. And one final note: when building your ecosystem, make sure you get advice from a partner who has the strategic, organizational, and technical expertise to bring it all together – like Anderson MacGyver.”
By Robbert Petterson
In a digital network economy, everything revolves around creating and delivering added value. To remain relevant, one must not only master technology but also understand how to collaborate with others. Robbert Petterson, Management Consultant and Product Lead Digital Business Research at Anderson MacGyver, uses current examples to show how organizations can strengthen their position in an increasingly complex playing field.
That your value within an ecosystem can change rapidly is evident from the impact of Elon Musk’s controversial actions and positions regarding fake news (alleged or not) on his X platform, his open support for Trump, and his interference in European politics. The result is a dramatic decline in demand for Tesla. While the need for electric cars remains undiminished. Competitors are gratefully capitalizing on this.
The message here is: never underestimate the role of consumers and citizens. It is crucial to know what they find important and valuable. And that value is generally not delivered alone, certainly not in a world of increasing digital networking. You therefore need a good understanding of the ecosystem in which you operate. To make this easier, we at Anderson MacGyver have developed the so-called ValueWeb, which provides insight into all actors and their mutual relationships.
The various players within this ValueWeb are characterized by specific activities, which—combined with the activities of others—are offered as a product or service to the consumer and end user. This results in an increasingly digital and dynamic ecosystem of customers, partners, and diverse economic and societal stakeholders.
To participate adequately in such a collaboration, it is essential to build what is known as a Digital Enterprise. Five essential and closely interconnected building blocks shape such a modern organization: a distinctive customer experience, a stable and efficient operational backbone, an adequate digital infrastructure, shared data, and digital intelligence. Everything must align with your role and position within your digital ecosystem. This is not only about the right technology but also about the right skills, the right leadership, and the right governance. This makes building a Digital Enterprise a strategic issue.
Better Customer Experience
Three examples show how each time one of the five building blocks serves as the springboard to success. Which component of the Digital Enterprise you choose depends on the specific context and ambitions. For example, a specialist in solar panel mounting materials wanted to improve the experience and connection with customers to support its European growth ambitions.
It operates within an ecosystem that includes the parent company, financial service providers, regulatory authorities, and distributors who in turn serve the market of homeowners and real estate parties through installers. By visualizing this ecosystem, the company discovered that the installer is actually the key actor and that a long-term relationship must be established there.
A well-thought-out digital ‘installers journey,’ based on customer knowledge and flexible front-end technologies, makes it possible to bypass the traditional distribution network. This places the specialist much closer to the end customer – which can be very important within the dynamics of the ecosystem.
Integrated Backbone
A globally operating leasing company is taking a different strategic approach. The company wants to become the first fully digital ‘Car as a Service’ provider in a transforming automotive sector. In doing so, it responds to the trend from ownership to consumption. To realize this, the entire, heavily outdated core application had to be overhauled.
The company operates in a complex ecosystem with fuel and charging card providers, the ECB as a regulatory authority, maintenance and repair services, car brands, and consumers. As a spider in this automotive web, data exchange must be in order. Good direct contact with the consumer is impossible without the right customer experience. For all this, a scalable, fully integrated backbone was built. This all-encompassing platform is unique in the world and can be marketed ‘white label.’
Such a step requires strong leadership because with every innovation of processes and systems, you are faced with choices: where do you opt for market solutions, and where do you want to differentiate as a company? Moreover, you must decide where to grant local markets the necessary autonomy and where everyone must conform to the global standard.
Energy Transition
A local European grid operator faces the ongoing challenge of maintaining the balance between electricity supply and demand. In a reality where more and more energy is generated decentrally—among other things by the user—and where greater reliance is placed on sustainable but uncertain sources like sun and wind. Meanwhile, electricity demand is rapidly increasing. The current high-voltage grid, consisting of various assets, is therefore reaching its limits.
By preparing the grid with data and intelligence for the energy transition, a leap forward is made. From the ecosystem of construction and maintenance partners, energy producers, regional network providers, and large industrial consumers, large amounts of asset data are collected. This makes it possible to better predict energy demand, as well as maintenance of assets. Better choices can be made. For example, supplying a bit more electricity on cold days, because physical network components are less likely to overheat.
In addition to a modern data platform and an AI Competence Center, effective data governance is essential. Data from relevant sources is delivered to business users as an information product via dedicated Product Teams. Enabled by data-related Centers of Excellence and Platform Teams. This way, the balance between generation and consumption can still be guaranteed, even in increasingly complex dynamics.
Key Roles
To take the right steps as an organization and leader within a digital ecosystem, a good understanding of the desires and interests of all other stakeholders is fundamental. Consumers, citizens, and end users, in particular, play a key role. Therefore, research how you can best connect with them. Keep the most important stakeholders close, and thereby strengthen your position as a digital enterprise within this dynamic interplay of actors. This is how you build an organization that not only participates in the digital ecosystem but also helps shape it.
‘Know your role and value within the larger whole’
Modern business ecosystems are like digital jungles: complex, dynamic, and full of interdependencies. During the recent CIO Masterclass by Anderson MacGyver, leaders from the tech and business world got an in-depth look at how organizations can remain relevant within the networked economy and society. From Tesla shame to local heroes, the masterclass demonstrated that technology is only one part of the story…
As many people, I initially think of nature when I hear the word ecosystem,” said moderator Fiep Warmerdam in her opening speech. “For example, the ‘Circle of Life’ from The Lion King, where everything is connected and balanced: the lion hunts the gazelle but nourishes the grass on which herbivores graze after its death. A disruption in this balance, caused by greed or a lack of respect, ultimately leads to misery for all. A similar balance applies to most of our business ecosystems.”
The moderator herself once worked at an e-commerce platform that, to deliver value to customers, depended on the right partners within a broad and complex partnership. The company enables product suppliers to automate the management and publication of product data across various marketing and sales channels. Examples of platforms it integrates with include Zalando, eBay, Google Shopping, Amazon, Facebook, and Instagram. Additionally, it connects with price comparison websites.
“Many different partners, and therefore many integrations and data flows,” says the Anderson MacGyver consultant, who immediately highlights three fundamental features of digital ecosystems. It’s also important that the right players are involved. “For leading players, you’re only interesting once you work with other big names.” APIs and software as the backbone provide a high degree of agility, meaning it’s essential to continually add value and maintain your position within the ecosystem’s dynamics.
Tesla Shame
The speed at which your value within an ecosystem can change is illustrated by colleague Robbert Petterson with a current example. “Are there any Tesla drivers here? So few? Who’s too ashamed to admit it?” The consultant and researcher refers to Elon Musk’s controversial actions around fake news on his X platform, his open support for Trump, and his involvement in European politics. “The result is a dramatic drop in demand for his brand, while the demand for electric cars remains. Competitors are, of course, taking advantage of this.”
The message from Robbert Petterson is: never underestimate the role of consumers and citizens. “It’s crucial to know what they find important and value.” And you generally don’t deliver that value alone, especially in a world of increasing digital interconnectivity. “So, you need a clear understanding of the ecosystem in which you operate.” To make this easier, Anderson MacGyver has developed the ValueWeb, which visualizes all the actors and their relationships.
To effectively participate in such a partnership, the consultant argues, you need to build a Digital Enterprise. Five essential and closely interlinked building blocks shape a modern organization: a distinctive customer experience, a stable and efficient operational backbone, an adequate digital infrastructure, shared data, and digital intelligence. Everything must align with your position within your digital ecosystem. It’s not only about the right technology but also about the right skills, leadership, and governance. This makes building a Digital Enterprise a strategic issue.
Real-world Examples
He gives three examples where one of the five building blocks is the springboard to success. To grow, a specialist in mounting materials for solar panels worked on a digital ‘installers journey’ to improve relationships with the installers serving the end customer. A large leasing company wants to become the world’s first fully digital “Car as a Service” provider. Its new integrated and scalable backbone is unique globally and can be marketed as a “white label” platform. An energy grid operator is moving forward by using data and intelligence to prepare its high-voltage grid for the energy transition.
To take the right steps as your own Digital Enterprise, understanding the wishes and interests of other parties within the digital ecosystem is fundamental. “Keep a close eye on consumers and citizens,” concludes Robbert Petterson. “Investigate how you can best align with them and solidify your position within this dynamic interplay of actors as a digital company.”
Would you prefer to be part of someone else’s digital ecosystem, or would you want to create one yourself? This question is central to the presentation by Lauri Koop, former CEO of DPG Media Online Services and, until the end of the first quarter this year, the head of Aimwel: a DPG subsidiary that automates marketing campaigns for the recruitment sector. The Finnish-Estonian tech leader then gave a fascinating insight into the dynamics of online media, where one must deal with the dominance of American tech giants.
Technology as the Engine
Technology plays a central role in how modern ecosystems serve the customer. “Look at Uber, Spotify, Apple, Amazon, Microsoft, Google, and so on,” says Lauri Koop. “Every big company wants its own ecosystem.” The profit lies in several areas: new revenue streams and business models, accelerated adoption of new technologies, lower costs, and more efficient processes. And last but not least, they give the owner power and control.
“Once you have or are part of an ecosystem, others can’t easily push you out,” continues the Aimwel CEO. “At least five of the seven largest companies in the world have or are building a digital ecosystem.” Only oil company Aramco and chip maker Nvidia – which is working hard on an ecosystem with software companies – remain more traditional. It’s also clear that the Americans control this dynamic.
What does this mean for his own professional domain? The fact is that media companies are highly overrepresented in online search results because they share so much information and interlink search engine-friendly articles. They can also form the link to a range of affiliate partnerships and handy apps, bringing people, products, and services together. They must, however, be visible within the environments of tech giants like Meta and Google, who control much of the power.
Building Your Own Ecosystem
Teaming up with these big players costs a lot of money. “Almost half of every advertising euro ends up in the pockets of tech giants and smaller players in the ecosystem,” says Lauri. This makes it worthwhile for media companies to be in control of their own ecosystem.
This can be achieved by companies like DPG Media using one-time permission for commercial actions across all their titles and brands. This greatly expands their reach. Local heroes emerge as a result: successful ecosystem-like platforms, with examples such as Funda.nl and Bol.com. Open ecosystems, according to Lauri Koop, have the greatest chance of success because they provide more value to the end-user.
Lauri concludes with a summary of key points for anyone wanting to claim a leading position in a digital ecosystem: know what the user wants and what you can offer, work with the right strategic partners, and be aware of the potential impact of new activities. You don’t want success in one area to come at the expense of other valuable activities.
Search Engine Out of the Game?
Finally, during the interactive Q&A session, an interesting point was raised. One of the masterclass attendees mentioned no longer using search engines, instead navigating online via ChatGPT and other AI services. Lauri Koop confirmed that this is a visible trend. “Visitor flows are increasingly finding their way through new channels. It’s evident that business models will change.”
The rise of AI once again highlights the volatile online media dynamics, where things can suddenly take on a different perspective. According to Robbert Petterson, this is a good reason to keep a clear understanding of what value you are delivering with which partners to whom. “Get closer to the consumer, citizen, and end-user – stay with them, respect them, and maintain your role in the ecosystem.” And thus, the story, as in any living ecosystem, returns to its origin: the interdependence that keeps everything moving.
By Anton Bubberman
What is the essence of a true digital enterprise and what can you do as a company or leader to realize it? Anderson MacGyver’s Digital Enterprise model offers a solution. Anton Bubberman leads the Data Guild within the consultancy firm. He explains how his professional scope aligns with the digital ambitions of clients.
The Digital Enterprise model places the organization within the context of the market and business ecosystem, and then focuses on five essential building blocks: a strong customer experience, a robust operational backbone, a flexible digital infrastructure, shared data and digital smartness. In combination, these fundamental components ensure a culture of continuous improvement and agility, allowing the organization not only to respond to change, but also to predict and capitalize on it.
Data is at the core
Data is at the core of the digital enterprise. Combined with the digital infrastructure, it forms the basis for digital smartness, which extends to both the customer experience and the backbone. In addition to solving common data-related pain points such as quality, availability and security, the gains from good data management are particularly important in the pursuit of scalability and smartness. For an ultimate customer experience and optimal operational efficiency and optimal interoperability in the business ecosystem.
At Anderson MacGyver we speak of Data to Value. This approach is based on three pillars: providing strategic direction, creating a technically sound data foundation, and doing what is necessary to deliver value on time at scale. All this must be tackled together. You can only work on data quality or technology if you can explain what concrete value will be delivered.
For example, in companies with a lot of legacy IT, the realization of a data platform is often on the priority list. But without a strategic vision or intended result you won’t get much further. The same applies to another one-sided approach or focus. Preferably start with cases designated as urgent by management – which can vary from advanced track & trace within a logistics company to relatively simple management dashboards. You then look at what is needed to realize such a valuable opportunity.
Holistic view
A holistic view of availability, control and use enables you to get maximum value from data and realize digital smartness. A lot of attention is paid to realizing a company-wide data driven culture in which data is used as a solution for preventing risks or realizing opportunities.
In short: data is the foundation of digital smartness and the strength of the Digital Enterprise – making it one of the key assets. Click here to learn how to transform your organization into a Digital Enterprise and take the first step towards a successful future.
By Onno Wasser
What is the essence of true digital entrepreneurship and what can you do as a company or leader to realize such a digital enterprise? Anderson MacGyver’s Digital Enterprise model offers a solution. Onno Wasser leads the Technology Guild within the consultancy firm. He explains how he connects to the digital ambitions of clients from his profession.
The Digital Enterprise model places the company within the context of the market and business ecosystem and then focuses on five essential building blocks: a strong customer experience, a robust operational backbone, a scalable digital infrastructure, shared data and ‘digital smartness’. In combination, these core components ensure a culture of continuous improvement and agility, allowing the organization not only to respond to change, but also to predict and capitalize on them.
Different starting point
A ‘fit for purpose’ IT environment has always been important. However, with the pursuit of a Digital Enterprise, the starting point sometimes changes. Companies are still busy solving pain points such as outdated technology, poor integration, or excessively high IT costs. With digital ambitions, this goes hand in hand with an enticing perspective: realizing distinctive digital customer experiences, new business models, optimal processes and interoperability within chains and ecosystems.
The role of technology remains largely unchanged. Both at the customer- and employee-oriented front end and in the backbone, IT must fully align with the strategy, activities and objectives of the organization. With modernization, rationalization, and/or improvement, you still work on a suitable target landscape based on an architectural vision, strategic priorities, costs and business value. Selecting and implementing IT solutions is also part of this.
Maintaining control
Depending on the nature and objectives of the organization, you can opt for standard solutions, customization and/or sourcing at both the front and back end. In practice, more and more companies are obtaining capabilities from the market that they do not have or cannot realize themselves – the digital infrastructure in particular lends itself well to sourcing.
Regardless of what exactly you outsource, maintaining and arranging control is fundamental. The idea that an IT supplier will solve everything for you is a major pitfall. For digital transformations, as an organization, you ideally need to free up your best people.
Whether you are solving a pressing pain point or working on new digital possibilities, it often starts with getting the house in order. From a stable foundation, you can work on further developing customer experience, operational efficiency and digital intelligence. Incidentally, these are and will remain large and comprehensive transformations.
In short: appropriate solutions, enabling technology and a scalable and open digital infrastructure are crucial. Click here to learn how you can transform your organization into a Digital Enterprise and take the first step towards successful digital entrepreneurship.
By Josip Cicak
What is the essence of a true digital enterprise and what can you do as a company or leader to realize it? Anderson MacGyver’s Digital Enterprise model offers a solution. Josip Cicak leads the Strategy Guild within the consultancy firm. He explains how his professional focus on business strategies aligns with the digital ambitions of clients.
The Digital Enterprise model places the organization within the context of the market and business ecosystem, and then focuses on five essential building blocks: a strong customer experience, a robust operational backbone, a flexible digital infrastructure, shared data and digital smartness. In combination, these core components lay the foundation for a culture of continuous improvement and agility, allowing the organization not only to respond to change, but also to predict and capitalize on it.
Setting a goal
Strategy involves providing direction and taking actions to achieve a set goal. As a company, you cannot see this separately from your position and added value within the ecosystem in which you operate: partners, suppliers, customers and other stakeholders. When striving for a Digital Enterprise, strategic adjustments often need to be made on the five pillars mentioned. Preferably in coherence.
Although digital propositions and customer experiences require a lot of attention, the operational backbone must also be in order. This means standardization, cost efficiency to unlock capital needed for improving products and services with smart solutions. Everything you do must be in line with your distinctive character within the context of the business ecosystem. In other words: what do you do as an organization, for whom and for what purpose?
Holistic approach
Strategy, technology and organization must be approached in congruence. This way you can find the most suitable IT for different activities. Standard platforms and market solutions for generic business actions, and more degrees of freedom in technology and data choices for differentiating business activities – or something in between. A critical look at business activities or customer experience can lead to a strategic or organizational recalibration.
When shaping a digital enterprise, the role of leadership is crucial. As Anderson MacGyver we provide directors with all the necessary tools to tackle all strategic, technological and organizational challenges from a holistic perspective.
In short: the model provides board members with insights into the interrelated strategic building blocks. Learn how to transform your organization into a Digital Enterprise. Click here to download the whitepaper ‘How to become a Digital Enterprise’ and take the first step towards a successful future.
By Edwin Wieringa
What is the essence of a true digital enterprise and what can you do as a company or manager to realize it? Anderson MacGyver’s Digital Enterprise model offers a solution. Edwin Wieringa leads the Organization Guild within the consultancy firm. He explains how his professional scope aligns with the digital ambitions of clients.
The Digital Enterprise model places the organization within the context of the market and business ecosystem, and then focuses on five essential building blocks: a strong customer experience, a robust operational backbone, a flexible digital infrastructure, shared data and digital smartness. In combination, these fundamental components ensure a culture of continuous improvement and agility, allowing the organization not only to respond to change, but also to predict and capitalize on it.
Interrelated challenges
Organizing a digital enterprise focused on business value has three strongly interrelated challenges: executing the strategy; application of technology that meets the needs of consumers, customers and business; and combining exploitation and exploration – or ambidexterity where turnover and innovation go hand in hand.
A holistic approach, addressing all three challenges, is fundamental to achieving strategic and business goals. To this end, the organization must be aware of the added value within the business context and what needs to be done to achieve digital ambitions. You then determine the direction and roadmap for tech, data and organization. For all this, Anderson MacGyver has a proven collection of methods, techniques and metrics.
Although continuous attention must be paid to the optimal basis of back end processes and infrastructure, the most benefit can be achieved at the front end: offering the right digital products and services through the desired channels and the associated user experience. Smart application of data is crucial to improve customer processes.
Four levels
Generating the highest business value requires an effectively designed organization. This ideally happens at four levels: digitally driven leadership and competencies, management via a coordinating layer to execution, where multidisciplinary teams deliver what is needed. A control layer verifies whether all this is in line with the principles.
Digitally driven leadership and capabilities are required at all organizational levels. This includes the right working methods, culture and ‘digital appetite’. To build a bridge to the optimal application and organization of technology based on business opportunities and distinctive added value for the customer, organization and ecosystem partners.
In short: the Digital Enterprise model offers a structure to distinguish teams focused on agility from those centered on stability and efficiency. Learn how to transform your organization into a Digital Enterprise. Click here to download the whitepaper and take the first step towards a successful future.
How do you make GenAI a successful part of your overall data journey? For over 10 years, Frank Ferro has been generating business value with data and AI. After many years as a senior executive at PostNL and a temporary role as Program Director GenAI at ANWB, he will soon take up the position of Director of ICT at Amsterdam UMC. During a recent CIO Masterclass at Anderson MacGyver, he shared his vision and experiences. Here’s a summary.
In various sectors, the focus has long been on physical products and services, but attention is increasingly shifting toward data and algorithms. These are no longer just used to enhance customer experience and optimize business processes but are also becoming marketable products in their own right.
To effectively work with traditional and generative AI, three things are recommended: a safe and controlled environment, proper governance, and maximum independence from major tech players. The foundation for this is a solid data management structure and IT architecture, which organizations have often already been working on for some time.
Moreover, it is crucial to know exactly what you are doing. This usually starts with improving the necessary knowledge level within the organization. This requires genuine attention, as even a basic level of data literacy is often lacking.
This approach allows you not only to work on the required quality of data—both centrally and from within the business—but also to explain why you are using AI, where, and how. For example, when an algorithm makes decisions in a call center environment, it should be transparent what the AI is doing and for what purpose. The same applies to fraud detection applications.
In the early stages, it’s best to choose a straightforward, engaging “moonshot case” that generates visible business value for everyone. Without active involvement and support from the business, initiatives are unlikely to succeed.
Controlled Environment
A key recommendation is to use GenAI in a safe and controlled environment. Just like WhatsApp, where the data itself may be secure, metadata—such as who you contact and when—can reveal more than you might wish.
For instance, the free version of ChatGPT is not entirely watertight in this regard. However, the Enterprise version provides a secure, controlled AI environment. This allows even non-IT professionals to experiment and work with it, using their own personal and professional configurations. Examples include rewriting executive announcements or other official communications in plain language, which can save executive and communications teams significant time.
Another example is deploying a large language model (LLM) to answer customer inquiries via email at scale or to generate code for programmers—a practice already commonplace in many companies.
For most applications, humans will still remain in control for now. Microsoft Copilot, for instance, is explicitly not an autopilot. It acts as an assistant that can significantly boost productivity, but it is not error-free.
Proper Governance
Step two: ensure proper governance. Start by establishing a Data & AI Governance Board, which can assist at the executive level in making decisions about the potentially sensitive or impactful use of data and algorithms.
Equally fundamental is control over reliable data—not only to ensure process efficiency and achieve goals but also to comply with laws, regulations, and privacy and security requirements. Implement robust central and decentralized data management and quality control.
Interestingly, the “data owner” is often not the “data lord.” In other words, the person responsible for data quality is not always the one using the data to create valuable and intelligent solutions for the business.
Therefore, it is wise to embed data management within the business itself. Teams can then take responsibility for cleaning their own datasets for specific initiatives or use cases, even when data quality across the organization is not yet optimal. Waiting to start with GenAI until all company data is clean and ready may result in never getting started at all.
Meanwhile, you should work on the master data, ensuring, for instance, that all customer data is collected and accessible within a single system. For new initiatives or technical possibilities involving customers, there should always be a connection to the master data management system.
Virtual Federative Approach
A central vision and policy are necessary for an organization to reach the desired maturity level in data and AI. However, to make progress within specific business units or divisions, you can adopt a virtual federative approach. This involves assigning staff from the central tech or data department to specific business units or projects.
Over time, data governance and data management can increasingly be handled and discussed at the decentralized level—for example, during planned meetings or sessions. Initiatives with potential risks related to security, privacy, or ethics can then be escalated to the central Data & AI Governance Board.
You should also consider conducting an ethical assessment to determine whether new digital possibilities and plans align with the organization’s values and principles. Often, this will quickly clarify whether something is feasible or not. Such assessments can also help identify risk mitigation measures.
Maximizing Independence
Finally, strive for maximum independence from big tech. It’s fine to use services from Microsoft, Google, and other major players, but avoid becoming dependent on them. Instead, select services and providers that add the most value in your context, and don’t put all your eggs in one basket.
Ensure you have a control layer capable of integrating with multiple LLMs. This enables you to use the most effective LLM for each use case.
In summary, GenAI offers unprecedented opportunities to create business value but requires a well-thought-out vision and approach. Ready to take the next step? Anderson MacGyver combines years of experience with challenges in strategy, organization, data, and technology to help drive new digital developments. Want to know more? Contact Anton Bubberman to share your ambitions and challenges. We’re happy to help!
By Tim Beswick
We are often asked whether becoming an AI-driven enterprise requires something different than becoming a data-driven enterprise. In this series of blog posts, Anderson MacGyver shares her point of view on this topic. For those who want to start from the beginning, you can read:
Part 1: How do we become an AI-driven enterprise?
Part 2: Data-to-AI-to-Value journey
Part 3: theme 1: The generative / general-purpose AI model buzz
Part 4: theme 2: Business process redesign requiring even more attention for people change
Part 5: theme 3: Additional risks and different measures
Now, let’s dive into the last part: the fourth underestimated theme.
4. Even greater challenges in accessing AI talent
Theme four of the four underestimated themes
It is widely acknowledged that demand for data talent is higher than supply. This imbalance increases when including specific AI capabilities in the equation.
AI relies on talent in domains that are most scarce. It concerns domains such as software engineering, data science, machine learning engineering, NLP engineering, robotics engineering, data engineering and multidisciplinary agile development. It is important to take this into account and include the following in your journey to becoming an AI-driven enterprise.
- Focus; do not run after abstract visions but work with the business on defining and prioritizing tangible Data-to-AI-to-Value opportunities. Direct your scarce talent towards these highest priority opportunities.
- Retention; Do not fall into the trap of promising the most advanced AI applications in your organization to attract talent. You will probably disappoint and quickly lose anyone who was driven by this after a while. Throwing away your recruitment investment, creating inflated costs through constant delay and handovers. Instead, be honest and clearly articulate what truly makes your organization attractive; your societal role, your working atmosphere, your maturity stage and associated opportunity to be part of something new, etcetera. Attract talent that is driven by your organization’s true characteristics and stand a higher chance of being an attractive environment for your AI talent for a longer period.
- Strategic sourcing; Pay attention to defining a sourcing strategy. Utilize all sourcing options to your benefit. Carefully consider where to vest your inhouse talents. Assess which external suppliers can be leveraged for which scope. Investigate options to collaborate in your eco-system if there are potential synergies and there is no commercial value in differentiation in your eco-system.
Recap:
In this series of blog posts, we looked into the question of how the journey to being an AI-driven enterprise differs from the journey to being a Data-driven enterprise. We described how AI-driven enterprises unlock value by using digital systems that, based on data, learn and adapt and generate new video, image, text, sound and code and/or trigger actions or autonomously act.
We shared how, like for Data-to-Value journeys, successful Data-to-AI-to-Value journeys are built on the following four good practices:
- Create a commonly understood business value centric vision, goals, and strategy.
- Define tangible business value opportunities as bridges between business value and data.
- Use these as the guiding stars for focusing your transition efforts.
- Pay attention to the undercurrent of people change.
In addition to these four good practices, the following themes require specific attention in cases where AI plays a major role in an organization’s digital transformation journey:
- The generative- / general-purpose AI model buzz.
- Business process redesign requiring even more attention for people change.
- Additional risks and different measures.
- Even harder access to AI talent.
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By Anton Bubberman
From opportunities in customer experience to radical efficiency improvements: AI is a game-changer if you know how to apply it. Yet, there is a risk in implementing it carelessly. How can AI be deployed in a valuable and responsible manner? Data to Value expert Anton Bubberman outlines the current state of affairs and provides companies and their leaders with tools to strategically embed AI in the modern Digital Enterprise.
Everyone has some level of experience with AI by now and therefore an opinion on it. Interestingly, opinions vary widely. Some consider it an over-hyped buzzword, while others warn that we are underestimating its power. Some see mainly opportunities in AI, others see threats—possibilities versus responsibilities.
As with many technological advancements, we are probably prone to overestimating the short-term impact and underestimating the long-term effects. Tech companies contribute to this tendency by boasting about technology still in development—it often takes years before it reaches the market. And when it does, we are no longer impressed. At such moments, we underestimate the real changes it can bring.
Take big data, for example, where the buzz from years ago has largely died down. This leads us to retrospectively label it a hype. But let’s not forget: our investments in big data have given us tools like large language models such as ChatGPT, which can read and interpret PDFs, photos, audio, and video files without opening them. And this is just the beginning.
Three Crucial Success Factors
Considering these developments, it’s well worth becoming an AI-driven Digital Enterprise. To achieve this, three fundamental success factors come into play. I like to compare these to chess, jazz, and philosophy. But first, let’s consider where we currently stand…
European legislation defines AI as a machine-based system designed to operate autonomously to varying degrees. It can adapt to circumstances to deliver diverse outputs, such as predictions, creations, recommendations, and decisions that impact physical or virtual environments.
AI becomes more powerful as its autonomy and adaptability increase. We’re moving from relatively simple rule-based computing to the holy grail: artificial general intelligence (AGI), which matches human cognitive abilities. Already, AI can independently perform complex tasks in various domains and learn to adapt to new situations.
From Robot Dog to Back Office
Some experts believe AGI is still half a century away; others think we will reach it by 2025. Until then, individuals and organizations exist on a continuum between consuming and building increasingly advanced digital intelligence. AI will embed itself more and more into the operating systems and applications of our devices and systems, linked to both personal and business data. But what steps are we taking ourselves, as leaders and as companies?
At Anderson MacGyver, we help organizations become Digital Enterprises. We have developed a model for this, based on five critical building blocks. At the core is ‘digital smartness’ alongside ‘shared data’, supported by ‘digital infrastructure’ at the base, with ‘customer experience’ and the ‘operational backbone’ flanking it on either side. Additionally, the Digital Enterprise is embedded in an ecosystem of customers, partners, and other stakeholders.
In terms of AI, the possibilities are vast: from robot dogs scanning physical production environments to intelligent front-office systems for diverse forms of human communication—social, supportive, advisory, and more, in any language. And alongside these, tools to monitor and enhance both customer experience and operational processes in the back office.
Thinking Ahead, Improvising, Philosophizing
Like chess, AI revolves around thinking ahead, planning, and evaluating. The playing field is constantly changing, as are the opportunities and threats within your organization and ecosystem. Organizations and their leaders must remain agile, always contemplating the next move.
The connection to jazz lies in the apparent ease of playing and improvising, which often disguises the long period of practice required. Beyond physical skills, one must master theoretical frameworks. Mastery demands dedication, encompassing hard skills as well as soft skills—such as interacting with other band members.
Similarly, in the digital realm, alongside technical prerequisites, an AI-driven culture is essential. This culture should critically assess outcomes for their added value and ethical dimensions. While music and jazz may be hobbies for me, AI cannot be treated as a side project within an organization. True mastery demands significant investment.
AI also requires philosophical awareness of its ethical impact. It has the potential to propel individuals, organizations, and others forward significantly, but this power comes with risks. Like a surgeon’s scalpel, AI can achieve wonders in skilled hands but cause harm when misused or mishandled. With tools like AI, one must guard against risks such as information bubbles, misrepresentation, and bias.
Building a Better World
We must remain mindful of how we use AI for our customers and other stakeholders. They need to trust us, rely on us, and know that we understand the impact it has on them. Yes, jobs will disappear, and even more jobs will change. But in capable hands—with the right policies, guidelines, mindset, and behavior—AI holds the power to achieve great things. For instance, creating an intelligent and scalable Digital Enterprise. And perhaps even a better world to live in.
As AI becomes increasingly embedded in our daily lives and business operations, it’s up to companies and their leaders to guide its application. What first step will you take today?
Anton Bubberman is a Senior Management Consultant and Guild Lead Data to Value at Anderson MacGyver. He has extensive technology and data experience across sectors ranging from healthcare to energy and finance.
Anderson MacGyver
The core purpose of Anderson MacGyver is to harness the unrealized business value for our clients by leveraging the powerful potential of technology & data. We provide strategic advice and guidance to board members and senior management to shape and drive their digital journey.