On the verge of a systems breakdown
The past year has been really difficult. The COVID-19 pandemic hit us hard and forced us to rethink a lot of dynamics. Many still think that the pandemic broke our system. Truth is that the system was already broken and just waiting for that little nudge to collapse. We should have realized that most businesses were in a dead end street, running towards a wall that they would hit one day or another.
That’s because most of the structures we had been building were too numb, too robust and too globally oriented:
1. Comfortably numb.
We let our organizations grow numb and neglected to take care of our people and our planet. No matter how hard companies shout that they put the customer in the center of their universe and no matter how convincing they claim to put employees first, it becomes pretty clear that most companies still rely on ‘good old’ operational measures and forget about customers and employees whenever shareholder value is under threat.
Comfortably Numb as in swimming in large data lakes without actually doing anything with it, but looking in the rear view mirror and projecting the past into the future. Numb as in not using the data that were collected or as in not even collecting any other data than those that fit the assumptions from the past and fed the existing processes.
2. Robust.
We all know that shareholders highly dislike risk and want to minimize it whenever they can. As a result, companies are risk averse by definition. They operate under the false belief that the only way to minimize risk is by defining strict procedures, KPIs and reports that create rigid companies. Ironically, these mechanisms against risk also kill off any form of innovation that is more than just incremental.
3. Global
As shareholder value forces companies to maximize operational excellence, they go global for three reasons.
First, because operational excellence run by Excel sheets, forces companies to source globally, or re-locate. Companies are always looking for ways to optimize profitability, not taking into account the effects on people and planet.
Second, to maximize the ROI on fixed assets like a production site, a headquarter, a marketing division,… companies try to scale up the sales of products and services. For years ‘blue ocean strategy’ was the bible: find new markets for existing products. Why not export our products?
Third, just because it can be done. Internationalization is not even that difficult. The supply chain assets are in place and impact on people and planet is still not a KPI that defines shareholder value. So why care?
But sooner or later, our delusions would turn on us. Endless growth on a limited planet is not an option. A change was long overdue.
Creating the perfect antidote
Not caring for people and planet, not being data driven, being rigid and global, had become the standard way of growing a successful business in the 20th century. The universe in which those companies were and still are conducting their businesses, has been changing so fast in the last decade and will keep on changing in the decades to come. Soon the gap between that business model and the needs and demands of customers will be so huge, that it will kill them. The sad part is that they knew but were too stuck to stop the wheel from spinning. Covid-19 created a unique window of opportunity to re-start the business model in a different way.
Why would we ever go back to that destructive and egoistic old “normal”, when we enter the post COVID-19 era?
Why not create the perfect antidote: an economy in which companies are connected dots that collect, share, analyze, process and activate data in smart (as opposed to numb) ecosystems that are good for people and planet, antifragile, and local.
The ticket to ride in this new smart ecosystem economy is data, data and data. Everything, everybody and every action will become measurable, and will leave digital traces. Those data can be transformed into information that can be used to out-clever the competition. When one data source is combined with another in a clever way, that may lead to completely new insights and revenue streams that one could have never imagined. As a result, data sharing has become the domain of big interest for companies in the quest for new business models.
The holy grail?
Before you start to throw a party because you think you have found the Holy Grail, you better beware: that holy grail may come at a high price.
Those companies that have the guts to make the right strategic choices and that dare to dive into the data driven ecosystem economy, may create unseen future value – often not tied to traditional industry lines as we have known them for decades. But they need to realize that there are huge potential risks that are concrete and measurable. There is also no absolute guarantee as to the future outcome of sharing data in an ecosystem.
I am guiding a couple of companies on their way to that ecosystem economy for the moment and we have been confronted with quite a lot of hurdles and barriers in between the data sharing dream and actually realizing a data driven ecosystem.
To whom it may concern, these were the hurdles that we were confronted with:
Game of data
When companies want to explore the full potential of combining data streams, they soon find out that data management is excruciatingly hard. It gets worse, though: data management in an ecosystem is even more atrocious: it is like a whole other universe, with completely different rules and behavior. It’s very much like Game of Thrones. We’ll call it ‘Game of Data’.
Seriously, it is true that it sounds tempting to enrich your own data with data from other sources to increase the quality of the output, such as products, services and even business models to enhance (future) value creation. But companies soon discover the following important problem areas:
1. Trust
Data can be misused, maybe even abused, or end up in the wrong hands. Outdated technology, bad governance and data leaks can lead to data not being deployed as originally intended and as agreed upon by the participating parties.
2. Cost and complexity
Every data transaction carries costs that may lead to problems of a technological or procedural nature. With regard to technology, bad connectivity, mismatching standards and a lack of data compatibility must be avoided. As for procedures, once again it’s about differences in knowledge and skills, as well as organizational structures and internal rules that must be aligned. It is better to bring technological challenges together on a common platform and to outline and implement collective governance there.
3. Internal competition
For most participants, this type of collaboration will be new. The whole data-landscape appears to be largely untapped territory and it seems like there are new products, services and business models that can be discovered every day. It is only logical that companies are scared to lose their competitive advantage when sharing their data. Players from the old economy, in particular, fear throwing the door wide open to new rivals who are better armed technologically to do clever things with ‘their’ data. More digital players fear that traditional players will want to steal their technology and people. On top of that, all players in the ecosystem fear that the ‘owner’ of the platform will draw too much of the value creation toward themselves.
4. Missed financial opportunities
Another consequence of the fact that everything related with data is still largely unknown territory is the danger that companies, by sharing data as their first approach, may not see the potential profitability. By focusing on their participation in the ecosystem, individual value creation may not be optimized. The danger also lies in value creation by one participant in the ecosystem (improving logistics for example) being partly absorbed by the ecosystem and not completely by the concerned party.
If these four crucial topics are not sufficiently managed within an ecosystem, that will result in potential dangers that continue to outweigh potential value, and the ecosystem will not be able to get on course and is thus doomed from the start.
The importance of ecosystem values
What’s important is that companies understand how to create and maintain the right context in order to keep the data-driven ecosystem together. Companies must be aware of the potential value, possible risks and latent sources of conflict that are unique to ecosystems. That is why good governance is needed.
Collective and socially relevant goals
First and foremost, an ecosystem has to claim a very outspoken strategic position in the market around one or more collective and socially relevant goals (good for people and planet) . By getting the participants in the ecosystem to sign a non-compete agreement for that specific claim, you can remove the risk of mutual competition and foster the trust needed to share sensitive data with each other. Moreover, participants can be assured that their data are being used correctly thanks to automatic privacy tools that protect the sources of data while they are being processed in the ecosystem.
The basic attitude towards data cannot be clear, expressed and documented enough. Any leeway for interpretation undermines trust and can thus undermine the ecosystem. The definition of what is deemed to misuse or even abuse of data must be clearly set out. This could include collecting or sharing data without authorization and sharing data outside of the ecosystem. These are obvious examples, but they must be defined. One of the ecosystem’s crucial roles is to monitor the values of an ecosystem closely.
Inclusive
Data must contribute to inclusive cooperation between companies. We must take into account the differences between participating companies without losing sight of equality. Data must contribute to making the ecosystem stronger as a whole and must be available to everyone. Data must never shut participants out and the management of data must not have any negative impact on participants.
Well managed
Data management increases the impact and freedom of participating parties. Managing collected data ensures influence over the collection and use of that data. It offers the possibility of being independent and of being freely able to decide what must be done with the data.
Legal and monitored
All companies in the ecosystem work together to ensure a fair and secure data landscape. In order to maintain a balance of power structures and avoid any abuse of power, it’s important for the data streams to be under control. Data is gathered in one context, and should be used honestly and implemented as effectively as possible.
Open and transparent
Transparency and openness are the foundations of the ecosystem. By being transparent, the platform shows what it does with what data. Access to data is to be correctly granted and long-lasting accountability is created by making the system transparent.
By dealing with data openly, ecosystems enable trust. Shared standards are very important for the ecosystem, which mainly allow for easy reuse and foster openness. By dealing with data and information openly and transparently, everyone is able to participate on an even basis of information, using the same knowledge and insights.
Collective
Data collected by participating companies is for collective use. The impact, sustainability and manageability of data exchange must be well organized, so that participants feel the benefits. The supervision of technology, what is allowed and what is not allowed, must be safeguarded in a meaningful way for everyone.
The functions of an ecosystem.
To find the right and delicate balance between autonomy and collaboration, each member within an ecosystem needs to know the ‘functions’ within an ecosystem and these roles need to be clear and well defined:
1. The platform
Here data is collected and processed into enriched data and thus information. The platform is also the producer and guardian of governance. The aim of the platform itself is not to add to value creation, but to process and enrich the data that is the foundation of value creation. As a result, the platform is a very neutral component and (in a traditional economic context) is a cost-center and not a profit-center. The way in which this cost-center is paid for must be determined in advance: it can be done on the basis of a set distribution framework or on the basis of the value of the enriched data (minus the cost of data input) or a combination of the two.
2. The participants.
They feed the platform with data and they use the enriched data and new information to develop new products, services, concepts, business models to generate new value. Participants can participate in several ecosystems. The products, services or business models that they create often become new sources of data that continue feeding into the platform through short feedback loops.
3. The enablers.
They look after the infrastructure of the ecosystem (the hardware, security and computing power for instance) and are duly compensated. Participants can also serve as enablers. Enablers may also feed external data into the ecosystem in turn, but not all enablers have to be participants in the ecosystem. They can also be utility providers. However, given that their data is also important, agreements with ‘external’ parties concerning data management and use are equally important where possible, especially with a specific enabler – the network enabler. This specific type is responsible for connectivity: a network enabler ensures that the data travels quickly. Network enablers are often not true participants in the ecosystem. However, due to the fact that they have access to the data, clear agreements must be established with them. It is vitally important to ensure speed, safety and a clear network in a well-functioning ecosystem.
Conclusion
If companies want to enter or start a smart ecosystem that collects and shares data from within and outside of a traditional industry, a company or an activity, they need well established values to prevent the potential problems of such new co-operations. Ecosystems bring parties together around one or more collective and socially relevant goals and keep them together to foster value creation together, while still giving each the freedom to innovate and develop themselves. This is not something that can be done with the old rules of conducting business and a whole new universe of functions and values needs to be created.
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