EU Projects FutureEnterprise Project

Blockchain and smart contract business models for distributed autonomous innovative organisations

Written by FutureEnterprise by Jonathan Cave.
Blockchain technologies are spreading, attracting both innovative adherents and inflated expectations. Although widely understood as a means of implementing payments in the ‘zero-trust’ spaces of global marketplaces, they have wider implications. This post will consider the potential of robust, secure, distributed and transparent ledgers to support new forms of enterprise, primarily because the technology can (in principle) facilitate the productive coordination of individuals and (especially small) enterprises. It does so by allowing individuals or enterprises that are not locked into long-term formal arrangements or relationships to (depending on your perspective) trust each other or to dispense with the need for costly third-party trust verification. In order to realise this potential, however, a range of issues must be tackled, including problems of business culture, the perceptions and processes of regulators and spillovers from the current hype (and anti-hype) surrounding the current headline use of Blockchains to facilitate electronic payments with a high degree of anonymity.
A ledger is a system for recording and transferring value – it thus helps to keep track of the ‘bottom-line’ performance of even a complex entity and to provide a channel for the exchanges among parties who make different contributions to generating and capturing value, with costs and benefits a different times. Therefore, a ledger is a means of compensating costly activity and a way of giving the parties involved a common and (hopefully) reliable insight into how things are going. It is also a special case of a public database, and thus an institutional technology.
A Blockchain is a decentralised ledger platform (Evans 2014). The decentralisation is backed by cryptographic methods which in effect ensure that anyone (or anyone with permission) can see what is written in the ledger, that anyone (with permission from everyone) can modify it, and that anyone using it can be sure that the contents are accurate and authentic. In effect, it keeps a cumulative record of the transactions affecting a given token of value. These are combined cryptographically and new transactions added to the chain through computationally complex activities that a) ensure that the publicly accessible ledger is reliable, up-to-date and visible to all and b) that the process of modification is sufficiently cumbersome that multiple new transactions involving the same value cannot occur simultaneously (the double-spending problem). These characteristics are obviously valuable in organising private commercial (and other) activity where dedicated rules of access and modification and the need for assured authenticity are of crucial importance. This is not limited to market-facing activities, but extends to dealings between governments and businesses (as we will discuss below). Payments obviously require these characteristics; they must be legal tender in the sense that people receiving a claim on value must know that it can be re-used and will be accepted by others, no matter where it comes from or where it goes to. They must also know (as a matter of common knowledge) that the value involved will be properly transferred in the sense that the recipient fully owns it and the payer no longer owns it. For money transfers, this means that the same token cannot be re-used or re-spent.
This is particularly important in the current Internet-mediated and globalised context, where transfers may need to be: highly automated; too fast for human scrutiny or control; carried out by algorithms; complex in structure; and spread across entities who do not know each other ex ante and have no cost-effective means of verifying identities or following-up agreements. Money itself and other financial instruments deliver some variant of these functions, backed by third parties such as governments or banks. But each of these trust service providers has, for one reason or another, found it necessary or advantageous to limit the scope and speed of value transfer services, giving rise to e.g. exchange rates, strategic transactions costs and potentially fraudulent opportunities for derivative creation and manipulation[1].
Such manipulation is particularly troublesome for small and innovative enterprises, which typically lack the resources fully to underwrite highly risky ventures and may thus be starved of capital. They cannot easily overcome information asymmetries, and in any case the risks affecting their profitability – and thus the capacity of the economy to identify and direct capital to ‘good idea’ and away from ‘bad ideas’ – depend on a wide range of factors including systemic risk in the economy (which will affect different businesses in different ways) and the incentives driving the behaviour of the firm itself and those to whom it is connected by financial or value chain relationships.
An example will illustrate the point. When a firm borrows seed capital from an investor, it should pay a risk premium to compensate the investor for bearing the risk of failure. At the same time, the premium cannot fully compensate the investor. To agree a contract, therefore, the parties have to come to a common view of the magnitude of the risk and its correlation with other risks (e.g. in the investor’s portfolio[2]). But the relationship does not stop there – if, for example, the investor also funds a rival, demands accelerated payment or calls in the loan or withholds additional financing needed to cope with e.g. delay, the investor can manipulate the probability of success. This is unproblematic providing the investor and the borrower divide the proceeds – both want the venture to succeed. But if the investor can hedge against failure by buying a swap (a CDS) that pays him off in the event of default, this connection is weakened. If (as is unfortunately the case) the investor, or third parties in a position to influence the success of the business can buy an unbounded number of these swaps, they may find themselves actively preferring failure of the original venture. They may, indeed, even seek to encourage ‘start-ups’ that are (or can be made) doomed to fail. Due diligence and transparency should help, but the problem may be complicated by secrecy rules, complexity and changes after the loan has been made and the venture undertaken. The ability to keep track of such related investments and actions in an open, distributed and trustworthy fashion could – in principle – greatly reduce the scope of this problem.
This is not the only solution, of course. As asset pricing models have demonstrated, markets have ways of identifying and pricing (assessing the combined magnitude and severity of) risks. In an ideal world, therefore, the prices of such swaps should provide an accurate measure of risk that does not depend on detailed public accounting and complex modelling of interactions. However, such ‘low-information’ approaches have proven disastrous precisely because of their low-tech nature; informed and uninformed investors can use them, and there is little incentive to work out what the price signals actually mean, when they can rapidly be sold on to other investors guided by the same naïve acceptance of market data. This was one of the main problems associated with the use of the Gaussian Copula formula (Salmon 2012[3]).
Therefore, a suitable structure of shared accounting for value that could be audited and verified would seem ideal, and Blockchains can certainly perform this function.
But there is nothing in the Blockchain story that requires the ledger system to be used for money transfers. As the Economist noted in a 2015 article,
“Ledgers that no longer need to be maintained by a company—or a government—may in time spur new changes in how companies and governments work, in what is expected of them and in what can be done without them.”
The growth of Blockchains has been associated to economies of scale and scope driven by Moore’s[4], Kryder’s[5] and Nielsen’s[6] Laws (see Davidson et. al. 2016[7]). In the context of small and agile enterprises, these advantages are magnified when the underlying technology is applied first to more complex transactions than payments and second, to the structure of industry itself. This can be understood from the perspective of Transactions Cost Economics (Williamson 1979[8]); Blockchains are a more cost-effective way of carrying out transactions, minimising not only the data-handling costs but also the agency costs associated with e.g. monitoring and verification.
What can be accomplished using Blockchains instead of firms or markets? Following Williamson, inefficiency in governance (and thus the blocking of some innovations) arises from the conjunction of bounded rationality (and incomplete information with asset specificity and opportunism. Opportunism is generally controlled through markets or hierarchical organisations, which impose hefty costs in exchange, including an embedded resistance to even the most productive disruptive change (though hierarchies are somewhat better than markets). But Blockchains tackle opportunism by technical means and economic incentives, effectively creating spot markets to carry forward what is in essence a pure promise of behaviour to create a durable asset without individual commitment.
But hierarchies and relational contracts did not come into existence only to tackle opportunism. Hierarchies exploit the incompleteness of contracts (using ‘position’ as a token) and relational contracting requires and rewards trust among parties. But Blockchains require contractual completeness while firms constitute networks of incomplete contracts.
It seems possible, in theory at least, to replace a complete network of incomplete contracts with an incomplete network of complete contracts. Put slightly differently, the ‘anonymity’ of a Blockchain is qualified – the identities of payers and receivers are securely unknown, but the path taken by tokens of value (the transactions themselves) are known with certainty. What matters is this; how much information must be known, and to whom, in order for the system to function?
Money itself has followed a trajectory that illustrates the point. Originally, cash thrived because it was legal tender, but also because it was anonymous as to both the identities of the parties and the previous history (except for being anchored to a root authority who struck the coins). It created opportunities for strategic corruption (including forgery and theft) and was costly to protect, transport and move over places and times. Therefore, alternatives (financial assets, credit cards, etc.) were developed that dealt with the new problems – but in the process they created ‘traces’ that weakened anonymity (for good or ill). Bitcoins and other cryptocurrencies based on Blockchain technology began as a way to restore what was lost without losing the transactional and ICT-friendly advantages of other virtual payment schemes.
The same applies to contracts. Instead of human-executed contracts that explicitly and permanently define their terms, we can now use smart contracts (self-executing digital contracts – Szabo 2005[9]) to govern interactions and transactions where humans cannot (for reasons of scale, complexity and velocity) venture and thus to connect organisations in a more agile, intelligent and innovation-friendly fashion. This, in turn, leads to a host of effectively decentralised applications including Distributed Autonomous Organisations (DAOs – Mainelli and Smith 2015[10]). These connections already dominate thinking about the architecture and governance of the internet of things (IoT), which ultimately requires decentralised registers for reasons of scale.
The IoT example also points up a further possibility, that Blockchains might use limited memory. At the moment, sufficiently extended Blockchains become ever more cumbersome to use and slow down. They also suffer from the problems that refreshment cycles become long (a matter of minutes) relative to the speed with which the value can be ‘spent’ and that compromises in the record that necessitate killing a specific Blockchain – a principle trust mechanism – can effectively result in ex post repudiation of other transactions along the chain. But these can be mitigated by a ‘moving window’ whereby early parts of the history can be separated or replaced with ‘catch-up’ links, creating an authentic record while preserving practicality.

[1] Examples are provided by e.g. collateralised debt obligations where a host of assets of different degrees of risk can be aggregated and re-divided into tranches ranging from the secure and expensive to the highly risky and cheap. This recombination, and the ability separately to contract for the underlying debts (through credit default swaps) makes it almost impossible to assess the true value and price of risk or even to track the flow of value through the system.
[2] In other words, the value of an investment to a risk-averse investor does not depend solely on the probability of profit or loss, but on the correlation of these events with profits or losses in his other investments. If the risks of the investment are negatively correlated with other assets, they help to smooth the returns to the portfolio and generate additional benefits for the investor; if they are uncorrelated or positively correlated, they will leave risk the same or even magnify it. This cannot be determined simply from the expected return on the investment. If the ‘portfolio’ is taken to be the whole market, this incremental contribution to performance is the ‘beta’ in the Capital Asset Pricing Model (CAPM).
[3] Salmon, Felix. “The formula that killed Wall Street.” Significance 9, no. 1 (2012): 16-20.
[4] Processing costs halve every 18 months.
[5] Storage costs halve every 12 months.
[6] Bandwidth costs halve every 24 months.
[7] Davidson, Sinclair, Primavera De Filippi, and Jason Potts. “Economics of blockchain.” Available at SSRN 2744751 (2016).
[8] Williamson, Oliver E. “Transaction-cost economics: the governance of contractual relations.” The journal of law & economics 22, no. 2 (1979): 233-261.
[9] Szabo, N. (2005) “Secure Property Titles with Owner Authority” at:
[10] Mainelli, M., and Mike Smith. “Sharing ledgers for sharing economies: an exploration of mutual distributed ledgers (aka blockchain technology).” The Journal of Financial Perspectives 3, no. 3 (2015): 38-69.
EU Projects FutureEnterprise Project

Digital Enterprise #6: A new form of enterprise unfolded – tech and business trends combined

Written for FutureEnterprise collaboratively by NTUA (Iosif Alvertis) and EPFL (Gianluigi Viscusi).
We have discussed already in previous posts how the recognized technological trends are implemented in practice, or how they are about to transform 5 traditional industries in Europe. We have even presented how someone may work to become a new form of enterprise, and we have given a detailed description of the different business components that comprise a digital enterprise (D3.1.2), which with the proper management it may evolve into a new form of enterprise which seeks for new business models.
Thus the main questions, which this article is going to answer, are: How can a new form of enterprise be formed if it is based on the upcoming technological trends? How does everything get together to form a digitalized organization that may move faster from business model to business model?
Future Enterprise
Figure 1 shows a variation of the “cell-form” of a digital enterprise, unfolded to show how different technological and business trends are combined in order to generate the digital enterprise of the future.
Digital Workspace (with light blue color) consists of new concepts and the supporting infrastructures. In more detail:

  • Modern digital workspaces tend to support the co-creation and collaboration between their employees, either in the office or remotely. Every interaction that is made lately in the workspace requires high levels of digital skills, meaning that people who are not familiar or not trained in digital technologies may not be able to adapt in future job placements. Such behaviors will be driven by enterprise gamification systems that will possibly help train and motivate employees. The concept of the future workspace is concluded with the enterprise mobile apps, which may apply both on mobile device but also on wearable devices; with all these applications employees and employers will be able to measure their performance, build better behaviors and interact more easily with their digital environment.
  • Digital infrastructure will support this new status quo and such a new mentality for digital workspaces. Automated operations are going to eliminate human, physical effort on standardized operations (e.g. logistics); enterprise 3D printing will reduce the cost of prototyping and will decrease the costs of on-demand and personalized production; cloud computing and API platforms have already started to reduce the costs of IT and make developing software easier, more scalable and cheaper; machine intelligence will offer most effective algorithms, improve the analysis of data and visual signals, and facilitate decisions; quantum computing will increase cryptography power and will make unsolvable problems easier to calculate and simulate, allowing companies to optimize their operations and decisions; prescriptive analytics will take all this power of algorithms and machine intelligence, and combine them with existing and new types of analytics in order to provide better predictions and estimations on the future, and allow managers to make better decisions based on understable information; extreme big data are already here, and about to change the way we analyze huge, unstructured and real-time data to give meaning on them; NLP and Q&A will reduce the pain of interaction with upcoming technologies, either internally into the workspace or during the interactions with the customers; finally, crowdsourcing will make it easier to collect feedback from external resources, either structured through propriatery applications or unstructured through social media platforms which hold much valuable, but not easily extracted information.

Digital Borders & Digital Environment (with red color) define the endpoints of interaction of a digital enterprise with its external environment. For simplicity, we organize them in input endpoints, output endpoints and the relative connections:

  • Output endpoints have to do with various technology and concepts that increase the speed at which the organization delivers its output, as well as the way they interact with other organizations: web of things allows a digital organization to not only establish programmable connections with devices in their premises, but together with the Blockchain technology allows them to build more trustful connections with their customers; automated delivery will bring physical products more easily to the customers; collaborations and clusters will increase with similar digital enterprises in order to form more flexible and scalable business models, without the need to change the internal operations or change any endpoint (i.e. the other organization is expected to have an interoperability endpoint); and finally, the IPR & licening component will manage not only the intellectual rights of the outcomes, but will also be able to monitor the proper, licensed usage of the services and the products of the organization.
  • Input endpoints include the concepts and technologies that make it easier for an organization to receive physical and digital input (mainly). Thus, modern organizations will mostly require: customization endpoints will allow the organization to better collect the options of their customers, and transform those requirements into actions; social analytics will allow them to understand the social changes, the emerging trends and the power of the social networks on influencing the masses; open data will be a valuable input from publicly available data that describe a broader social and urban life context; authorization & trust will control, calculate and validate who has access, physically and digitally, in specific layers of the organization; cyber, digital risk & governance will predict and simulate possible risks on the environment of the organization, and will allow the management to properly manage the authorization framework; finally, the interoperability endpoint will facilitate the connection with external system and information, as well as validate the status of the internal systems and their compliance with standards and best practices.
  • The connections of digitalized organizations are expected to be easier and more valuable: the intelligent city will allow the organization to use the autonomous transportation infrastructure to move around their physical assets, while the wireless connections will allow easier integration of web of things into the city, and the real-time feedback for the urban context of the organization and its customers; the intelligent factory, an expected digitalized future enterprise, will be easily integrated and will facilite real-time and customized production; the intelligent home will increase the speed at which digital products are delivered, will facilitate their consumption, and will build more trustful business models with the customers, as it will be easier to charge them based on usage, and to lease solutions to them; last but not least, the collaboration and clustering with similar enterprises of the future will allow the construction and the constant evolution of new networks of digital enterprises.

Digital Innovations (with purple color) refer to a playbook that enterprises of the future will be able to use in order to remain competitive and to explore new markets. Provided that those organizations are digitalized, in a matter of worskpace and endpoints, they will be in the position to constantly experiment with their business models. Enterprises of the future will be able to explore new business models by builidng a digital – or a digitally controlled – supply chain, by trying to digitalize their processes, by creating digital marketplaces to sell not only digital products but also services on enhanced offerings (i.e. physical products with services delivered after-sale to create a more powerful user experience and even create new revenues), manage their finance digitally, and at the end experimenting on transforming physicalproducts into digital, virtual experiences.
Digital Strategy (with orange color) cannot be enabled unless a digital organization is present. Referring to this term, we don’t refer to actually a digital asset or technology, but actually on the business and corporate strategy of enterprises of the future which are going to be boosted because of the new technologies; they will be supported by systems which are better connected and more deeply integrated through real-time analysis, while the amount of data will grow and computational power adequate to support most types of analyses. Taking into consideration, as well, the playbook of available innovations, it is a matter of the managers to run simulations, decide, measure and adopt into feedback loops, in order to apply more effective strategies on all the different parts of their business. To a certain extent, some decisions may even be taken automatically, based on the changes that the organization senses in its environment. For example, customer strategy may change if social changes show a change in preferences, or an emerging trend, in order to capture a new segment. Brand management may require launching a new brand, in order to capture the new identified segment without disrupting the old business. Pricing for this segment may become dynamic based on the analytics of sales, change automatically on a bidding marketplace and inform the existing customers that have subscription or per usage plans. New channels may be enabled, to advertise and sale on this new segment, and a new partnership may be needed with a new supplier and a retailer to complete this new business model. Looking for the alternatives, searching for the trust of the organization, suggesting M&As and checking any legal implications may be part of all the future Business Intelligence, IT solutions (which are not there yet).
Digital Leadership (with green color) requires further steps in relation to the digital strategy for its realization. New models will need to support leaders of the future, in order to monitor how differnt parts of the business apply, translate them into behaviors that in time build a culture, and define the critical points where such behaviors break or need to change. Based on them, simulations for changing the organization may be needed. We need to mention that a future enterprise may need to be more agile, change their operations faster in order to enable new business models; such fast changes may require faster hiring, even firing some workforce, or at least the development of more agile and horizontal skills on the employees. Driving people into constant changes may be risky and definitely needs the proper management rules and tools, as well as the change in mindset in order to be effective. We have seen how many big enterprises have collapsed during the digital era because they couldn’t adapt (e.g. Kodak), thus we expect more challenges to emerge in that business area.

EU Projects FutureEnterprise Project

FutureEnterprise Technological Trends: What’s coming for 5 Traditional Industries?

Written for FutureEnterprise.
As mentioned in one of the previous posts, in FutureEnterprise we released a roadmap of the major technological trends that are expected to affect future enterprises, from the perspective of the company.
As depicted in the figure below, the idea is that these trends are orchestrated, together with new business models (i.e. innovations), in order to allow an enterprise create better capacities and build a competitive advantage, even a new business stream in the digital economy.
Although the aforementioned list of technological trends is particularly valuable for all possible stakeholders (e.g. enterprises, researchers, entrepreneurs), it might seem a bit generic for enterprises that conduct their business in specific domains. To address this need, the FutureEnterprise consortium recognized 5 traditional industries (namely: Agriculture and Fishing, Construction, Fashion and Creative Industries, Food and Drink (Beverage) and Tourism) on the basis of their importance to the European economy (according to desk research and literature review), as well as their relevance to the FutureEnterprise concepts.
Such industries were used by FutureEnterprise as example cases in order to select the most relevant trends and provide simple, concrete examples that demonstrate the possible advancements and offerings.
Agriculture and Fishing
The following table presents the most relevant technological trends for the Agriculture and Fishing industry along with short examples.

Trend Example
Internet of Things Sensors deployed in the field/farm exchanging real-time weather data.
Smart Machines/Ubiquitous computing Based on real-time collected and processed weather data, watering mechanisms start operation.
Hybrid/Federated/Mobile Cloud Farmers being able to “manually” start processes from every place.
LTE (Long Term Evolution 4G) Faster uploading of collected sensor data.
Big Data Fast processing of sensor data relevant to the crop’s condition.
Wearable/ultra-portable computing Being able to analyse seawater or crop condition with a smart watch.
APIs/ Web of Things Sensors deployed in the field exchanging real-time weather data.
Smart Dust Small sensors attached to trees in order to wirelessly and remotely monitor the microclimate around them.
Prescriptive Analytics Data insights (e.g. visualisations) relevant to weather conditions, seawater temperature acting as main decision parameters.
Autonomous Vehicles Sprinkler cars, being able to move amongst trees, automatically turning on based on soil humidity levels.
5G Real-time streaming of high-definition video of the crop, in order to identify abnormalities.
Machine Intelligence Smart watering systems providing the necessary amount of water to each plant, based on computer vision and historical plant’s health and growth data
Ambient Intelligence Based on real-time collected and processed weather data, watering mechanisms start operation.
Enterprise Mobility Being able to run/monitor his/her business from a distance and control his farming activities
Drones Spray drones, being able to spray individual trees, automatically activated based on soil humidity levels.

The customised hype curve (similar to Gartner’s hype cycle [1]) for the Agriculture and Fishing industry can be seen in the following figure:
The following table presents the most relevant technological trends for the Construction industry along with short examples.

Trend Example
Enterprise 3D Printing Manufacturers being able to print parts such as screws, insulating materials etc.
Internet of Things Various sensors in the construction venue optimising the process and ensuring security.
Big Data Being able to quickly and effectively process large volumes of data can prove extremely helpful in construction projects that need to take into consideration geological, environmental, weather data etc. (e.g. construction of a sea bridge).
Gamification Allowing potential customers experiment with and provide indirect feedback on new types of products (e.g. smart houses), through a reward mechanism (e.g. free “smart” services for one year).
Crowdsourcing Allowing potential customers provide opinions of relevant innovations (e.g. smart houses).
APIs/ Web of Things Architects design tools disclosing design data via APIs, facilitating remote collaboration with manufacturers’ infrastructures.
Smart Dust Tiny sensors embedded in the house providing data for personalised and proactive house-related services.
Volumetric & Holographic 3D Displays Customers being able to preview their house and ask for specific changes and/or ameliorations.
Prescriptive Analytics Prescriptive analytics can aid enterprises related to construction proactively respond to upcoming trends.
Autonomous Vehicles Autonomous vehicles conveying dangerous materials, protecting humans from such procedures.
Machine Intelligence Intelligent machines recognising flaws in the construction process and automatically correcting them.
Drones Drones could facilitate safe delivery of raw materials in places difficult to reach in the construction venue.

The customised hype curve for the Construction industry can be seen in the following figure:
Fashion and Creative Industries
The following table presents the most relevant technological trends for the Fashion and Creative industries along with short examples.

Trend Example
Enterprise 3D Printing Being able to print a newly designed piece of clothing for testing and showcasing purposes.
Internet of Things Various sensors providing the exact conditions of a workspace, allowing the interior designer make a holistic proposal for optimising working conditions (e.g. lighting, air conditioning etc.) in an office.
Hybrid/Federated/Mobile Cloud Securely storing, sharing and being able to seamlessly access your designs from any device.
LTE (Long Term Evolution 4G) Using high bandwidth to stream creativity content to consumers
Big Data Being able to quickly and effectively process large volumes of data (for example media information) that can reveal future trends and needs of customers.
Wearable/ultra-portable computing Smart clothes that allow to perform specific operations which otherwise require the existence of specific equipment.
Gamification Allowing potential customers experiment with designs and provide feedback, through a reward mechanism (e.g. early access to a new piece of clothing).
Crowdsourcing Allowing potential customers experiment with designs and provide feedback, through a reward mechanism (e.g. early access to a new piece of clothing).
APIs/ Web of Things Linking together media data with services for improved customer experience and allowing the provision of side services.
Responsive and adaptive web design As designers utilize all kind of devices from any place, responsive and adaptive web design heavily applies in this industry.
Quantified Self Measuring everything concerning a person might result to very useful input for specific creative industries (e.g. clothing industries).
Volumetric & Holographic 3D Displays Visually reproducing an object can find a large number of applications in the creation of designs, as they leave the 2D paper and can become truly interactive
Prescriptive Analytics Prescriptive analytics can aid clothes’ designers recognize needs and trends and come up with ideas that will prove successful.
5G High definition content to be reachable by consumers improving their viewing and interactions experience
Enterprise Mobility Advertisers can find benefit in being able to fully perform their activities in any place that might constitute e.g. a customer’s premises or the desirable place for an advertisement.

The customised hype curve for the Fashion and Creative Industries can be seen in the following figure:
Food and Drink (Beverage)
The following table presents the most relevant technological trends for the Food and Drink (Beverage) industries along with short examples.

Trend Example
Internet of Things Various sensors providing insights on the food’s packaging, nutrition value, orientation etc.
Big Data Being able to quickly and effectively process large volumes of data that can reveal future trends and needs of customers.
Wearable/ultra-portable computing Real-time calculation of related values such as calories and/or diabetes level.
Gamification Allowing potential customers experiment with and provide indirect feedback on new types of services (e.g. packaging), through a reward mechanism (e.g. discount coupons).
Crowdsourcing Allowing potential customers provide opinions of relevant innovations (e.g. long-life milk).
Prescriptive Analytics Prescriptive analytics can aid enterprises related to food and drink (beverage) proactively respond to upcoming trends.
Machine Intelligence Automated treatment of sensitive products in order to extend their lifecycle and/or protect their nutrition value.
Enterprise Mobility Mobility in order for departments of food businesses to be as close as possible to the main volume of customers is of the utmost importance.
Drones Drones could facilitate timely and personalised delivery of food, based on customers’ request.1

The customised hype curve for the Food and Drink (Beverage) industry can be seen in the following figure:
The following table presents the most relevant technological trends for the Tourism industry along with short examples.

Trend Example
Internet of Things Various sensors providing insights on the tourists’ habits allow enterprises provide personalised services.
Mobile Money Facilitating tourists’ payments through mobile money.
LTE (Long Term Evolution 4G) Fast networks allowing seamless utilisation of touristic services through mobile devices.
Big Data Being able to quickly and effectively process large volumes of data that can reveal future trends and needs of customers.
Wearable/ultra-portable computing Smart devices offered to tourists serving them with innovative offerings that improve their touristic experience
Gamification Allowing potential customers experiment with new types of touristic services, through a reward mechanism (e.g. free accommodation and/or tickets).
Natural Language Search/ Natural-Language Question Answering Real-time question answering on touristic topics might constitute a service of exceptional value.
Crowdsourcing Allowing potential customers provide feedback, through a reward mechanism (e.g. free trips).
APIs/ Web of Things Multi-channel access to hotel services for improved customer experience and allowing the provision of “linked” side services.
Responsive and adaptive web design Well-designed user-friendly web portals constitute an asset when attracting tourists.
Volumetric & Holographic 3D Displays Visually reproducing an object can find a large number of applications in touristic services.
Prescriptive Analytics Prescriptive analytics can aid tourism-related enterprises proactively respond to upcoming trends.
Autonomous Vehicles Autonomous trips in touristic places can constitute a successful attraction.
Virtual Currency Virtual currencies can facilitate touristic services’ payments.
5G Fast networks allowing seamless utilisation of touristic services through mobile devices.
Enterprise Mobility Being able to constantly relocate your enterprise would be of the utmost value for tourism-related entrepreneurs.

The customised hype curve for the Tourism industry can be seen in the following figure:


EU Projects FutureEnterprise Project

Open platforms and Data Driving Future Enterprise Business

Written for FutureEnterprise by Oscar Lazaro, Innovalia Association.
Much has been written already and will be written about digital transformation of European Industry. Our European industrial fabric is mainly composed by SMEs, so it is of great importance that the digitalization of European industry is SME friendly to be successful. But which are the elements that we need to consider for a successful business transformation and how they relate to each other?
Industrial digitalization is not a mere evolution of current industrial practices. It represents a profound transformation in the tools and processes on top of which enterprises will base and perform business. The issue is no longer “if” European industry (including SMEs) will go through a digital transformation but on the contrary – “when” and “how”. So, the main question for European industry is how to go about this digital transformation and to understand which are the issues and trends that will drive them, so they can be ready and become active in this transformation that will affect their businesses.
Digital transformation is not a simple technology adoption process. On the contrary, digital transformation has profound organisational and behavioral implications on the workforce. It is not just a matter of demographic aging of the European workforce, it is a matter of acceptance of new forms of businesses, roles and responsibilities in workplaces, and innovative uses of smart products and operation of intelligent processes that we will have to embrace.
European industry needs to anticipate such scenarios and procure the right methods, paths and technologies for a digital transformation. It is a full transformation of business that will revolve around new software and system architectures, such as Open Platform FIWARE, IBM Bluemix, German initiative on Industrial Data Spaces, SIEMENS MindSphere or SAP HANA and new platforms yet to emerge that will extend current event-driven and service-oriented architectures towards data centric ones. The emergence of federations of connected data across stakeholders related by a common and agreed digital value network for new business value creation will be the norm and those companies not being able to embrace the transformation will soon be history. Future enterprise success will be strongly linked to their ability to quickly transform innovation at product, process or service level into business profit. It is not about individual business models anymore, business should transcend the individuality and adopt a collective business development through agile cross-domain partnerships.
How European industry can deliver it in a cost effective manner is the challenge we currently face. However, this is no longer an IT buy-sell transactional model. Digital transformation entails a collaborative model where industrial demand and IT offer collaborate through open IT platforms that connect business assets and digital ecosystems to leverage competitive advantages. According to the very recent EC communication of 19th April 2016 by Commissioner Ottinger, digital transformation of European industry will be driven by 4 main streams that will need to be addressed concurrently:

  • Digital Manufacturing Platforms
  • Digital Innovation Hubs
  • Digital Workforce
  • Smart Policies

But how do all these elements relate to each other and how should European industry approach future enterprise environments and transformation?
Digital industrial value chains, the ecosystems for future growth. It is important for industry and SMEs to understand which will be the forces driving such streams and to design strategies that will allow them to evolve and migrate towards new business models. One profound change in the digitalization of our European industry is the fact that European large industry and SMEs should start defining and structuring the future digital value chains. Compared to traditional value chains, digital value chains are far richer and incorporate many different and complementary elements, which make very difficult for single companies to dominate the complete digital value chain. Collaboration will not be optional anymore but a fundamental vector in “business as usual” operations. This makes the role of multi-sided ecosystems a strategic asset in the development of prosperous business environments for growth and employment to flourish. So, the first strategic element for European industry is to understand and clearly delineate the new forms of current and emerging digital value chains and to establish a position of their value proposition in that context.
Open platforms and digital innovation hubs for collaboration and development of competitive advantages. How will European industry be able to “navigate” such digital value chains? It is important to realise that digital transformation will drive business development and business processes towards increasingly hyper-connected solutions at global scale. This implies that industry in general and SMEs in particular, to remain competitive, will not be able to rely only on their own skills and capabilities. Collaboration and interoperability at many dimensions (organizational, business and technical) will need to be realized in a flexible and cost-effective manner. The ability of products and services to “connect” and “enrich” each other will be an inherent part of the digital value networks that will emerge. Closed platforms will not be able to realise the desired market features. So, platforms (be them proprietary or based on open source initiatives) will evolve into open solutions. Hence, the second strategic element for European industry to remain competitive: it will need to define a migration and integration path towards the adoption of open platforms that can be multi-homed across the various digital value chains created in collaboration with customers and providers. The need to jointly and simultaneously nurture both the open platforms and the multi-sided ecosystems is equally important. Open platforms should be connected to strong communities of product and service development to ensure that strong digital value networks are conformed based on the advanced and added value business processes leveraged by the open platforms. Digital transformation implies that IT processes will also evolve from the traditional IT procurement towards stronger partnerships and collaborations, whereby European industry is capable of creating digital value through digital services co-developed with IT companies.
Data driven business operations. However, a key question remains for European industries that is, which type of open platforms should be developed, which type of functionality should they support and which business processes should we develop and operate on top of them? It is now evident that data and services to extract actionable information will drive the future and competitiveness of European industry. Therefore, European industry should master data-driven business operations. This means that European industry should hold a priority to develop the capability to exploit data driven services for the optimization of both internal business operations but maybe more importantly to optimize the type of services that industry could deliver to their customers and “coopetitors” (collaborators and competitors) in a data driven digital value network. The third strategic element for European industry is therefore to design their data-driven strategy based on an evolutionary approach from an initial stage of smart use of data towards the final aim of settling data-driven business and value propositions. The stronger the data-driven digital value chains European companies can build on top of open platforms and digital business ecosystems, the increased growth we should expect. Hence, the stronger and more solid European Industrial Data Space we can collectively construct, the better foundations will be made available for European industry to compete successfully at global scale.
Product-service systems. Products are a driving force of the so called “real economy”. However, it is equally true that business profits are increasingly built on services that revolve or are intimately linked to the physical product. This implies that data-driven digital transformation should be coupled with a clear strategy on a rich and solid product-service system design and operation. The fourth strategic element for European industry is therefore how to transform their current product-centric business strategies towards product-service centric ones, which will deliver additional business value towards industry and customers. The development of product-service systems through data-driven open platforms, ecosystems and digital value chains will imply that cross-sectorial alliances will need to be develop both to smarten the product features but also to secure and process the product and service information while the smart products are “in use”. The design of value propositions based on product-service systems implies higher degree of interoperability between industrial and IoT service platforms that European industry will need to carefully consider.
Human-centred digital transformation. Finally, digital transformation will not occur “disconnected” from the human factor. The operation of systems and services will need to be performed by humans that are an integral part of the digital transformation. Human factors are the fifth strategic element that European industry will need to consider. European industry will need to design and adopt strategies for technology adoption, usability and (up)re- skilling of their workforce. This element is fundamental to the successful deployment and capitalization of the benefits associated to the business and technical dimensions of the digital transformation and should not be underestimated.
European industry is facing interesting times. Important decisions lay ahead in terms of policy decision for a single digital European market and the free flow of data, business strategies for development of added value and innovative product-service system propositions and ICT investments for optimization of business operations. European industry global competitiveness and digital readiness, as well as, the capability to create good quality digital jobs will be very much linked on one hand to our ability to create a digital culture that spans our customers, providers and workforce to operate in this new digital environment. On the other hand, it will depend on being able to jointly develop solid, SME friendly, European open industrial data platforms and digital innovation hubs for data-intensive business operations across flexible digital value chains.

EU Projects FutureEnterprise Project

Digital Enterprise #5: How to become a New Form of Enterprise

Written for FutureEnterprise collaboratively by by NTUA (Iosif Alvertis) and EPFL (Gianluigi Viscusi).
In the related blog post of the “Digital Enterprise” series, the term “new forms of enterprises” has been adopted to reflect the latest evolutionary phase of a Digital Enterprise, and they can be simply viewed as the 2nd generation of digital enterprises. This hypothetical organization has accomplished to render every digital process and infrastructure of the organisation, internal and external, aligned and managed under common strategic, business and operational goals; thus every offering, and its basic operations can be exposed under a common interface (i.e. a digital marketplace) that is deeply integrated into the organisation and provides a strong, common, secure authorization layer, integrated with an intelligent management system for business rules that express the underlying business strategy.

At the end, new forms of enterprises are “Digital Enterprises of the Future, driven by constant business model transformation and innovation, acting as multi-sided platforms built on – as well as emerging from – digital innovations at the global, as well as local level, to produce shared value for their whole ecosystem”

It is more than clear that building or transforming a company into such a new form of enterprise is a constant effort, which may include different, multi-disciplinary aspects. In particular, such an organization should (a) grow its existing business, while it (b) experiments with new business models, it (c) tests new markets and it (d) integrates new technologies into its operations in order to increase the rate of innovation it generates and keep being competitive.
Making the hypothesis that an organization and its environment is static, the Digital Business Innovation framework proposed by FutureEnterprise may be used to digitize all the different operations of it and generate a fully digital enterprise. But based on the given definition, this organization should look for constant transformation, and decide for the next market to move towards. How should practically an organization work on becoming a “New Form of Enterprise”?
Business Model Innovation Transforming Digital Enterprises
In this Section we provide a mapping of a set of BMIs identified in Deliverable D1.2.1 on the value chain primary activities (product and market related activities) and support activities (related to infrastructure, technology, procurement, and human resource management). The mapping shown in Figure 1 has been adapted from Viscusi (2015),  proposing a sequence of adoption of the different business models by a generic enterprise willing to approach digital business innovation. The colour refers to the main design element implied by the considered business model innovation, that are adapted from Amit & Zott (2010) as follows:

  • green for “structure”, which refers to how the activities are linked,
  • blue for “governance”, which refers to who performs the activities, and
  • red for “content”, which refers to what activities have to be performed

Green BMIs are more oriented towards execution, while the red ones focus more on differentiation as competition target. It is worth noting that governance elements (blue BMIs) represent a key element for moving from execution to differentiation or vice versa.

Figure 1: Business Model Innovations Impact on value chain primary and secondary activities

As an example, considering the support activities in Figure 1, the adoption of BMIs such as, e.g., BMI#2 – Physical to Virtual and BMI#17 – Competency Centre, allows an integrate organizational change oriented towards execution of all of the support activities, namely firm infrastructure, human resource management, technology development, and procurement. As to the primary activities, these execution oriented have their complements represented by BMI#7 – Supply Chain Integration (covering logistics and operations), BMI#2 – Physical to Virtual and BMI#3 – Produce on Demand that are also a key basis for further adoption of differentiation oriented BMIs (such as, e.g., multi-sided platforms).
How we can get there?
Our initial analysis regarding the research state of play and market perception for digital enterprises has shown that we are not in the position to have a fully functional ecosystem of digital organizations. Various related articles imply that we are not yet there. In brief, in FutureEnterprise we believe that the digital leaders of the future should adopt the following approaches:

  • The leadership and the organization should develop a culture of experimentation, where new ideas, new approaches and new solutions will be tested, to explore how digital and business model innovations may transform current status quo.
  • The organizations that lead modern innovations look to have more flexible corporate structures, where less hierarchy, more agile processes and bottom-up approaches drive innovations, in operations that may create strategic advantage (e.g. in design and coding, not in assembly lines).
  • The organizations should aim for the technological excellence, by hiring people with proven digital skills and mindset; the competition in such workforce is high, thus motivations, vision and wages need to be formed accordingly. Even high level managers should have good understanding of the digital economy, and should integrate even artificial intelligence (AI) in the management operations.
  • The management team, even the lower levels of hierarchy, should be aware of all the available business model innovations: business, design and technology should be integrated in modern solutions. In that direction, the BMIs as documented and suggested in FutureEnterprise, may become a Handbook for Business Strategists that want to lead the digital era.

Even if an organization has all the assets, in many cases it may be difficult to change its mindset and challenge existing business. In that direction, the management may need to embrace existing frameworks that facilitate corporate changes, like the management of change or the FutureEnterprise DBI framework.
Is it futile to chase the digital enterprise dream?
Many people may consider that becoming digital should not be a self-fulfillment goal, as it drives an organization outside its main goals: creating value and being sustainable. Sure, an organization should test and grow its business model before thinking of scaling and dominating a global market, where being digital makes more sense.
But being digital in advance, or at least working to be digital, may unveil multiple opportunities that the leadership couldn’t even imagine. For example, Amazon invested early on on digital infrastructures, even if it risked its existence by closing continuously negative fiscal years; on the other hand, its investment on scalable server infrastructures allowed them to build a profitable business on Cloud Computing, while its digitally efficient operations allowed them to create another business by leasing external e-shops into their main website, and offering their services to them.
Another point that we want to raise is that being digital is a continuous effort, and not a status; as long as technologies change (all the time) and new digital innovations emerge, a new form of enterprise is “doomed” to work on its transformation into something new, to chase the evolution that will keep it into a strong player. Actually, this is the meaning of doing business, and this may indicate a decrease on the lifecycle of modern business organizations. But at the end, a new form of enterprise is a set of traits, a mindset of competences that continuously works on new, digitally-enabled solutions; thus, it is an instance of a continuous process, not a status.

Screen Shot 2016-05-20 at 3.08.50 PM
Figure 2: Innovation Paths towards new forms of enterprises

This article is part of the blog series named “Digital Enterprise”, including the following articles:

Further readings

  • Viscusi,G.(2015)”Digital business innovation: roadmaps and attitudes from a FutureEnterprise perspective” ,in Génie Logiciel, vol. 115, p. 36-41.
  • Alvertis, I., Kokkinakos, P., Koussouris, S., Lampathaki,  F., Psarras,  J., Viscusi,  G. and Tucci,  C. (2015) “Challenges Laying Ahead for Future Digital Enterprises: A Research Perspective,” in Advanced Information Systems Engineering Workshops SE  – 20, vol. 215, A. Persson and J. Stirna, Eds. Springer International Publishing, 2015, pp. 195–206.
  • Zott, C., & Amit, R. (2010). Business model design: an activity system perspective. Long Range Planning, 43(2-3), 216–226.doi:10.1016/j.lrp.2009.07.004
EU Projects FutureEnterprise Project

Building a successful, European multi-city team. Myth or opportunity?

Written for FutureEnterprise by Maria Logotheti.
When in business school, you have probably learned that face-to-face (F2F) communication is a more effective employee communication channel compared with computer-mediated communication (CMC). Looking at the European startup scene and talking with some of them (including Parquery, Darwin Insurance and Commit Software), a European, multi-city located appears to be a common trait and an enabler spurring further growth. Without the ambition of being an academic qualitative study, this post intends to unveil how this is possible even if the teams do not meet every day.
Pros of a dispersed team:

  • Complementary mentality. Team members coming from different backgrounds have the ability to tackle problems and opportunities from different points of view;
  • Open-mindedness. It is the ecosystem that surrounds us that provides both entrepreneurs as well as their colleagues stimuli and ideas;
  • Proximity to customers. When approaching more than one market, it is valuable to talk and understand customers from different countries, both because of language skills and experience.

How to overcome complexities:

  • Identify a common language everybody speaks seems obvious, but let us repeat it one more time. Whether English or any other, for a team to be successful they all shall master a language;
  • Make use of computer mediated communication is obviously key. It is important, for teleconferences and videoconferences to be successful to follow even with more care the golden rules of organizing meetings. In particular, talking with the startups who have often used a trial and error approach, it is definitely necessary to prepare telcos in advance with an appropriate agenda and material properly circulated. In addition, effectiveness of the moderator, time selection (within Europe rather simple, but when the team enlarges it is also a factor), focus and audio quality also play a key role. It may be old fashion to write minutes, but at least do ensure that one of the participants is in charge of summarizing the key takeaways to be circulated within the hours following the conference call;
  • Organize F2F meetings with frequency as appropriate to stage of development, travel budget and important events such as clients’ meetings, trade fairs, networking events.

Organizing a typical working week:

  • Have a clear identification of the team cumulative goals and allocate them with clear expected outputs;
  • Keep agenda synchronized with the tools that best suit your needs. Here there is no simple answer and you and your team may have to try different tools before selecting the most appropriate tool or often bundle of tools. Indeed a task management platform may be appropriate to visually map all the pending activities and collect information coming from different sources;
  • Assess outcome at the end of the week and define areas needing more focus.

Building a long lasting team:

  • Ownership/Tight-Strategic Partnership. All startups we have talked to either have one of the founders/entrepreneurs in every office on a daily basis or have exclusive partnership agreement with every key part of the team. This appears, particularly in early stage, important to build appropriate enterprise culture and outsourcing proved complicated to manage and control;
  • Teaching/Learning and Cross-fertilization. Without willingness to share and openness to learn, there is no point in working in a team, let alone a dispersed team;
  • Hiring carefully. Hiring is even more complex because, in addition to the technical/soft skills required for the job, it is important that the team is built on reliable, responsible colleagues. A strategy adopted by one of the interviewed companies included screening 150 resumes received, preselection of 15 candidates to attend a 3 months course paid by the enterprise and, after 1 month of internship, selection of the 5 new teammates.

How ecosystems could facilitate the blossoming of dispersed teams

  • Networking opportunities amongst entrepreneurs, featuring participation of those founders that had successfully built an effective dispersed team;
  • Universities and institutions can support the temporary co-location of the entire team to attend workshops, hackathons and the like leveraging on travel budget support and/or existing facilities during time of limited use (i.e. summer);
  • Associations and chambers could support partner identification and selection.

Entrepreneurs of today and tomorrow have the opportunity to gain additional effectiveness provided they are able to leverage on a dispersed, multi-city, European team.

EU Projects FutureEnterprise Project

Innovation in Future Enterprise

Written for FutureEnterprise by David Osimo (Open Evidence)

We are used to consider innovation to be the introduction of a new technology. Across history, when we think of an innovation, the plow, the steam engine, electricity, as well as the internet come to mind.

And in fact, traditionally, ICT innovation in business refers to the adoption of new tools, such as ERP or e-commerce by companies . I’d like to argue that recent technology trends should change our consideration of ICT based innovation in companies.

ICT is no longer simply one of the “cases” of innovation: today, ICT changes the innovative process itself. And it does so because technology today is able to “augment” human capacity for innovation. Through technology, we are able to leverage unused creative resources and develop innovative business models for deploying them.

There are three main trends that underline this new “ICT for innovation” paradigm.

First, the sharing economy can be considered as the ultimate stage of “Web 2.0”, a kind of “Web 2.0 of Things”, built on the notion that users can become providers. It started with the provision of technology: processing power ([email protected]), storage (P2P) and access (WiFi sharing). It then moved to content: audiovisual (YouTube), contacts (LinkedIn), feedback (TripAdvisor). It finally pervaded everything: from rooms (AirBNB) to transport (Uber), from funding (Kickstarter) to consumer goods (Wallapop). Innovation lies in the exploitation of network economies even in very traditional sectors, and transform them in services that “get better the more people use them”.

The second important trend is big data. Big data is not just a way to uncover spending patterns of consumers: it can help uncovering unexpected correlation and predict future events. It can help identifying problems and opportunities before they become apparent to all. Companies using big data are more productive and more likely to launch new products and services. Today, there are dedicated platforms such as Kaggle that allow companies to organise competitions for data analysis to identify algorithms that can predict, for instance, hotel bookings.

Last but not least, new, flatter forms organisation built around the social web helps uncover microexpertise necessary for problem solving through open innovation. Being able to reach out to the communities of experts is already a fundamental factor of competitiveness for companies. Online platforms such as Innocentive help identifying the right experts in the open community that can help solving wicked problems.

These three trends are positively interrelated and self reinforcing. Large companies are trying to leverage them to reinvent themselves and self-disrupt by incubating startups and launching intrapreneurship initiatives. ICT can help leverage unused resources (sharing economy), collective intelligence (open innovation), and new competitive factors (big data).

In conclusion, what matters today is the capacity to design these new innovation processes; the skills to implement platforms and services where innovation takes place; and finally the capacity to assess and evaluate the return on investment of these processes to ensure continuous learning and continuously re-design and improve.

EU Projects FutureEnterprise Project

Business Model Innovation – Moving from Value Proposition to Value Extraction

Written for FutureEnterprise by Gigi Wang, Board Member & Chair Emeritus, MIT/Stanford Venture Lab. 

The first step in building a successful start-up is developing the Value Proposition or creating a product or service that provides significant value and benefits to a target customer in addressing the need that they have.  In order to build a successful business, the next step is to develop an approach for Value Extraction or making money, reducing costs and creating a profitable business.

When I was working on my MBA degree in the UC Berkeley Haas School of Business evening program, I used to take very neat and detailed notes in each class (good Asian student background).  Since my fellow students often missed class because of work obligations, I would make copies of my notes and share it with the absent ones with no thought of getting payment.  Years later, when I was listening to the COO of Webvan (well-funded Internet start-up that launched in late 1990’s), he talked about how he always had the entrepreneur spirit, and how he sold copies of his class notes while he was getting his MBA at UCLA.  Why didn’t I think of that when I was sharing my notes?  Because I was too focused on the Value Proposition, and didn’t think of Value Extraction.

One important factor in figuring the business model is identifying WHO THE CUSTOMER IS.  Customers can play different roles, they key ones being the USER, the BUYER, and the PARTNER.  Take for instance, home consumption beer in the United States.  The primary user is male, while the primary buyer is female (usually wife or girlfriend), and the partner is the retail outlet.  If any of these customers are not engaged in the business strategy, then beer sales don’t take place, and no revenue.  So it’s critical to understand who all the different customers are in your business, and to develop a strategy and tactics to provide value to each of the different customers.  So the beer producer’s advertising campaigns have to reach both the men and the women, and they also have to have a strategy to engage retail outlets to carry their product.

In developing a business model, the key equation to build upon is PROFITS = REVENUES – COSTS.  Anything that increases revenues, or decreases costs, thereby increasing the profits will improve the business model.  Creative new ways to increase revenues or decrease costs results in a more innovative business models.  Over time, new technologies and process emerge, enabling the emergence of new business models.  In the 1990’s, the Internet took hold of the world, and spawned new Internet-based businesses like Amazon, eBay, and more.  In the 2000’s, wireless devices became mainstream and mobile apps and content businesses like app-stores such as iTunes and Spotify emerged and thrived, while in the 2010’s, smart phones with even more capabilities like location based services resulted in companies like UBER and restaurant reservation apps.  Often, these new companies thrived because of their innovative business models versus because of innovative new technologies.  UBER leveraged existing mobile device trends and existing location based technologies to build a business which created new revenue streams for car owners with excess capacity and time and UBER getting a cut of that business.  Their business model was the innovation in utilizing excess capacity to generate revenues, not their technology.

With the rise of Internet enabled devices in the areas of consumer, enterprise, and industrial, a lot of data is being collected which can be analyzed and used to predict trends and outcomes or to run processes.  This has given rise to Data Monetization as a popular business model.  Google keeps offering free services, but is it really free?  In exchange for the free services, Google is collecting consumer behavior data from all of us users and monetizing by selling targeted advertising to companies trying to reach us.  Another historical example of creative business model innovation is how grocery stores initially installed bar code scanners as a way to manage inventory and bar code scanners resulted in being a cost center to the business.  Then the grocery stores figured out that the in addition to collecting data on inventory levels, they were collecting valuable data on consumer buying trends.  So the grocery stores packaged the data collected on buying trends and sold it to the consumer goods companies.  Amazing instance of transforming the bar code scanner from a cost center into a revenue center.

One of my favorite examples of an innovative business model transformation is the gaming broadcast service Twitch.  It spun out of, a “free” streaming video service struggling to survive because it hadn’t come up with a profitable business model.  One of’s executives then developed a concept to utilize’s streaming video technology for a service for gamers to go online to video broadcast their game-play where other gamers could login to watch them play.  Top gamers on Twitch easily have up to 10,000 viewers watching them play which provided a captive audience for targeted advertising.  Revenues skyrocketed and Twitch was acquired by Amazon in 2014 for close to $1 billion.  Such an amazing example of transforming an unprofitable business to a highly profitable one by innovating the business model and how to generate revenues.

EU Projects FutureEnterprise Project

An Ideological-Technological Exploration of Blockchain

Written for FutureEnterprise by David L. Shrier, Managing Director, MIT Connection Science (

In this Year of Blockchain, we see the technology attracting nearly 10% of fintech venture funding (fintech itself approaching $19 billion this year).  The bitcoin blockchain is only one flavor of a proliferation of coins (by one count over 700), and “colored coins” are only one flavor of blockchain.  It’s helpful to have a reliable taxonomy when seeking to classify these distributed cryptographic ledgers.  In this post, we will explore a new model for thinking about blockchain variations.

Most blockchain taxonomies focus on the functional architecture (Is it permissioned or permissionless?  Is it public or private?).  We are not going to dwell on these models here, and direct readers to the division proposed by ArthurB – although it has been pointed out that his statement “Applications which do not attempt to evade oppressive governments have little or no reasons to use decentralized systems” isn’t precisely true.  There are numerous examples of a need for trust technologies when absolute trust in a third party is absent, having nothing to do with governments – eBay selling is the most trivial example, but equities security trading would be another.

Instead, in our view, understanding implementation of blockchain requires understanding implementers, users, and their respective objectives.  This context-based analysis of blockchain provides a novel lens on selecting a platform and allocating resources to it.  Broadly speaking, when we incorporate ideology into the technological analysis, we see three categories:

  • Libertarians: A substantial number of bitcoiners believe that government has no role in regulating society, and bitcoin usage is an expression of political belief.  AML/KYC is anathema to their belief systems.  This isn’t to say that all bitcoin users and companies feel this way – to the contrary, a large number of bitcoin companies employ or developed policies based on the Windhover Principles that MIT helped shepherd.  Rather, a vocal segment of bitcoin miners and developers assert a proprietary ownership of the technology, and vigorously reject anything that compromises their idealized view of how it should be used.  To quote a recent post on Reddit: “if you aren’t working to make Bitcoin better (read: more private, more fungible, more scalable) than you should keep your dirty, groveling sycophant paws off of it.”[i]  It’s a vigorously-expressed point of view but one shared by a number of users who engage each other regularly in self-reinforcement.
  • Technocrats: A broad middle of technocrats don’t automatically assume either government regulation or total freedom from regulation, but rather see blockchain as a flexible technology without ideology.  Ethereum would fall clearly into this category.  A host of “smart contract” and other applications are being built on top of the Ethereum platform, which has a substantially shallower learning curve than the notoriously complex bitcoin blockchain.
  • Rules Followers: The industry-led consortia such as R3 and Hyperledger accept, a priori, that regulation applies to blockchain (for example with respect to AML/KYC as it applies to currency and other financial-related matters).  While perhaps not as passionate in espousing their views as the Libertarians, these Rules Followers are making an ideological choice embedded into the fabric of their chosen technology platform.  (Corda doesn’t technically use “blocks” but we are describing all distributed ledger technologies as blockchain for convenience).

Longer-term use of blockchain at scale will likely come from one of the latter two categories.  At same time, the passion that the libertarians feel has caused them to think “outside the box” and question assumptions, resulting in a new way of transacting that is transparent, open and decentralized.  In fact, blockchain as such would not exist with those passionate libertarians driving its creation and adoption.

Given the attitudes of some of the Libertarians, how can the creative energy of the innovators behind the bitcoin blockchain be accessed to support a broader technology revolution?

For additional insights on the blockchain impact on future markets, you may view my presentation in the FutureEnterprise webinar.

More on the blockchain revolution is also covered in the following white paper series:

  • Blockchain & Financial Services: 5th Horizon of Networked Innovation: May 3
  • Blockchain & Transactions, Markets & Marketplaces: May 10
  • Blockchain & Infrastructure (Identity, Data Security): May 17
  • Blockchain & Policy (with U.S. Treasury Office of Financial Research): May 24

Email [email protected] for a copy.

[i] /u/throw_awa5 posted 27 April 2016 accessed 30 April 2016.

EU Projects FutureEnterprise Project

Collaborative Ecosystems – You are not alone

Written for FutureEnterprise by Stuart McRae (IBM).
It is one of the ironies of the age of digital business that the transformation it enables is more about interpersonal relationships than technology.
From the earliest days of disruptive businesses enabled by the Internet (with Amazon, and the way it used reviews) the social aspect of engaging customers with new services has been at the forefront – spreading their popularity, educating the market, providing insights and driving customer loyalty.
Social interaction soon became the core to review sites like TripAdvisor, crowdfunding platforms like Unbound, messaging services like Snapchat, and the new generation of businesses whose online presence is delivered only through social media sites. The watchword of the digital age has become “engagement“. Engaging prospects, engaging customers, engaging partners, engaging employees, engaging citizens – the Internet has become a platform for conversations.
This isn’t just about what we used to call “Web 2.0” and the way it enables generated content and social networking. The magic happened when that was combined with Smartphones, Cloud Computing, Big Data and Analytics, to create more effective ways to communicate and collaborate: a new way to work. The Internet of Things and Cognitive Computing will continue to build on this, creating even more transformational possibilities through new forms of engagement.
Which is all having a profound impact on business models and how organisations work. The impacts are clear everywhere, but the opportunities are greatest in the entrepreneurial sector. Traditional businesses find it hard to change and their legacy often stops them from taking advantage of new possibilities. A new business doesn’t have that problem.
But as the sudden blossoming of these new capabilities shows, timing is everything and nowhere is that more true than for the entrepreneurial start-up trying to get established. Align the potential of emerging technologies, an evolving business environment, appropriate changes in regulation and the right mood in the market, and the world can shift dramatically. Get the timing wrong, and all that is left is the fight without the success – plus, hopefully, valuable lessons that should encourage a true entrepreneur to try again until they get both the timing and strategy right.
Entrepreneurship is about both ideas and execution. Having an idea isn’t the same as innovation, which is a collaborative process that takes a spark and turns it into a fire by bringing together expertise and action. Good execution uses the skills of the experts not just to implement an idea, but create a business around it.
Incubators have become a proven way of bringing the necessary ingredients together, adding mentoring, resources and a supportive community to help turn ideas into businesses. Whether these are geographic (one study found 40 in London alone) or distributed (like the New Way To StartUp competition), a host of new businesses are getting started because people are being brought together to support and help one another.
However, in the digital age, if there is no incubator available locally, you can build your own. If your enthusiasm is visible, your vision is clear and your approach is open, you can engage with the expertise, mentoring and resources you need to create your own support system. Don’t stop at crowdfunding finance, but crowd-source the advice, mentoring and skills you need as well. All you need is an aptitude for and focus on networking (and few business leaders succeed without that). There are lots of people who will make connections for you, even if they can’t help themselves. After all, this is the sharing economy.
There are positives and negatives to building your own ecosystem: whist it might not be as easy as slotting into an existing, defined structure, or as motivating as having like minded people around you every day, creating a personalised ecosystem that is independent of location can bring in contacts that would not otherwise be available and create a support community around you that can help to differentiate you in the market. But don’t forget, your ecosystem is made up of relationships. Online social media is a great way to find people, coordinate activities and keep in touch, but face to face meetings build trust and better provide emotional support. Whether it is grabbing a coffee or getting your network together at a relevant event, meeting people is just as important in business as it ever was.
Conferences and seminars are happening all the time – but try to find the ones that aren’t just about sitting through PowerPoint presentations but offer workshops and unconference sessions that focus on opportunities to debate – and, of course, include lots of time for networking, enabling you to expand your ecosystem.
Or you can simply organise your own meet-up for your ecosystem (there are online services for that, too) – perhaps in the corner of a friendly coffee shop, tearoom or pub. Use your network to invite other start-up businesses – who knows the ways it might turn out that they can help you, or you can help them.
Being in a start-up is very different today to how it was when I was doing it 35 years ago. But the most transformational thing about being an entrepreneur in the digital age you no longer need to do it alone: you can build your own ecosystem. Just as you no longer need to build infrastructure but can source everything (from IT platforms to HR, programming to collaboration, a web site to marketing services) as services from the Cloud, learn how to use social media and social networking tools to create, nurture, grow and manage your own ecosystem.