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|title=Future Enterprise, a Roadmap for the Sensing Enterprise
|pdfUrl=https://ceur-ws.org/Vol-1414/paper9.pdf
|volume=Vol-1414
|dblpUrl=https://dblp.org/rec/conf/ifip5-8/LampathakiAKKPV15
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==Future Enterprise, a Roadmap for the Sensing Enterprise==
https://ceur-ws.org/Vol-1414/paper9.pdf
FutureEnterprise, A Roadmap for Sensing Enterprise
Fenareti Lampathaki Iosif Alvertis Sotiris Koussouris
National Technical University of National Technical University of National Technical University of
Athens, Heroon Polytechniou 9, Athens, Heroon Polytechniou 9, Athens, Heroon Polytechniou 9,
15780 Zografou, Greece 15780 Zografou, Greece 15780 Zografou, Greece
flamp@epu.ntua.gr alvertisjo@epu.ntua.gr pkokkinakos@epu.ntua.gr
Panagiotis Kokkinakos John Psarras Gianluigi Viscusi
National Technical University of National Technical University of Ecole Polytechnique Fédérale de
Athens, Heroon Polytechniou 9, Athens, Heroon Polytechniou 9, Lausanne -College of Management
15780 Zografou, Greece 15780 Zografou, Greece of Technology, EPFL-CDM –
skous@epu.ntua.gr john@epu.ntua.gr ODY 1 16 (Odyssea) Station 5 CH-
1015 Lausanne, Switzerland
gianluigi.viscusi@epfl.ch
Christopher Tucci
Ecole Polytechnique Fédérale de
Lausanne -College of Management
of Technology, EPFL-CDM –
ODY 1 16 (Odyssea) Station 5 CH-
1015 Lausanne, Switzerland
christopher.tucci@epfl.ch
Abstract
The circumstances for shifting to new kinds of economies and to new
ways of doing business are compelling, with the concept of the sharing
and circular economies opening up novel ways to reconcile the quest for
growth and business value with the environmental prudence perspective:
“doing more with less”. The evolution of Sensing Enterprises is
expected to capture new business value across supply chains and drive
digital business innovation to undiscovered pathways in product design,
development of product-to-service approaches, customer engagement
and internal structure and performance. In this paper, a glimpse of the
business models innovations that are relevant for Sensing Enterprises is
provided, leading to the elaboration of the research challenges to
accelerate new forms of enterprises, mainly along the following
dimensions: (a) Collaborative, Real-time, Proactive Business Analytics-
as-a-Service, and (b) Innovative, Web-based Business Models for New
Kinds of Economies.
1. Introduction
Currently the Internet is influenced by multiple forces whose actual impact in everyday business has not been yet
Copyright © 2015 by the paper’s authors. Copying permitted only for private and academic purposes.
In: M. Zelm (eds.): Proceedings of the 6th Workshop on Enterprise Interoperability, Nîmes, France, 27-05-2015, published at http://ceur-ws.org
apprehended. In this constantly changing and challenging environment, successful companies of the future will be
characterized by open and blurry boundaries and will compete by outreaching to harness external knowledge,
resources and capabilities, and becoming hubs for innovation and magnets for uniquely qualified minds (Tapscott &
Williams, 2014). Stimulating break-through innovation for added value products and services is in fact well
acknowledged at policy level and embedded in the mind-sets of leading enterprises, successful entrepreneurs, and
forward-looking researchers, yet recognized philosophies of doing business 'better' are still not integrated in the
strategies and approaches of many companies, especially in Europe which has traditionally struggled to convert its
scientific excellence into successful market products (EC, 2012). As a consequence, the European industry, in
general, lags behind its global rivals with respect to digital business innovation, factors that will become more and
more crucial as the global economy recovers.
To fully exploit the potentiality inherent to the future IoT (Internet of Things) and smart objects, there is a need to
decentralise intelligence, moving to a scenario where the enterprise is seen as a smart complex entity capable of
sensing and reacting to (business) stimuli (EC, 2013). The 'Sensing Enterprise' is characterized as an enterprise
making use of the sensing possibilities provided by interconnected 'environments', anticipating future decisions by
using multi-dimensional information captured through physical and virtual objects, and providing added value
information to enhance its global context awareness (Santucci et al, 2013). Among the implications of the Sensing
Enterprise are (EC, 2013): context awareness, dynamic configurability, information requirement and processing,
multi-identity enterprises and enterprise entities, and relationships between humans and objects.
In the context of our work in the EC-funded FutureEnterprise project, the term “new forms of enterprises” has
been adopted to reflect the next evolutionary step of a Digital / Sensing Enterprise, along the following definition:
New forms of enterprises are “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 including that beyond monetisation”.
Along these lines, the present paper aims at discussing a number of instrumental research challenges that need to
be tackled by researchers and practitioners in order for new forms of enterprises to evolve and flourish. In section 2,
the methodological approach is presented, leading to sections 3 and 4 that summarize the business models
innovations and the identified research challenges related to the sensing enterprise. Section 5 concludes this work and
presents next steps along this approach.
2. Methodology
In order to pave the research path towards future developments that accelerate new forms of enterprises, a
brainstorming methodology featuring 5 steps was followed:
1. Multiple sustainable business model innovations, based on bibliography (Amit & Zott, 2012), (Keeley et al, 2013),
(Model Behavior, 2014), (Osterwalder & Pigneur, 2010) and experts input, were collected.
2. Common or directly related business model innovations were circulated internally, discussed and merged. In total
30 business-model-innovations were identified and reported, but upon merging, 21 business-model-innovations
remained.
3. Various business models were studied in detail to enable brainstorming under different perspectives about what
research directions should be put forward. In detail, the analysis of the business model innovation was done for the
following aspects:
- Existing technologies that enable specific business model innovations nowadays.
- Dependency with innovation diffusion (Rogers, 2003) / acceptance factors (Chesbrough, 2010), analysed under both
the current situation in Europe and the future desirable scenario: Possible changes in the way business is done, as
described in Porter’s Value Chain; Ethical issued that may arise; Technological obstacles or difficulties; Societal
characteristics that might favour or prevent the adoption; Political situations that might arise; Industry opportunities
and threats (i.e. as identified in Porter’s five forces); Economic issues that might affect a business model innovation.
- Changes in existing business models that such business innovations could bring, accordingly to the business model
canvas elements (Osterwalder & Pigneur, 2010), i.e. value proposition, channels, customer relationships, customer
segments, key resources, key activities, partnerships, cost structure and revenue structure.
- Key research directions needed to enable or boost every business model innovation as described, characterised with
the expected impact on enterprises, SMEs and startups (i.e. web entrepreneurs).
4. The results were iteratively circulated to a number of experts to validate, refine and update the analysis.
5. The key research directions from various business model innovations, were classified under four (4) Grand
Challenges that provide the necessary focus for research activities for the upcoming years in order to come as close as
possible to a Desirable Scenario of the future that promotes prosperity, social caring and equal opportunities.
Figure 1: Roadmapping Methodology
It needs to be noted that in the following sections, the parts of our work that are relevant for Sensing Enterprises
will be presented.
3. Business Models Innovations related to the Sensing Enterprise
According to Chesbrough (2010), while companies may have extensive investments and processes for exploring new
ideas and technologies, they often have little if any ability to innovate the business models through which these inputs
will pass. This matters - the same idea or technology taken to market through two different business models will yield
two different economic outcomes.
In our work, a number of business models innovations along their research directions have been identified for
sensing enterprises that want develop the capability to innovate their business models.
Table 1: List of BMIs and Research Directions
ID Research Direction Title
BMI#1 - Closed-Loop Production
CLP.01 Real-time, big data analytics in sensing enterprises
CLP.02 Social, behavioural changing platforms
BMI#2 - Physical to Virtual
PtV.01 Mobile enabled shopping
PtV.02 Digital Ecosystems of Virtual Products
BMI#3 - Produce on Demand
PoD.01 Interactive, Personalised and Responsive Marketplace platforms
PoD.02 Demand driven production through Gamification Systems
PoD.03 Interoperable and collaborative enterprise-wide platforms
BMI5 - Sell One, Give One
S1G1.01 Smart Prescriptive Business Analytics
S1G1.02 Configurable Products through 3D printing systems
S1G1.03 Crowdsourcing platforms for service/product creation and access
BMI#7 - Supply Chain Integration
SCI.01 Supply Chain Business Intelligence
SCI.02 Sensor-based, open, supply chain environments
SCI.03 Workforce support and safety through ICTs
SCI.04 Knowledge based platforms
SCI.05 Smart Supply Chain Support Agents
BMI#12 - Bait & Hook (Subscription model)
BaH.01 Flexible IPR management platforms
BaH.02 Crowd-sensing and smart feedback ICT infrastructures
BaH.03 Real-Time Prescriptive and Predictive Market Analytics:
BMI#13 - Differential Pricing & Customisation
DIP.01 Market Insights and Business Analytics through Big Data powered
Social Platforms
DIP.02 Smart, Differential Charging Platforms
BMI#15 - Micro-Franchise
MFR.01 Big Data for Micro Franchising
MFR.02 Compact business-intelligence solutions
BMI#16 - Behaviour Change
BHC.01 Game-based Customer and Employee Behavioural Change Systems
BHC.02 Open-standard, social-impact measuring platforms
BMI#19 - Transparency
TRA.01 Open Enterprise-wide APIs
TRA.02 Intuitive and Responsive Visual Analytics
BMI#20 - Unbundling
UBL.01 Collaborative, lean-startup oriented project management platforms
UBL.02 Real-time, prescriptive analytics platforms for shop floor processes
BMI#21 - Multisided platform
MSP.01 Product and Service Coupling Collaborative Hub platforms
MSP.02 Big Data Analytics for Multisided Marketplaces
MSP.03 Decentralised community platforms
MSP.04 Virtual Currency Enablers
4. Research Challenges for the Sensing Enterprise
With a perspective towards 2030, a radically different context for business analytics and their provision of them to
enterprise personnel, whether these are highlevel executives or shop floor workers, is anticipated. Thanks to smart
devices, and to the unparalleled deployment of sensor grids and the progress in IoT technology, enterprises will be in
a position to collect enormous amounts of data, exceeding the current classification of Big Data and will possess raw
business knowledge that could be turned into intelligence. Enterprise data will be delivered in real-time and in huge
amounts, and new novel approaches for extracting the meaningful part of it would be necessary, while also
transportation of this data would require next generation network infrastructures.
Radically different business realities in which prosperity and wellbeing of humans prevail against the backdrop of
pure shareholder’s value at any cost will also emerge. Disruptive and creative technologies, like the Internet of
Things, Big Data, Social Media, Mobile and Cloud Computing, have been put in place to be used as a means to an
end: how to generate value from more efficient resource use and conduct business in a sustainable manner that
benefits all stakeholders and the overall society. The design of products and services, as well as the overall business
operation, shall abide by the principles of flexibility, durability, restoration and prosumption.
In total, the draft release of the roadmap includes four (4) Grand Challenges that collectively contain 25 research
challenges:
- Grand Challenge 1: Collaborative, Real-time, Proactive Business Analytics-as-a-Service, dealing with a radically
different context for business analytics for the enterprise personnel, either high-level executives or shop floor
workers.
- Grand Challenge 2: Innovative, web-based business models for new kinds of economies, exploring the definition,
experimentation and constant evolution of novel business models that challenge traditional operating models, follow
the paradigms of the Sharing Economy and the Circular Economy, and capitalize on novel technologies and Future
Internet assets in business environments in order to introduce unique innovation propositions at multiple levels,
ranging from the innermost configuration and the core offerings of an enterprise, to the customer-facing, networking
elements of its business system (user experience).
- Grand Challenge 3: Distributed, Innovation-driven Enterprise Platforms, embodying a radically different context for
business innovation and collaboration among organisations, where platforms promote collaboration among
enterprises and web entrepreneurs, boost productivity and enable business innovation in consistent lifecycles; from
invention to production, from supply chain management to ERP systems, and from customers’ adoption to
collaboration with internal business functions or external partners.
- Grand Challenge 4: Dynamic discovery and negotiation of the intellectual property rights’ flow, addressing effective
management, monitoring, identification and creation of IPRs and knowledge generation and handling, through the use
of innovative ICT tools and platforms that will exploit the collaborative features of existing platforms and the power
of analytics. As depicted in Figure 2, the proposed Grand Challenges follow the logical pattern in value creation,
where one starts with creating or maximising its current intelligence operations and then, based on the material
collected, he starts experimenting and simulating different alternatives, until he decides to implement a chosen
pathway to innovation. In accordance, GC#1 aims to tackle research issues that will maximise the efficiency and the
effectiveness of enterprises based on assets they currently possess, or that they can easily generate as they already
possess the raw material (e.g. data, processes and people), while GC#2 works on the intelligence generated from the
GC#1 outcomes to experiment and simulate alternative business models which can be used to drive the enterprise and
an entrepreneur forward, allowing its transformation to a more sustainable, collaborative and value generating entity.
GC#3 and GC#4 pick-up from that exact point, as they are formulated around research questions that will help an
enterprise deploy the desirable business model innovations, offering the baseline tools and platforms for the actual
establishment and management of collaborations, the introduction of new ways of working and the definition of rules
for securing and managing each party’s work, such as the intellectual properties to be created (or to be used).
Figure 2: Interrelation of Grand Challenges and the flow of Business Model Transformation
In the case of Sensing Enterprises, GC#1 and GC#2 are more relevant. In particular, the following challenges need
to be met in the next 3-5 years
- RC1.1: Multi-source Data Analytics Services for Real-Time Business Critical Decisions
- RC1.2: Predictive and Prescriptive Crowd-based Analytics powering Business Innovations
- RC1.5: Generation and Exposure of SMEs Analytics over federated cloud-based platforms
- RC2.4: Instant, crowd market validation of Business Innovations
- RC2.6: Innovation Diffusion & Adaptation Patterns and Techniques
In the next 5-10 Years:
- RC1.4: Enterprise-wide smart, personalised intelligence and delivery systems
- RC1.8: Proactive safety and security safeguarding recommendation and notification systems using real-time data
analysis
- RC1.6: Smart and Collaborative APIs for cognisant business processes
- RC1.7: Responsive and Dynamic Visualisation and Augmented Reality Services for Business Functions
- RC2.1: Circular Supply Chain Management
- RC2.3: Collective Ideas Flow on ever-evolving and interactive Business Plan Lifecycles
In the next 10-15 years:
RC1.3: Business Transformation Platforms combining Human Knowledge with Information Flows
5. Conclusions
In the aftermath of the recent financial crisis and in light of the emergence of disruptive technological paradigms,
how to conduct business in an ever-changing environment appears more challenging than ever. The surging app
economy, manifested within a platform-oriented, mobile-driven and collaboration-rooted era, has already paved new
paths for digital business innovation.
In the present paper, a number of research challenges to be tackled in the years to come in order for enterprises to
evolve towards new forms of enterprises have been elaborated. Next, iterative steps along our approach include: (a)
further elaboration of the research challenges based on case studies along the Digital Business Innovation aspects and
(b) recommendations on how to maintain a “live” roadmap, with contributions by any interested stakeholder.
Acknowledgements
This work has been partly funded by the European Commission through the Project Future Enterprise: Road
mapping, Research Coordination and Policy activities sup-porting Future Internet-based Enterprise Innovation (Grant
Agreement No. 611948).
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