=Paper=
{{Paper
|id=None
|storemode=property
|title=Monitoring Innovation in Virtual Enterprises: an Agile Semantic Approach
|pdfUrl=https://ceur-ws.org/Vol-915/paper_6.pdf
|volume=Vol-915
|dblpUrl=https://dblp.org/rec/conf/invit/DiamantiniKM12
}}
==Monitoring Innovation in Virtual Enterprises: an Agile Semantic Approach==
https://ceur-ws.org/Vol-915/paper_6.pdf
Monitoring Innovation in Virtual Enterprises:
an Agile Semantic Approach*
Claudia Diamantini1, Benjamin Knoke2 and Michele Missikoff1
1
Dipartimento di Ingegneria dell’Informazione,
Università Politecnica delle Marche - via Brecce Bianche, 60131 Ancona, Italy
{diamantini,missikoff}@dii.univpm.it
2
BIBA – Bremer Institut für Produktion und Logistik GmbH
Hochschulring 20 · D-28359 Bremen / Germany
kno@biba.uni-bremen.de
Abstract. In this paper, the key ideas adopted in the BIVEE project to monitor
and support an innovation venture are illustrated, and developed in the context
of a virtual enterprise (VE). The proposed approach is based on two pillars: a
novel framework, further split into three parts, and the support of a semantic
platform. In particular, the novel framework is split into the Virtual Enterprise
Modelling Framework (VEMF), the Business Innovation Reference Framework
(BIRF) and the Innovation Monitoring Framework (IMF). VEMF is aimed at
providing a unique approach to the modelling of a VE, overcoming the
divergences that the different real enterprises forming the VE may exhibit. The
BIRF is aimed at providing guidelines for carrying out effective innovations in
a VE. Finally, the IMF provides a set of methods, including Key Performance
Indicators (KPIs), to monitor performances of activities and the achievement of
planned goals. The second pillar is represented by a semantic platform relying
on a federation of ontologies that allow the business context to be semantically
enriched in a formal way.
1 Introduction
This paper addresses the problem of monitoring innovation in the context of a virtual
enterprise (VE). A VE is essentially a network of cooperating enterprises getting
together to achieve a production (of goods and/or services) that could not be achieved
if separated [1, 7]. Today, an enterprise is required, in parallel to the value production,
to be able to constantly innovate. While the structure and organization of a VE is
(supposedly) conceived to be optimal for the value production activities, innovation
projects are difficult to manage in a distributed, loosely coordinated (beyond
production) context. For this reason, the idea is introduced that in parallel to a value
production organization there should be an innovation oriented organization that is
referred to as Virtual Innovation Factory (VIF). A VIF is a production factory aimed
at manufacturing an immaterial good: innovation, where its nature is essentially
*
This
work
has
been
partially
funded
by
the
European
Commission
through
the
Project
BIVEE:
Business
Innovation
and
Virtual
Enterprise
Environment
,
Grant
No.
285746
knowledge. Therefore, a VIF is conceived to take pre-existing ‘raw knowledge’,
manipulate and enrich it to achieve the sought innovation, seen as a complex body of
knowledge (in case, partially materialised in the form of running prototypes). This
paper describes the key ideas behind the organization and operations of a VIF, with a
focus on the monitoring of the innovation activities.
Innovation is about change. However, when starting an innovation venture a fuzzy,
intuitive, rather incomplete idea is the start of the undertaking. Therefore, the
innovation venture is mainly about a progressive collection and organization of
knowledge to refine the initial idea (innovation objective) and to identify the
transformations that are needed for the enterprise to achieve at best the innovation
objective. The enterprise is a complex world and in principle innovation can focus on
any single aspect of it. However, in accordance with a number of studies [8] it is
intended to carry out a focused study, with four innovation targets. The first two
concern product innovation, i.e., goods and services offered to customers. Then the
focus is on production processes, where innovation can bring important advantages to
the enterprise and, as effect, to price and quality for the customers. Finally,
technology is considered as one of the major enabler used both in the production
processes and in the final products. Despite a clear focus of intention, an enterprise
has to be considered a complex organism where all its parts are connected and
interdependent. Therefore, even in case of a focused innovation project, addressing
one specific innovation target, all the rest of the enterprise will be impacted.
Figure 1 - An overview of the VIF approach
The proposal is based on two key pillars: a novel framework and the support of a
semantic platform. The framework is further split into three parts: the Virtual
Enterprise Modelling Framework (VEMF), the Business Innovation Reference
Framework (BIRF) and the Innovation Monitoring Framework (IMF). The VEMF
allows for a unified approach in modelling the different enterprises forming the VE,
the BIRF provides a coherent strategy for achieving the innovation objective in the
context of a VE, IMF provides the methods and metrics for the measurement of the
performances of activities and the achievement of planned goals. The second pillar,
the Semantic Base (based on a federation of ontologies) guarantees a precise,
rigorous, unambiguous approach to the three above frameworks. It is also the base of
the semantic platform aimed at providing a number of semantic services.
In the next sections the methodological pillars of the BIVEE approach are illustrated.
Because of the lack of space, the focus of the discussion will be on innovation in the
perspective of innovation monitoring. Hence, the BIRF and IMF parts of the
framework will be detailed, together with the Semantic Base.
2 BIRF: Business Innovation Reference Framework
As anticipated, it is intended to address Innovation with an industrial approach, seeing
innovation as a manufactured product (largely immaterial.) It is essentially a refined
knowledge product that starts from an asset of base knowledge (representing the
current VE and the innovation options) and then is refined and enriched until the
‘innovation product’ is released. With this in mind, the Virtual Innovation Factory
(VIF) can be described as a parallel production factory that coexists with the ‘value
production’ enterprise. Today, the innovation ventures are generally carried out by a
specific department of the enterprise (e.g., the R&D Department). The BIVEE project
is aiming to move from this traditional approach, opening the innovation activities to
the whole enterprise beyond the dedicated department, and to external actors and
stakeholders (customers, suppliers, universities); all of them will participate in the
VIF. It is important to underline that it has been decided to move in the direction of an
Open Innovation (as described by [3]) perspective where the VIF staff is not ‘a
priory’ defined and the actors may change from a moment to another, within the same
innovation venture.
A VIF operates according to a paradigm and guidelines defined by the BIRF
(Business Innovation Reference Framework). The latter, that is not tightly
prescriptive, to allow the maximum freedom to the innovation teams, it is suggested
to organise the activities according to four Waves:
• W1 – Creativity: This first wave starts with an innovation idea or a problem
to be solved, described by a number of preliminary documents (such as
notes, emails, tweets, etc.) eventually summarized in one summary document
(Innovation Proposal Summary). It requires the creation of an innovation
team, establishing connections between different units, and the definition of
a preliminary agenda. All this is reported in a first set of documents.
• W2 – Feasibility: In this wave the scope and the intended impact need to be
defined, including a first account of technical and financial feasibility. A
refined planning is needed to justify the required investment, predicting the
cost/benefits and the chance of success.
• W3 – Prototyping: This wave features the first implementation of the initial
ideas, achieving a first full scale working model. Such a model is tested and
analyzed to verify the actual performance and characteristics, giving also the
possibility to rethink some design.
• W4 – Engineering: This final wave starts from the knowledge acquired with
the prototype(s) and aims at producing the specification of the final version
of the new product (essentially the Bill of Materials and manufacturing
procedures), ready for the market, and the corresponding production process.
This concluding wave also requires addressing other issues, from the market
strategy to the training of the employees.
Figure 2. The innovation waves
The idea of waves, instead of phases, emerged since their starts are sequenced in the
time, but they are tightly interconnected and the start of a new wave does not imply
that the previous one has been accomplished. Furthermore, in the proposed document-
centric approach, there will be often the need to jump back and forth in order to
complete a document or to correct it on basis of later findings. For instance, during
the prototyping wave there can be new findings that require the revision of the
previous financial feasibility study, obliging the team to rethink some parts of the
marketing strategy. The wave approach is sketchily depicted in Fig. 2.
During the innovation venture, the knowledge production is related to the creation of
a number of documents, according to pre-defined templates. One of the key
contributions of BIRF is the definition of what kind of information is needed in each
wave and a set of document templates, distributed along the four innovation waves,
conceives to gather and organise such information, guiding the innovation activities
and recording the achieved results. The description of information and document
templates falls outside of the scope of the present paper.
3 IMF: Innovation Monitoring Framework
The key objective of the BIVEE project concerns the methodological and
technological solutions to systematically support innovation in VEs. To this end, from
a methodological point of view, the following elements are in development:
• A systematic approach, with guidelines and business innovation document
templates, to be adopted in carrying out innovation. This is represented by the
BIRF.
• A dedicated modelling approach for the key aspects of the VE, relevant for
enterprise innovation. This is represented by the VEMF framework.
• A systematic approach, available to the innovation team, to monitor the
innovation going on in the VE, concerning both the quality of the innovation
target and the effectiveness of the innovation activities, providing a continue
assessment and an early discovery of unexpected deviations, with information
useful to correct them. This is represented by the Innovation Monitoring
Framework (IMF) that includes a system of KPIs and methods to derive them.
KPIs as tool to measure process performance have gained massive attention during
the last decade, also for networked environments (see e.g. [2, 5, 6]). However, very
little work focuses on innovation. In the IMF a set of key performance indicators
(KPIs) is introduced that aims at supporting the assessment of the innovation to check
if the venture is proceeding in the right direction, with the right pace. These KPIs are
associated to specific activities, to monitor their progress, and their outcomes, to
monitor the quality and the achieved business objective. The business objectives are
prioritized according to the innovation and business strategy of the VE. The IMF
organises the business objectives in eight groups:
• Reliability describes the ability of the network to constantly achieve its
innovation goals. It has a reversed relationship with the error rate of the outcome
of the measured activities.
• Velocity aims at pushing a low duration of the measured activities. The cycle
time of each activity is a typical KPI that can always be measured and describes
the time needed between the start and the end of an activity.
• Adaptability is the ability of the VIF to react to obstacles and varying demands
that arise from external or internal reasons. This can be for instance an increased
demand for a higher product quality or reduced costs of some components (see
how contradictory business objectives can be).
• Cost Orientation comprises the KPIs that measure the negative financial
dimension of expenses. A lower cost in carrying out innovation grants a higher
profit and leads to a higher business success.
• Asset Orientation contains KPIs that measure the positive financial dimension
of resources that cycle within an activity. In the innovation context, resources
are mainly intangible (knowledge) and assets mainly relates to the knowledge
power of knowledge workers. KPIs measuring the money spent on employee
training/development, or the amount of investment devoted to new products
belong to this class.
• Innovative Potential is the ability of a VEE to create ideas and to successfully
lead them into the market. This includes a certain level of creativity as well as
successful innovation management to reach for the market.
• Customer Orientation groups all measurements that are connected to the fact
that the sought innovation is geared towards the satisfaction of the customers.
Typical KPIs are the rating of customers’ focus groups or the target value
proposition.
• Network Orientation describes the objective of an optimal collaboration within
the VIF that is inherently a distributed, networked organism. The expected
number of new partnership made during idea development is an example of KPI
in this class.
These Business Objectives are are based on the Value Reference Model, created by
the Value Chain Group1, the performance measurement of [5] and the agility aspect
1
The Value Reference Model as it is part of the Value Chain Business Process Transformation
Framework (http://www.value-chain.org/en/cms/?1960)
described by [4] that has been adopted with the network orientation. The mentioned
literature is mainly focused on a value production evironment, the contribution of the
BIVEE project focused on its revisiting in the perspective of business and enteprise
innovation. In fact, the KPIs differ between Innnovation and Production. The KPIs on
produition (P-KPIs) address the Production Space and are aimed at optimising the
value production of a VE, conversely the KPIs on innovation (I-KPIs) apply for the
activities withing the Innovation Space and aim at optimising the innovation
capabilities of the VIF. Within the innovation space, the I-KPIs are aligned to the
activities to develop innovations. Each KPI is assigned a wave, activity, business
objective, name, unit of measurement and is provided a brief description about its
content. For instance, the amount of investment devoted to new products is aligned to
the activity Idea Generation within the Creativity Wave and it is connected to the
business objective Asset Orientation, as already said. The unit of measurement
(UOM) is %, since it is calculated as the ratio between R&D investment devoted to
new products and the toal of R&D investments.
4 The Semantic Platform
In order to provide a formal grounding for the three frameworks, BIRF, IMF and
VEMF, a method based on the semantic annotation of model elements is used.
Semantic annotation consists in the linking of model elements to one or more
ontological resources (e.g., concepts). To this end, the problem space of VIF has been
partitioned and conceived as a federation of ontologies that will provide the required
semantic base. Then, the VE models, the innovation venture, the KPIs, etc., will be
suitably annotated by using one or more of the following ontologies.
• Domain ontology (DomOnto) that models the business domain in which the
VE operates, including the manufactured products and services.
• Process Ontology (ProcOnto) that models the activities performed by the VE,
organized in two main sub-classes: production activities that will be affected by
the innovation, and innovation activities.
• Actor&Role Ontology (AROnto) that models the active entities operating in
the VE, and beyond, when relevant (including competencies and skills.)
• Resources Ontology (ResOnto). The production innovation means, including
technology and locations, except the HR.
• KPI Ontology (KPIOnto) that models the entities (referred to in the DomOnto
and ProcOnto) and related phenomena that are intended to keep under control. In
particular, here all the dimensions that characterize each selected KPIs are
defined along with the measures they are based on the formulas and algorithms
to calculate actual KPI values. The description is outlined according to the W5H
method (see below.)
• Business Ontology (BusOnto) represents the relevant business entities / info,
such as order, invoice, with the carried information.
• Document Ontolgy (DocOnto). Since all the info / knowledge need to be
documented, this onto describes all of the VE docs that are relevant in the
innovation venture.
The semantically enriched VIF resources can be managed by using a number of
advanced services, such as consistency checking and semantic search and retrieval.
Within the KPI Ontology, each KPI will be characterized according to the W5H
Method, detailed according to the following 6 dimensions: What (WT), Why (WY),
Who (WO), When (WN), Where (WR), How (HW). Therefore, a KPI is formally
represented by a 6-tuple:
KPI = (WT, WY, WO, WN, WR, HW)
When instantiating the above tuple for a specific KPI the 6 components need to be
specified, according to the ontologies presented below. In particular:
• What – this is about the business entity (activity) that is intended to be measured
(or assessed). Depending on the nature and target of the innovation, different
ontologies will support this. E.g., DomOnto in case of manufacture product
innovation, ProcOnto in case of process and/or service innovation, ResOnto in
case of technology innovation (considered as a production resource2).
• Why – this is a complex dimension and allows explaining the goals and
expected benefits aimed with the innovation venture. Potentially all the
ontologies are involved. Goal decomposition will be extensively adopted. In
BIVEE, the innovation goals are categorise according to the eight business
objectives.
• Who – this dimension reports different actors and roles, from stakeholders to
partners to actual executors. AROnto is the reference ontology that reports also
the capabilities and responsibilities of each role. This is particularly important in
a VE, where it is necessary to know who is responsible of what and what are the
activities currently assigned.
• When – the time dimension is important to identify a point of time interval.
Formally, it can be considered a resource and therefore represented within the
ResOnto ontology.
• Where – this is the location, intended also as an administrative location (legal
site) or geographical location. In a networked enterprise it is particularly
relevant. In particular, when dealing with the monitoring of innovation in a
distributed, networked environment (i.e., the VIF), this information becomes
crucial since it concerns the information on the place where the measurements
takes place. (The formal aspects of the ‘Where’ are represented in the ResOnto,
to avoid the proliferation of Onto.)
• How – this dimension has a double meaning: behavioural and instrumental. At
first, it is essential to specify how to perform the measure / assessment, what
methods will be adopted, including algorithms and formulas (if any) that will be
hosted in the KPIOnto. Here, also the underlying KPMs will be clarified. Since a
given KPI can be obtained in different fashions by different end users, here the
key issue is to provide a clear semantics. Besides a description and a few (non
mandatory) examples a formal representation of formulas is given. The formal
representation enables reasoning mechanisms for KPIs reconciliation, rewriting,
and consistency checking of the whole system of indicators in the Semantic
Base. Then, the end users will have the option of adopting one of the provided
2
Please note that we avoid the building and maintenance of a Technology Ontology that would
exceed our scope
formulas / method or define a proprietary3 one, as long as its nature (i.e.,
semantics) is preserved. The second parameter required is specified if specific
instruments, including software tools, online forms, etc. (as specified in the
ResOnto) are needed to achieve the assessment.
5 Conclusions and Future Work
This paper presented a synthesis of part of the work conducted in the BIVEE project
to monitor and support innovation in a Virtual Enterprise Environment. In particular
the modeling effort has been discussed, with a description of the framework that
serves as a reference for classifying the key entities involved in an innovation
endeavor, and a description of the Semantic Base guarantying a precise, rigorous,
unambiguous approach to the representation of the above framework. Initial
feedbacks by the end-users participating in the projects allow pushing on this model-
based, semantically rich approach, refining the framework and developing semantic-
based services. This is the matter of future work.
Bibliography
1. Barnett, W., A. Presley, M. Johnson and D. Liles (1994) "An Architecture for the Virtual
Enterprise". IEEE International Conference on Systems, Man, and Cybernetics, San
Antonio.
2. Bongsug, K.C. (2009) "Developing Key Performance Indicators for Supply Chain: An
Industry Perspective". Supply Chain Management: An International Journal, Vol. 14, No. 6,
pp. 422 -428.
3. Chesbrough, H. (2003) Open Innovation: The new Imperative for Creating and Profiting
from Technology. Boston, Massachussetts: Harvard Business School Press.
4. Cusumano, M. A. (2010) "Staying Power - Six enduring principles for managing strategy
and innovation in an uncertain world". Oxford University Press, New York.
5. Hieber, R. (2002) Supply Chain Management – A Collaborative Performance Measurement
Approach. vdf Hochschulverlag AG, ETH Zürich.
6. Kaplan, R. S., Norton, D. P. (2001) "Transforming the Balanced Scorecard From
Performance Measurement to Strategic Management: Part 1". Accounting Horizons, Vol. 15
No. 1., pp. 87-104.
7. Nikitas A. Assimakopoulos and Aggeliki D. Theodosi (2003) "A Systemic Approach for
Modeling Virtual Enterprise’s Management Features". Tamkang Journal of Science and
Engineering, Vol. 6, No. 2, pp. 87-101 (2003)
8. OECD Oslo manual on GUIDELINES FOR COLLECTING AND INTERPRETING
INNOVATION DATA. Third edition.
http://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/OSLO/EN/OSLO-EN.PDF
3
We are considering a formal language that, suitably edulcorated, can be adopted by end users