Measuring innovation using key performance indicators

Abstract

When undertaking innovation, developing Key Performance Indicators/KPIs represents an important tool for insuring that all process objectives are met. To this end, a specific methodology is required in order to identify not only meaningful indicators, but also other support elements. Such tool allows innovative SMEs (Small and Medium Enterprises) to enhance their decision making by accurately measuring innovation process performance and by optimizing their process. Present paper aims to establish the main requirements for developing meaningful KPIs in order to effectively measure innovation. As such, a case study is presented emphasizing the importance of correlating specific objectives, related results and key performance indicators. The need for establishing and using a common language for the innovation process is also emphasized. Standard language Business Process Model and Notation (BPMN) was employed to enhance process communication between users.

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Procedia Manufacturing 00 (2017) 000–000
www.elsevier.com/locate/procedia
* Paulo Afonso. Tel.: +351 253 510 761; fax: +351 253 604 741
E-mail address: psafonso@dps.uminho.pt
2351-9789 © 2017 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the Manufacturing Engineering Society International Conference 2017.
Manufacturing Engineering Society International Conference 2017, MESIC 2017, 28-30 June
2017, Vigo (Pontevedra), Spain
Costing models for capacity optimization in Industry 4.0: Trade-off
between used capacity and operational efficiency
A. Santanaa, P. Afonsoa,*, A. Zaninb, R. Wernkeb
a University of Minho, 4800-058 Guimarães, Portugal
bUnochapecó, 89809-000 Chapecó, SC, Brazil
Abstract
Under the concept of "Industry 4.0", production processes will be pushed to be increasingly interconnected,
information based on a real time basis and, necessarily, much more efficient. In this context, capacity optimization
goes beyond the traditional aim of capacity maximization, contributing also for organization’s profitability and value.
Indeed, lean management and continuous improvement approaches suggest capacity optimization instead of
maximization. The study of capacity optimization and costing models is an important research topic that deserves
contributions from both the practical and theoretical perspectives. This paper presents and discusses a mathematical
model for capacity management based on different costing models (ABC and TDABC). A generic model has been
developed and it was used to analyze idle capacity and to design strategies towards the maximization of organization’s
value. The trade-off capacity maximization vs operational efficiency is highlighted and it is shown that capacity
optimization might hide operational inefficiency.
© 2017 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the Manufacturing Engineering Society International Conference
2017.
Keywords: Cost Models; ABC; TDABC; Capacity Management; Idle Capacity; Operational Efficiency
1. Introduction
The cost of idle capacity is a fundamental information for companies and their management of extreme importance
in modern production systems. In general, it is defined as unused capacity or production potential and can be measured
in several ways: tons of production, available hours of manufacturing, etc. The management of the idle capacity
Procedia Manufacturing 22 (2018) 906–911
2351-9789 © 2018 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 11th International Conference Interdisciplinarity in Engineering.
10.1016/j.promfg.2018.03.128
10.1016/j.promfg.2018.03.128 2351-9789
© 2018 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientic committee of the 11th International Conference Interdisciplinarity in Engineering.
Available online at www.sciencedirect.com
ScienceDirect
Procedia Manufacturing 00 (2018) 913–918
www.elsevier.com/locate/procedia
2351-9789 © 2018The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 11th International Conference Interdisciplinarity in Engineering.
11th International Conference Interdisciplinarity in Engineering, INTER-ENG 2017, 5-6 October
2017, Tirgu-Mures, Romania
Measuring innovation using key performance indicators
Geanina Silviana BanuP
a,
P0F*
P
a
PProcess Innovation Nucleus S.R.L., 289 Calea Bucuresti Street, Mihailesti, Giurgiu, 085200, Roman ia
Abstract
When undertaking innovation, developing Key Performance Indicators/KPIs represents an important tool for insuring that all
process objectives are met. To this end, a specific methodology is required in order to identify not only meaningful indicators, but
also other support elements. Such tool allows innovative SMEs(Small and Medium Enterprises) to enhance their decision
making by accurately measuring innovation process performance and by optimizing their process. Present paper aims to establish
the main requirements for developing meaningful KPIsin order to effectively measure innovation. As such, a case study is
presented emphasizing the importance of correlating specific objectives, related results and key performance indicators.The need
for establishing and using a common language for the innovation process is also emphasized. Standard language Business
Process Model and Notation (BPMN) was employed to enhance process communication between users.
©2018The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 11th International Conference Interdisciplinarity in
Engineering.
Keywords: Key Performance Indicators;standard language.
1. Introduction
When undertaking innovation, an enterprise should perform an in-depth assay of the main characteristics of the
innovation process in order to properly understand the requirements of successful innovation. The main
characteristics of the innovation process can be summarized as follows [1]:
* Corresponding author. Tel.: +40-724-384-111.
E-mail address: pin.company.office@gmail.com; geanina.banu@pinucleus.ro
Available online at www.sciencedirect.com
ScienceDirect
Procedia Manufacturing 00 (2018) 913–918
www.elsevier.com/locate/procedia
2351-9789 © 2018The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 11th International Conference Interdisciplinarity in Engineering.
11th International Conference Interdisciplinarity in Engineering, INTER-ENG 2017, 5-6 October
2017, Tirgu-Mures, Romania
Measuring innovation using key performance indicators
Geanina Silviana BanuP
a,
P0F*
P
a
PProcess Innovation Nucleus S.R.L., 289 Calea Bucuresti Street, Mihailesti, Giurgiu, 085200, Roman ia
Abstract
When undertaking innovation, developing Key Performance Indicators/KPIs represents an important tool for insuring that all
process objectives are met. To this end, a specific methodology is required in order to identify not only meaningful indicators, but
also other support elements. Such tool allows innovative SMEs(Small and Medium Enterprises) to enhance their decision
making by accurately measuring innovation process performance and by optimizing their process. Present paper aims to establish
the main requirements for developing meaningful KPIsin order to effectively measure innovation. As such, a case study is
presented emphasizing the importance of correlating specific objectives, related results and key performance indicators.The need
for establishing and using a common language for the innovation process is also emphasized. Standard language Business
Process Model and Notation (BPMN) was employed to enhance process communication between users.
©2018The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 11th International Conference Interdisciplinarity in
Engineering.
Keywords: Key Performance Indicators;standard language.
1. Introduction
When undertaking innovation, an enterprise should perform an in-depth assay of the main characteristics of the
innovation process in order to properly understand the requirements of successful innovation. The main
characteristics of the innovation process can be summarized as follows [1]:
* Corresponding author. Tel.: +40-724-384-111.
E-mail address: pin.company.office@gmail.com; geanina.banu@pinucleus.ro
914 Geanina Silviana Banu /Procedia Manufacturing 00 (2018) 913–918
•the innovation process comprises of numerous events, various key people, a common context and a defined time-
frame.
•the innovation process is initiated as a result of planning and decision making, but it can also be triggered by
shocks sent by the market manifesting its needs.
•the innovation process should never be viewed as a linear sequential flow of activities.
•failure happens frequently and generates either discontinuance when innovation is rejected or opportunity when
innovation is “reinvented”.
•the innovation process should be opened both to the innovators and the adopters of the innovation.
•an efficient innovation process cannot guarantee the success of innovation but can influence the innovation
success rate.
Innovation requires proper planning of activities, realistic objectives, constant monitoring of unfolding activities
and measuring of results [2], [3]. Considering the intricacy of the innovation process as underlined by the above
characteristics, the aim of the paper is to emphasize the importance of developing meaningful KPIs in order to
measure innovation.
Various methodologies have been created and employed by enterprises for the purpose of developing KPIs.
Nevertheless, a generic methodology should be researched and identified. Such methodology should be easily
employed for the purpose of ensuring that process objectives are met. To this end, the research problem refers to
identifying a generic methodology for developing meaningful KPIs. The results of the research are applied in the
case of an unfolding innovation process.
2. Methodology
A secondary research was conducted in order to identify a generally accepted methodology for developing KPIs.
As a result, a set of KPIs has been established to support the implementation of a research and innovation project,
referred to as NANOAPPARATUS, undertaken by an innovative SME (Small and Medium-sized Enterprises) from
Romania. Moreover, Business Process Modeling was employed in order to facilitate the comprehensive
understanding of the innovation process and to efficiently implement and communicate it.
3. Results/main findings and contribution
Establishing a correlation between objectives, expected results and KPIs represents an important strategy tool
when planning the efficient management of a business process, especially in the case of the innovation process
representing a high-risk process. Developing KPIs should be undertaken as a systematic process based on revising
and in-depth analysis. This applies to research and innovation processes regardless of the nature of research.
Scientific and technological advancement requires the guidance of high performance innovation management. This
is also the case of the publicly funded NANOAPPARATUS research and innovation project implemented by Process
Innovation Nucleus S.R.L., the aforementioned innovative SME from Romania.
With input from the innovation consultant having the role of supporting the efficient implementation of
NANOAPPARATUS innovation process, the following methodology for developing KPIs was identified as being
comprehensive and largely employed by enterprises, having the main steps bellow [4], [5], [6]:
•Define and understand project objectives;
•Define and describe project results;
•Design and describe project activities;
•Develop and describe KPIs.
The referred methodology for developing KPIs was adapted to meet the specific of NANOAPPARATUS project
and modeled (Fig. 1) using the standard modeling language Business Process Model Notation 2.0. Furthermore, Fig.
1 depicts the methodology elements performed before and after starting the implementation phase of

Geanina Silviana Banu / Procedia Manufacturing 22 (2018) 906–911 907
Available online at www.sciencedirect.com
ScienceDirect
Procedia Manufacturing 00 (2018) 913–918
www.elsevier.com/locate/procedia
2351-9789 © 2018The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 11th International Conference Interdisciplinarity in Engineering.
11th International Conference Interdisciplinarity in Engineering, INTER-ENG 2017, 5-6 October
2017, Tirgu-Mures, Romania
Measuring innovation using key performance indicators
Geanina Silviana BanuP
a,
P0F*
P
a
PProcess Innovation Nucleus S.R.L., 289 Calea Bucuresti Street, Mihailesti, Giurgiu, 085200, Roman ia
Abstract
When undertaking innovation, developing Key Performance Indicators/KPIs represents an important tool for insuring that all
process objectives are met. To this end, a specific methodology is required in order to identify not only meaningful indicators, but
also other support elements. Such tool allows innovative SMEs(Small and Medium Enterprises) to enhance their decision
making by accurately measuring innovation process performance and by optimizing their process. Present paper aims to establish
the main requirements for developing meaningful KPIsin order to effectively measure innovation. As such, a case study is
presented emphasizing the importance of correlating specific objectives, related results and key performance indicators.The need
for establishing and using a common language for the innovation process is also emphasized. Standard language Business
Process Model and Notation (BPMN) was employed to enhance process communication between users.
©2018The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 11th International Conference Interdisciplinarity in
Engineering.
Keywords: Key Performance Indicators;standard language.
1. Introduction
When undertaking innovation, an enterprise should perform an in-depth assay of the main characteristics of the
innovation process in order to properly understand the requirements of successful innovation. The main
characteristics of the innovation process can be summarized as follows [1]:
* Corresponding author. Tel.: +40-724-384-111.
E-mail address: pin.company.office@gmail.com; geanina.banu@pinucleus.ro
Available online at www.sciencedirect.com
ScienceDirect
Procedia Manufacturing 00 (2018) 913–918
www.elsevier.com/locate/procedia
2351-9789 © 2018The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 11th International Conference Interdisciplinarity in Engineering.
11th International Conference Interdisciplinarity in Engineering, INTER-ENG 2017, 5-6 October
2017, Tirgu-Mures, Romania
Measuring innovation using key performance indicators
Geanina Silviana BanuP
a,
P0F*
P
a
PProcess Innovation Nucleus S.R.L., 289 Calea Bucuresti Street, Mihailesti, Giurgiu, 085200, Roman ia
Abstract
When undertaking innovation, developing Key Performance Indicators/KPIs represents an important tool for insuring that all
process objectives are met. To this end, a specific methodology is required in order to identify not only meaningful indicators, but
also other support elements. Such tool allows innovative SMEs(Small and Medium Enterprises) to enhance their decision
making by accurately measuring innovation process performance and by optimizing their process. Present paper aims to establish
the main requirements for developing meaningful KPIsin order to effectively measure innovation. As such, a case study is
presented emphasizing the importance of correlating specific objectives, related results and key performance indicators.The need
for establishing and using a common language for the innovation process is also emphasized. Standard language Business
Process Model and Notation (BPMN) was employed to enhance process communication between users.
©2018The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 11th International Conference Interdisciplinarity in
Engineering.
Keywords: Key Performance Indicators;standard language.
1. Introduction
When undertaking innovation, an enterprise should perform an in-depth assay of the main characteristics of the
innovation process in order to properly understand the requirements of successful innovation. The main
characteristics of the innovation process can be summarized as follows [1]:
* Corresponding author. Tel.: +40-724-384-111.
E-mail address: pin.company.office@gmail.com; geanina.banu@pinucleus.ro
914 Geanina Silviana Banu /Procedia Manufacturing 00 (2018) 913–918
•the innovation process comprises of numerous events, various key people, a common context and a defined time-
frame.
•the innovation process is initiated as a result of planning and decision making, but it can also be triggered by
shocks sent by the market manifesting its needs.
•the innovation process should never be viewed as a linear sequential flow of activities.
•failure happens frequently and generates either discontinuance when innovation is rejected or opportunity when
innovation is “reinvented”.
•the innovation process should be opened both to the innovators and the adopters of the innovation.
•an efficient innovation process cannot guarantee the success of innovation but can influence the innovation
success rate.
Innovation requires proper planning of activities, realistic objectives, constant monitoring of unfolding activities
and measuring of results [2], [3]. Considering the intricacy of the innovation process as underlined by the above
characteristics, the aim of the paper is to emphasize the importance of developing meaningful KPIs in order to
measure innovation.
Various methodologies have been created and employed by enterprises for the purpose of developing KPIs.
Nevertheless, a generic methodology should be researched and identified. Such methodology should be easily
employed for the purpose of ensuring that process objectives are met. To this end, the research problem refers to
identifying a generic methodology for developing meaningful KPIs. The results of the research are applied in the
case of an unfolding innovation process.
2. Methodology
A secondary research was conducted in order to identify a generally accepted methodology for developing KPIs.
As a result, a set of KPIs has been established to support the implementation of a research and innovation project,
referred to as NANOAPPARATUS, undertaken by an innovative SME (Small and Medium-sized Enterprises) from
Romania. Moreover, Business Process Modeling was employed in order to facilitate the comprehensive
understanding of the innovation process and to efficiently implement and communicate it.
3. Results/main findings and contribution
Establishing a correlation between objectives, expected results and KPIs represents an important strategy tool
when planning the efficient management of a business process, especially in the case of the innovation process
representing a high-risk process. Developing KPIs should be undertaken as a systematic process based on revising
and in-depth analysis. This applies to research and innovation processes regardless of the nature of research.
Scientific and technological advancement requires the guidance of high performance innovation management. This
is also the case of the publicly funded NANOAPPARATUS research and innovation project implemented by Process
Innovation Nucleus S.R.L., the aforementioned innovative SME from Romania.
With input from the innovation consultant having the role of supporting the efficient implementation of
NANOAPPARATUS innovation process, the following methodology for developing KPIs was identified as being
comprehensive and largely employed by enterprises, having the main steps bellow [4], [5], [6]:
•Define and understand project objectives;
•Define and describe project results;
•Design and describe project activities;
•Develop and describe KPIs.
The referred methodology for developing KPIs was adapted to meet the specific of NANOAPPARATUS project
and modeled (Fig. 1) using the standard modeling language Business Process Model Notation 2.0. Furthermore, Fig.
1 depicts the methodology elements performed before and after starting the implementation phase of

908 Geanina Silviana Banu / Procedia Manufacturing 22 (2018) 906–911
Geanina Silviana Banu /Procedia Manufacturing 00 (2018) 913–918 915
NANOAPPARATUS, elements which were analyzed and/or defined and systematized according to the referred
methodology.
Fig. 1. Methodology for developing KPIs to measure the NANOAPPARATUSproject results. Adapted from [4]. [5], [6].
In order to develop the NANOAPPARATUS project KPIs, a comprehensive correlation between project
objectives, activities and results was established allowing for identifying measures to support achieving the
objectives. The following requirements were considered when developing the NANOAPPARATUS project KPIs:
•The KPIs should comply with the particular characteristics of NANOAPPARATUS innovation process;
•The KPIs should rely on clearly identified and rated measures;
•The KPIs should support implementing project activities and achieving project objectives;
•The KPIs should reflect only available data;
•The KPIs should allow for reevaluation and further improvement;
•The KPIs should impact also the results of the organization’s activities and not only those of project activities.
Table 1 presents three examplesof KPIs developed to measure the results of the experimental development phase
of NANOAPPARATUS.
Table 1. Key performance indicators/ KPIs description
No.
Objectives
Results
KPI
Measure
1. Designing a prototype
for producing
nanopowders at
industrial scale
(TRL 9 )
Developing high
quality nanopowders
for automotive industry
and other industries
Identifying the
chemical
composition of input
materials using
specific analysis
techniques –
identifying at least
five types of input
materials to be
processed into
Increasing
performance of the
apparatus for
producing
nanopowder (i.e. the
product) by
developing input
chemical composite
materials to ensure
low resource
Minimum 3 criteria for identifying
the chemical composite materials (i.e.
comprising of the input material to be
processed into nanopowders and the
selected catalysts), such as:
I. Identify chemical
composite materials able
to determine the reduction
of the melting point.

Geanina Silviana Banu / Procedia Manufacturing 22 (2018) 906–911 909
Geanina Silviana Banu /Procedia Manufacturing 00 (2018) 913–918 915
NANOAPPARATUS, elements which were analyzed and/or defined and systematized according to the referred
methodology.
Fig. 1. Methodology for developing KPIs to measure the NANOAPPARATUSproject results. Adapted from [4]. [5], [6].
In order to develop the NANOAPPARATUS project KPIs, a comprehensive correlation between project
objectives, activities and results was established allowing for identifying measures to support achieving the
objectives. The following requirements were considered when developing the NANOAPPARATUS project KPIs:
•The KPIs should comply with the particular characteristics of NANOAPPARATUS innovation process;
•The KPIs should rely on clearly identified and rated measures;
•The KPIs should support implementing project activities and achieving project objectives;
•The KPIs should reflect only available data;
•The KPIs should allow for reevaluation and further improvement;
•The KPIs should impact also the results of the organization’s activities and not only those of project activities.
Table 1 presents three examplesof KPIs developed to measure the results of the experimental development phase
of NANOAPPARATUS.
Table 1. Key performance indicators/ KPIs description
No.
Objectives
Results
KPI
Measure
1. Designing a prototype
for producing
nanopowders at
industrial scale
(TRL 9 )
Developing high
quality nanopowders
for automotive industry
and other industries
Identifying the
chemical
composition of input
materials using
specific analysis
techniques –
identifying at least
five types of input
materials to be
processed into
Increasing
performance of the
apparatus for
producing
nanopowder (i.e. the
product) by
developing input
chemical composite
materials to ensure
low resource
Minimum 3 criteria for identifying
the chemical composite materials (i.e.
comprising of the input material to be
processed into nanopowders and the
selected catalysts), such as:
I. Identify chemical
composite materials able
to determine the reduction
of the melting point.
916 Geanina Silviana Banu /Procedia Manufacturing 00 (2018) 913–918
Implementing
NANNOAPPARATUS
project with the help
of an interdisciplinary
team, whose members
come both from private
and public
organizations
nanopowders
Identifying and
preparing at least six
catalysts in order to
establish the
chemical composite
materials to process
for producing
nanopowders.
consumption and
high value added.
II. Identify chemical
composite materials based
on their triboelectric
properties.
III. Select the input materials
to be processed into
nanopowders with high
value added.
2.
Designing a prototype
for producing
nanopowders at
industrial scale
(TRL 9 )
Developing high
quality nanopowders
for automotive industry
and other industries
Procurement of the
input materials to be
processed into
nanopowders and the
necessary catalysts.
Procurement of all
materials,
components and
subcomponents of
the prototype for
producing
nanopowders
Increase the
correlation between
actual financial
resources needed,
projected budget
and experimental
development
expected results
Implementing an evaluation
methodology for solutions proposed
to improve scientific results during
the experimental development stage,
comprising of minimum 3 criteria:
I. The projected budget
should not be affected
with more than 5% when
making changes.
II. The proposed technical
solution for designing the
prototype should be
altered only of strongly
and quantifiably justified.
III. The basic scientific
elements of the technical
solution should suffer no
significant change.
3. Performing the
successful market
uptake of the new
process for producing
nanopowders in 24
months from signing
the financing
agreement
Developing high
quality nanopowders
for automotive industry
and other industries
Obtaining a patent for
method for producing
nanopwders; Direct
and indirect
exploitation of method
for producing
nanopowders once the
European patent is
granted; filing for a
new patent application
as a result of
experimental
development
Granted European
patent for method for
producing
nanopowders; Patent
validation in at least
three jurisdictions in
Europe (e.g.
Germany and Great
Britain, including
Romania); New
patent application
filed for apparatus
for producing
nanopowders which
is to be developed as
a result of the
project.
New “Knowledge
management system”
implemented within
the organization as a
result of the project.
Technical
specifications
elaborated for the
developed
Increase innovation
success rate by
identifying as many
external channels as
possible for
accessing expertise
in critical areas of
the project
The use of external channels of
expertise, such as external suppliers
with expertise in areas of the project.
The organization’s
capacity to
identify external expertise is
measured by:
I. The number of minimum
requirements for selecting
the innovation
consultants. The
following minimum 3
criteria are recommended:
-Experience in the field
of innovation
(experienced
personnel and similar
experience);
-Suppliers ‘capacity to
develop innovations
(number of
successfully
developed innovative
ideas within last five
years –minimum 1);
-The price –

910 Geanina Silviana Banu / Procedia Manufacturing 22 (2018) 906–911
Geanina Silviana Banu /Procedia Manufacturing 00 (2018) 913–918 917
nanopowders.
Evaluated
environmental
impact of the fully
developed
technology for
producing
nanopowders.
Certified prototype
for producing
nanopowders
Increase innovation
success rate by
increasing team’s
capacity to
document the
innovation process
performance ratio.
Team’s capacity
to document the
output data of the experimental
development increases the input of
correct and efficient data for the
innovation activities to follow. Said
capacity is measured by:
-
The number of team
members documenting
in a systematic
manner the output
data o
f the
experimental
development -
minimum 2 is
recommended.
Fig. 2. Innovation activities to support R&D –sub-process of NANOAPPARATUS innovation process.
918 Geanina Silviana Banu /Procedia Manufacturing 00 (2018) 913–918
As NANOAPPARATUS will unfold and generate measurable values, thresholds can also be defined. Considering
that the case study NANOAPPARATUS is a new process, measurable values will continue to change, thus creating
comparators for the developed KPIs. In order to define thresholds and to meet process targets, it is very important to
register all values and to keep record of all changes taking place as innovation process unfolds.
When implementing the aforementioned methodology for developing KPIs, the need arose for using a common
language of the NANOAPPARATUS innovation process. As such, the standard language Business Process Model
and Notation (BPMN) was employed [7]. It allowed for integrating all process data, human and financial resources
and basic time elements to be unitarily represented, processed and communicated to process users and stakeholders.
Business Process Modeling with the help of BPMN is possible by employing specific modeling instruments. For the
purpose of this paper Bizagi Modeler freeware instrument was employed. Other modeling programs are possible for
same purpose.
Fig. 2depicts a sub-process of the NANOAPPARATUS innovation process comprising the innovation activities
to support R&D. The referred sub-process is shown as an example of how to model a flow of activities into a
dynamic sequence allowing for continuous process evaluation and optimization.
The entire sequence of activities specific to NANOAPPARATUS innovation process was modeled using BPMN
and various “what if” scenarios were created and compared based on criteria pertaining time and resources. As such,
process bottlenecks were identified allowing focusing efforts on developing process KPIs.
4. Conclusions
A generic methodology for developing meaningful KPIs was identified. Furthermore, said methodology is linked
with the use of Business Process Modeling in order to ensure that a process can be handled as standard process by
all its users. Present research supports the use of Business Process Modeling for the management and automation of
business processes, allowing for real time process handling and quick access to all process data.
The methodology for developing KPIs is applied in the case of an unfolding innovation process with the purpose
of optimizing it by assigning measures to systematically achieve process objectives. Further focusing on step by step
measuring the process performance level should allow for real time reevaluation of ongoing innovation activities
and related results.
Acknowledgements
This work is disseminating results of the project “Prototype for verifying the practical potential of an innovative
nanotechnology and production line /Prototip pentru validare nanotehnologie inovatoare si linie de productie”,
having SMIS 104269 and Financial Agreement 71/08.09.2016. The project is co-funded by the European Regional
Development Fund through the Competitiveness Operational Programme 2014-2020.
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Geanina Silviana Banu / Procedia Manufacturing 22 (2018) 906–911 911
Geanina Silviana Banu /Procedia Manufacturing 00 (2018) 913–918 917
nanopowders.
Evaluated
environmental
impact of the fully
developed
technology for
producing
nanopowders.
Certified prototype
for producing
nanopowders
Increase innovation
success rate by
increasing team’s
capacity to
document the
innovation process
performance ratio.
Team’s capacity
to document the
output data of the experimental
development increases the input of
correct and efficient data for the
innovation activities to follow. Said
capacity is measured by:
-
The number of team
members documenting
in a systematic
manner the output
data o
f the
experimental
development -
minimum 2 is
recommended.
Fig. 2. Innovation activities to support R&D –sub-process of NANOAPPARATUS innovation process.
918 Geanina Silviana Banu /Procedia Manufacturing 00 (2018) 913–918
As NANOAPPARATUS will unfold and generate measurable values, thresholds can also be defined. Considering
that the case study NANOAPPARATUS is a new process, measurable values will continue to change, thus creating
comparators for the developed KPIs. In order to define thresholds and to meet process targets, it is very important to
register all values and to keep record of all changes taking place as innovation process unfolds.
When implementing the aforementioned methodology for developing KPIs, the need arose for using a common
language of the NANOAPPARATUS innovation process. As such, the standard language Business Process Model
and Notation (BPMN) was employed [7]. It allowed for integrating all process data, human and financial resources
and basic time elements to be unitarily represented, processed and communicated to process users and stakeholders.
Business Process Modeling with the help of BPMN is possible by employing specific modeling instruments. For the
purpose of this paper Bizagi Modeler freeware instrument was employed. Other modeling programs are possible for
same purpose.
Fig. 2depicts a sub-process of the NANOAPPARATUS innovation process comprising the innovation activities
to support R&D. The referred sub-process is shown as an example of how to model a flow of activities into a
dynamic sequence allowing for continuous process evaluation and optimization.
The entire sequence of activities specific to NANOAPPARATUS innovation process was modeled using BPMN
and various “what if” scenarios were created and compared based on criteria pertaining time and resources. As such,
process bottlenecks were identified allowing focusing efforts on developing process KPIs.
4. Conclusions
A generic methodology for developing meaningful KPIs was identified. Furthermore, said methodology is linked
with the use of Business Process Modeling in order to ensure that a process can be handled as standard process by
all its users. Present research supports the use of Business Process Modeling for the management and automation of
business processes, allowing for real time process handling and quick access to all process data.
The methodology for developing KPIs is applied in the case of an unfolding innovation process with the purpose
of optimizing it by assigning measures to systematically achieve process objectives. Further focusing on step by step
measuring the process performance level should allow for real time reevaluation of ongoing innovation activities
and related results.
Acknowledgements
This work is disseminating results of the project “Prototype for verifying the practical potential of an innovative
nanotechnology and production line /Prototip pentru validare nanotehnologie inovatoare si linie de productie”,
having SMIS 104269 and Financial Agreement 71/08.09.2016. The project is co-funded by the European Regional
Development Fund through the Competitiveness Operational Programme 2014-2020.
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