R&D Project Portfolio Management at Volvo Powertrain (2008)
1. R&D Project Portfolio Management at
Volvo Powertrain
Conceptualizing new project selection tools
Master of Science Thesis in the Master Degree Programme:
Management and Economics of Innovation
JOHAN SVENNUNG
CHRISTOPHER SÖDERSTRÖM
Department of Technology Management and Economics
Division of Project Management
CHALMERS UNIVERSITY OF TECHNOLOGY
Göteborg, Sweden, 2008
Report No. E 2008:092
2.
3. MASTER’S THESIS E 2008:092
R&D Project Portfolio Management at Volvo Powertrain
Conceptualizing new project selection tools
Johan Svennung
Christopher Söderström
Supervisor, Chalmers: Per Svensson, Head of Department and Senior Lecturer
Supervisor, Volvo Powertrain: Sören Udd, Advanced Engineering Manager
Department of Technology Management and Economics
Division of Project Management
CHALMERS UNIVERSITY OF TECHNOLOGY
Göteborg, Sweden 2008
5. III
EXECUTIVE SUMMARY
This report describes how Volvo Powertrain has organized their Advanced Engineering
project selection activities in what is called the Advanced Engineering Planning Process
(AEPP). This planning process consists of many elements which provide structure, while at
the same time allowing for flexibility. Also, three, by the literature, recommended tools for
project selection are in use within the process – roadmaps, sub project portfolios and pairwise
comparisons. Moreover, besides product features, a quite large number of informal evaluation
criterions are being used for screening and selecting projects.
Many problems and drawbacks with the current project selection activities have been
identified. This includes: lack of guidelines and criterions; need for comparing project
proposals from different units; need for more systematic project prioritization meetings;
projects prioritizations are highly influenced by individuals, and somewhat by chance;
prioritization discussion can be very verbose as well as too hasty; low-risk projects are often
chosen instead of more complex long-term projects. However, several advantages with these
selection activities have been identified as well. This includes getting constructive feedback
and criticism, and thorough discussions creating organizational anchoring of the projects and
understanding of why the projects are important.
A Technology Merit Evaluation Tool (TMET) is suggested in order to address these issues as
well as increasing the value of the project portfolio, the risk-reward balance of the portfolio,
and the alignment between the business strategy and the portfolio. The TMET consists of a
scoring model and a bubble chart. It is suggested that VPT uses a scoring model for
evaluating project proposals upon relevant criterions – including product features. This would
produce a ranking list of the projects as well as increasing the structure, systematization and
objectivity during project selection activities. The bubble chart can be used for increasing the
balance of the portfolio as well as communicating the result from the scoring model.
One suggestion is that the sub systems first use the TMET for ranking their project proposals
in connection to the creation of AE Sub Programs. The proposals they are unsure to receive
founding for should afterwards be sent to a cross-functional group with participators from the
sub systems, Concept and Product Planning and perhaps even GAEC. This group then ranks
this blend of proposals so that resources can be allocated to the best projects, independently of
which source created them. However, these ranking activities should start with the criterion
ratings already made within each sub system in order to save time. Moreover, guidelines
should be derived from the scoring model’s criterions and used when screening project
proposals and creating roadmaps earlier during AEPP.
Furthermore, perceived advantages of AEPP appear to be or result from the structure and
flexibility of this approach. However, it seems as VPT should consider increasing the
communication, feedback and knowledge sharing between different units and participators in
AEPP. There also appears to be a need for more and better distributed deadlines and time
plans.
Keywords: project portfolio management, project selection, technology selection, strategy
implementation, resource allocation, R&D management, scoring model, evaluation criteria.
6. IV
ACKNOWLEDGEMENTS
We would like to thank everyone – inside and outside Volvo Powertrain – for their
participation in and contribution to the project that have resulted in this report. It would not
have been possible to run this project without you or reaching the result that have been made.
It has indeed been a rewarding and developing experience. The support and feedback from
our supervisors Per Svensson and Sören Udd have been insightful and decisive. A special
thank goes to Niklas Thulin for acting as a gate-keeper, letting us into Volvo Powertrain’s
organization and making Sören Udd interested in our involvement.
Johan Svennung, Christopher Söderström
Göteborg, 2008
7. V
Table of contents
1. INTRODUCTION ............................................................................................................1
1.1. Volvo Powertrain AE require a project selection tool...................................................1
1.2. Deliverables in this report ............................................................................................2
2. RESEARCH DESIGN AND METHODS........................................................................3
2.1. Research design elements.............................................................................................3
2.1.1. Literature review...................................................................................................3
2.1.2. Investigation of external organizations ..................................................................3
2.1.3. Exploring VPT AE................................................................................................4
2.1.4. Workshops at VPT................................................................................................4
2.2. Validity and reliability of the research design...............................................................5
3. REVIEW OF PROJECT PORTFOLIO MANAGEMENT LITERATURE .................7
3.1. The need for project portfolio management and the existing research...........................7
3.2. Defining project portfolio management........................................................................8
3.3. The three goals in project portfolio management..........................................................9
3.4. Towards a project portfolio management theory framework.......................................10
3.4.1. Framework for organizing project portfolio management ....................................12
3.5. Complexities involved in and problems due to poor project portfolio management ....14
4. METHODS AND TOOLS USED IN PROJECT PORTFOLIO MANAGEMENT ....15
4.1. Methods and tools for value maximization.................................................................15
4.1.1. Scoring models....................................................................................................16
4.1.2. Pairwise comparisons and analytical hierarchy procedures ..................................19
4.1.3. Project evaluation and selection criterions ...........................................................20
4.2. Methods and tools for achieving a balanced portfolio.................................................23
4.2.1. Bubble charts ......................................................................................................23
4.2.2. Pie charts ............................................................................................................24
4.3. Methods and tools for achieving a strong link between strategy and the portfolio.......25
4.3.1. Roadmaps ...........................................................................................................25
4.3.2. Sub project portfolios..........................................................................................25
5. INVESTIGATION OF SCA TISSUE AND VOLVO AERO........................................27
5.1. SCA Tissue’s project selection process and methods..................................................27
5.1.1. SCA Tissue’s scoring model ...............................................................................29
5.1.2. Using the scoring model and the result ................................................................30
5.2. Learning from Volvo Aero Corporation .....................................................................31
5.2.1. The current project selection approach at VAC....................................................31
5.2.2. Previous project selection methods and tools used within VAC...........................31
5.3. Commenting the SCA Tissue and VAC cases ............................................................33
6. THE PPM APPROACH AT VOLVO POWERTRAIN AE .........................................34
6.1. Volvo Powertrain’s product development organization structure................................34
6.2. Volvo Powertrain’s Advanced Engineering Planning Process ....................................34
6.2.1. Roadmaps development ......................................................................................36
6.2.2. AE project selection ............................................................................................37
8. VI
6.2.3. Concept...............................................................................................................38
6.2.4. Sub processes of AEPP .......................................................................................38
6.2.5. Volvo Technology involvement ..........................................................................39
6.2.6. Product Planning.................................................................................................40
6.3. Five sub systems – Five AEPP sub processes.............................................................40
6.3.1. Combustion.........................................................................................................41
6.3.2. Hybrid Technology .............................................................................................44
6.3.3. Base Engine ........................................................................................................47
6.3.4. Driveline.............................................................................................................51
6.3.5. Control Systems..................................................................................................53
6.3.6. Comparing the sub systems AEPP approaches ....................................................56
6.3.7. Drawbacks and other issues in AEPP that a TMET could address........................58
6.4. Analysing the AEPP approach ...................................................................................61
6.4.1. The use of tools and methods ..............................................................................61
6.4.2. Organizational aspects.........................................................................................62
6.4.3. Procedural aspects...............................................................................................62
6.4.4. How to improve AEPP........................................................................................63
7. TMET DESIGN, USE AND CONSIDERATIONS .......................................................65
7.1. A Scoring model and a bubble chart to include in the TMET .....................................65
7.1.1. The TMET needs to be complemented ................................................................67
7.2. Using the TMET........................................................................................................68
7.2.1. How to use the TMET in AEPP...........................................................................69
7.2.2. Aspects of importance to consider.......................................................................73
7.3. Developing a more simple version of the TMET........................................................77
7.4. Concluding remarks...................................................................................................78
REFERENCES...................................................................................................................79
Appendix I: Interview guide ..............................................................................................83
Appendix II: Additional theory and methods to consider for project selection...............89
A.II.1. Financial tools ...................................................................................................89
A.II.2. S-curves and technology cycles .........................................................................90
A.II.3. Technology categorization.................................................................................91
A.II.4. Techno economic chain .....................................................................................94
A.II.5. A more quantitative scoring model ....................................................................96
Appendix III: Project evaluation and selection criterions ................................................98
9. VII
List of abbreviations
AE Advanced Engineering
AEPP Advanced Engineering Planning Process
AEWS Advanced Engineering Workshop
AHP Analytical Hierarchy Procedure
CEO Chief Executive Officer
EIRMA European Industrial Research Management Association
GAEC Global Advanced Engineering Committee
IRI Industrial Research Institute
NPV Net Present Value
PD Product Development
PDMA Product Development and Management Association
PhD Doctor of Philosophy
PPM Project Portfolio Management
PWC Pairwise Comparisons
QFD Quality Function Deployment
R&D Research and Development
RM Roadmap
RM1 Roadmap Level 1
RM2 Roadmap Level 2
RM3 Roadmap Level 3
RM4 Roadmap Level 4
ROI Return on Investment
SCA Svenska Cellulosa Aktiebolaget
TMET Technology Merit Evaluation Tool
VAC Volvo Aero Corporation
VPT Volvo Powertrain
11. 1
1. INTRODUCTION
Project Portfolio Management (PPM) is an area of practice which addresses the need to
choose projects to launch or proceed with among attractive and suitable project ideas and
ongoing projects – due to scarcity of resources. The interest in PPM among researchers and
practitioners has been growing in the recent years (Dawidson, 2006). As technological
innovation is now days the most important driver of many competitive successes one might
recognise the increased importance of PPM (motivating the increased interest) as PPM is one
element of strategic management of technological innovation (Schilling, 2008).
This report is the tangible result from the master thesis work that have been performed
together with a local part of the global R&D-unit at Volvo Powertrain (VPT) in order to
address problems and opportunities facing them in their daily work that concerns the PPM
practice. The goal has been to improve their PPM approach in general and to develop a tool
that can be used for ranking their technology development project proposals according their
suitability.
1.1. Volvo Powertrain AE require a project selection tool
VPT is a business division that belongs to Volvo Group. Their objective is to develop and
produce heavy engines, gearboxes and driveshafts for other divisions within Volvo Group
[website A]. These products are used as parts in the other divisions’ products such as trucks,
busses, construction equipment vehicles, as well as marine and industrial engines. VPT are
delivering annual volumes amounting to 200,000 engines and 80,000 gearboxes [website B].
The R&D operation at VPT consists of Advanced Engineering (AE) activities, developing
new technology, and Product Development (PD) activities, developing new products.
However, VPT AE has more interesting AE project ideas than what their present and future
resources can support. This means that VPT AE needs an appropriate approach, including
processes and methods, for selecting the projects that would contribute to their division’s
overall objective as much as possible. VPT AE includes those individuals and units involved
in AE activities and related efforts.
The main foundation or tools for project selection at VPT AE today are their product and
technology roadmaps. The roadmaps show ongoing and planned projects in the AE phase and
PD phase. The roadmaps show were and when the output from the various AE projects will be
used as input for the PD projects and at what time these latter should be industrialised.
The current decision making for project selection does not use any formalised foundation
besides the roadmaps (excluding project descriptions and cost estimates). The decision
making is mainly based on assessments by the individuals involved in the project selection
process and discussions between them. This is judged by VPT AE to be insufficient or at least
that there exist opportunities for improvements.
VPT AE has therefore expressed a desire to develop a Technology Merit Evaluation Tool
(TMET). The TMET is envisioned to be used for evaluating potential and running projects
along different criterions, including expected contributions from the projects to important
12. 2
product features. Further project evaluation criterions that VPT AE initially judged as
possibly suitable for the TMET are project cost, probability of success, and timing.
1.2. Deliverables in this report
The overall purpose of the master thesis project was to improve the way project selection is
performed within the AE operation of VPT, and thereby increasing the likelihood that the
right technologies are developed in the end. In order to make this contribution, the following
deliverables are included in this report:
• A presentation of the ‘state of the art’ and ‘state of the science’ literature of:
o Project portfolio management
o Project selection methods and tools
o Evaluation criterions
• A description of the current situation at VPT, including:
o The project portfolio management approach at VPT
o The evaluation criterions and methods used at VPT
• A description of relevant methods and learning from other appropriate firms
• A foundation and suggestions for VPT regarding how to develop a Technology Merit
Evaluation Tool
13. 3
2. RESEARCH DESIGN AND METHODS
In order to accomplish the goals and objectives outlined in section 1 the following were done:
literature review; investigation of VPT AE; investigations of external firms; two workshops at
VPT AE.
2.1. Research design elements
2.1.1. Literature review
The literature review created a foundation for the forthcoming empirical investigations and
activities as it provided an understanding of what questions to ask and the ability to interpret
the given answers as well as assessing their importance. Finding suitable tools was of
particular importance. The literature study was continued in parallel with the remaining parts
of the work, but with lower intensity during the end phase. The literature that was reviewed
can be categorised into one or more of the following subjects: Project portfolio management;
Project selection; Technology selection; Technology management; R&D management;
Innovation management; Strategic management; Project management; Strategic market
management; Research design and methods.
2.1.2. Investigation of external organizations
The investigation of PPM approaches at external firms involved SCA Tissue and Volvo Aero
Corporation (VAC). Common for these two firms are that they were judged as appropriate
due to similarities regarding firm size, development operations, international spread, presence
or activities. VAC was also appropriate as they are a part of Volvo Group, because they
develop products that are similar to VPT’s, and they also have only a few large customers in
the subsequent stage in the value chain.
Regarding SCA Tissue, a more important reason for choosing this firm was due to the
recommendation given by Ola Dawidson, who has performed in depth research of their PPM
approach, as well as written the latest PhD thesis concerning PPM at Chalmers University of
Technology. He has also worked with project portfolio management together with Product
Planning at VPT. SCA Tissue was simply perceived as being most advanced regarding PPM
(in the immediate surroundings) as well as having developed and used tools that were
anticipated as appropriate for VPT AE.
The main difference of the investigation of SCA Tissue and VAC is that the investigation of
the former focused upon how PPM is performed today and is going to be performed, whereas
the latter investigation focused upon project selection procedures, tools and learning’s from
years a little more back in time.
Common for both investigations was that responsible and experienced managers were
interviewed. The face to face interviews were transcribed and tape recorded, while this was
not possible for the phone interviews.
14. 4
Two representatives from SCA Tissue were interviewed: Malin Andersson, who is an
International Business Project Manager; and Anders Gustafsson who is a manager at Wiper
Systems. They both belong to the Category department which include both the product
development and marketing units. The product development and marketing units is located in
Göteborg and south western Germany. These interviews were not controlled by the
researchers as the interviewees were quite self-driven, revealing and structured when
describing their project selection approach and tools – in this way they were more like
informants then respondents.
Three representatives from Volvo Aero were interviewed: Bengt-Olof Elfström, a Research
Director, Oskar Brännström who is an Innovation Manager, and Ulf Högman, currently PhD
student at Chalmers but with many years of R&D experience from VAC. They all belong to
the Department of Innovation Management and Technology Planning at VAC, in Trollhättan,
Sweden. The interviews were performed in a semi-structured manner with interview guides.
2.1.3. Exploring VPT AE
Initially, the supervisor from VPT described their organizational structure and their Advanced
Engineering Planning Process (AEPP) – the PPM process – and documents of these two
elements were received. The supervisor also compiled a list of ten appropriate people
involved in the AE activities to conduct interviews with – nine from VPT AE and one from
Volvo Technology. Furthermore, two representatives from VPT Product Planning were
interviewed as these are important stakeholders of AEPP as well as information suppliers to
AEPP.
These twelve interviews were one to two hours long and interview guides were used for all of
them. The interview guide used at VPT AE was based on PPM literature, but particularly on
the PPM framework developed by Dawidson (2006) and the interview guide used by
Sandgren et al. (2005). This guide can be found in Appendix I. Additional interview guides
were developed for the interviews with Product Planning and Volvo Technology. All
interviews were semi-structured as well as tape recorded and transcribed.
2.1.4. Workshops at VPT
Two workshops were conducted together with the managers at VPT who previously had been
interviewed. The first workshop was opened with a description of how the different units
within VPT AE participate in and carry out work within AEPP, as well as what advantages
and disadvantages with these approaches they have identified. This was done in order to let
the managers discuss and analyze AEPP and the sub processes and the related problems, as
well as creating consensus of what needs to be done. The interview findings were validated
during the discussions as well. These discussions were quite deep and contained opinions
whether the perceived problems actually are real and not misunderstandings among the
managers, if the problems are possible to solve and how to solve them et cetera. The
workshop proceeded after these discussions with a presentation of how SCA Tissue handles
project selection which was subsequently followed with discussions of how such an approach
and method could be adjusted, implemented and used at VPT AE.
15. 5
Ten managers from VPT and one from Volvo Technology participated in the first workshop,
while six of these participated during the second workshop.
The purpose with the second workshop was to let the responsible managers at VPT AE
discuss how to design, implement and use a TMET. The focus was in particular upon
identifying appropriate criterions for evaluating project proposals. A compilation of
evaluation criterions recommended by the PPM literature had been distributed in advance for
the managers to review and prepare themselves for the second workshop. This compilation
was then analyzed together during the workshop in order to identify and choose appropriate
criterions. It was also discussed how to implement and use a tool based on these criterions and
potential problems that could be anticipated.
2.2. Validity and reliability of the research design
The concept of validity deals partly with whether a particular research design observes,
identifies or measures what it is supposed to do (Bryman et al., 2007). While the concept of
reliability refers to what degree a research design is not exposed to random influence and if
the research processes can be repeated with the same results. The validity of the research is
perceived as high due to the following reasons:
• The study is based on relevant PPM literature
• AEPP documents received from the local AE Manager at VPT were investigated
• The VPT interview guide was tested during the first interview and improved from here
• The interviews were conducted with centrally involved and responsible managers,
who are considered as key people in AEPP
• As the interviews were recorded and transcribed, it is likely that the interviewees
carefully considered their answers before providing them
• Many empirical findings were validated during the first workshop
• Some of the interviewees at VPT reviewed and corrected parts of draft reports1
• The findings are internally coherent
• The descriptions are relatively thick
• The reliability is considered high
The following factors have negative impact upon the validity
• Only nine interviews were conducted with VPT AE (excluding the supervisor)
• Not every part of each sub system were represented
• Only representatives from one local site were participating
• No Sub System Directors participated in the study
1
This was done by interviewees representing Base Engine, Control Systems and Driveline. The local AE
Manager performed a similar review with corresponding adjustments as well.
16. 6
Further on, the reliability is consider high since it were two researchers (Holmén, 2007)
investigating multiple sources (Remenyi et al., 1998). These sources are:
• Documents and interviews
• Managers from different units, responsibility areas, and levels
• Workshops
Also, contributing to the reliability as well, the research was conducted in a careful and
systematic manner (Bryman et al., 2007).
17. 7
3. REVIEW OF PROJECT PORTFOLIO MANAGEMENT
LITERATURE
In this section a review of ‘state of the art’ and ‘state of the science’ PPM literature is
outlined. The focus is upon why PPM is needed, the existing research, definitions, goals of
PPM, theoretical frameworks, and difficulties with PPM. Section 4 illustrates different tools
and methods to use in PPM and project selection criterions.
3.1. The need for project portfolio management and the existing
research
It is argued that technology development, product development and innovation in general
have become increasingly important due to increasing competition. At the same time, the pace
at which these activities are performed is increasing, while the complexity and risk inherent to
these activities are increasing as well (Schilling, 2008; Tidd et al., 2005). In businesses
characterized by high competition, technology and marketing resources are too scarce to be
allocated to wrong projects (Dawidson, 2006).
Firms engaged in technology and/or product development projects need to identify the right
projects and the right amount of projects to spend their resources on. Hereby avoiding
allocating scarce resources to wrong projects or spreading them too thinly among too many
projects. PPM is an area of practice and theory which addresses this need (Blichfeldt et al.,
2007; Cooper et al., 2001; Dawidson, 2006; Martino, 1995).
However, it is also recognized that PPM approaches are used in other commercial areas of
importance such as marketing, when implementing new work processes and production flows,
when implementing new systems and processes in manufacturing and information systems,
when dealing with environmental issues, and construction projects, et cetera. (Archer et al.,
1999; Blichfeldt et al., 2007).
Early research mainly focused on tools, methods and techniques for evaluating projects and
project portfolios, often in a quite unempirical way – not considering the practical usability of
the tools nor testing them in practice (Dawidson, 2006). There have been over a hundred
studies published in books and articles during more than forty years discussing well over a
100 different techniques used for project evaluation and selection. These techniques have
often had a mathematical nature (such as linear, dynamic and integer programming). However
many of these techniques are not widely used as they are too complex, requires too much
input data, they fail to account for risk and uncertainty in a satisfying manner, they fail to
recognize interrelationships between projects, or are just to difficult to understand and use
(Archer et al., 1999; Dawidson, 2006).
During the last decades, research on PPM has become more and more explorative, now with a
more complete managerial focus, studying how companies are practicing PPM and what the
best practices are (Blichfeldt et al., 2007; Dawidson, 2006). However, the contributions are
judged as limited when it comes to how PPM activities (e.g. decisions, preparations,
discussions) should be arranged, how tools and methods should be used in these activities, as
well as which participants should be involved and how they should be involved. The
18. 8
contributions are not providing a satisfying understanding of important aspects concerning the
above mentioned elements (Dawidson, 2006).
Rather, the contributions made are providing fragmented advices of a normative nature
regarding how to set up PPM, which people to involve and how to organize them (Blichfeldt
et al., 2007; Dawidson, 2006). Here, Blichfeldt et al. (2007) recognizes the work by
Dawidson (2006) as one of a few “valuable exceptions”. Furthermore research on PPM still
needs to be of an explorative nature, contributing to building the knowledge of how and why
companies organise and carry out PPM as they do, as well as what consequences PPM has for
project work (Blichfeldt et al., 2007; Dawidson, 2006). However, the existing research is seen
as important achievements, building knowledge in the area and creating an understanding of
essential factors for successful PPM (Dawidson, 2006).
Some examples of managerial advices given by the common literature outlined by Dawidson
(2006) are:
• It is critical which people are involved and how they are organised
• Organisational functions that should be involved includes sales, marketing,
manufacturing and R&D
• High-level teams should be responsible
• The PPM process should be formal, and should handle all projects in their entirety
• The list of active and new projects should constantly be revised as the PPM process is
dynamic
• There exists no single, general, best way to organise the PPM work – the best way is
situation specific for each company
3.2. Defining project portfolio management
A project portfolio can be said to be the set of projects under development and planned
projects, at any point in time (Archer et al., 1999; Patterson et al., 2005; PDMA [website C]).
The concept PPM is said to include activities such as: evaluating, screening, and prioritizing
ongoing projects and existing project proposals, and in turn selecting the portfolio and
allocating resources. Moreover, PPM is perceived as a dynamic and ongoing process as
projects are accelerated, killed or reprioritized by reallocating resources – hereby adjusting the
portfolio (Blichfeldt et al., 2007; Dawidson, 2006).
It is favorable to clarify the difference between program management and PPM. Program
management aims to integrate and manage a set of related projects in order to achieve benefits
that would not have been possible if the projects were managed independently – hereby
creating more value than the mere sum of the individual projects. The focus is upon
dependencies among projects in order to improve the co-ordination and resource utilization.
PPM, on the other hand, can concern projects that are connected with each other, but the
projects can also be independent of each other (Dawidson, 2006).
19. 9
3.3. The three goals in project portfolio management
The literature emphasizes three different goals of PPM, but first looking upon the connection
between PPM and other processes and activities facilitates the understanding for these goals.
The context in which PPM are seen to exist are illustrated by EIRMA (2002) in Figure 1.
Figure 1: The context for project portfolio management (adapted from EIRMA, 2002)
Strategy development is guided by the firm’s vision and mission, while at the same time,
defining a firm’s vision and mission is a strategic task (Grant, 2005). However, the realisation
or implementation of strategy is first made when resources are allocated and spent. This is the
connection between strategy and PPM. PPM is implementing strategy by choosing and
allocating resources to different projects with guidance from business and product strategy
(Dawidson, 2006). Parts of the PPM literature elaborates in detail upon the connection
between stage-gate processes, project reviews and PPM and how these should be integrated
(Cooper, 2006; Cooper et al., 2002a, 2002b, 2001).
PPM can be said to fundamentally concern resource allocation among projects. However, in
order to perform this successfully, one should recognize that PPM has three, somewhat
conflicting, goals that all have to be addressed to assure maximum gain from PPM (Cooper et
al., 2001; Dawidson, 2006):
• Maximize the value of the portfolio
• Achieving a balanced portfolio
• Achieving a strong link between strategy and the portfolio
Choosing the right projects with respect to the first goal, maximization of value, means
selecting projects in order to maximize short and long-term profitability, return on
investments and probability of success. This goal recognizes that some projects have a better
cost-benefit ratio than others, but also that there can be important independencies between
20. 10
projects. Another important aspect here is that the total value of the portfolio will depend on if
each project is given enough resources or if the resources are spread too thinly between to
many projects.
The goal of achieving a balanced portfolio concerns the need to have an appropriate balance
between various important aspects. Aspects such as the amount of long-term projects
compared with the amount of short-term projects, and high-risk projects versus low-risk
projects. Other important aspects to balance projects concerns different technologies, products
and markets, as well as different project types, from product improvements to fundamental
research. To much focus on short-term projects or projects concerning specific markets would
restrain the organization in the long-term or in other markets.
The last goal, a strong link to strategy, addresses the need to allocate resources in alignment
with the organizational strategy. Aspects to consider here are: to what degree the final project
portfolio fit with strategy; how much the portfolio contributes to the realization of strategy
and achieving the strategic goals; and if the project portfolio reflects the difference in
priorities between different strategic objectives and guidelines.
It can be noted that these goals are somewhat in conflict with each other. Maximizing the
value of the portfolio might for example be done by choosing short-term low-risk projects
focused upon only one or a few markets. This could possibly have negative impact upon the
balance and strategic link goals. Conversely, a portfolio that has a strong link to strategy
might be sacrificing the probability of success aspect, and in turn the value maximization goal
(Cooper, 2006).
3.4. Towards a project portfolio management theory framework
The three goals of PPM are fundamental guidelines that need to be considered in order to
successfully identifying and selecting the right projects. However, other aspects are also of
importance. How the actual work routines are designed and how the work are carried out are
of importance for PPM. Archer et al. (1999) has developed a framework for project portfolio
selection that aims to address such aspects. The framework divides the PPM work into
different stages, while at the same time allowing for flexibility when it comes to what
methods and tools that are used for evaluating and selecting between projects. The framework
is illustrated in Figure 2.
21. 11
Figure 2: Framework for Project Portfolio Selection (Archer et al., 1999)
The main process it self begins with pre-screening of projects and aims to reduce the number
of proposals or to make sure that they have potential. Strategic guidelines help make sure the
projects proposals fit with strategy. Other considerations could be a feasibility analysis and
estimates needed to evaluate the projects later on. In the next stage, individual project
analysis, a more in-depth analysis of the individual projects is performed. Factors considered
here might be the expected return on investment (ROI) or net present value of each project, as
well as the risk and resource requirements associated with each project.
During the following screening stage, projects are now evaluated against pre-defined
criterions which are relevant for the analysis-output from the preceding stage. The ROI
estimates could for example be compared to a minimum-ROI-criterion that has to be
exceeded. The pre-screening and screening stages aim to reduce the amount of projects before
the more extensive and time consuming project evaluations that takes place during the
selection stage.
The actual project portfolio selection begins after the screening stage. Here Archer et al.
(1999) suggests a two-step procedure in order to select the right projects. First the value or
benefit of each individual project should be estimated by the use of some appropriate tool or
method. Appropriate with regard to the nature of the projects and the amount of them. In the
second step, all project interactions, resource limitations, and other constraints should be
included in an optimization of the overall portfolio. These two steps address the maximization
goal stated in the previous section.
The final stage, portfolio adjustment, addresses the two remaining PPM goals. Participators
have to adjust for strategic resource allocation directives on project categories, as well as
adjusting the portfolio in order to achieve an appropriate balance of relevant aspects. Other
judgmental adjustments can be made as well. However, if the portfolio is adjusted too much,
then it might be necessary go back to the selection stage as the optimization with regard to
project interactions and other constraints might not be valid after these adjustments.
22. 12
3.4.1. Framework for organizing project portfolio management
Dawidson (2006) recognizes the partial validity of this framework outlined above: “[t]his
model seems to include all activities of importance for project portfolio management”.
However, he criticizes the framework for assuming that all decisions are made in a linear
logical process, where all projects are dealt with in the same process. His own work shows
that PPM can be organized and carried out trough several (parallel) sub-processes and sub-
processes of sub-processes. Furthermore, the critique also point out how the framework do not
account for how different people are involved in the different stages.
The purpose of Dawidson’s (2006) work was to determine aspects of importance for
organizing PPM. In order to accomplish this, a framework for aspects of importance when
organizing PPM was developed. It was supposed to facilitate the understanding of how PPM
is carried out, structuring empirical data and the following description and analysis of the
same empirical data.
The meaning of ‘organizing’ underlying the framework is: “…the arranging of project
portfolio management activities (e.g. decisions, preparations, discussions) and the manner of
using tools, methods and techniques in these activities as well as the way of involving
organisational participants in the activities. Thus, organising project portfolio management is
seen here as involving three areas: procedural aspects, organisational aspects, and aspects
regarding the use of tools, methods and techniques for supporting the project portfolio
management activities.” (Dawidson, 2006; page 5)
A summary of the framework is illustrated in Figure 3. It is referred to Dawidson (2006) for a
deeper discussion about these aspects displayed in bullet form and why they are of
importance. However, the customer aspect mainly refers to company internal customers –
individuals and organizational units – with different requirements on the process and interests
in the out put.
The requirements different internal customers might have can typically be that the selected
project portfolio supports strategic and tactical objectives or to be informed of what projects
have been or probably will be selected. The information can be needed for making
preparations for supporting the projects and the following implementation activities, including
securing resources in order to be able to make these contributions.
23. 13
Figure 3: Summary of framework for the study of organizing project portfolio management (adapted
from Dawidson, 2006)
PROCEDURAL ASPECTS
• Customers
oRequirements on the process
• Activities
oDiscussions
oPreparations
oDecisions
• Sequence of activities
• Selection process
oGeneral processes
oSub-processes
oRegular updates
• Review process
oGeneral processes
oSub-processes
oRegular updates
• Connection with company-internal
processes
oIndividual project processes
oStrategy process
oOther internal processes
THE USE OF TOOLS AND
METHODS
• The combination of tools and
methods
oRequirements to be fulfilled
oAdaptations of the tools and
methods
• Sequence of application to the
process
• Tools’ and methods’ use in the
process:
oDiscussions
oPreparations
oDecisions
ORGANIZATIONAL ASPECTS
• Organizational setting
• Participants
oIndividuals
oGroup/Forums
• Connection with the process
• Type of activity connected with:
oDiscussions
oPreparations
oDecisions
24. 14
3.5. Complexities involved in and problems due to poor project
portfolio management
PPM is said to be a complex managerial task due to factors such as (Dawidson, 2006;
referring to Archer et al., 1996):
• Multiple and often conflicting objectives
• Difficulties of determining trade-offs among different criteria
• Qualitative and quantitative measures must sometimes be compared
• Interdependences among projects
• Multiple constraints for the project portfolio to take into consideration
• The number of possible combinations of projects can be enormous
• Projects at different stages of maturity are compared
• Usually several individuals with different perceptions involved in the decisions
This can be contrasted with what is said to be some of the consequences if having no PPM or
only poor PPM. According to Tidd et al. (2005) and Cooper et al. (2001), such consequences
are: resources spread to thinly; negative impacts on costs and the ability to meet deadline;
high failure rates; success of unimportant projects instead of important ones; projects entering
the portfolio due to politics, emotions or other factors; increased time to market and weak
market impact; failure to support strategy.
25. 15
4. METHODS AND TOOLS USED IN PROJECT PORTFOLIO
MANAGEMENT
There are an extensive amount of different methods, tools and techniques (as well as variants
and adaptations of them) developed for assisting managers with PPM (Archer et al., 1999;
Cooper et al. 2001; Dawidson, 2006; Martino, 1995). There are also many approaches for
categorizing these methods and tools. Schilling (2008) uses a two-dimensional categorization,
from informal to highly structured methods, and from entirely qualitative to strictly
quantitative methods. Martino (1995) uses a more specific grouping of methods and tools:
Ranking; Economic; Decision Theory; Portfolio Optimization; Simulation; Cognitive
Modelling; Cluster Analysis; and Ad hoc methods. Dawidson (2006) and Cooper et al. (2001)
categorizes methods and tools according to which of the three PPM goals they are applied to
address – value maximization, achieving balance, and achieving a strong link to strategy.
There seems to be no consequent distinction made in the PPM literature regarding the
difference between methods, tools, and techniques. However, it is suggested that techniques
are more practical focused than methods, while tools seems to be more specific and might be
a part of a method or a technique (Dawidson, 2006).
Methods and tools discussed in the subsequent sections are currently in use within VPT AE or
have been identified as particularly interesting for them, as well as relevant for the later
sections in this report. However, other tools, models and theories in use and/or recommended
by the literature for R&D project selection are discussed in Appendix II. These are indeed
perceived as something for VPT AE to consider.
It is referred to Cooper et al. (2001) and Martino (1995) for a more extensive and detailed
review of methods and tools. Martino’s review has a more mathematical and programming
focus; however, the methods are not more complex than that they can be used by support from
ordinary spreadsheet software such as Excel.
Research indicates that the best performers at PPM uses more tools per business compared to
the poor performers. The poor performers relay more often on financial methods and less
often on strategy methods, then top performers do. It is recommended that firms use three or
more tools and methods (Cooper et al., 2001).
4.1. Methods and tools for value maximization
Common for the value maximization tools are that they produce rank-ordered list of projects.
However, a large difficulty is the amount of data required as input and the often low validity
of the data, and in turn, the output from the tools – particularly from the quantitative-financial
ones (Cooper et al., 2001). This is one reason for why the financial models have been
criticised. On the other hand, Boer (2004) state that it is not the financial models that should
be criticised but rather the “stupidity” of using them incorrectly. In his book he argues that
financial models in the form of net present value and option analysis (real options) should be
used for R&D strategy and project selection (see Appendix.II.1.). His book encloses a CD-
ROM to assist the user when applying financial models to project selection.
26. 16
4.1.1. Scoring models
Scoring models belongs to the most recommended tools for value maximization and PPM in
general (Cooper, 2006; Cooper et al., 2001; Davis, 2001; EIRMA, 2002). They consist of
various main criterions and sub criterions which are used for evaluating projects along
different aspects. Each project is rated on each main and sub criterion, wherefrom a total score
can be calculated for each project, which in turn can be used for ranking the projects. The
criterions should be based on known success factors that can separate winners from losers. Or
differently stated; the criterions should be predictors of a future project success or failure. If
strategic criterions are used, then the scoring model help achieve alignment of the project
portfolio with strategy as well.
Besides providing a ranking list, each project score can also be compared to a predefined
minimum score. Whereupon the project is dismissed if the total project score is lower than the
limit, or has a too low rating on one or more specific criterions that have been judge as
especially important to have a high rating (Cooper et al., 2001). Figure 4 illustrates main
criterions recommenced for R&D projects (Cooper, 2006; Cooper et al., 2001) and Product
development projects (Cooper et al., 2001).
Research & Development Product Development
Business strategy fit Strategic alignment and importance
Strategic Leverage Product and competitive advantage
Probability of technical success Market attractiveness
Probability of commercial success Leverage core competencies
Reward Technical feasibility
Financial reward
Figure 4: Project evaluation and selection criterions for R&D and product development (Cooper, 2006;
Cooper et al., 2001)
Anchored rating scale phrases
An especially important element of scoring models is the rating scales used for the rating
projects along the different criterions. These rating scales usually consist of four or five steps
with numbers representing the different ratings, for example 0, 4, 7, 10 or 1, 2, 3, 4, 5.
However, it is generally recommended that that the rating scales should be complemented
with corresponding anchored scale phrases2
. This means that each rating number in advance
should correspond to an anchored scale phrase, which is supposed to capture what it takes for
a project to be given that rating on that criterion. If an anchored scale phrase is the most
accurately description of a project compared to the other phrases that belongs to that criterion,
then the project is rated with that phrase’s corresponding rating number.
The anchored scale phrases provide a standardized basis for how multiple participators can
rate projects easily together. As such, it is a simple and robust basis for obtaining multiple
ratings easily and reliably from multiple persons that make evaluations at different times.
2
These kinds of rating scales are also called Likert scales (Bryman et al, 2007).
27. 17
Anchored scale phrases also increase the structuring of the exercise (Cooper, 2006; Cooper et
al., 2001; Davis et al., 2001; EIRMA, 2002).
Figure 5 illustrates sub criterions with anchored scale phrases for the main criterion
‘Probability of technical success’ (Cooper et al., 2001). The following five bullets are
recommended anchored phrases to the sub criterion ‘Competences and skills’, which is
another recommended alternative sub criterion for the ‘Probability of technical success’ main
criterion (Davis et al., 2001):
1. This has never been done before
2. This is new to us; but it is not new to the world
3. This is not new to us; but it is not one of our present competences
4. It is a good fit with our core competencies; but we have not done a project like this
5. We are experts and have done this before
Anchored scale phrases
Criterions 0 4 7 10
Size of
technical gap
Large gulf
between current
practice and
objective; must
invent new science
“Order of
magnitude”
change proposed
Step change short
of “order of
magnitude”
Incremental
improvement;
more engineering
focus
Program
complexity
Difficult to define;
many hurdles
Easy to define;
many hurdles
A challenge; but
do-able
Straight-forward
Technology
skill base
Technology new
to the company
Some R&D
experience but
probably
insufficient
Selectively
practiced in
company
Widely Practiced
in company
Availability of
people and
resources
No appropriate
people / facilities;
must hire / build
Acknowledged
shortage in key
areas
Resources are
available; but in
demand; must
plan in advance
People / Facilities
immediately
available
Figure 5: Anchored scale phrases for sub criterions for the Probability of technical success criterion
(adapted from Cooper et al., 2001)
Weightings
It is often recommended to weight the main and sub criterions in order to let their relative
importance have impact on the project scores and the final ranking list (Brenner, 1994;
Cooper et al., 2001; Davis et al., 2001; EIRMA, 2002). The determination of weights can be
done with help of the Delphi method, simple opinion polls, or trough the use of relevant
research results (Cooper et al., 2001). Brenner (1994) explains a step by step procedure for
developing a scoring model, he recommends using pairwise comparisons (see section 4.1.2.)
for determining the weightings. However, Brenner’s pairwise comparisons tool uses a five
degree rating scale for conducting the pairwise comparisons. This weighting procedure also
28. 18
complements the pairwise tool afterwards with discussions of whether the output seems
plausible or need adjustment before the weightings are settled.
Cooper et al. (2001) discusses how different set of weightings can be used for different set of
project types, such as sustaining projects, new business projects and must-do projects.
However it is recommended to not compare project scores that have been received trough the
use of different set of weightings, as different set of weightings means different scoring
models which in turn imply less comparability.
Benefits from using scoring models
Scoring models have several strengths and there are many benefits with using one (Cooper et
al., 2001). Scoring models addresses multiple goals, as they contribute to both maximizing the
value of the project portfolio and achieving a strong link and alignment between strategy and
the project portfolio. Also, complex decisions of prioritization are reduced to answering a
manageable number of specific questions.
A major strength is the process itself that people go through as they discuss ratings on
different criterions and different rankings on projects since this might generate:
• learning
• consensus
And reveal or identify:
• strengths and weaknesses of project proposals
• different opinions
• critical areas that have been ignored
• critical information gaps
• actions or improvements that needs to be undertaken
Scoring models can be compared to a meeting agenda, they are a good foundation to facilitate
systematic, constructive and comprehensive discussions; more like a decision support tool
than a decision tool per se. There will usually be important aspects and characteristics of
various projects not captured by the specific tool design that need to be considered before
selecting the project portfolio (Cooper et al., 2001).
Managerial concerns
Managerial concerns regarding the use of scoring models include the following (Cooper et al.,
2001). First, the result from scoring models should not automatically be believed. Sometimes
people tend to exaggerate the precision that scoring models have, creating an imaginary
precision. Second, criterions sometimes overlap or correlate with each other, in which case
projects that are scoring high on specific criterions will automatically score high on other
criterions as well. Third, scoring models do not assure that the resulting list achieves the
highest possible scores for a given total R&D expenditure, if not explicitly accounted for. For
example, large projects tend to score higher then smaller projects. But if the ranking list
would consists of project scores divided by R&D costs (score/cost), then smaller projects
might enter the project portfolio instead of larger ones due to better resource efficiency.
29. 19
Furthermore, it have also been discovered that scoring models tend to produce ranking lists
where many of the individual project scores have values that are very close to the mean value
of the total set – many of the project scores clusters around the same score that is (Cooper et
al., 2001; EIRMA, 2002). One way to solve this could be to, instead of rating projects
individually on each criterion, rank-order the entire set of projects on each criterion – and then
distribute ratings with respect to this ranking order. For example, if project A, B and C were
rank-ordered in the following way on a specific criterion – C, A, B – then C might be given
the rating 3, A rating 2, and B rating 1, on that criterion (Cooper et al., 2001).
4.1.2. Pairwise comparisons and analytical hierarchy procedures
Pairwise comparisons (PWC) are a method where all individual project proposals are
compared pairwise with every other project proposal (Martino, 1995). If project B is assessed
as superior to project A, then project B are given one point. Applying this method to a set of
N projects will demand for N (N – 1) / 2 comparisons. This has also been referred to as global
comparisons.
Figure 6 shows a PWC matrix which can be realized with Excel for example. The left hand
table indicates that Project A is superior to Project D and E, whereas Project C is superior to
all other projects, while Project E is inferior to all of the other. The comparisons points are
entered into the right hand matrix; whereupon the points are summed row-wise in order to
produce a ranking list of the project set.
Figure 6: Project comparisons (to the left) and a corresponding pairwise comparisons matrix
Another possibility is to also assess “how much better” a specific project proposal is
compared to another proposal with the use of an anchored scale (slightly better, much better,
very much better) with corresponding points (1, 2, 3) (Brenner, 1994; Martino, 1995).
Yet another, simplified and faster PWC method is to identify the best and the worst project
which gets 100 points and 0 points respectively. Each other project is then compared to these
two reference projects and receives a score between 0 and 100 which reflects their suitability
relatively to the two reference projects (Martino, 1995).
A more advanced version of PWC is the Analytical Hierarchy Procedure (AHP). In this
method, each project is pairwised compared to each other project on a number of weighted
criterions (see Figure 7). One PWC matrix is used for each criterion. All or some of the
criterions can in turn have sub criterions with their own PWC matrixes, where that output are
00000E
11000D
41111C
31101B
21100A
CountEDCBAProjects
E >
ED >
A, B, D, EC >
A, D, EB >
D, EA >
Projects
30. 20
used as input to the matrix one level above. The points from each matrix are weighted and
added in order to produce a ranking list of the projects (Martino, 1995).
Figure 7: Three AHP matrixes for three different criterions and weights
4.1.3. Project evaluation and selection criterions
Several authors are recommending firms engaged in R&D and product development project
selection activities to use project selection criterions in various ways. From guidelines and
questions to answer during screening activities to full size scoring model tools to be used
during the portfolio selection. However, common to these authors, where perhaps Martino
(1995) is a differential example, is that they provide very limited, if any at all, discussions
upon or justifications to why specific criterions are more appropriate than others. Also, what a
specific criterion actually means or refers to are often omitted. It seems as some kind of
education in strategic management of technology and innovation (or equivalent) or extensive
hands-on experience in these matters is presumed of the reader. However, when there are
anchored scale phrases accompanying the criterions than these usually provide an indirect but
quite sufficient explanation of what the criterions are meant to evaluate.
The criterions for R&D project selection recommended by Cooper and colleagues (Cooper,
2006; Cooper et al., 2001) are justified by declaring them as elements of one of the best
scoring models they had seen during their research, combined with validations of the model’s
reliability from the company who developed used it. On the other hand, the criterions
recommended for product development projects are said to be based on elements taken from
several leading firms, combined with extensive research into what the critical success factors
for new products are (Cooper et al., 2001) (see Figure 4).
The criterions, with corresponding anchored scale phrases, recommended by Davis et al.
(2001) are output from an IRI3
project, developing a scoring model together with member
companies that could be applied to most industrial R&D situations; or at least a platform that
easily could be modified by individual companies. Sheasley (2000) seems to be
3
Industrial Research Institute; members including BP, GE, GM, IBM, Intel, NASA, Nokia, Toyota;
http://www.iriinc.org/
Project Rankings
Probability of
technical success
Strategic fit Probability of
commercial success
Weight 0.5 Weight 0.3 Weight 0.2
00000E
11000D
41111C
31101B
21100A
C
o
u
n
t
EDCBAProject
00000E
11000D
41111C
31101B
21100A
C
o
u
n
t
EDCBAProject
00000E
11000D
41111C
31101B
21100A
C
o
u
n
t
EDCBAProject
31. 21
recommending his suggested criterions from experience as a technical manager in the
speciality-material industry.
A compilation of R&D project selection and PPM selection criterions found in the literature
can be found in Appendix III. The main and sub criterions recommended by different authors
have been organized into groups, labelled with the main criterions for R&D project selection
recommended by Cooper (2006). A reduced version of this compilation is illustrated in Figure
8 and Figure 9. The difference is that Figure 8 and Figure 9 do not show which authors that
have recommended what criterions. Also, criterions that have been judged as equivalent have
been removed to some extent. The criterions listed should be interpreted on the basis of what
group label they belong to.
However, this grouping of the main and sub criterions found in the literature have been done
on the basis of the author’s own judgment. Therefore, a few criterions have been placed in
more than one group, mainly the two probability of success groups; while a few criterions
belongs to an group with a title that might seem contradictive with respect to the criteria (for
example, cost belonging to the reward group as cost have negative impact upon the reward).
Regarding recommendations for screening questions designed for product development
projects, it is referred to Schilling (2008).
Brenner (1994) discusses a step by step approach for managers to use when developing their
own criterions and weighting them according to their importance. The approach draws upon
the pairwise comparison tool (section 4.1.2.) for selecting the right criterions according to
their importance (ranking criterions instead of projects). The first step is to generate criterions
in workshops with help from questions used to activate and energize the discussions:
• What are the factors that have made your projects successful?
• What are the characteristics of the projects that have helped your career?
• What criteria do you use when choosing a project?
• What makes a project good?
• What do you try to avoid in a project?
• When you think about a project, what characteristics do you consider?
• Where does your organization tend to be successful?
Recall from section 4.1.1. that criterions should be predictors of future project success or
failure.
Business Strategy Fit Strategic Benefits/Leverage
• Strategy fit
• Strategy impact (importance)
• Resource availability
• Drawing upon core competencies
• Reducing a gap or weakness in the
business plan or strategic position
• Attractive for a Real Options
approach
• Targeting specific contracts
• Proprietary position (intellectual
property matters)
• Platform for growth
• Durability (technical and marketing)
• Potential for future improvements
of the technology
• Synergy with corporate units
• Impact on other business activities
Figure 8: Strategic evaluation and selection criterions
32. 22
Probability of Technical Success
• Technical Gap
• Technical or Project Complexity
• Technological skill base
• Availability of people and facilities
• Existence of a product champion
• Degree of internal commitment
• Degree of internal competition for
resources
• Source of project proposal
• Proprietary position
• Access to external technology
• Manufacturing capability
• Soundness of ideas
• Level of understanding of underlying
principles
• Magnitude of potential advance in
performance
• Understanding of structure and/or
property relationships
• Understanding of correlation of
properties and benefits
• Flexibility of technical design
• Number of benefits that could be
enhanced
Probability of Commercial Success
• Market need / maturity / size / share
• Sales volume
• Commercial applications
development skills
• Distribution channels
• Ability to exploit Market / Brand /
Image strengths
• Product life cycle
• Raw materials supply
• Regulatory and political impact
• Environment, health, and safety
aspects and regulations
• Importance of benefits in cited
markets
• Understanding of correlation of
properties and benefits
• Strength of differentiation
performance
• Understanding of market trends /
drivers / value chain
• Commercial assumptions
• Market participants and structure
• Competitive intensity
• Customer strengths (business to
business)
Reward
• Contribution to profitability, cash
flow, revenue
• Return on investment
• Payback period
• Cost-benefit
• Development time
• Development cost
• Time to commercial start-up
• Synergies with ongoing projects or
other project proposals
• Competitive advantage
• Growth opportunity
• Knowledge accumulation potential
Figure 9: Probability of technical and commercial success and reward evaluation and selection criterions
33. 23
4.2. Methods and tools for achieving a balanced portfolio
One of the three PPM goals is to achieve a balanced project portfolio. Tools and methods used
for balancing project portfolios include bubble charts, pie charts, and histograms. These are
all producing visualisations used for over viewing the project portfolio and potential projects
not yet included, as well as initiating discussions whether what constitutes the right project
portfolio with regard to important aspects to balance (Cooper et al., 2001; Roussel et al.,
1991).
4.2.1. Bubble charts
Bubble charts, or bubble diagrams, basically consists of two axes representing two
dimensions (or parameters) of project characteristics that have been judged as important for
balancing the project portfolio and selecting projects proposals. The most popular dimension
combination is risk and reward, where reward represents anticipated benefits from projects,
whereas risk represent probability of technical and/or commercial success (Cooper et al.,
2001). The projects are displayed along the two axes as circles – bubbles that is – depending
on their assessed characteristics with respect to the axes-dimensions – how much risk and
reward that is associated with each project (see Figure 10).
The exact design of these circles or bubbles can be varied to a very large extent in order to
display particular information for each project proposal. For example, the size of the bubble
could represent the project cost, project risk, development time, time to market, et cetera.
Similarly, the colour and the pattern inside the circle edge can be used to display, besides the
already mentioned variables, technology type, product category, market or segment
addressed, market newness, et cetera.
Figure 10: Bubble chart with risk and reward dimensions
Risk
Reward
100%
100%
0%
0% (high risk)
34. 24
There are a large amount of dimension pairs and individual dimensions that have been
declared as more or less suitable for bubble charts. The following list provides examples of
dimensions to balance (Cooper et al., 2001; Roussel et al., 1991):
• Fit with strategy and/or strategic importance
• Innovativeness
• Durability of competitive advantage
• Potential reward
• Competitive impact of technologies (base, key, pacing, embryonic) (see Appendix II)
• Probability of success / risk
• Cost
• Time to completion (long-term / short-term)
• Markets and markets segments
• Product categories / lines
• Project types (new technology, technology improvements/extensions, cost reductions,
fundamental research, platforms)
Examples of popular dimension combinations are illustrated Figure 11.
Popular bubble chart dimension combinations
Risk Reward
Technical newness
(Known to the company)
(New to the company)
(New to the world)
Market newness
(Known to the company)
(New to the company)
(New to the world)
Ease to do Attractiveness
Strength Attractiveness
Cost Timing
Strategic focus or fit Benefit
Cost Benefit
Technological competitive
position or strength
Technological maturity
Figure 11: Example of bubble chart dimension combinations (Cooper et al., 2001)
4.2.2. Pie charts
Pie charts are ordinary statistical circle diagrams used for displaying different category
percentages (see Figure 12). They are suitable for visualising the percentages of different
project types that constitute the project portfolio, usually as percentages of the portfolio
budget. Such project categories could be: fundamental research; platform programs; new
product developments; updates and extensions; and maintenance. Other categories to balance
could be different markets or customer types which the projects are aimed at (Cooper et al.,
2001).
35. 25
Figure 12: Pie chart displaying the resource balance between different project types
4.3. Methods and tools for achieving a strong link between strategy
and the portfolio
Tools for aligning the project portfolio with strategy includes roadmaps, sub portfolios, and
scoring models that build in strategic criterions (Cooper et al., 2001).
4.3.1. Roadmaps
Roadmaps can be said to illustrate a management group’s view of how to get where they want
to go or how to achieve desired objectives – a strategy planning and implementation tool.
Product roadmaps define products and product launches in a timeline, and also how product
lines will evolve and future generations. Technology roadmaps can be derived from product
roadmaps and show how to get there. That is, illustrating technologies, technology projects
and technological competences that are needed for implementing the product plans in the
product roadmaps. Selecting projects with roadmap support is one approach for increasing the
fit between strategy and the project portfolio (Cooper et al., 2001). For more on roadmaps and
technology roadmaps see for example Albright et al. (2003), Faijerson et al. (2008),
McMillan (2003), Phaal et al. (2003), and Whalen (2007).
4.3.2. Sub project portfolios
Sub project portfolios are basically a formal split of the project portfolio budget into sub
budgets whose proportions are decided by reviewing the business, product or technology
strategy. In this way, the project portfolio is partly aligned with strategy as the resource
allocation to different areas is predetermined with respect to strategy. Relevant dimensions to
consider for a sub project portfolio split are (Cooper et al., 2001):
36. 26
Strategic goals – projects might aim at different strategic goals
Product lines – projects might aim at different product lines
Market segments – projects might aim at different markets
Technology types – projects might draw upon different technologies; technologies might be in
different states, e.g. base, key pacing, and embryonic (see Appendix II.3.).
Project types – new product development, platforms, fundamental research, improvements.
Technology newness versus market newness – technology known to the company, new to the
company or new to the world; versus market known to the company, new to the company or
new to the world
Geography – projects might aim for different geographic markets.
Pie charts and bubble charts can be effective tools for visualising how resources are or should
be distributed between the sub portfolios (see section 4.2.2.).
37. 27
5. INVESTIGATION OF SCA TISSUE AND VOLVO AERO
In this chapter follows a description of, for VPT AE, relevant methods and learning’s from
investigations of other appropriate firms.
5.1. SCA Tissue’s project selection process and methods
SCA is a Swedish corporation with 50 000 employees around the world. They have
production in about 40 countries and operations and sales in 90 countries. SCA is divided into
four business areas: Personal Care; Tissue; Packaging; and Forest Products.
At SCA Tissue, the Category department – product development and marketing – was
previously, within the department, divided into units with focus on consumers and Away
From Home (AFH) customers (organizations) respectively. Recently, integration of these two
parts has been initiated. The following description of how SCA Tissue handles project
selection challenges is an approach that was just to be implemented shortly after the
interviews were held. However, the approach draws on the best practises from the previous
consumer and AFH approaches. The approach have also been presented and anchored
internally.
When SCA Tissue was to develop their new project proposal evaluation and prioritization
method, the following goals or requirements for the method was determined:
• Simple process with enough flexibility
• Objective project screening filters
• Well known parameters (criterions)
• Support and encourage creativity and innovation
• Create an appropriate environment and attitudes
• Insight driven (understanding the customer and the technology)
The requirements are more or less self explaining. However, the requirement of well know
parameters captures the desire that the method should be based on criterions and concepts that
was already known and understood by the ones that were going to be involved in the project
selection activities.
The project selection method is in fact a project selection process, fundamentally very similar
to the project selection process proposed by Archer et al. (1999) which was discussed in
section 3.4. SCA Tissue themselves perceive their method as a Funnel Process with five
phases. The phases in order are:
1. Opportunity Phase,
2. Idea Phase,
3. Concept and Business Case Development;
4. Product Development Project and Product Launch Project;
5. Market Development / Product Launch.
Moreover, there are four filters which separate the five phases by screening and dismissing
ideas and project proposals before the next phases is entered. It is perceived as a Funnel
38. 28
Process as the amount of opportunities identified in the first phase responds to a much larger
amount than the products that are entering the markets during and after phase five.
This selection process is running in parallel with the strategy process and there is a tight and
extensive communication between these two processes. The participants in both of the
processes needs to be aware of what developments, advancements, discoveries, decisions etc.
have been made in the other process. An example of this is that the filters (based on
criterions) between the phases changes to some extent if the strategy changes. Also the
weightings of different criterions are changed in order to align the project selection with the
new business strategy and priorities.
Opportunity Phase
The first phase, the opportunity phase, involves finding new opportunities by external analysis
and gathering information about customers and markets, while letting strategy point out the
direction and where to focus. This creates insights about customers and consumers,
technology, and competitors. The phase ends with an insight and opportunity filter which
screens the insights and opportunities that have been identified against pre-defined criterions
or evaluation dimensions. These are:
• Strategic fit and other strategic drivers
• Market potential – size and growth potential
The insights and opportunities that are perceived as most appropriate and having the highest
potential with respect to these criterions enters the second phase, while the rest are placed in
an idea bank.
Idea Phase
Insights and opportunities that enters the second phase, the idea phase, are used as seeds from
which ideas about solutions or marketing offerings are created. These ideas are categorized
according to from which source they were generated. The first source is formal idea
generation workshops within the Category units. These workshops resemble brainstorm
sessions. Another source is internal bottom-up ideas from Category and the rest of the firm.
Belonging to the third category are ideas which can be described as cost saving activities for
existing products. The forth category consist of externally generated ideas from customers,
suppliers, inventors and others.
The end filter for idea screening is based on the same criterions as the opportunity filter.
However, as the ideas are more developed and extensive, compared to the insights and
opportunities, more criterions are added in order to structure and evaluate this additional
information and knowledge. The idea filter consists of the following criterions:
• Strategic fit and other strategic drivers
• Market potential – size and growth potential
• Customer fit and attractiveness
• Implementation complexity (done before or new to the company, need new resources
and capabilities?)
39. 29
Concept and Business Case Development
After the idea phase, the last and most extensive phase before product development follows.
Here, concepts and business cases are developed. A concept includes detailed descriptions
about product and production prototypes. Research has been made regarding what materials to
use as well as what production technology to use. Appropriate distribution channels are also
described and market implementation tactics have been drawn up, including who the customer
are, how to reach them and what to offer them. A business case has the same content as a
concept, but estimations of investments costs and profits as well as time to market have also
been performed. The end filter for this phase consists of a complete scoring model which will
be described next.
5.1.1. SCA Tissue’s scoring model
The scoring model that is used by the Category units evaluates and rank-orders the business
cases (the project proposals) developed during the third funnel phase. The model is mainly
used as a discussion foundation to direct the discussions in the forums where decisions are
made and to assure that the right factors and aspects are addressed and discussed. The
benefits, according to SCA Tissue, are that it becomes obvious during the discussions that
there exist weaknesses and gaps within the different project proposals that are discussed. It
becomes hard to hide the weaknesses and gaps. Furthermore, this approach also helps
avoiding personal liking of projects, pet projects and even opinions from family members.
The main criterions of the scoring model are divided into two categories – reward and risk –
and are illustrated in Figure 13. Some of the criterions were used earlier in the first and
second phase. The three first criterions in the reward category are semantically the same as in
the idea filter. However, the aspects meant to be captured by the Implementation complexity
criteria within the idea filter is now captured more or less by all the risk category criterions.
All the main criterions have corresponding sub criterions as indicated in Figure 13, however,
SCA Tissue did not reveal all of these sub criterions. The main criterions are also weighted in
order to account for their varying importance and what the strategic directives and focus
implies at the time the scoring model is used.
SSCCAA TTiissssuuee’’ss ssccoorriinngg mmooddeell ccrriitteerriioonnss
RREEWWAARRDD
• Strategic alignment and
importance
• Fit; Importance; Impact
• Market attractiveness
• Size and growth; Margin;
Competitive situation; Patentability
• Customer attractiveness/fit
• Contribution
• Spillover effects (to other
product areas)
RRIISSKK
• Commercial risk
• Technical risk
• Development, technology and
marketing experience
• Project cost, investment and
time to market
Figure 13: SCA Tissue's scoring model criterions, divided into risk and reward categories
40. 30
The sub criterions are rated on a four degree scale – were the ratings can be 0, 4, 7 and 10 –
with corresponding anchored scale phrases (see section 4.1.1.). The ratings of main criterions
are not just the average rating of corresponding sub criterions. Main criterions are given their
own ratings based on new assessments and evaluations. These ratings are of course
significantly influenced by the discussions about and ratings on their sub criterions, but these
main ratings also consider other aspects and knowledge that was not captured by the sub
criterions.
When all the main criterions have been rated for all project proposals, the scores for each
project on the reward and risk category respectively are calculated. The two scores for each
project are then transformed into percentages of the maximum score that could be obtained in
each of the reward and risk categories. These percentages are used to plot each project in a
Risk-Reward bubble chart as illustrated in Figure 14.
Figure 14: Adaptation of SCA Tissue's bubble chart
5.1.2. Using the scoring model and the result
It is responsible people from the Category department’s sub departments – product
development, consumer marketing, and marketing towards organizations – who use the
scoring model together in cross-functional groups. However, four different groups or
constellations are responsible for one of the four different product categories within Category.
Each product category group handles up to 15 project proposals with the scoring model.
It should be noted that the project scores are not formally compared between the product
categories, for two reasons. First, it is believed that different groups would score the same set
of projects differently, partly because difference in rating scale treatment. Second, there is a
fear that such a comparisons between product categories would increase the final scores as
there are various individual benefits from having projects from one owns product category
launched. For example, being the originator of a large project or being a project leader (or
involved in some other way) for a large project might benefit the individual carrier or provide
other benefits.
Risk
Reward
100%
100%
0%
0% (high risk)
41. 31
Instead, the people that were involved when applying the scoring model from the four product
categories gets to present and motivate their best project proposals for a higher-level forum of
managers that will decide how resources will be allocated between product categories and to
which projects. The foundation that is created from the discussions when using the scoring
model is now an advantage when projects must be justified to resource providers. As the
participators in the scoring activities have systematically discussed important aspects of the
project proposals, identified strengths and weakness and also how to exploit and avoid these,
they now have a proper foundation to lean on when arguing for their project proposals.
Of course, the other groups will also be able to provide well-worked out, thought trough
arguments. With respect to this, one can still expect hard competition for the resources, but
the probability that the most appropriate projects are selected should be increased.
Regarding the bubble charts that are constructed from the project scorings, these are used like
executive summaries which make it easier to explain and illustrate why one have chosen or
would like to choose some projects instead of others – why they are more appropriate.
5.2. Learning from Volvo Aero Corporation
Volvo Aero Corporation (VAC) is a Swedish corporation with about 3500 employees around
the world. VAC has offices in Norway, the USA and their headquarters are in Sweden. In
total they have five main customers such as Rolls-Royce, Pratt & Whitney, and General
Electric. VAC’s business area is to develop and manufacture high-technology components for
aircraft, rocket and gas turbine engines, in cooperation with the world's leading engine
manufacturers [website D].
5.2.1. The current project selection approach at VAC
VAC faces similar kinds of problems as VPT. VAC’s approach is mainly built upon processes
mainly involving discussions concerning ideas and project proposals. The company has one
large process, which during the spring includes operational planning and strategy processes
which results in a business plan, strategic prioritizes, a product plan, and a development plan.
In the autumn these plans are broken down to a unit level.
5.2.2. Previous project selection methods and tools used within VAC
Some units at VAC have experience of using various kinds of tools for project generation,
evaluation and selection. During the 90ies, they applied tools taken from literature about R&D
strategy, PPM and project selection (Roussel, 1991). These tools included, among other,
bubble charts (e.g. technology newness and market newness axes) and technology
categorization (see Appendix II.3.). The tools contributed with value as they brought new
perspectives, analysis approaches and created a good overview. Basically, the tools took their
R&D planning and selection activities and discussions to a higher level.
The tools helped them during the first couple of years, analysing their current position and
where they needed to go. However, the output from and conclusions and insights generated
42. 32
with help from the tools did not change much after these first years and therefore did not
contribute with enough value compared to the time and efforts needed for using the tools.
Two reasons for why the tools demanded too much time have been identified. First, the tools
were based on and included relatively unfamiliar concepts and definitions which meanings
had to be relearned each year as they were not used frequently enough. Second, the tools were
applied from scratch each year instead of updating the output from the last year.
Later on during the current decade, some units at VAC used Quality Function Deployment
(QFD) as a method to identify important technology areas to work with and in turn generating
and selecting projects. QFD is a method that generally is used in order to translate customer
requirements into development needs, and encourages communication between engineering,
production and marketing (Tidd et al., 2005).
The original method is comprehensive; hence VAC designed their own QFD-method4
on the
basis of their strategic process. The method was based on three different perspectives;
Probability of success, Importance, and Bearing. Probability of success concerned, among
other, short-term and long-term aspects. Importance involved aspects like potential reward
and turnover. Bearing concerned whether the projects and their technology deliverables would
function within the products and how long their usefulness would last.
These three aspects were assessed and compared together by a cross-functional group
consisting of people from the market and engineering departments. The method was based on
that the members of the cross-functional group had ideas and a lot of knowledge in the area.
VAC used the method in order to:
• To make a useful ranking to reach decisions
• To get a better understanding of the market
• To make it easier to describe how the decisions were made
• Get a higher motivation to start a project
With this tool, the cross-functional group could identify which products their efforts should
focus upon and which technologies they had potential to leverage in order to make
contributions. The products and technologies to work with were visualized in histograms in
order to create an overview and facilitate discussions. After having identified which
technologies to work with in order to contribute to specific products, then they started to
develop project proposals for achieving the objectives.
VAC identified a couple of issues and drawbacks with this tool and approach. First, the
procedure took a lot of time, as it usually were about ten people involved, spending 8
meetings, 2 hours long each. The second drawback was that some times the tool only
confirmed what they already knew. This was mentioned as reasons for why they stopped
using the tool.
To conclude, the tool was similar to a scoring model as different evaluation criterions were
used for identifying and ranking products, areas and technologies to work with. This method
developed by VAC involved a significantly more complex project rating procedure as well as
a more complex algorithm for producing the ranking list, compared to SCA Tissue’s approach
4
This method was specifically designed by a smaller unit at VAC, including Ulf Högman
43. 33
and what the current PPM literature recommends. However, the main difference is that VAC
used this “scoring model” for identifying and selecting areas to work with (which
technologies for which markets), and when this was done, starting to develop project
proposals.
5.3. Commenting the SCA Tissue and VAC cases
SCA Tissue’s project selection process appears to be thoroughly thought trough. They begin
with generating as much “insights and opportunities” as possible. These elements are
thereafter systematically reduced in number while simultaneously gradually evolving them
into entire product and market development proposals. These activities are guided by business
strategy from beginning to the end.
Two things are particularly clear. First, this approach has much similarity with existing
literature recommendations, particularly with what have been written by Archer et al. (1999)
and Cooper et al. (2001). Secondly, the approach appears to be simple, efficient and flexible.
It does not introduce complex structures or procedures, nor does it introduce time demanding
efforts not generally associated with new product development planning activities.
It is believable that SCA Tissue’s project proposals are of a more, from each other,
independent nature as they in the end are complete product development projects. For VPT
AE on the other hand (as will be shown later), each of their project proposals are just one of
many other proposals which aim to create desired features and properties in one or several
future products. This is likely one factor, among others (e.g. product complexity), making
such a simple project selection approach insufficient for VPT AE.
VAC’s approach on the other hand, here the empirical data is unfortunately insufficient for
making a satisfying description of either their current or previous approaches. However, they
have previously benefited from the use of various project selection tools, but these were not
implemented in a sustainable manner.
There are some particularly relevant learnings for VPT AE from these cases. It is
advantageous if the concepts and criterions making up methods and tools to be used are
familiar to and understood by the users. For SCA Tissue, this was a requirement from the
beginning. For VAC, the lack of such understanding was one factor appearing to have
contributed to the abandoning of one or more tools. Also, new tools can introduce new and
useful perspectives and way of thinking, but they should be designed and used with thoughtful
considerations so that they supply more value than what they cost to use. Being recommended
by the literature is not enough.
Moreover, SCA Tissue, have found an effective way to use guidelines and screening
criterions along their project selection process. This could show to be very useful in VPT AE
as well. Regarding the use of their scoring model, it is quite clear that the real benefit is the
structured and extensive discussion created with this tool. It is not the ranking lists that are the
primary benefits as these are not even used during the final resource allocation.
44. 34
6. THE PPM APPROACH AT VOLVO POWERTRAIN AE
VPT AE has organized their project selection activities with starting point in their global
Advanced Engineering Planning Process (AEPP) – this is the heart of their project portfolio
management (PPM) approach. However, to fully understand how project selection is carried
out, a brief overview of their global organization structure is beneficial. Thereafter, a
description of AEPP is outlined, followed by deeper description of how different units are
operating within the scope for AEPP.
6.1. Volvo Powertrain’s product development organization structure
VPT’s main sites are located in Sweden, France and USA – these will be referred to as local
sites. On the highest level, the organization structure can be described as a
geographic/functional matrix organisation, with one column for each local site, while the rows
consist of functions named Product Development (PD), Purchasing, and Manufacturing,
respectively. A number of support functions are placed under the CEO.
This means that the PD function is global. However, PD in turn is structurally organized as a
geographic/technology-area matrix organisation. Local PD functions at each local site
constitute the columns while sub systems represent the rows – the different technology-areas.
A number of support functions are placed under the head of global product development.
There are five sub systems, one for each technology area. These technology areas are Base
Engine, Combustion, Control Systems, Driveline, and Hybrid Technology. Each sub system
has a Sub System Director who manages the global sub system. Each sub system is
responsible for technology development activities and belonging support activities. The larger
part of engineers within the global PD organization belongs to a sub system, and is located on
one of the three local sites.
The product development activities at each local PD site is organized trough three
departments which can be thought of as responsible for different phases during the ordinary
product development activities. These are Concept (which are responsible for the first
phases), Engine Programs, and Complete Powertrain and Driveline Program. These three
departments are, obviously, responsible for whole concepts and development programs, but
their product development activities depends on ordering large amounts of work from the
various departments within the sub systems. Or differently stated, the engineers within the sub
systems participates in and delivers to the concept and program projects and activities. The
three local PD managers have several staff below them, including Advanced Engineering
(AE). One AE Manager at each site is responsible for the local AE activities and these three
managers coordinate and drive the global AEPP.
6.2. Volvo Powertrain’s Advanced Engineering Planning Process
In order to identify important technology development activities that needs to be carried out
for various reasons – in the end, due to requirements to increase or at least sustain the
competitiveness of the Volvo Group – a process called Advanced Engineering Planning
45. 35
Process (AEPP) have been designed and implemented. This process coordinates the AE-
project selection activities. AEPP and its main activities are illustrated in Figure 15. The
figure is rather schematic and the stages with corresponding activities represented by yellow
icons are in reality more smoothed out and overlapping than what it appears from Figure 15.
However, the figure illustrates in what order different activities are meant to be completed as
the later activities uses the output from the preceding activities as input.
Figure 15: VPT's Advanced Engineering Planning Process
AEPP starts with quarter one, Q1, and ends with quarter four, Q4. The process takes one year
to complete and coincide with regular years. AE Input can be categorized as follows:
• VPT Business Plan
• Long-term product plan and strategy
• Authority regulations and incentives
• Future market needs – Product Feature Plan
• Technology – Research, Suppliers, Competitors
Input
Q1
Q2Q3
Q4
Roadmap Level 1
10 year project
plan
Roadmap Level 2
Technology
Scenario
AE Project
Plans
Cost estimates
Global
AE plan
RoadmapsRoadmapsRoadmaps
Level 3&4
GAEC
AEWS
AE Input
AE Sub
Programs
Budget
frames
AE Plan
Review 2
AE Plan
Review 1
…. year n
