Validity influenced by assumptions

This section discusses the influence on assumptions used in this research on the validity of research results. Only the major assumptions are included and assessed for their certainty of being true and their sensitivity on results.

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Company strategy as objective directive

Chapter 2: Maturity Vision: The company strategy defines and supports the company’s main objective and is present in the company context before optimization takes place. The highest level of maturity represents the highest objective as stated in the company strategy and is

assumed as being defined within a company.

This assumption is used in creating the maturity vision. If this assumption is wrong, a different source for interpreting an objective perspective aiming at company success is required for PDMO model and PDPMA model execution. Alternative solutions could for example compare and examine model results of multiple independent stakeholders to find the common perspective which is independent from individual biases. However, this assumption can be accepted in the scope and practicability of this research. Since company strategy reflects and aims at company success and is well known business essential, absence or inadequate formulation of the company strategy would already suggest that the company first needs to focus on determining what company success entails in their context before focus can be put on effectively and efficiently optimizing PD practices in specific. ‘Success’ is defined as “the fact that something wanted or is tried to get is achieved”. Therefore, a statement which defins what is wanted is required, in business context addressed by the company strategy. For utilizing research results, this assumption needs to be true.

Company success as highest maturity dimension

Chapter 2: Maturity Vision: The capability of performing the highest objective of achieving company success is the highest location of maturity.

Having all decision makers understanding and seeing the broader maturity vision as basis for objective decision making is the next step after interpreting the company strategy, leading to performance of the PDMO model and the PDPMA model respectively if PD process maturity requires optimization based on the PDMO model results. If this assumption is not true, the named ‘company strategy’ might not reflect the aim of achieving success of a single company, but may be based on a higher organizational strategy, including objectives of that maturity dimension to work towards organizational success. The research results allow focus on higher organizational objectives, company success overall is used in the concept models with flexible interpretation of on what operational level – success of a single company within a big organization or success of the large organization – the company success dimension acts. It is flexible and open to choose the highest objective dependent on the context and intended results, as long as its perspective is interpreted and used as highest directive for optimization decisions during performing the concept models.

7.2 Discussion

Quantification is only appropriate in relation to a context

Chapter 1: Introduction: Maturity, capability, effectiveness and efficiency cannot be quantified or estimated without a close relation to the context.

Figuratively speaking, if one company aims to achieve a randomly chosen 7.3 grade out of

10 on efficiency, another company might aim for increasing efficiency from a 9.7325 to a

9.7330 out of 10. The contexts of the companies determine everything for interpreting those numbers. For example, the bakery on the corner of the street wants some spare time to spend it on selling his goods on the marketplace, aiming for an increase of efficiency from 5 to 7.3 out of 10 which might be sufficient to achieve his objective. However, if an automobile parts developing company needs to increase efficiency to keep-up to requirements of high performing customers, 7.3 out of 10 will not even be close to performances of competitors, and minor improvements of the secondly mentioned efficiency increase determine who has competitive advantage. The added value of the research results relies in this assumption, since complex multi-criteria decisions would not be necessary if the context did not have influence on the effectiveness and efficiency of solutions. Since industry and academy both struggle with finding appropriate solutions per context and solutions that do not take into account the context are not utilized effectively and efficiently, this assumption can be accepted in this research’ context.

Success on maturity dimensions and factors related

Chapter 2: Maturity vision and Chapter 3: PDMO model design: Success of a maturity factor is a necessary but not sufficient condition for success of a maturity dimension.

Consequently, PD process success is a necessary but not the only condition for PD success, which in its turn is a necessary but insufficient condition of company success. This assumption can be accepted, after it is reasoned by using logic sense. A maturity dimension is based on a – it may be an underdefined – set of maturity factors. The success of the dimension is not defined by summing the successes of the maturity factors, as the functioning of a ‘system’ cannot be guaranteed with validated functioning of its ‘parts’. This provokes the use of the word ‘insufficient’. However, a dimension that contains a maturity factor which is ineffective or inefficient, can never be effective and efficient itself. Therefore, it is necessary to have high maturity on the maturity factors for success on the maturity dimension, proving validity of the word ‘necessary’. With this combination, the assumption can be accepted within the context of this research.

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Summarizing validity influenced by assumptions

Based on previous discussion of the assumptions, their influence on the research results are summarized. Assumptions are discussed for their certainty of being true and the sensitivity of the validity of research results. Assumptions with high certainty or low sensitivity are not threatening to the validity of results, assumptions with low certainty and high sensitivity are threatening and validation of the assumption is required in future research or future design iterations must target the designs’ sensitivity for these assumptions.

Assumptions with high certainty or low sensitivity:

- The capability of performing the highest objective of achieving company success is the highest location of maturity.

- Maturity, capability, effectiveness and efficiency cannot be quantified or estimated without a close relation to the context.

- A high – or, success on a – maturity factor is a necessary but not sufficient condition for high – or, success on a – maturity dimension on a higher location.

Assumptions with low certainty and high sensitivity

- The company strategy defines and supports the company’s main objective and is present in the company context before optimization takes place. The highest level of maturity represents the highest objective as stated in the company strategy and is assumed as being defined within a company.

For utilizing the research results, (1) this assumption needs to be proven as being true or (2) the design needs to be adapted in future developments counteracting on the sensitivity for this assumption. Since a mature company strategy can be seen as a business essential, the author recommends for these situations to implement option one (1), and advices to first define an appropriate and mature company strategy that reflects company success before optimizing other processes within the company. Doing otherwise may result figuratively in optimizing a road that leads into a ravine, since the end point is not known.

7.2 Discussion

This section states recommendations for future research which are identified during this research. Research and development recommendations for the PDMO and PDPMA model designs are stated and additional validation steps are recommended that may lead to development of design iterations in the future. The transformation of the model in a practical software tool enables application in practice. However, before that is possible, future research and development steps are required.

Develop the models

The concept models are sensitive to the quality of the given input information. Therefore, it is recommended to investigate opportunities for a measurement step which validates given input as it travels through the models. Since this research’ results present the designs from the concept phase, such details are not yet included.

The information visualization and structuring methods in the concept models are evaluated for their capability of fulfilling the stated requirements. However, how capable they are is not assessed in detail. Comparison and selection of other visualization methods as well is required to design iterations of the concept models, and assure mature information visualization and structuring methods. Additional literature research on data visualizations, taxonomies and ontologies can be useful for achieving that. Iterations for taxonomy visualizations such as stated in Müller & Schumann (2003) can form inspirations for future visualization methods, enabling deliberate comparison of static, dynamic, conventional and multivariate visualization methods for the intended functions.

The difficulty of relating contexts to process structures, is the required mix of practical and theoretical knowledge. This might be a reason why existing literature does not often state how to adapt developed artefacts to fit specific contexts. However, this functionality is required for the PDPMA model development. For developing the PDPMA model further, the context ontology needs to be connected to required functionalities. Most of them can be identified by PD specialists in industry or by logic sense, since it is a small step to get from such detailed company aspect parameters to connected functions. Best practices can support with identifying those relations, but are not preferred. In parallel, the model and method ontology needs to be complemented with a broad range of existing process structures. For this process – with theoretical knowledge from the Design Science domain – information on product development processes and their artefacts is required. It needs to be implemented in the database with taking them apart in small model and method parts, which can be evaluated for their reason for existence. The reason for existence is