Distribuciones Linux vinculadas a la Seguridad Informática

Relevant validation techniques

With appropriate validation techniques, the design results, statements and design entities are validated. This chapter discusses the validation techniques as identified by R.G. Sargent (2010), which are appropriate for validating the maturity vision. Thereafter, design results and statements are seen as design entities, validated for fulfilling the main objective.

Validated entity: Company Strategy as directive

As main statement, the maturity vision determines that the company strategy is the perspective from which decisions for optimization need to be made. Due to uncertainties in the company context and their sensitivities on decision results, perspectives and biases have their chance to influence the decision making process. As D.K. Pace (2004) states to the point:

“Sometimes the ‘best’ results are too costly, would take too long to obtain, or have some other impediment, so ‘appropriate’ results that have adequate fidelity for the intended use of

the model or simulation serve as the referent”.

Decision making on what is appropriate for the intended use of the model or simulation in a specific context is required and involves many stakeholders, perspectives and biases. The maturity vision is designed as vision above the stakeholders’ individual objectives and biases and puts focus on decisions contributing to company success. For that, the company strategy defines what ‘company success’ entails and determines the level of ‘best’ which is appropriate to the context. This sounds as a reasonable vision.

Results of the research by Xiaoying, Qianqian & Dezhi (2008) support the maturity vision. A suitable validation technique is comparison to other models. The vision is compared to the ideas behind a model for describing relationships between business performance, business strategy, information system strategy and information system performance (Xiaoying, Qianqian, & Dezhi, 2008). They describe these relationships through a conceptual model. They conclude that achieving improved business performance cannot be guaranteed with improving a single one of the supportive dimensions – there are no factors impacting business performance solely – and that alignment of strategies may contribute to increase business performance in some contexts. So, not one single dimension is responsible for business performance and the amount of contribution after optimization depends on the context. These findings fully support and recognize the value of the developed maturity

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vision which states that it might be sensible to identify other dimensions – beyond business strategy, information system strategy and information system performance – which combined contribute to the business performance dimension (labelled as company ‘success’ or ‘maturity’ in this research) and indicate their contribution to success. This would create a more complete image on impacts of dimensions in specific contexts on company success, enabling indication and identification of best dimensions to target for optimization.

Validated entity: Maturity factors, required but not sufficient for success

An often mentioned statement in this research is the role of maturity factors and their contribution to higher level success. The vision builds on a set of maturity factors contributing in their way to the higher maturity dimension, with company success or company maturity as highest dimension. As shown in the previous paragraph, the research of Xiaoying, Qianqian & Dezhi (2008) supports this vision.

Only serendipity34 _{is an exception of this statement, but this does not comply the research}

scope. Besides the comparison to other models as validation technique, rationalization is a suitable in this situation as well. For the assumption of PD process maturity being a required but not a sufficient condition for PD success, its contrary has been proven in industry as well. For example, if the Swiss inventor George de Mestral would not have walked through the Alpine where ‘burdock’ plant seeds stuck to his clothes and dog’s fur and if he did not have been annoyed by stuck zippers in his life, he did not have the inspiration and design idea to develop the successful Velcro product (VELCRO, 2019). Considering that some successful products are developed without intended, structured and organized processes, accidental discoveries can lead to a product development success. These developments based on chance encounters, are labelled as serendipity. But, such successes based on chance appear incidentally. As this research scope and the research of Xiaoying, Qianqian & Dezhi (2008) focus on company or business success as leading, no product development company would ever agree on the risks of that, and steer on coincidences, chance or beneficial incidences. Therefore, the assumption that PD process success is a required but not sufficient condition for PD success automatically applies for this research’ context and scope.

34 Serendipity: the fact of something interesting or pleasant happening by chance (Oxford Learner’s Dictionaries, 2019).

7.1 General validation and evaluation

Validated entity: Bottom-up optimization processes

Optimization is performed from process to higher dimensions’ success (a bottom-up approach), where selection for optimization uses a top-down approach. The vision states that company maturity is the highest maturity dimension in this maturity vision and that supportive maturity factors can be identified. More levels under that can be identified afterwards, repeatedly until the process level is identified. Therefore, this process of identifying and mapping maturity dimensions often follows a top-down strategy (not always – e.g. if looked from existing processes and worked towards maturities – but imaginably, most times). Besides that, the maturity vision states that maturity factors need to be focused on for optimization, not maturity dimensions. This means that maturity optimization occurs specifically in a bottom-up process. No literature reference is found that states directly the same difference between the two processes, however, with use of rationalization both options can be sketched and clarified further for validation.

Changing higher locations directly is too abstract where context influences are unknown, therefore a bottom-up approach is preferred with company strategy as directive for decisions. As indicated in the model of Xiaoying, Qianqian & Dezhi (2008), there are no insights in dimensions that directly influence company success. If someone would ask a person to build a bridge over a canal, it is unlikely for the person to start the first meter by building a six-car wide tarmac bridge. Most people would start with a light beam framework that reaches completely across the canal to see if the concept is right, and then stepwise increase the functionalities and quality to meet expectations. For optimization projects, one would expect an equivalent approach. For improving the higher dimension directly, it is often not known beforehand what maturity factors are influencing, where the optimization would end in and how uncertain and detailed context aspects influence the results. Since the context has high influence on the effectiveness, efficiency, capability and maturity, higher level optimization without taking the detailed context and higher company strategy influences into account, is certainly ineffective if aimed for continuous company success. Therefore, in order to optimize (change) on a certain organizational level, it is preferred to change lower levels towards higher levels instead of changing top-down. However, the risk of this approach is that changing lower locations without focus on the company strategy is not effective as well, since it is not guaranteed that the implementa- tions will contribute to those higher objectives. A gap in modern maturity assessments and audits is that company strategy or higher objectives are not always taken into account as leading for the optimization project, resulting in limited improvement of the higher maturity dimensions. Consequently, the vision dictates to preferably optimize with a bottom-up approach, taking into account the higher maturity dimensions as higher objectives and directives for optimization decisions.

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