Arnoud Franken

Executing Strategic Change: Understanding the Critical Management Elements that Lead to Success

Despite the availability of many methodologies, management approaches, and literature on strategy execution, research suggests that seven out of ten organizations fail to successfully execute their strategies. However, three out of ten organizations do appear to succeed. To find out what these organizations do differently, ten key management elements for successful strategy execution were identified from the literature as well as seven business benefits that could be realized if these elements were performed effectively. Next, 93 organizations were surveyed, followed by focus group meetings with senior managers. While mastery of formal methodologies and development of business cases are important, successful strategy execution is critically dependent on having a portfolio of change programs that are explicitly aligned with the organizations strategy. Further, this portfolio needs to be supported by the strategic leadership team and managed within a culture conducive to change. There are specific actions that organizations need to take to identify which elements of their strategy execution capability need to improve in order to take their performance to the next level.

A dynamic capabilities perspective of IS project portfolio management

Organizations use information systems project portfolio management (IS PMM) to reconfigure their IS resources and capabilities to match changing market and economic conditions. IS PPM can therefore be characterised as a dynamic capability. We investigate how firms developed and adapted IS PPM to match the turbulent recessionary conditions witnessed after 2008–2009. This study contributes to an understanding of IS PPM by identifying the constituent dynamic capabilities and providing empirical examples of adaptation. To our knowledge, the study is the first to apply the notion of second order dynamic capabilities to the IS domain and also makes an important contribution to the more general concept of dynamic capabilities by providing empirical evidence and theoretical justification of the increased detailed, centrally controlled and analytical nature of IS PPM dynamic capabilities in recessionary conditions.

SOX, compliance, and power relationships

There are several tactics CIOs can use for SOX compliance implementation. A pivotal one is understanding their relationship with the CEO, CFO, and auditors.

Organisational forms and knowledge management: one size fits all?

In the new economy, a firms sustainable competitive advantage flows from its ability to create and exploit new knowledge. Consequently, the need for executives to manage this process effectively is greater than ever. The extant knowledge management literature contains an implicit assumption that a standard approach with universal applicability to this process exists. Yet many organisations adopting this approach fail to realise the anticipated benefits. In this paper, the underlying causes for these failures are discussed and the assumption of a standard knowledge management approach critically challenged. To this end, the organisational form framework by Miles and Snow is integrated, for the first time, with the knowledge management models by Nonaka. Through the integration of these two frameworks, it is shown that the choice of knowledge management approach cannot be unqualified but must be closely aligned with the organisations strategic and operational form in order for the anticipated benefits to be reaped. Our analysis suggests three conclusions: One, Prospector-type organisations will tend to adopt Bottom-Up approaches for effective knowledge creation; two, Defender-type organisations will tend to adopt Top-Down approaches; and three, Analyser types will adopt Middle-Up-Down knowledge creation approaches. We provide directions for future research.

When It Takes a Network: CREATING STRATEGY AND AGILITY THROUGH WARGAMING

Rational, analytical, directed approaches for strategy creation and execution may work for creating value by conventional, hierarchically structured organizations operating in stable environments. However, when the basis of competition shifts from product features to an experience delivered by a network of independently acting participants in a complex and fast-evolving market environment, approaches based on command and control do not work. For order to emerge from such chaos and to gain more control over success, strategy based on reason alone is not enough to inspire action in others. To understand what it takes to effectively make strategy under such circumstances, this article shows how the UKs Royal Marines, in collaboration with more than a dozen different stakeholder groups, developed a novel adaptation of wargaming to affect strategic change in Afghanistan. It also demonstrates the broad applicability of this strategic approach.

Enhancing Flow Field Measurements Through Adaptive Multidimensional Data Sampling

A way to gain insight into the flow field conditions in turbomachinery is by carrying out a series of point measurements in a cross section of the flow, for example, with a miniature multihole pressure probe. A problem commonly encountered in situations like these is the selection of a suitable measurement grid layout and density for obtaining all essential information in a cost-effective and timely manner. In order to achieve the latter, a novel adaptive multidimensional data sampling technique has been developed at Cranfield University. This paper describes the underlying principles of this technique, the algorithms utilized, and the results obtained during its successful application to data sets of two different flow fields in a high-speed research compressor.

Accelerating the Calibration of Multihole Pressure Probes by Applying Advanced Computational Methods

The miniature multihole pneumatic pressure probe is widely regarded as a cost-effective, easy-to-use, and accurate method for performing two- or three-dimensional flow field measurements in turbomachinery. The major downside to the use of these probes is that the influence of fabrication imperfections on probe characteristics necessitates an extensive and highly time-intensive and, therefore, costly calibration of each individual probe. Unless these probes can be fabricated to such standards that make individual probe calibrations superfluous, the only way to significantly reduce the time and costs associated with probe calibration is to shorten the calibration process. The latter is only possible if all essential information can be obtained from less calibration data. This paper describes an approach to the calibration of a series of multihole pressure probes in which advanced computational methods are used to make this possible. By exploiting the key features of a probes characteristic this approach requires only a fraction of the size of a conventional calibration database for the accurate modeling of the relationships between port pressures and flow conditions. As a result, calibration time and costs can be reduced without the sacrifice of quality.

Enhancing Flow Field Measurements Through Adaptive Multi-Dimensional Data Sampling

A way to gain insights into the flow field conditions in turbomachinery is by carrying out a series of point measurements in a cross-section of the flow, for example, with a miniature multi-hole pressure probe. A problem commonly encountered in situations like these is the selection of a suitable measurement grid layout and density for obtaining all essential information in a cost-effective and timely manner. In order to achieve the latter, a novel adaptive multi-dimensional data sampling technique has been developed at Cranfield University. This paper describes the underlying principles of this technique, the algorithms utilized, and the results obtained during its successful application to data sets of two different flow fields in a high-speed research compressor.Copyright

Accelerating the Calibration of Multi-Hole Pressure Probes by Applying Advanced Computational Methods

The miniature multi-hole pneumatic pressure probe is widely regarded as a cost-effective, easy-to-use and accurate method for performing two- or three-dimensional flow field measurements in turbomachinery. The major downside to the use of these probes is that the influence of fabrication imperfections on probe characteristics necessitates an extensive and highly time-intensive and, therefore, costly calibration of each individual probe. Unless these probes can be fabricated to such standards that make individual probe calibrations superfluous, the only way to significantly reduce the time and costs associated with probe calibration is to shorten the calibration process. The latter is only possible if all essential information can be obtained from less calibration data. This paper describes a novel approach to the calibration of a series of multi-hole pressure probes in which advanced computational methods are used to make this possible. By exploiting the key features of a probe’s characteristic this approach requires only a fraction of the size of a conventional calibration database for the accurate modeling of the relationships between port pressures and flow conditions. As a result, calibration time and costs can be reduced without the sacrifice of quality.Copyright

REDUCING AERO-ENGINE DEVELOPMENT TIME AND COSTS BY USING ARTIFICIAL INTELLIGENCE

As a result of market pressures, aero-engine manufacturers are forced to continuously improve the performance of their products whilst simultaneously reducing development time and costs in order to remain competitive. One of the consequences of continuously doing-more-with-less is that the ever more complex test data is not always (thoroughly) analyzed anymore, simply because engineers often don’t have enough time for this task and/or due to a lack of sufficient electronic storage space for this data. As a result, available information that could contribute to a faster and cheaper way of improving the design and performance of a jet-engine is sometimes ignored or even deleted. More than once these practices have led to the performing of unnecessa ry additional tests in order to re-obtain certain pieces of information. Needless to say, this wastes time and money. In order to solve these problems, a novel concept is proposed and discussed in this paper. In this concept, neural networks are used to au tomatically extract valuable information from test data and present this information to its users. This paper further discusses why functional-link neural network are more suitable for this application than multi-layer neural networks. Furthermore, the paper discusses the approach taken for the development and validation of this concept.