Tobias Knabke

Understanding Information System Agility -- The Example of Business Intelligence

To achieve strategic advantage in todays turbulent environments, it is crucial for organizations to draw increasingly faster conclusions out of changing circumstances. As most decisions today are based on data collected by Information Systems (IS), the IS itself must become more adaptable. This is particularly challenging in the domain of Business Intelligence (BI) Systems since the underlying architectural approach of enterprise-wide decision support systems is not build upon agility, but on reliability and robustness over a period of time. In order to determine the agility of BI, a unique understanding of agility and its underlying criteria is required. This paper provides a literature review which aims to summarize the known criteria from IS literature that can be applied to the domain of BI. The results can be interpreted as a framework for understanding the agility of BI systems and form the basis for generating mandatory criteria for assessing agility.

Impacts of In-memory Technology on Data Warehouse Architectures – A Prototype Implementation in the Field of Aircraft Maintenance and Service

Given today’s dynamic market situations, organizations need to internalize the capability to react flexibly on external and internal driven changes. Of course this capability must be supported by the IS landscape. This holds particularly true in the field of aircraft maintenance. For a service provider it is critical to know the age and structure of its equipment pool. This information is vital in offering processes to attract potential customers and to meet service level agreements of existing clients. As current Business Intelligence (BI) architectures fall short in supporting these processes in adequate time and flexibility, we introduce a prototype using an in-memory based BI architecture. The presented artifact proves to have the capability to support business critical processes in a new way. This leads to faster analyses supported by the BI system and also indicates enhanced agility for BI in terms of flexibility and adaptation.

Grundlagen und Einsatzpotentiale von In-Memory-Datenbanken

In der unternehmerischen Praxis wachsen die Anforderungen an eine starkere Verzahnung von operativen und analytischen Tatigkeiten. Dies erfordert ein Umdenken sowohl in der Organisation als auch in der IT-Strategie, da in den meisten Unternehmen derzeit operative und analytische Systeme voneinander getrennt sind. Eine Verschmelzung von operativen und analytischen Tatigkeiten ist mit den bisher eingesetzten IT-Systemen und den aktuellen Technologien nicht oder nur mit erheblichem Aufwand moglich. Durch die zunehmende Wirtschaftlichkeit von In-Memory (IM)-basierten Datenbanken und Applikationen verringert sich der zu erbringende Aufwand jedoch erheblich. Die IM-Technologie besitzt damit das Potential, auch im Unternehmensumfeld einen Zustand zu etablieren, der im privaten Alltag langst selbstverstandlich ist – eine durchgangige Informationsversorgung.

Building novel capabilities to enable business intelligence agility: results from a quantitative study

The class of business intelligence (BI) systems is widely used to guide decisions in all kinds of organizations and across hierarchical levels and functions. Organizations have launched many initiatives to accomplish adequate and timely decision support as an important factor to achieve and sustain competitive advantage. Given today’s turbulent environments it is increasingly challenging to bridge the gap between establishing a long-term strategy and quickly adopting to the dynamics in market competition. BI must address this field of tension as it was originally used to retrospectively reflect an organization’s performance and build upon stability and efficiency. This study aims to understand and achieve an agile BI from a dynamic capability perspective. Therefore, we investigate how dynamic BI capabilities, i.e., adoption of assets, market understanding, and intimacy as well as business operations, impact the agility of BI. Starting from a literature review of dynamic capabilities in information systems and BI, we propose hypotheses to connect dynamic BI capabilities with the agility to provide information. The derived hypotheses were tested using partial least squares structural equation modeling on data collected in a questionnaire-based survey. The results show that the lens of dynamic capabilities provides useful means to foster BI agility. The study identifies that technological advancements like in-memory technology seem to be a technology enabler for BI agility. However, an adequate adoption and integration of BI assets as well as the focus on market orientation and business operations are crucial to reach BI agility.

Considering Risks in Planning and Budgeting Process --- A Prototype Implementation in the Automotive Industry

Corporate budgeting, planning and risk management are crucial functions in todays organizations. Yet, these important functions are often separated in different departments although both rely on similar information. This paper suggests connecting the underlying data structures by means of a software prototype. The suggested solution is based on a planning and budgeting solution running in a major European automotive company. The current Business Intelligence system is extended by hierarchical risk and value driver model that follows the organizations structure. It utilizes a risk-adjusted corridor planning approach based on Monte Carlo simulations. Instead of common point estimates the approach uses ranges that consciously represent uncertainty. As a result budgeting and forecasting are informed by additional knowledge. Hence, behavioral risk that is immanent in any planning activity can be managed.