Defining analytics maturity indicators: A survey approach

2017 | International Journal of Information Management | Citations: 14

Authors: Lismont, Jasmien; Vanthienen, Jan; Baesens, Bart; Lemahieu, Wilfried

Abstract: a b s t r a c tThe ability to derive new insights from data using advanced mach ... Expand

Abstract: a b s t r a c tThe ability to derive new insights from data using advanced machine learning or analytics techniques can enhance the decision-making process in companies. Nevertheless, researchers have found that the actual application of analytics in companies is still in its initial stages. Therefore, this paper studies by means of a descriptive survey the application of analytics with regards to five different aspects as defined by the DELTA model: data, enterprise or organization, leadership, targets or techniques and applications, and the analysts who apply the techniques themselves. We found that the analytics organization in companies matures with regards to these aspects. As such, if companies started earlier with analytics, they apply nowadays more complex techniques such as neural networks, and more advanced applications such as HR analytics and predictive analytics. Moreover, analytics is differently propagated throughout companies as they mature with a larger focus on department-wide or organization-wide analytics and a more advanced data governance policy. Next, we research by means of clustering how these characteristics can indicate the analytics maturity stage of companies. As such, we discover four clusters with a clear growth path: no analytics, analytics bootstrappers, sustainable analytics adopters and disruptive analytics innovators. Collapse

Topics: electronic mail marketing intelligence electronic market marketing management social media

Methods: survey regression analysis method cluster analysis parametric test ANOVA

Generating Value from Open Government Data

2013 | International Conference on Information Systems | Citations: 10

Authors: Jetzek, Thorhildur; Avital, Michel; BjÃ, Niels

Abstract: A driving force for change in society is the trend towards Open Government Data ... Expand

Abstract: A driving force for change in society is the trend towards Open Government Data (OGD). While the value generated by OGD has been widely discussed by public bodies and other stakeholders, little attention has been paid to this phenomenon in the academic literature. Hence, we developed a conceptual model portraying how data as a resource can be transformed to value. We show the causal relationships between four contextual, enabling factors, four types of value generation mechanisms and value. We use empirical data from 61 countries to test these relationships, using the PLS method. The results mostly support the hypothesized relationships. Our conclusion is that if openness is complemented with resource governance, capabilities in society and technical connectivity, use of OGD will stimulate the generation of economic and social value through four different archetypical mechanisms: Efficiency, Innovation, Transparency and Participation. Collapse

Topics: innovation management world wide web open data IS economics economic surplus

Methods: partial least squares regression archival research survey conceptual modelling statistical power analysis

Theories: lemon market theory transaction cost economics theory of economic growth

DETERMINANTS OF USAGE VARIATIONS OF BUSINESS INTELLIGENCE & ANALYTICS IN ORGANIZATIONS – AN EMPIRICAL ANALYSIS

2013 | International Conference on Information Systems | Citations: 0

Authors: Malladi, Suresh; Krishnan, M S

Abstract: While Business Intelligence & Analytics (BIA) applications are increasingly bein ... Expand

Abstract: While Business Intelligence & Analytics (BIA) applications are increasingly being adopted into business, there is a significant variation in using them to empower organizational business functions. There is a paucity of empirical research examining the drivers of extensive usage of BIA in organizations. Drawing on TechnologicalOrganizational-Environmental theoretical framework, we present and test a conceptual model of factors associated with the extent of organizational usage of BIA. We find that sophistication of data-related infrastructure in firms drives usage while challenges related to data management hamper the extent of usage. Further, we find that large organizations have a higher propensity to use BIA in business functions while managerial challenges related to integration and talent management prevent extensive usage. Finally, we find that industry competitive intensity influences usage extent. This study highlights the antecedents of usage and can help researchers and practitioners to understand what factors can enable firms to use BIA extensively. Collapse

Topics: data management diffusion of innovation business function innovation management business process management

Methods: survey conceptual modelling literature study robustness check logistic regression

Theories: theory of everything