524 research outputs found

    Enhancing public sector enterprise risk management through interactive information processing

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    IntroductionFederal agencies are increasingly expected to adopt enterprise risk management (ERM). However, public sector adoption of ERM has typically focused on the economic efficiency of tax-financed activities based on control-based practices. This reflects an emphasis on quantifiable concerns that invariably directs attention to risk, that (by definition) relates to identifiable and measurable events, thereby downplaying uncertain and unknown aspects of public exposures. This is a potentially serious shortcoming as government entities often act as society's risk managers of last resort. When extreme events happen what were previously considered private matters can quickly turn into public obligations. Hence, there is a need for proactive assessments of the evolving public risk landscape to discern unpredictable-even unknowable-developments.MethodsThe article reviews recent empirical studies on public risk management practices, effects of digitalization in public sector institutions, current strategic management research, and insights uncovered from a recent study of risk management practices in federal agencies. On this basis, the article explains how the ability to generate value from ERM can be enhanced when it intertwines with local responsive initiatives and central strategic risk analyses. It can form a dynamic adaptive risk management process where insights from dispersed actors inform updated risk analyses based on local autonomy and open exchange of information. This approach builds on specific structural features embedded in culture-driven aspirations to generate collaborative solutions. Its functional mode is an interactive control system with open discussions across levels and functions in contrast to conventional diagnostic controls that monitor predetermined key performance indicators (KPIs) and key risk indicators (KRIs).FindingsBacked by theoretical rationales and empirical research evidence, it is found that applications of ERM frameworks can produce positive results but is unable to deal with a public risk landscape characterized by uncertain unpredictable conditions with potentially extreme outcome effects. It is shown how interactive exchange of fast local insights and slow integrated strategic risk analyses supported by digitized data processing can form a dynamic adaptive system that enable public sector institutions to deal with emergent high-scale exposures. It is explained how the requirement for conducive organizational structures and supportive values require a new strategic risk leadership approach, which is contrasted to observed practices in federal agencies that are constrained by prevailing public governance requirements.DiscussionThe need to deal with uncertainty and unknown conditions demands a cognitive shift in current thinking from a primary focus on risk to also appraise complexity and prepare for the unexpected where data-driven methods can uncover emergent exposures through dynamic information processing. This requires strategic risk leaders that recognize the significance of complex public exposures with many unknowns and a willingness to facilitate digitalized information processing rooted in a collaborative organizational climate. If handled properly, adoption of ERM in public risk management can consider emergent dimensions in complex public exposures applying interactive information processing as a dynamic adaptive risk management approach incorporating digitized methods to solicit collective intelligence for strategic risk updating

    Strategic Orientations of Internationalizing Firms: A Comparative Analysis of Firms Operating in Technology Intensive and Common Goods Industries

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    The strategic orientations of global integration and local responsiveness (the I-R framework) continue to dominate analyses of internationalization strategies and identify the basic strategy typologies of multinational enterprise. Much effort has been devoted to verify the generic strategies established within the original I-R framework but few studies have investigated their implied performance effects. In conformity with the foundations of the I-R framework we characterize the strategic orientations by their implied corporate decision structures and strategy processes and analyze their performance associations in two distinct industrial environments. The evidence from this analysis contradicts predictions in the conventional I-R framework. We explain this conundrum from a resource-based perspective as firms operating in technology intensive environments outperform when they have access to diverse multinational resources whereas firms in common goods businesses gain economies from global product standards

    Analysis of time-to-event for observational studies: Guidance to the use of intensity models

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    This paper provides guidance for researchers with some mathematical background on the conduct of time-to-event analysis in observational studies based on intensity (hazard) models. Discussions of basic concepts like time axis, event definition and censoring are given. Hazard models are introduced, with special emphasis on the Cox proportional hazards regression model. We provide check lists that may be useful both when fitting the model and assessing its goodness of fit and when interpreting the results. Special attention is paid to how to avoid problems with immortal time bias by introducing time-dependent covariates. We discuss prediction based on hazard models and difficulties when attempting to draw proper causal conclusions from such models. Finally, we present a series of examples where the methods and check lists are exemplified. Computational details and implementation using the freely available R software are documented in Supplementary Material. The paper was prepared as part of the STRATOS initiative.Comment: 28 pages, 12 figures. For associated Supplementary material, see http://publicifsv.sund.ku.dk/~pka/STRATOSTG8

    The Sensing of Frontline Employees Against Executive Expectations

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    The literature suggests that important strategic initiatives can derive from employees within the organization as they respond to needs and opportunities observed in daily operations. This seems to indicate that employees have a good sense of the firm’s operational capabilities observed through direct interactions with colleagues, customers and partners. Executives make their own judgments about the corporate capabilities from discussions with various managers, other executives and industry specialists. But, the information gathered by executives may be qualitatively different from the conditions sensed by the employees. So, we arranged a contest between operational capabilities assessed by employees and executives and the relationship to subsequent firm performance. Based on more than 400 individual data points collected from two medium-sized organizations over a period of eighteen months, advanced distributed lag time-series analyses show that the sensing of front-line employees (surprisingly) is a better medium-term predictor of organizational performance than executive judgments. These results have implications for the way organizations set up their management information and communication structure

    A New Approach to Strategic Control

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    Recent advances within the dynamic capabilities view emphasize the “sensing” of employees as an important part of the micro-foundations of dynamic capabilities: By putting in place organizational processes that mobilize and exploit information gathered by individual employees from their operating environment, firms can update insights about performance outcomes and improve strategic decision-making. We test empirically the extent to which firms can ascertain performance outcomes by drawing on employee knowledge. Our empirical setting is the Scandinavian hospitality sector with respondents among frontline service employees. Using a time series approach, we show that employee respondents (collectively) assess medium-term organizational performance better than management and the financial models available to them

    Using Updated Information from the Frontline

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    Effective strategy-making in turbulent industries needs current insights that can inform ongoing decisions around adaptive strategic moves. Frontline employees involved in the daily business transactions are the first to see the subtle changes not otherwise observed by top managers. Top management with dominant logics anchored in previous business contexts usually receive updated information from performance reports for prior periods. All the while, we discern a human inclination linked to the position of power where managers subconsciously discard updated information from frontline employees. We present an experiment to investigate these effects and discuss the implications for strategic response capabilities among firms
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