Pam Ad Kleingeld

Interdependence and fit in team performance management

Purpose – To evaluate a proposed prescriptive model for the design of effective combinations of performance goals and pay‐for‐performance plans for the performance management of teams.Design/methodology/approach – The idea underlying the model – in which task, goal, and reward interdependence and their fit play a dominant role – is that a pay‐for‐performance plan should support the team goals and the goals of individual team members as well as support the way in which team members need to cooperate. To obtain a first notion on the models validity, it was applied to evaluate a pay‐for‐performance plan for management teams at a large IT company. This evaluation consisted of an in‐depth study of three management teams, using a case study methodology.Findings – Combinations of fit among type of team, performance goals, and pay‐for‐performance plan (established by a fit between the interdependence constructs and/or by an overlap in the content of the goal and pay indicators) are more effective than combinatio...

Quantifying the Performance of Workflows

Abstract Business process redesign is one of the most powerful ways to boost business performance and to improve customer satisfaction (Limam Mansar & Reijers, 2005). A possible approach to business process redesign is using redesign best practices. A previous study identified a set of 29 different redesign best practices (Reijers, 2003). However, little is known about the exact impact of these redesign best practices on workflow performance. This study proposes an approach that can be used to quantify the impact of a business process redesign project on all dimensions of workflow performance. The approach consists of a large set of performance measures and a simulation toolkit. It supports the quantification of the impact of the implementation of redesign best practices, in order to determine what best practice or combination of best practices leads to the most favorable effect in a specific business process. The approach is developed based on a quantification project for the parallel best practice and is validated with two other quantification projects, namely for the knockout and triage best practices.

Trade-offs in the performance of workflows: quantifying the impact of best practices

Business process redesign is one of the most powerful ways to boost business performance and to improve customer satisfaction [14]. A possible approach to business process redesign is using redesign best practices. A previous study identified a set of 29 different redesign best practices [18]. However, little is known about the exact impact of these redesign best practices on workflow performance. This study proposes an approach that can be used to quantify the impact of a business process redesign project on all dimensions of workflow performance. The approach consists of a large set of performance measures and a simulation toolkit. It supports the quantification of the impact of the implementation of redesign best practices, in order to determine what best practice or combination of best practices leads to the most favorable effect in a specific business process. The approach is developed based on a quantification project for the parallel best practice [8] and is validated with two other quantification projects, namely for the knockout and triage best practices.

Development of a Non-Melanoma Skin Cancer Detection Model

Background: The incidence and prevalence of skin cancer is rising. A detection model could support the (screening) process of diagnosing non-melanoma skin cancer. Methods: A questionnaire was developed containing potential actinic keratosis (AK) and basal cell carcinoma (BCC) characteristics. Three nurses diagnosed 204 patients with a lesion suspicious of skin (pre)malignancy and filled in the questionnaire. Logistic regression analyses generated prediction models for AK and BCC. Results: A prediction model containing nine characteristics correctly predicted the presence or absence of AK in 83.2% of the cases. BCC was predicted correctly in 91.4% of the cases by a model containing eight characteristics. The nurses correctly diagnosed AK in 88.3% and BCC in 90.9% of the cases. Conclusions: Detection or screening models for AK and BCC could be made with a limited number of variables. Nurses also diagnosed skin lesions correctly in a high percentage of cases. Further research is necessary to investigate the robustness of these findings, whether the percentage of correct diagnoses can be improved and how best to implement model-based prediction in the diagnostic process.