Cricket being an extremely competitive game; players are always under pressure to perform and improve continuously. Talent enhancement in cricket is conventionally achieved through practice under coach's supervision and analysis using costly assistive technology. Although this approach is workable, but it is constrained due to nonavailability of quality coaches, equipment, and in many cases the limited domain knowledge of the coaching staff. This constraint is significant for a country like India where 55,000 matches and 1,210,000 players play cricket daily. The literature review did not reveal any algorithm/model/framework focused on the issue of talent enhancement. In this paper, we present an alternate/supporting approach based on comparison of the players’ overall talent class viz‐a‐viz the corresponding performances of the player against the 28 aspects of talent from cricketing perspective. The Ordered Weighted Averaging Aggregation (OWA) operator was used to aggregate the opinion of experts for assessment of talent classes in cricket. The normative data obtained for a cricket enthusiast was then compared using normalized adequacy coefficient with aggregated opinions of experts. This resulted in identification of the talent class of the cricketer. Subsequently, the weaknesses were identified by comparing the outcomes of the identified parametric tests for this cricket enthusiast with the value corresponding to his/her talent class. The algorithm was validated using two‐sided t test. A case showing implementation of algorithm is also explained.

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The literature review studies on ERP system indicate two main areas of thrust: the study of critical success factors for the risk aversion in ERP implementation projects and the ERP system selection studies. However, ERP system selection is a tedious and a time-consuming activity. The critical success factors (CSFs) serve as vital input ingredients to the ERP selection Models. It is however notable that, that none of the CSFs listing propagated by the researchers find a straightforward application in the selection procedure. The paper bridges the gap between the two thrust areas by proposing a framework for applying the prioritized CSFs listed for direct utilization in the selection process. An exhaustive review on the ERP selection techniques reveals the focus on AHP and/or the Fuzzy Logic approaches to ERP selection problem. A new approach to ERP selection problem with the extensions of the Fuzzy-TOPSIS is subsequently introduced and is illustrated by a solved numerical example. Also, the computational simplicity of the extensions of Fuzzy TOPSIS is demonstrated.