Computation of sales performance score and key cross-functional factors: a performance dynamics in IT/ITES

Purpose - The purpose of this research is to identify the cross-functional factors and their impact after exploratory factor analysis (EFA), especially in B2B context and constructing a model to interpret and quantify the influences (sales performance score) specifically to the IT/ITES companies. Design/methodology/approach - Getting answer for a corporate that where its current stand in the industry is important for the strategy making, especially for the sales team. Few academic researches charted direction toward cross-functional sales factors, but getting answer whether we can quantify that sales performance and identify what is the numeric benchmark value, is difficult. For the companies to understand the need to focus on which cross-functional factors and when, is also difficult. Findings - After 1,079+ literature study, concluded with the 25 antecedents strongly used in previous studies and 8 more on after focused group study, pilot study and discussion with the industry leaders, 35 questions addressing 33 indicators collected in 10 months duration from 310 sales professionals, 90+ IT companies. Three samples were removed as outliers using “Mahalanobis Distance Test” for multivariate analysis, dropped two variables by “Missing value Not at Random” (MNAR). Final 15 determinants of cross-functional sales performance indicators forming four best factors with very high reliability after EFA to form a future formative model and sales performance score. Research limitations/implications - (1) In this study no moderator and mediator effect are analyzed. (2) This study is the precursor to the final model construction. (3) Business down due to recession, global pandemic, terrorism, earthquake, war etc. are not considered during this analysis and study. Only the cross-functional reasons for natural business down have been considered and analyzed. (4) Exact “Sales Performance Score (SPS)” should be calculated after model forming, adjusting and confirmatory factor analysis. Practical implications - (1) The major implication of this study would be for IT/ITES companies. It will be very easy for them to quantify the sales performance and measure that scientifically. (2) There will be a way to measure, predict and take measurable actions in case sales performance of the company downfalls. (3) Also the impact will be known to the top management of the company well in advance so that they can make the proper strategy. This will be very useful in current situation when measuring business outcome and make strategy well in advance is of any company's utmost priority. Originality/value - Focusing on these identified factors companies can improve its sales performance. The authors contribute in creating a statistical model and computing a sales performance score, based on the final factor loading values, would be unique and unprecedented to measure the current industry performance by quantifying its standard or benchmark value for better strategic support toward the achievement of targets.