# Innovation in Company Labor Productivity Management: Data Science Methods Application
## 4 Discussion of Results: Management Decisions to Improve Employers' Health Quality  
On the next stage of the proposed technology, we examine different regression models of the investigated predictors (regressors) on labor productivity for each constructed cluster. The regression models quality (with a different composition of regressors) corresponding to each cluster is tested and the best ones were selected in terms of quality criteria--maximum determination coefficient (\(R^{2}\)) and minimum moving average approximation error (MAPE). Designed models give a clear idea of the different factors impact on the modeled indicator (labor productivity) and allow making predictions about the factors changes impact on labor productivity, Table 7.  
Some intercepts in the models are significant for the significance level of 0.05. It means that there are some other predictors for labor productivity modeling such as qualifications level, work experience, possession of the required competencies, production automation and digitalization level etc. The designed models for the analysis and forecasting of employees' labor productivity by their special cluster are totally statistically significant and permit the prediction of labor productivity with a high accuracy, since minimum moving average approximation errors are from 10.3% to 16.6% for different models. These models are used to predict labor productivity under various scenario options for influencing factors about health quality. For obtaining beneficial effects for business, the idea of a healthy lifestyle and a management system aimed at preserving the employees' health has a number of significant functions. First, it is a motivational function. An investment into employees' health, which \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Predictor (Regressor)**} & \multicolumn{3}{c}{**Regression Coefficient for Models, Different by Employees’ Clusters**} \\  & **1** & **2** & **3** & **4** \\ \hline age & 2.2938 & \(-\)3.4964 & 2.4323 & \(-\)0.3619 \\ child & \(-\)3.8365 & \(-\)5.6638 & \(-\)6.5767 & \(-\)76.8798 \\ gender & \(-\)3.8608 & 37.5001 & \(-\)0.7216 & \(-\)40.0442 \\ mar & 16.3362 & \(-\)24.5735 & 38.9882 & \(-\)22.7630 \\ edu & \(-\)9.5457 & 83.0892 & \(-\)0.3464 & 29.0374 \\ chron\_dis & \(-\)23.6031 & 38.1560 & \(-\)0.7990 & \(-\)5.0536 \\ bad\_health & 15.9159 & 105.3204 & \(-\)20.1630 & \(-\)40.0442 \\ health\_ass & \(-\)30.3469 & 139.8367 & 23.9315 & \(-\)40.0442 \\ nutr & \(-\)13.0980 & 136.2081 & \(-\)12.1418 & 26.6200 \\ bad\_hab & \(-\)23.6031 & \(-\)80.6174 & \(-\)3.4200 & \(-\)46.6946 \\ Regression intercept & 139.0025 & 249.9718 & 109.6893 & 460.2615 \\ \(R^{2}\) & 0.84 & 0.73 & 0.71 & 0.76 \\ MAPE & 10.3 & 16.6 & 12.1 & 11.6 \\ \(F\)-test & 4.1 & 4.1 & 4.6 & 4.3 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Regression results by employees’ clusters (significant parameters are marked in red). is accompanied by certain measures and actions, is an element of the corporate social responsibility system. The existence of the social package for employees is an indicator of a companies' status and its reputation. These increase employees' loyalty to the company and are strategically important to their motivations. Secondly, a company development strategy is an element of its corporate culture. Healthy lifestyle ideas adopted by employers become part of the informational internal corporate environment and have a great team-building effect. Organization of a set of management decisions to employees' health preserve is based on the following activity types: socio-psychological, financial-economic and material-technical. Activities related to socio-psychological factors provide employees' values orientations, motivation for a healthy lifestyle, training and creation of a favorable moral and psychological climate and an atmosphere of team cooperation, development and implementation of a recreational activities system. Pedagogical tools are used here.