# A Continuous Monitoring and Reallocation Method for Successful Decisions in Change Management
## 4 Experiments and Results
### First Experiment's Results and Analysis
At \(t=14\) for 100.000 iterations, the total performance for the proposed CoMoRe method is 1091 and has exceeded the initial total performance (981), while the total performance for the CCMM is less than the initial total performance, with a value of 886. Thus, the new desired state that improves performance over the initial state is reached in a shorter time. Figure 4: Comparison of average total performance between CCMM and CoMoRe methods after 100 (a), 1.000 (b), 10.000 (c), and 100.000 (d) repetitions. Table 7 compares the Total Performance Improvement (TPI) in percentage between the two methods at all time intervals. The Total Performance Improvement is defined as follows:  
\[TPI=\frac{TP_{CoMoRE}-TP_{CCMM}}{TP_{CCMM}}\times 100 \tag{10}\]  
where \(TP_{CoMoRE}\) and \(TP_{CCMM}\) denote the total performance with the CoMoRe and CCMM methods, respectively. As presented in Table 7, the lower total performance at time \(t\) = 7 and \(t\) = 8 is approximately 71% higher for the CoMoRe method compared to the CCMM method. As a result, \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \multicolumn{8}{c}{**Total Performance**} \\ \hline
**Repetitions** & \multicolumn{2}{c}{**100**} & \multicolumn{2}{c}{**1.000**} & \multicolumn{2}{c}{**10.000**} & \multicolumn{2}{c}{**100.000**} \\ \hline
**Time (\(t\))** & **CCMM** & **CoMoRe** & **CCMM** & **CoMoRe** & **CCMM** & **CoMoRe** & **CCMM** & **CoMoRe** \\ \hline
0 & 981 & 981 & 981 & 981 & 981 & 981 & 981 & 981 \\
1 & 885 & 932 & 887 & 933 & 887 & 933 & 886 & 933 \\
2 & 666 & 820 & 671 & 818 & 672 & 819 & 671 & 819 \\
3 & 521 & 707 & 526 & 707 & 526 & 708 & 526 & 708 \\
4 & 434 & 634 & 441 & 632 & 441 & 634 & 441 & 633 \\
5 & 369 & 575 & 376 & 573 & 376 & 575 & 376 & 575 \\
6 & 312 & 524 & 321 & 522 & 321 & 524 & 321 & 524 \\
7 & 277 & 491 & 287 & 489 & 286 & 491 & 286 & 491 \\
8 & 277 & 491 & 287 & 489 & 286 & 491 & 286 & 491 \\
9 & 311 & 525 & 322 & 524 & 321 & 526 & 321 & 526 \\
10 & 365 & 579 & 377 & 579 & 377 & 581 & 376 & 581 \\
11 & 459 & 670 & 473 & 675 & 472 & 676 & 472 & 676 \\
12 & 562 & 775 & 578 & 780 & 577 & 782 & 576 & 781 \\
13 & 707 & 921 & 724 & 925 & 722 & 926 & 722 & 926 \\
14 & 877 & 1082 & 889 & 1091 & 887 & 1091 & 886 & 1091 \\
15 & 1046 & 1246 & 1054 & 1255 & 1051 & 1256 & 1051 & 1256 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of total performance results for 100, 1.000, 10.000, and 100.000 repetitions between the proposed CoMoRe method and the CCMM method for 10 workers and tasks (\(n=10\)). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Total Performance Improvement**} \\
**Repetitions** & **100** & **1.000** & **10.000** & **100.000** \\ \hline
0 & 0.00\% & 0.00\% & 0.00\% & 0.00\% & 0.00\% \\
1 & 5.27\% & 5.25\% & 5.28\% & 5.30\% \\
2 & 23.12\% & 21.95\% & 21.99\% & 22.01\% \\
3 & 35.83\% & 34.33\% & 34.52\% & 34.43\% \\
4 & 46.10\% & 43.31\% & 43.56\% & 43.52\% \\
5 & 55.87\% & 52.28\% & 52.66\% & 52.66\% \\
6 & 68.07\% & 62.65\% & 63.15\% & 63.09\% \\ Time(\(t\)) & 7 & **77.54\%** & **70.75\%** & **71.51\%** & **71.44\%** \\
8 & **77.54\%** & **70.75\%** & **71.51\%** & **71.44\%** \\
9 & 68.85\% & 63.01\% & 63.69\% & 63.65\% \\
10 & 58.40\% & 53.64\% & 54.30\% & 54.36\% \\
11 & 46.04\% & 42.77\% & 43.40\% & 43.38\% \\
12 & 37.85\% & 34.90\% & 35.49\% & 35.47\% \\
13 & 30.21\% & 27.79\% & 28.33\% & 28.33\% \\
14 & 23.35\% & 22.75\% & 23.07\% & 23.07\% \\
15 & 19.08\% & 19.03\% & 19.52\% & 19.45\% \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Comparison of Total Performance Improvement for 100, 1.000, 10.000, and 100.00 repetitions between CoMoRe and CCMM methods for 10 workers and tasks (\(n=10\)). the plans for change are more likely not to be rejected in the early stages, something that usually happens in the change management process. From the above data, it is evident that a specialist change process manager has the tools to deal with the RIC effect as a consequence of change and make optimal decisions.