# A Continuous Monitoring and Reallocation Method for Successful Decisions in Change Management
## 3 The Continuous Monitoring and Reallocation (CoMoRe) Method  
### Problem Description  
The problem that we attempted to solve in this work concerns the management of employee resistance to change. Although the change is intended to improve performance through the transformation of the business, we usually see the opposite. This happens in many cases because the expected change is not fully implemented as a result of strong resistance to transformation efforts. The process of change is described by a change curve in the literature [5]. First, there is a sharp drop in employee performance, and then it takes a significant amount of time for the desired result to be achieved. In many cases, this drop and the corresponding time can be so critical that the change plan is ultimately abandoned.  
The NuRe method [51] is the first attempt to extend the classic idea of the HRAP by incorporating continuous monitoring. During the period of change, the manager continuously monitors staff performance and decides when to perform a single reallocation of staff to tasks. This reallocation reduces the overall resistance of nurses to using a new health information system.  
The proposed continuous monitoring and reallocation (CoMoRe) method extends the idea of the NuRe method by continuously readjusting staff allocation throughout the process of change at regular time intervals. In this way, the RtC of each employee is taken into account regularly, and the assignment can be altered in the early stages of change. It is posited that through implementing this regular readjustment, the task performed by each worker will be optimized for maximum performance. Although the idea of continuous monitoring and reallocation can be applied to all change management problems, in the following, it is applied to a simple problem governed by the following constraints:  
1. Every task is assigned to only one worker.
2. Every worker is assigned to only one task.  
In addition, the following assumptions are made:  
1. Each worker will be able to carry out all available tasks.
2. Each worker has an initial known performance for each task.
3. The resistance presented by each worker during the change period follows the change curve model [5].  
More specifically, suppose there is a business that wants to make a change in a process that includes \(n\) jobs carried out by \(n\) workers. The business aims to be the most productive and utilize human resources to achieve the greatest overall performance. This can be accomplished by optimizing staff allocation. When the change process begins, individual performance will change due to the effect of resistance to change. The goal of the business remains the same. In addition, the business wants to minimize the time required for change implementation and achieve a positive effect on overall performance. The formulation of this problem is based on the mathematical model of the HRAP. The objective function includes the performance \((Pij)\) of each employee \((i)\) in each task \((j)\). This objective function should be maximized to achieve the best performance. The mathematical model of performance is formulated in the following.  
Proposed mathematical model--objective function:  
\[\text{Maximize}\sum_{i=1}^{n}\sum_{j=1}^{n}P_{ij}x_{ij} \tag{5}\]where _Pij_ is the performance when worker \(i\) is assigned to task \(j\), subject to the following constraints:  
\[\sum_{i=1}^{n}x_{ij}=1\quad\forall j=1,...,n \tag{6}\]  
\[\sum_{j=1}^{n}x_{ij}=1\quad\forall i=1,...,n \tag{7}\]  
\[x_{ij}=\begin{cases}1&\text{if worker $i$ is assigned to task $j$}\\ 0&\text{otherwise}\end{cases} \tag{8}\]