Methodology for business processes optimization within the dynamic model for business processes improvement

Introduction. An organization, which should be competitive on the market, has to have a set of qualities. They include operational productivity, administrative efficiency, agility, shorter turnaround times and increased shareholder value. The key for reaching those results is the business process improvement. The main objective of business process improvement is identifying and eliminating of those, which are of non-value-added, as well as those should be simplified, which bring less or greater value-added of an organization. A continuous process most often leads to a change in both the production and the managerial structure. This change requires a reorganization of existing business processes, which in turn leads to the need of their improvement. Optimization should be consistent with the chosen strategy and company structure. One of the most important strategies in organizational performance is applying the outsourcing i.e. some inter-organizational to give up outside supplier. In this connection, one of the fundamental problems in organizational management is suitable selection of business processes supplier. In this connection the organization, must research the relationships between level of supplier selection factors and level of business process improvement factors. Further, the business process’s improvement should take into consideration the following aspects: “flexibility” — showing the possibility of the managing bodies to take decisions related to the strategic reorientation or revision of the goals in accordance with the changes in the environment; “wholeness” — the existing and potential relations and interactions among all activities, processes and business processes in the organization to be used in order to achieve the specified common goal; and, “strategic range” — all events related to the business process optimization have to be in conformity with the company strategy. The practice shows that the applied methods of optimization would be more efficient, if you take into account the dynamics of the reasons that starts the improvements. The dynamic model of business processes improvement presents the optimization itself like a process, which is developing in time. It examined the reasons of improvements in their development and combines described features. It is constructed of three modules. The first module is functioning as an early warning system and is monitoring the presence of changes in the organizational environment. In the second module, the actual improvement of the processes is done and the third one depicts system of objectives in the organization.

The purpose of this paper is to present a methodology for the optimization that is used in the second module of the dynamic model of business processes improvement.

Essence of optimization. In the dynamic model for business process optimization, the improvements can be divided into two stages, running one after another — preparatory stage and optimization stage. In the first stage, the real business processes are aggregated and presented as vectors — resultant vectors. The goal of the improvement is also presented as a vector, called the goal vector. After the transformation, the comparison between the resultant and the goal vector is made in the optimization stage. If the comparison shows deviations in favor of the goal vector then is needed depth analysis and improvement of the process. Otherwise, it is concluded that the existing company process is better than the specified goal. Therefore, there is no need of improvement. The mathematical laws to calculate the vectors are used for conversion, comparison and improvement of presented processes.

Preparatory stage of optimization. Preparatory phase of the optimization consists of several phases that must be pass through.

GSL News: latest news in the field of Russian and international law, taxation, audit.
Phase 1: Consistent presentation of the processes. All processes in the organization, even parallel flowing, should be presented in a consistent form. This is necessary for two reasons. The first is associated with clear and precise process visualization. Another reason stems first from the need of assess the condition of the entire process chain and on this basis to make improvements in critical processes. The practical implementation of this phase is possible because the visualization of the process is essentially an abstract action.
Phase 2: Defining range of the observation. The range is determined by the needs of the researcher/user of information. The size of the vector must be selected according to these requirements.

Phase 3: Collecting the necessary data. The collected data must be objective and qualitative. For presentation of a business process as a vector is necessary to use the appropriate data for each constituent process or activity. The required information must correspond to the real characteristics of the object. The primary data needed to build a vector most often are obtained from the implementation plan, from the control system or from used software. Furthermore, the information must meet to three conditions: First, all data must be generated from a one single source. Second, when a process goes through different departments and there is no centralized unit to generate a summary, each department generates data. They are collecting and assessing, then some information might be neutralized. The third condition is related to the dimension of the data. The parameters of the process must be in the same dimension.

Phase 4: Classification of the components of the parameters. This classification is important for the actual process’s improvement at the optimization phase. Components of the parameters are divided into positive and negative. The positive elements of the parameters should be increased in the process of improvement. Conversely, negative elements are variables that need to be reduced. This separation of the elements that build parameters is an abstract and not related to the mathematical sense.

Phase 5: Determination of collective and non-collective parameters. Collectives parameters are those whose individual vectors can be calculated in absolute terms. This stems from the fact that with the actual values can be made specific calculations. Non-collective parameters are not calculated in absolute terms, because it will lead to the wrong result. These parameters are calculated in relative terms, but individual components are directly related to the business process. Then must be determined the ratio of each parameter into the total score. The result is used to correct each parameter.

Phase 6: Determination the number of axes of the coordinate system. The number of axes depends on the number of observations. For each next observation, it must be added an axis and spatial dimensions are increased. Each axis is named to one parameter in the coordinate system.

Phase 7: Transformation of real business process to vector. On this phase abstractions of real processes is performed. Each process step is represented as a vector. The sequence and length of vectors are identical with process steps. Transformation must start from the zero point of the coordinate axis. The end of the first vector marks the end of the first process step. The start point for the next step represents the end of the previous vector. In a way it builds, vector which describing the second step and each other to the end of the business process. The length and direction of each vector depends on the values of each process step. These values are presented as scalar magnitudes, building a vector (partial vectors). The real process values will correspond to end of the vector that is built at the beginning of the coordinate system or the end of the previous vector. Mathematical representation of the vector is actually a description of the vector components. The procedure for the conversion of real business process to vector must be repeated until entire process chain of the organization is visualized.

Phase 8: Calculation of the resultant vector. The process of optimization requires evaluation and improvement of both individual process steps (partial vectors) and sum of all vectors. For this purpose, the resultant vector is calculated which the sum of all vectors is corresponding to each step of the process.

Phase 9: Calculation of the weight of individual vector components. Individual components of the resultant vector can be weighted depending on the chosen improvement goal.

Phase 10: Construction of goal vector. For this purpose, it is necessary to construct a vector that represents the purpose of improvement. Firstly, the goal is marked on the coordinate system. Then from the start point of the coordinate system to the point that indicates the desired improvement descends vector, called goal vector.

When the phases of the preparatory stage are completed must be pass to the optimization stage.

Optimization stage.

Phase 1: Determination of the process effectiveness. First, we have to determine the effectiveness of the real process. In case of deviation, it can be calculated with how much of the value each vector component (each process) is needed to improve to achieve the “ideal” goal. Measure of efficiency is the ratio of the “overall efficiency”. When an overall efficiency greater than zero — the goal vector is larger than the resultant. There- fore, the goal process is more effective than the real one. In this case, it has to proceed to the subsequent steps and measures for process improvement. Otherwise, the real process is more efficient than the goal one and optimization is not currently needed.

Phase 2: Determination of potential of improvement. At this stage of optimization a comparison between the sub-processes of the real and the goal process is made. This is done by comparison of their vector component (partial vectors). The potential for improvement is based on the calculated single effectiveness of each single vector. Partial real vectors are subtracted from the partial goal ones to form a new resultant vector. It corresponds to an absolute goal for improvement for each process. If any of the compared vectors that formed new resultant vector is less than zero, the real process is more efficient than the goal one and vice versa.

Phase 3: Setting the priorities for improvement. Prioritization of the objects of optimization is complementary to the second phase. From the sum of all processes in the organization must be selected those that will affect the achievement of the objective. Comparison between the positive and negative components to the partial goal and resultant vectors is performed. In this case, the difference between them will be a single rate of efficiency. If the coefficient is greater than zero, partial positive vector components dominate. Although the goal vector is more effective than the resultant one, optimization is not required.

Phase 4: Determination of parameters of the goal vector. In this phase, the goal vectors are analyzed and evaluated. It provides an opportunity to assess the individual sub-processes of the goal process. It is idealized and does not know whether the number and length of its sub-processes coincides with the real process. This information can be obtained through the early warning system and other specialized sources.

Phase 5: Application of improvement tools. The goal in the fifth phase in the model for business process optimization is to implement a set of tools through which real critical processes are transformed into goal one.

Phase 6: Evaluation of the results of improvement. In the sixth phase, imitating the organization and its processes is done and obtained results can actually be put into practice. Verification to achieve the common goal with improving the real process is performed through the simulation. Simulation process can be repeated to achieve more stable parameters of improvement.

The term Offshores” or “offshore corporation” is used in at least two distinct and different ways.


Reorganization of real business processes is done through the described methodology for process improvement. The parameters, under which the optimization is done, may be n-number depending on the necessity. To achieve stable parameters of improved processes the process improvement itself can be divided into two main phases — preparatory phase and optimization phase. In the first phase, the goal and the real process are presented as vectors. In the second phase, have to make the comparison between these two vectors. In case of deviations from efficiency in favor to the goal process, must proceed to determination the potential and priorities for improvement. Then have to be implement improvement tools and have to be perform simulations to determine the rate of achievement of corporate goals. The practical application of presenting methodology in combination with early warning system, where the monitoring of organization environment is done, allows the achievement of sustainable and efficient improvements of all processes in the organizations.

Source of the article: