Open AccessModel of optimal organization maturity management under conditions of interference and uncertainty
Author(s) -
Mikhail Dorrer
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1399/3/033086
Subject(s) - maturity (psychological) , kalman filter , service integration maturity model , capability maturity model , process (computing) , computer science , state vector , work (physics) , control (management) , operations research , process management , control theory (sociology) , mathematics , engineering , artificial intelligence , mechanical engineering , psychology , developmental psychology , physics , software , classical mechanics , programming language , operating system
The article proposes a mathematical model of the optimal process for managing levels of organization maturity in the presence of interference in the source data. This work is a part of the solution to the more general problem of developing a system for managing the maturity level of business processes in an organization. Changes in organizational maturity of a company are described in terms of a managed dynamic system. It is shown that such a model adequately reproduces a number of effects in the behavior of the system of indicators of the organizational maturity of the company. The paper uses the method of analytical design of optimal Kalman-Letov regulators (ADOR), as well as a recursive Kalman filter that estimates the state vector of a dynamic system based on incomplete and noisy data. The constructed model demonstrates plausible behavior in predicting the process of organizational maturity managing. Reproduces the effect of accelerated growth of controlled indicators defined as a priority in the model. Using the Kalman filter allows one to form a control action on the dynamics of organizational maturity indicators in such a way that the target values of maturity levels are achieved even under conditions that are significantly distorted when measuring the initial data. The proposed methodology for optimal management of the organization’s maturity level is demonstrated by the example of evaluating and forecasting the maturity level of one of the departments of a technical university.