Continuous Improvement Maturity Models: How to View Them Effectively

Continuous Improvement Maturity Models: How to View Them Effectively

DOI: 10.4018/IJSSMET.2019100102
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Maturity models seek to enhance a business with the passage of time. The purpose is to attain a competitive advantage. Various maturity models are accessible, including the continuous improvement maturity model (CIMM). The model offers outstanding techniques and practice models in addition to tools, skill sets, and a proper mindset to process improvement. This article analyzes the need for Continuous Improvement Maturity Models in a company. Hence, the current maturity of a company cannot be indicated by this model. There is a need for progress and knowledge to combine and improve the company's level of maturity. The model assessment refers to an instrument that is research-based and assists the users to set a goal assessment of the maturity level. The purpose of designing this model is for it to be utilized by any manufacturing company. A series of repetitive phases are required by this instrument, and its moderations and validation are based on various case-studies and semi-structured interviews conducted with experts.
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McDermid and Bennet (1999) contended that the human variables to Software Process Improvement (SPI) had been overlooked, which harms their adequacy. Hall & Wilson (1997), likewise, proposed that involvements, feelings, and impressions of programming experts are affected because of the nature of programming created. This suggests such properties impact how programming experts carry on towards SPI execution approaches. In this manner, it is vital to distinguish the perspectives and views of diverse professionals about components that play a positive or negative part in the usage of the SPI program (Galli, 2017). These perspectives and encounters may furnish specialists with adequate information about the idea of issues that play a positive or negative role in the usage of SPI programs. Undoubtedly, this would help them in arranging SPI execution techniques.

Various empirical studies considered the aspects that negatively or positively impact SPI (for example, El-Emam et al., 1999; Rainer & Hall, 2003). A study of 138 people in 56 programming associations (Goldenson & Herbsleb, 1995) recognized the components vital for executing an effective SPI program. The creators distinguished related variables to effective as well as unsuccessful SPI programs (Goldenson & Herbsleb, 1995). Research of 56 programming associations that either executed an ISO 9000 quality framework or led a CMM-based process change activity. Based on this research, there were ten factors that influence hierarchical change in SPI (Stelzer & Mellis, 1998).

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