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Business process maturity of the transport-forwarding-logistics sector in Poland

Sawicki P., Jaworek P.

Research in Logistics & Production

2017

Vol. 7, No. 4

337--350

The paper deals with the evaluation of business process management development of the Polish TFL (Transport-Forwarding-Logistics) sector. Up to date, several studies of this type have been conducted, but TFL sector is marginally represented there or even omitted. Therefore, the authors have conducted their own research filling this gap. They have compared the results with the previous studies, as well as identified key determinants of the specific level of process maturity. Generally, there is no dominant level of process maturity at TFL sector in Poland. In particular, the lowest frequently occurred process maturity is level 3 (defined), which is typical for 15% of companies. The grades of other levels are bi-polarized below and above level 3. The largest group at TFL sector (a total of 44%) has been classified at level 2 (managed) and 1 (initial), with 25% and 19% of companies, respectively allocated there. The remaining companies are classified at level 5 (optimizing), and 4 (quantitatively managed), with percentage of 23% and 18%, respectively.

Szacowanie wskaźnika błędów jako narzędzie zarządzania jakością oprogramowania z uwzględnieniem modelu CMMI

Lotko P., Lotko A.

Problemy Jakości

2009

R. 41, nr 4

30-33

A process of software development is highly specific and it is especially hard to manage quality in it. One of the tools in this domain is, described in the article, the CMMI (Capability Maturity Model Integration), which integrates good practices concerning products or services development and maintenance. The model also makes it possible to perform a rating on a scale of maturity levels. From the 4th maturity level (quantitatively managed), an organization is expected to have quantitatively (i.e. with the use of mathematical models) expressed quality goals and use them as criteria in managing processes. In the article, a model estimating the defect rate in delivered software is presented. The model uses a quadratic regression function on the basis of the defect rate found during internal software tests and the length of engineering phase of the project.