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Unfortunately no significant statistics could be obtained for the mapped maturity models (CMMI, P3M3 and SE-CMM) for various reasons. These models are either relatively new (CMMI) or not implemented to the same extent as the SW-CMM (P3M3 and SE-CMM) and do thus not possess similar statistics. The reason, however, that these statistics were considered for normalising the mapped models is that the SW-CMM forms the basis of the majority of maturity models and the three mapped models in particular. CMMI and SE-CMM were developed by the same institute as SW-CMM, the Software Engineering Institute of Carnegie- Mellon University (CMMI-SE/SW/IPPD/SS, v1.1; SE-CMM, v1.1), and P3M3 regularly quotes, makes reference to, and claims to be derived from the initial works of the Software Engineering Institute (P3M3, v0.1). Process area structuring of the three selected models is thus extremely similar in nature. This structuring has probably the strongest impact on maturity level progression, which therefore allows for the consideration of the abovementioned statistics.

Furthermore, it was anticipated that more value would be derived for the maturity model lifecycle impact mappings if these median transition times were used to normalise the impact values aggregated per maturity level, even though the statistics used were not directly derived from the appropriate maturity models. Mappings not normalised present an extremely skewed picture of the impact of maturity levels, with the full lifecycle impact and support of maturity levels 2 and 3 far exceeding those of levels 4 and 5.

It can be argued that this is accurate when one considers the benefit brought about by later maturity levels. As the enterprise embarks on a mission to improve capability, the initial benefits experienced are large. The rate of improvement, however, slows with higher maturity levels, and thus slows the experience of benefits. This mapping is, however, not one of benefits, but rather one of lifecycle impact and support, both direct and indirect. Although impact and support could be considered benefits, they are often not linearly correlated and the benefits are often unquantifiable. It is felt that the impact on lifecycle activities is therefore better correlated with the time it takes to fulfil a certain maturity level, rather than the number of process areas within that maturity level. However, it is unfortunately not currently possible to test this

hypothesis, as there are no available statistics describing the impact of maturity levels on lifecycle phases. This study thus presents the first attempt.

2.3 Summary of mappings

In an effort to minimise the content of this dissertation, the detailed mappings have been omitted and replaced with a summary thereof. The intention of this summary is to condense the information depicted therein, and extract only what is crucial to fulfilling the objectives of the mapping process.

There are two types of summaries. The first (Table 12 – Appendix A) is a basic, tabulated extraction of the impacts of the maturity model levels (aggregation of the process area impacts) on the phases of the three lifecycles and then the total support (aggregation of maturity level impacts) provided by the maturity models for each of the phases of the three lifecycles.

The second summary constitutes three tables (Table 4, Table 5 and Table 6) – one for each of the selected models. Each table is sub-divided into the three lifecycles onto which the maturity models were mapped. Each of the sub-divisions is then further divided into four descriptive categories (columns) that collectively summarise the impact (or lack thereof) of a maturity level on a specific lifecycle. These categories are as follows:

 Impacted Phases – Lifecycle phases exhibiting an aggregated and normalised impact of more than or equal to 75% of the maximum aggregated and normalised impact for a specific maturity level and lifecycle.

 Primary KPA Contributors – Key Process Areas (or just process areas) that were found to be significant in their contribution to the realisation of the abovementioned impacted phases. Certain rules were devised to create a boundary that would separate impact contributing process areas from non-impact contributors (see Table 3).

 Non-impacted Phases – Lifecycle phases exhibiting an aggregated and normalised impact of less than or equal to 40% of the maximum aggregated and normalised impact for a specific maturity level and lifecycle.

 Comments – A brief description of the impact profile of a specific maturity level on the various phases of a specific lifecycle based on the abovementioned findings.

Aggregation, as mentioned above, refers to the summation of all process area impacts within a specific maturity level for each lifecycle phase. Normalisation was then performed for each aggregated maturity level impact based on the amount of time it takes to fulfil the requirements of a specific maturity level (see Section 2.2.4). A percentage of the maximum aggregated and normalised maturity level impact (for the specific lifecycle and maturity level) was then determined for each of these aggregated and normalised maturity level impacts.

Note that analysis of and comparison between lifecycle phase impacts was performed on a relative basis. The various phase impacts of a maturity level were compared with the phase receiving the highest perceived impact (percentage thereof calculated) for the specific maturity level. All summaries and interpretations will thus be made in relative terms, i.e., relative to the most significantly impacted phase.

Table 3 provides the minimum combinations of phase impacts of specific process areas on those lifecycle phases identified as impacted phases (above 75% of maximum). Note that not all possible combinations were considered, but rather only those that were encountered.

No. of phases identified as impacted at a specific maturity level

Minimum process area impact RATING combinations 1 3 2 4/1, 3/3 3 4/1/1, 3/3/2 4 4/2/1/0, 3/3/2/2, 3/3/3/0 5 4/2/2/1/0, 3/3/3/2/1, 3/3/2/2/2