ANÁLISIS DE LAS HOJAS DE COSTOS

The two figures discussed and presented in this section might be considered the crux of evaluating this research. Comparing the two

representations of the data at milestone 4, allowed the Researcher to test the question posed at the start of this thesis: “can 3D Information Visualisation provide construction clients with informative performance reports”?

It is important to remember that these milestone reports were not actually presented to the RSL Informants in the paired format shown in figures 8.11 and 8.12. The RSL Informants did not see both the s-curve and the data surface simultaneously. For each scenario/visit, the s-curves were shown first and then all of the data surfaces. The pairs are shown here in this format only to aid reader comprehension of the comparisons that were made. For example, see Chapter 7, hypothesis 1 which uses the mean

questionnaire scores to compare an RSL Informant's ability to assess current status. Effectively, it is each Informant’s response to the contrasting pairs shown in Figures 8.11 and 8.12 that determines whether they correctly identified project status at milestone 4. This identification was achieved by informants’ selection of the status codes at the end of each prototype questionnaire (see last section and Appendix 9).

For each pair shown, the s-curve is a two-month segment from the entire project Earned Value s-curves from the last section (Figures 8.9 and 8.10). Rather than covering a temporal period, the data surfaces reflect project status at a time T . Therefore, it should be noted that, for each pair, the real comparison is being made between the data surface and the s-curve at its right hand month boundary. It should also be re-stated that the s-curves

are showing overall project status, whereas the data surfaces present the

performance of individual tasks (here only at the summary task level). There may be corresponding high or low peaks between the two representations. However, it is also possible for the data surface to peak on an individual

project task, with no obvious correlation on the entire project s-curve. It is important to remember that the two visual methods are not directly

comparable. Procession only reports exception to the project's baseline cost and time.

Presenting Figures 8.11 and 8.12 in a paired format (s-curve vs. data surface) is not intended to assist the reader in understanding the data

presented. Rather, it is to aid the reader’s appreciation of the differing visual structures that formed the basis for comparison. By definition, 3D data

surfaces become more intelligible when a user exploits the added dimension by navigating, examining, rotating etc. For example, text that is difficult to read from one angle may become clearer when zoomed. Therefore, when viewing the 3D data surface element of each pair (Figures 8.11 and 8.12), it may prove difficult to appreciate the intelligibility that was added to the data. Ultimately, any improvement was best reflected by user satisfaction.

However, the paired visuals for each scenario are presented here (at

milestone 4), in order to compliment the reader’s overall grasp of the chosen methodology. In Figures 8.11, the colour scheme of the 3D data surface has been reversed to enhance the limited resolution possible with a screenshot.

At this point, it should be noted that the Earned Value s-curves for the entire project (Figures 8.9 and 8.10), do not show the actual project end. Both of the curves end at milestone seven, the baseline project end date. As there is slippage in both scenarios, complete s-curves would extend well beyond the base-lined timescale.

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Figure 8.11 Scenario 1: Earned Value s-curve at milestone 4 (top) as compared to Procession Initial Prototype vl.1 data surface (bottom), source:

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8.9 Chapter summary and contextualisation

This chapter has taken the theoretical evaluation methodology outtned in Chapter 7 and populated it with ‘live’ data for the two scenarios. In this case, preparing the files for Procession was over-complicated by the data not being in the Microsoft Project format. In addition, only basic schedule

information was available and estimated costings had to be added. Finaly, Monte-Carlo simulations were used to produce scenarios that seemed

statistically likely to result from the data. Traditional s-curves and Procession data files were produced for each scenario.

The completion of the work in this chapter represented the last stage before the evaluation of Procession. The Researcher now had an initial software prototype (Procession v1.1 ) and two fictionalised project scenarios with related 2D s-curves and 3D data surface files. The next chapter provides the results of the evaluation process, for both prototypes.