Refurbishment planning
200 180 160 140 120 100 80 60 40 20 0
Re-felting of main flat roof (phase 2): DSM1 (No precedence) Re-felting of main flat roof (phase 2): DSM2 (Guaranteed source of materials and contractor taking precedence) Re-felting of main flat roof (phase 3): DSM3 (BREEAM requirement taking precedence)
1.0
0.8
0.6
0.4
122 74 94
142 83 92
135 85 90
175 110 117
140 88 102
0.2
0.87 0.53 0.67
0.92 0.54 0.6
0.92 0.58 0.62
1.0 0.63 0.67
0.93 0.58 0.68
0 Option A Option B Option C Option D Option E Figure 4: Non-Financial preference ranking.
option, based upon the NHS/PSCP consensus on each comparison. Figure 3 shows the ‘non-financial preference’ in the ‘Total score’ column.
Consideration of cost issues What Figure 3 also illustrates is that a Benefit to Cost ratio function is designed into the prototype. Once the costs, or estimated costs, of each option are entered, the Model automatically provides a Benefit to Cost calculated financial preference. The ‘Add DSM’ button, which is visible in Figure 3, replicates the matrix to allow for sensitivity analysis testing through revisiting the criterion precedence (this can be seen in Table 2). For example, the user may choose to re-run the model to identify attaining a BREEAM requirement as the most desirable criterion. This would exponentially adjust the final scores and financial preference rankings with no requirement for input or calculation from the user.
Option A Option B Option C Option D Option E Figure 5: Benefit to cost preference ranking.
Presentation of the results It was identified that another key driver for the Model’s development was to provide evidence that a measured, calculated, and formalised process had been undertaken in ascertaining VFM, and, as importantly, in visualising and recording the decision- making process in a recordable and demonstrable manner. To enable the results of the decision-making process, and the sensitivity analysis testing, to be clearly visualised, and available for inclusion within a report format, the results of each decision matrix are modelled as simple graphs. The graphs are programmed to be dynamic, and therefore will update as changes or amendments are made to the decision-making phase. Figures 4 and 5 show the sensitivity-tested results of both ‘Non-Financial Preferences’ and also ‘Benefit to Cost Preference Ranking’. A good indicator of the value of this process can be seen if Option D in the case study is observed. Although
significantly more expensive in initial cost terms (Fig. 3), both financial and non- financial rankings recognise this as the preferred, or ‘best fit’ option. It should, however, be re-emphasised that the comparisons shown in Figures 5 and 6 are resultant from the NHS/PSCP criterion and options preferences, and value judgements ‘specific to the facility in question’. Figure 6 shows the complete ‘Decision-
making’ page. The multiple decision matrices undertaking the process of sensitivity analysis, and the graphs comparing the non-financial and financial preferences, are clearly displayed, and are dynamically connected through pre- defined Excel coding. Two further link buttons are visible in Figure 6. One of these connects directly to the uploaded Indicative Cost Plan, and the other provides a link to a future worksheet, which will be designed to carry out a Lifecycle Costing analysis of each relevant element or sub-element.
Figure 6. Decision-making page showing Sensitivity Analysis and Report Function. 42 Health Estate Journal September 2013
Total score
BTC ratio
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