What is Value for Money ?
The UK Department for International Development (DFID) defines Value for Money (VFM) as “maximising the impact of each pound spent to improve poor people’s lives.” (DFID, 2011). This echoes the UK National Audit Office’s definition, which defines VFM as being “the optimal use of resources to achieve intended actual outcomes”. A key element in both definitions is to make the best use of available resources to achieve sustainable development outcomes.
VFM can be measured on the basis of a set of standard indicators, which can help programme implementers (and their funders) assess whether or not their programmes are making the best use of available resources and whether the use of resources for these programmes are most beneficial from the public purse’s point of view. Answering those questions is neither an easy nor an immediate task: it requires conducting a “VFM analysis”, i.e. collecting and analysing data on the costs and results of the particular programme and interpreting the VFM indicators generated in such a way by comparing them with those of other programmes.
A key objective of conducting a VFM analysis is to help managers improve programme performance. It can give programme managers useful metrics to quantify the impacts of challenges they observe on the ground and identify the best interventions to address those challenges, which could include the reallocation of resources.
Crucially, a VFM analysis is not necessarily about saving money and reducing unit costs: it is about maximising actual outcomes and impacts. Whilst the VFM of a programme could sometimes be improved by reducing the costs of certain inputs, greater and more sustainable actual outcomes can also be delivered by spending more on certain inputs.
Interpreting the results of a VFM analysis requires putting VFM indicators into context. Indeed, costs and results are context-specific: the per capita cost involved in drilling boreholes in a remote part of arid northern Nigeria will inevitably be higher than in a community near a major town in the more accessible southern part of the country. So in this case, high input costs do not necessarily mean that the programme could be run in a more cost-efficient manner: they would simply reflect different operating conditions.
It results that a VFM analysis should consider all contextual elements for the programme: it is essential to gather as much information as possible on the operating conditions for the programme, its operating modalities and approaches. Therefore, we strongly recommend that a VFM analysis be considered as a tool to be added to the essential toolbox of programme managers and evaluators rather than being considered as a stand-alone piece of analysis.
VFM analysis: process overview
A VFM Analysis consists of gathering data along the programme’s results chain so as to be able to estimate VFM indicators across the five dimensions of VFM analysis, i.e. economy, efficiency/cost-efficiency and effectiveness/cost-effectiveness. A standard WASH results chain is presented below, whilst key VFM indicators are presented overleaf.
Figure 1. The WASH results chain
A VFM analysis starts by defining the scope for the analysis: which programme, across which territory, over which period. It will then be necessary to map the programme’s results framework against the WASH results chain diagram in order to identify and gather relevant data, both qualitative and quantitative. The VFM analyst can then compute the data to generate a set of standard VFM indicators, which can be compared across programmes in the same country or internationally. These results can then be used by managers to identify strengths and weaknesses in their programmes and understand what might drive the indicators (through qualitative analysis combined with regional and temporal comparisons).
The WASH results chain is composed of seven main elements:
1. Costs – the financial costs of inputs;
2. Inputs – the resources used, in terms of finance and staff time (capital and labour);
1. Process – the process by which inputs are transformed into results. Such processes can be the object of a programme evaluation but cannot be quantified through VFM analysis;
2. Outputs – the direct deliverables of the programme (number of water and sanitation facilities built, number of activities implemented such as CLTS triggering, etc.);
3. Assumed outcomes – the assumed outcomes resulting from the outputs, e.g. the is number of beneficiaries assumed to have gained access to WASH services as a result of the outputs of the programme’s interventions, based on existing standards and assumptions at country level, or based on lists of households;
4. Sustained actual outcomes – i,e, the actual change in poor people’s lives over time, such as the number of new people moving from using an unimproved water point to an improved one. The key difference with “assumed outcomes” is that “sustained actual outcomes” are measured based on household survey data before and after an intervention (e.g. 6, 12, 36 months after); i.e. based on the difference in key variables at baseline, endline and beyond. This captures the extent to which the outcomes have been achieved. Such data are only available if robust M&E and data collection frameworks are in place, which is seldom the case.
5. Impacts – the longer-term impact of the WASH programme, including the impact on health and education, e.g. reduced diarrhoea, increased school attendance, attendance, and on poverty reduction, which is the ultimate intended impact of DFID programming.
Table 1. Five key dimensions for evaluating VFM of WASH programmes
It is also important to consider sustainability and equity as an additional layer of analysis that cuts across the main VFM dimensions. The sustainability of programme results can be considered when measuring effectiveness and cost-effectiveness, as both are based on “sustained actual outcomes”. Equity can be considered at the level of outputs (the extent to which the programme has targeted outputs to address priorities in terms of improving equity) and at the level of sustained actual outcomes, where actual data on results at the level of the beneficiary population are collected. VFM analysis can assess whether the programme has been efficient at reaching targeted beneficiaries and can look at the costs per result for different groups. These groups can be defined in many ways, depending on how inequity manifests itself, i.e. through differences in income, gender, or social groups (e.g. castes).