Towards New Methodologies of Measuring Cost Efficiency and Cost Effectiveness of Geospatial Data

The difficulty in assessing the cost output and outcome for Geospatial Data Infrastructures (GDI’s) can be traced back to the differences between the various models and techniques that are applied interchangeably. These include economic models, statistical techniques, responsibility accounting and value approaches. Various publications have described either estimates of the total cost, possible benefits or alternative funding mechanisms needed for a GDI’s. Furthermore, a number of studies have been carried out to make an assessment of the cost of implementation in relation to the potential capitalized benefits. Most of these publications acknowledge that it is difficult to make a proper assessment of its cost, and even more difficult to assess its benefits, simply because most are very intangible. In one cannot properly assess the cost and benefits, than how can one even discuss mechanisms for funding, cost recovery free access? Are in fact the right questions posed for the right purpose? Perhaps the difficulty in estimating the benefits is not in the evaluation of benefits in relation to the cost, but already the proper assessment of the cost itself. Furthermore, the reason to address the cost and benefit question is in fact whether processes, structures and institutions are effective and efficient. Therefore, a different sort of cost measurement assessment may need to be made, focusing more on relative efficiency and effectiveness rather than absolute cost and benefits measurements. This article aims at addressing this issue of cost assessment from various perspectives. It is observed that, although obviously completely different in nature and results, the approaches in the research for health care, technical capital assets or environmental costs and impacts are useful for the question how to approach the GDI cost, cost efficiency and cost effectiveness questions. Similar to these other sectors the GDI concept doesn’t seem to fit either micro-, macroor other economic theories, which makes that – in addition to the various definitions which are around for GDI, resulting in semantic differencesthe system boundaries are not clear. The activities and the actors are operational in a network of national, organizational, inter-organizational and individual related parameters. The behavior and the benefits of GDI are therefore not conform either one or the other economic theory, but will have to rely on individual kinds of approaches. As a result, one can typically observe a difference in approach between a variety of micro-analyses within organizational or business boundaries, cost spending comparisons from a user perspective, sector or activity based cost impacts or national statistics showing public versus private spending, amongst very many others. The conclusion is that the cost of GDI problem needs to be decomposed into various approaches. These include microanalyses, activity-based analyses, cross-sector analyses and trans-organizational analyses such as virtual enterprises. Each of these approaches could contribute in its own way to the GDI and cost related questions. In particular the paradigms of value options approaches and that of virtual enterprises may provide the mechanisms to evaluate cost efficiency and effectiveness at a general level, whereas a practical way to control output performance norms could be to relate it to results obligations. A combination of these would relate the objectives of GDI to its actors, its activities, its market and its performance.