Written By Mihály Fazekas, 2 Jun 2015

Governments spend a significant portion of their budgets on public procurement: 19-53% of general government spending (OECD, 2011). However, the efficient and clean use of these resources is a fundamental concern across the globe. The lack of active transparency (i.e. the usability of disclosed public data – see embedded figure) and many ‘red flags’ of corruption and collusion suggest serious inefficiencies, jeopardizing countries’ competitiveness and growth prospects. Hence, the aim of DIGIWHIST (“The digital whistleblower: Fiscal transparency, risk assessment and impact of good governance policies assessed”) research project is to address these problems with innovative open data tools which make public spending more transparent, understandable and accountable.

Number of different standard forms used for publishing call for tenders, contract award announcements or contract completion announcements by country, 2009-2014, Nform=444, Ncountry=30

In the course of 2016, Digiwhist will develop and release an extensive database containing public procurement data from 34 European countries and the European Commission itself. It will do so following the Open Contracting Data Standard, while also extending it with a range of further collectible and relevant variables. As European countries don’t yet publish according to the Standard, Digiwhist will map country publication practices and design an open data tool translating current diverse data formats into a single standard format.

However, transparency of tender level data is often not enough, if one wants to understand thoroughly the possible inefficiencies encircling public spending. This is why public procurement data will be linked to company information, such as owners and profitability; public organisation data, such as deficit or number of employees; and political officeholder data, such as asset declarations.

While such a ‘Big Data’ approach is attractive to the technologically savvy, for most stakeholders a set of user-friendly indicators is the key to benefiting from the Digiwhist database. To address that need the project will generate a set of risk indicators or proxies for key aspects of corruption, collusion, transparency, and efficiency. These indicators solely derive from ‘objective’ administrative data while being fully actionable— that is, actors’ behavioral change would influence indicators allowing for assessing impact. For example, introducing the mandatory disclosure of government suppliers’ final beneficial owners could have a profound impact on corruption risks and bidder composition.

However, ‘Big Data’ can take us only so far, leaving one to wonder how to draw upon the rich local knowledge of those who directly experience procurement projects— and their results. Digiwhist will bring the large-scale data and risk indicators together with stakeholders’ local knowledge. This will be done through a set of national portals and web applications in each national language, enabling citizens and companies to directly add supplementary local information to every contract. Therefore, it will be possible to evaluate micro-level tendering information on e.g. extremely tight bidding deadlines, while having information on the winner companies’ political connections; while combining these with information from the ground on the appropriate or unsatisfactory fulfilment of a given contract. Imagine having not only the risk indicators of a highway contract, but also local photos evidencing the low quality of construction, e.g. potholes or missing parts.

The Digiwhist theory of change builds on the expectation that high quality open data and clear indicators on public spending and the use of public resources contribute to greater transparency. This, in turn, enables citizens and businesses to hold governments accountable and to improve the efficiency of government decisions and resource management. Actionable indicators in the hands of those stakeholders who lose out to corruption such as excluded bidders or citizens not receiving the quality services they expect help to organize them against corruption. The visibility of who is losing and the cost of corruption combined with an increased capacity of losers to organize themselves together are able to increase the control of corruption even in high corruption risk countries.