# 5. Conclusions and policy lessons

Based on the analysis, a set of data-driven policy recommendations can be put forward. Some of the recommendations provided in this section aim at improving the data infrastructure underpinning any future analysis, while others point at ways to improve public procurement policy and practice.

## 5.1. Improve the data publication framework

Data publication is generally of high quality, and a wide range of variables is available on the procurement notices. The share of missing data, including tender and organization identifiers, is low compared to many European countries. Yet, further steps are needed in the following directions:

1. Improve the access to and usability of the detailed public procurement data by introducing a bulk download option for structured data covering tenders published on both the old and the new national portals with clear distinction between tenders published according to the national threshold regulation versus those above the EU threshold regulation.

2. Limit the number of different publication templates. The use of 20+ different publication templates increases the chance of data errors.<sup>23</sup> Despite the many notice types, unawarded/cancelled contracts are only revealed indirectly in award notices.

3. Identifiers can be missing and not well structured, which makes it hard to connect tenders and contracts related to the same organizations. While the IDs for contracting authorities are mostly complete, unique identifiers are often missing for contractors.<sup>24</sup> 4. Missing values: certain fields are missing from the publications, such as information on subcontracting, consortia, or estimated prices. These should be stated explicitly in the source of each tender/lot.<sup>25</sup> 5. Additional data improvements: introduce clear correspondence between lots and resulting contracts. Multi-lot tenders often result in fewer contracts and it is not always possible to track such cases.<sup>26</sup>

## 5.2. Introduce continuous monitoring of corruption risks and use data-driven insights in day-to-day policy making

The analysis in this paper demonstrates the viability and potential of data-driven corruption risk analytics in Bulgaria and beyond. Communicating and making good use of such complex and rich datasets is nevertheless a challenge. Currently, a trove of datasets relevant to anti-corruption monitoring and policy making exists in Bulgaria. However, most users in the public sector and beyond lack advanced data science techniques to work with the data directly. Instead, users have varying levels and types of expertise, requiring a flexible and easily accessible way of communicating datadriven insights and supporting policy reform. This will be best achieved by using an interactive dashboard that contains not only the source data but also performance and risk indicators and warns the user about data quality shortcomings and analytical challenges. The dashboard could start by

> 23 For example, there are only three publications that are ‘Социални и други специфични услуги – комунални услуги’.

> 24 For example, https://app.eop.bg/today/121395, https://app.eop.bg/today/124511.

> 25 For example, each tender should contain explicit information on whether it is a public tender/framework/dynamic purchasing system.

> 26 Note that useful improvements have been already made to address this issue. Awarded contracts refer to lot numbers (or to a list of lot numbers) on the new procurement portal, which allows connecting lots with contracts in principle. Furthermore, the 2019/1780 regulation prescribes publishing item level submitted prices - albeit they are sometimes missing and the number of bids submitted to individual lots are not yet traceable.

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