Digital procurement governance: drawing a feasibility boundary

In the current context of generalised quick adoption of digital technologies across the public sector and strategic steers to accelerate the digitalisation of public procurement, decision-makers can be captured by techno hype and the ‘policy irresistibility’ that can ensue from it (as discussed in detail here, as well as here).

To moderate those pressures and guide experimentation towards the successful deployment of digital solutions, decision-makers must reassess the realistic potential of those technologies in the specific context of procurement governance. They must also consider which enabling factors must be put in place to harness the potential of the digital technologies—which primarily relate to an enabling big data architecture (see here). Combined, the data requirements and the contextualised potential of the technologies will help decision-makers draw a feasibility boundary for digital procurement governance, which should inform their decisions.

In a new draft chapter (num 7) for my book project, I draw such a technology-informed feasibility boundary for digital procurement governance. This post provides a summary of my main findings, on which I will welcome any comments: a.sanchez-graells@bristol.ac.uk. The full draft chapter is free to download: A Sanchez-Graells, ‘Revisiting the promise: A feasibility boundary for digital procurement governance’ to be included in A Sanchez-Graells, Digital Technologies and Public Procurement. Gatekeeping and experimentation in digital public governance (OUP, forthcoming). Available at SSRN: https://ssrn.com/abstract=4232973.

Data as the main constraint

It will hardly be surprising to stress again that high quality big data is a pre-requisite for the development and deployment of digital technologies. All digital technologies of potential adoption in procurement governance are data-dependent. Therefore, without adequate data, there is no prospect of successful adoption of the technologies. The difficulties in generating an enabling procurement data architecture are detailed here.

Moreover, new data rules only regulate the capture of data for the future. This means that it will take time for big data to accumulate. Accessing historical data would be a way of building up (big) data and speeding up the development of digital solutions. Moreover, in some contexts, such as in relation with very infrequent types of procurement, or in relation to decisions concerning previous investments and acquisitions, historical data will be particularly relevant (eg to deploy green policies seeking to extend the use life of current assets through programmes of enhanced maintenance or refurbishment; see here). However, there are significant challenges linked to the creation of backward-looking digital databases, not only relating to the cost of digitisation of the information, but also to technical difficulties in ensuring the representativity and adequate labelling of pre-existing information.

An additional issue to consider is that a number of governance-relevant insights can only be extracted from a combination of procurement and other types of data. This can include sources of data on potential conflict of interest (eg family relations, or financial circumstances of individuals involved in decision-making), information on corporate activities and offerings, including detailed information on products, services and means of production (eg in relation with licensing or testing schemes), or information on levels of utilisation of public contracts and satisfaction with the outcomes by those meant to benefit from their implementation (eg users of a public service, or ‘internal’ users within the public administration).

To the extent that the outside sources of information are not digitised, or not in a way that is (easily) compatible or linkable with procurement information, some data-based procurement governance solutions will remain undeliverable. Some developments in digital procurement governance will thus be determined by progress in other policy areas. While there are initiatives to promote the availability of data in those settings (eg the EU’s Data Governance Act, the Guidelines on private sector data sharing, or the Open Data Directive), the voluntariness of many of those mechanisms raises important questions on the likely availability of data required to develop digital solutions.

Overall, there is no guarantee that the data required for the development of some (advanced) digital solutions will be available. A careful analysis of data requirements must thus be a point of concentration for any decision-maker from the very early stages of considering digitalisation projects.

Revised potential of selected digital technologies

Once (or rather, if) that major data hurdle is cleared, the possibilities realistically brought by the functionality of digital technologies need to be embedded in the procurement governance context, which results in the following feasibility boundary for the adoption of those technologies.

Robotic Process Automation (RPA)

RPA can reduce the administrative costs of managing pre-existing digitised and highly structured information in the context of entirely standardised and repetitive phases of the procurement process. RPA can reduce the time invested in gathering and cross-checking information and can thus serve as a basic element of decision-making support. However, RPA cannot increase the volume and type of information being considered (other than in cases where some available information was not being taken into consideration due to eg administrative capacity constraints), and it can hardly be successfully deployed in relation to open-ended or potentially contradictory information points. RPA will also not change or improve the processes themselves (unless they are redesigned with a view to deploying RPA).

This generates a clear feasibility boundary for RPA deployment, which will generally have as its purpose the optimisation of the time available to the procurement workforce to engage in information analysis rather than information sourcing and basic checks. While this can clearly bring operational advantages, it will hardly transform procurement governance.

Machine Learning (ML)

Developing ML solutions will pose major challenges, not only in relation to the underlying data architecture (as above), but also in relation to specific regulatory and governance requirements specific to public procurement. Where the operational management of procurement does not diverge from the equivalent function in the (less regulated) private sector, it will be possible to see the adoption or adaptation of similar ML solutions (eg in relation to category spend management). However, where there are regulatory constraints on the conduct of procurement, the development of ML solutions will be challenging.

For example, the need to ensure the openness and technical neutrality of procurement procedures will limit the possibilities of developing recommender systems other than in pre-procured closed lists or environments based on framework agreements or dynamic purchasing systems underpinned by electronic catalogues. Similarly, the intended use of the recommender system may raise significant legal issues concerning eg the exercise of discretion, which can limit their deployment to areas of information exchange or to merely suggestion-based tasks that could hardly replace current processes and procedures. Given the limited utility (or acceptability) of collective filtering recommender solutions (which is the predominant type in consumer-facing private sector uses, such as Netflix or Amazon), there are also constraints on the generality of content-based recommender systems for procurement applications, both at tenderer and at product/service level. This raises a further feasibility issue, as the functional need to develop a multiplicity of different recommenders not only reopens the issue of data sufficiency and adequacy, but also raises questions of (economic and technical) viability. Recommender systems would mostly only be susceptible of feasible adoption in highly centralised procurement settings. This could create a push for further procurement centralisation that is not neutral from a governance perspective, and that can certainly generate significant competition issues of a similar nature, but perhaps a different order of magnitude, than procurement centralisation in a less digitally advanced setting. This should be carefully considered, as the knock-on effects of the implementation of some ML solutions may only emerge down the line.

Similarly, the development and deployment of chatbots is constrained by specific regulatory issues, such as the need to deploy closed domain chatbots (as opposed to open domain chatbots, ie chatbots connected to the Internet, such as virtual assistants built into smartphones), so that the information they draw from can be controlled and quality assured in line with duties of good administration and other legal requirements concerning the provision of information within tender procedures. Chatbots are suited to types of high-volume information-based queries only. They would have limited applicability in relation to the specific characteristics of any given procurement procedure, as preparing the specific information to be used by the chatbot would be a challenge—with the added functionality of the chatbot being marginal. Chatbots could facilitate access to pre-existing and curated simple information, but their functionality would quickly hit a ceiling as the complexity of the information progressed. Chatbots would only be able to perform at a higher level if they were plugged to a knowledge base created as an expert system. But then, again, in that case their added functionality would be marginal. Ultimately, the practical space for the development of chatbots is limited to low added value information access tasks. Again, while this can clearly bring operational advantages, it will hardly transform procurement governance.

ML could facilitate the development and deployment of ‘advanced’ automated screens, or red flags, which could identify patterns of suspicious behaviour to then be assessed against the applicable rules (eg administrative and criminal law in case of corruption, or competition law, potentially including criminal law, in case of bid rigging) or policies (eg in relation to policy requirements to comply with specific targets in relation to a broad variety of goals). The trade off in this type of implementation is between the potential (accuracy) of the algorithmic screening and legal requirements on the explainability of decision-making (as discussed in detail here). Where the screens were not used solely for policy analysis, but acting on the red flag carried legal consequences (eg fines, or even criminal sanctions), the suitability of specific types of ML solutions (eg unsupervised learning solutions tantamount to a ‘black box’) would be doubtful, challenging, or altogether excluded. In any case, the development of ML screens capable of significantly improving over RPA-based automation of current screens is particularly dependent on the existence of adequate data, which is still proving an insurmountable hurdle in many an intended implementation (as above).

Distributed ledger technology (DLT) systems and smart contracts

Other procurement governance constraints limit the prospects of wholesale adoption of DLT (or blockchain) technologies, other than for relatively limited information management purposes. The public sector can hardly be expected to adopt DLT solutions that are not heavily permissioned, and that do not include significant safeguards to protect sensitive, commercially valuable, and other types of information that cannot be simply put in the public domain. This means that the public sector is only likely to implement highly centralised DLT solutions, with the public sector granting permissions to access and amend the relevant information. While this can still generate some (degrees of) tamper-evidence and permanence of the information management system, the net advantage is likely to be modest when compared to other types of secure information management systems. This can have an important bearing on decisions whether DLT solutions meet cost effectiveness or similar criteria of value for money controlling their piloting and deployment.

The value proposition of DLT solutions could increase if they enabled significant procurement automation through smart contracts. However, there are massive challenges in translating procurement procedures to a strict ‘if/when ... then’ programmable logic, smart contracts have limited capability that is not commensurate with the volumes and complexity of procurement information, and their development would only be justified in contexts where a given smart contract (ie specific programme) could be used in a high number of procurement procedures. This limits its scope of applicability to standardised and simple procurement exercises, which creates a functional overlap with some RPA solutions. Even in those settings, smart contracts would pose structural problems in terms of their irrevocability or automaticity. Moreover, they would be unable to generate off-chain effects, and this would not be easily sorted out even with the inclusion of internet of things (IoT) solutions or software oracles. This comes to largely restrict smart contracts to an information exchange mechanism, which does not significantly increase the value added by DLT plus smart contract solutions for procurement governance.

Conclusion

To conclude, there are significant and difficult to solve hurdles in generating an enabling data architecture, especially for digital technologies that require multiple sources of information or data points regarding several phases of the procurement process. Moreover, the realistic potential of most technologies primarily concerns the automation of tasks not involving data analysis of the exercise of procurement discretion, but rather relatively simple information cross-checks or exchanges. Linking back to the discussion in the earlier broader chapter (see here), the analysis above shows that a feasibility boundary emerges whereby the adoption of digital technologies for procurement governance can make contributions in relation to its information intensity, but not easily in relation to its information complexity, at least not in the short to medium term and not in the absence of a significant improvement of the required enabling data architecture. Perhaps in more direct terms, in the absence of a significant expansion in the collection and curation of data, digital technologies can allow procurement governance to do more of the same or to do it quicker, but it cannot enable better procurement driven by data insights, except in relatively narrow settings. Such settings are characterised by centralisation. Therefore, the deployment of digital technologies can be a further source of pressure towards procurement centralisation, which is not a neutral development in governance terms.

This feasibility boundary should be taken into account in considering potential use cases, as well as serve to moderate the expectations that come with the technologies and that can fuel ‘policy irresistibility’. Further, it should be stressed that those potential advantages do not come without their own additional complexities in terms of new governance risks (eg data and data systems integrity, cybersecurity, skills gaps) and requirements for their mitigation. These will be explored in the next stage of my research project.

Urgent: 'no eForms, no fun' -- getting serious about building a procurement data architecture in the EU

‘EU Member States only have about one year to make crucial decisions that will affect the procurement data architecture of the EU and the likelihood of successful adoption of digital technologies for procurement governance for years or decades to come’. Put like that, the relevance of the approaching deadline for the national implementation of new procurement eForms may grab more attention than the alternative statement that ‘in just about a year, new eForms will be mandatory for publication of procurement notices in TED’.

This latter more technical (obscure, and uninspiring?) understanding of the new eForms seems to have been dominating the approach to eForms implementation, which does not seem to have generally gained a high profile in domestic policy-making at EU Member State level despite the Publications Office’s efforts.

In this post, I reflect about the strategic importance of the eForms implementation for the digitalisation of procurement, the limited incentives for an ambitious implementation that stem from the voluntary approach of the most innovative aspects of the new eForms, and the opportunity that would be lost with a minimalistic approach to compliance with the new rules. I argue that it is urgent for EU Member States to get serious about building a procurement data architecture that facilitates the uptake of digital technologies for procurement governance across the EU, which requires an ambitious implementation of eForms beyond their minimum mandatory requirements.

eForms: some background

The EU is in the process of reforming the exchange of information about procurement procedures. This information exchange is mandated by the EU procurement rules, which regulate a variety of procurement notices with the two-fold objective of (i) fostering cross-border competition for public contracts and (ii) facilitating the oversight of procurement practices by the Member States, both in relation to the specific procedure (eg to enable access to remedies) and from a broad policy perspective (eg through the Single Market Scoreboard). In other words, this information exchange underpins the EU’s approach to procurement transparency, which mainly translates into publication of notices in the Tenders Electronic Daily (TED).

A 2019 Implementing Regulation established new standard forms for the publication of notices in the field of public procurement (eForms). The Implementing Regulation is accompanied by a detailed Implementation Handbook. The transition to eForms is about to hit a crucial milestone with the authorisation for their voluntary use from 14 November 2022, in parallel with the continued use of current forms. Following that, eForms will be mandatory and the only accepted format for publication of TED notices from 25 October 2023. There will thus have been a very long implementation period (of over four years), including an also lengthy (11-month) experimentation period about to start. This contrasts with previous revisions of the TED templates, which had given under six months’ notice (eg in 2015) or even just a 20-day implementation period (eg in 2011). This extended implementation period is reflective of the fact that the transition of eForms is not merely a matter of replacing a set of forms with another.

Indeed, eForms are not solely the new templates for the collection of information to be published in TED. eForms represent the EU’s open standard for publishing public procurement data — or, in other words, the ‘EU OCDS’ (which goes much beyond the OCDS mapping of the current TED forms). The importance of the implementation of a new data standard has been highlighted at strategic level, as this is the cornerstone of the EU’s efforts to improve the availability and quality of procurement data, which remain suboptimal (to say the least) despite continued efforts to improve the quality and (re)usability of TED data.

In that regard, the 2020 European strategy for data, emphasised that ‘Public procurement data are essential to improve transparency and accountability of public spending, fighting corruption and improving spending quality. Public procurement data is spread over several systems in the Member States, made available in different formats and is not easily possible to use for policy purposes in real-time. In many cases, the data quality needs to be improved.’ The European Commission now stresses how ‘eForms are at the core of the digital transformation of public procurement in the EU. Through the use of a common standard and terminology, they can significantly improve the quality and analysis of data’ (emphasis added).

It should thus be clear that the eForms implementation is not only about low level form-filling, but also (or primarily) about building a procurement data architecture that facilitates the uptake of digital technologies for procurement governance across the EU. Therefore, the implementation of eForms and the related data standard seeks to achieve two goals: first, to ensure the data quality (eg standardisation, machine-readability) required to facilitate its automated treatment for the purposes of publication of procurement notices mandated by EU law (ie their primary use); and, second, to build a data architecture that can facilitate the accumulation of big data so that advanced data analytics can be deployed by re-users of procurement data. This second(ary) goal is particularly relevant to our discussion. This requires some unpacking.

The importance of data for the deployment of digital technologies

It is generally accepted that quality (big) data is the primary requirement for the deployment of digital technologies to extract data-driven insights, as well as to automate menial back-office tasks. In a detailed analysis of these technologies, I stress the relevance of procurement data across technological solutions that could be deployed to improve procurement governance. In short, the outcome of robotic process automation (RPA) can only be as good as its sources of information, and adequate machine learning (ML) solutions can only be trained on high-quality big data—which thus conditions the possibility of developing recommender systems, chatbots, or algorithmic screens for procurement monitoring and oversight. Distributed Ledger Technology (DLT) systems (aka blockchain) can manage data, but cannot verify its content, accuracy, or reliability. Internet of Things (IoT) applications and software oracles can automatically capture data, which can alleviate some of the difficulties in generating an adequate data infrastructure. But this is only in relation with the observation of the ‘real world’ or in relation to digitally available information, which quality raises the same issues as other sources of data. In short, all digital technologies are data-centric or, more clearly, data-dependent.

Given the crucial relevance of data across digital technologies, it is hard to emphasise how any shortcomings in the enabling data architecture curtail the likelihood of successful adoption of digital technologies for procurement governance. With inadequate data, it may simply be impossible to develop digital solutions at all. And the development and adoption of digital solutions developed on poor or inadequate data can generate further problems—eg skewing decision-making on the basis of inadequately derived ‘data insights’. Ultimately, then, ensuring that adequate data is available to develop digital governance solutions is a challenging but unavoidable requirement in the process of procurement digitalisation. Success, or lack of it, in the creation of an enabling data architecture will determine the viability of the deployment of digital technologies more generally. From this perspective, the implementation of eForms gains clear strategic importance.

eForms Implementation: a flexible model

Implementing eForms is not an easy task. The migration towards eForms requires a complete redesign of information exchange mechanisms. eForms are designed around universal business language and involve the use of a much more structured information schema, compatible with the EU’s eProcurement Ontology, than the current TED forms. eForms are also meant to collect a larger amount of information than current TED forms, especially in relation to sub-units within a tender, such as lots, or in relation to framework agreements. eForms are meant to be flexible and regularly revised, in particular to add new fields to facilitate data capture in relation to specific EU-mandated requirements in procurement, such as in relation with the clean vehicles rules (with some changes already coming up, likely in November 2022).

From an informational point of view, the main constraint that remains despite the adoption of eForms is that their mandatory content is determined by existing obligations to report and publish tender-specific information under the current EU procurement rules, as well as to meet broader reporting requirements under international and EU law (eg the WTO GPA). This mandatory content is thus rather limited. Ultimately, eForms’ main concentration is on disseminating details of contract opportunities and capturing different aspects of decision-making by the contracting authorities. Given the process-orientedness and transactional focus of the procurement rules, most of the information to be mandatorily captured by the eForms concerns the scope and design of the tender procedure, some aspects concerning the award and formal implementation of the contract, as well as some minimal data points concerning its material outcome—primarily limited to the winning tender. As the Director-General of the Publications Office put it an eForms workshop yesterday, the new eForms will provide information on ‘who buys what, from whom and for what price’. While some of that information (especially in relation to the winning tender) will be reflective of broader market conditions, and while the accumulation of information across procurement procedures can progressively generate a broader view of (some of) the relevant markets, it is worth stressing that eForms are not designed as a tool of market intelligence.

Indeed, eForms do not capture the entirety of information generated by a procurement process and, as mentioned, their mandatory content is rather limited. eForms do include several voluntary or optional fields, and they could be adapted for some voluntary uses, such as in relation to detection of collusion in procurement, or in relation to the beneficial ownership of tenderers and subcontractors. Extensive use of voluntary fields and the development of additional fields and uses could contribute to generating data that enabled the deployment of digital technologies for the purposes of eg market intelligence, integrity checks, or other sorts of (policy-related) analysis. For example, there are voluntary fields in relation to green, social or innovation procurement, which could serve as the basis for data-driven insights into how to maximise the effects of such policy interventions. There are also voluntary fields concerning procurement challenges and disputes, which could facilitate a monitoring of eg areas requiring guidance or training. However, while the eForms are flexible, include voluntary fields, and the schema facilitates the development of additional fields, is it unclear that adequate incentives exist for adoption beyond their mandatory minimum content.

Implementation in two tiers

The fact that eForms are in part mandatory and in part voluntary will most likely result in two separate tiers of eForms implementation across the EU. Tier 1 will solely concern the collection and exchange of information mandated by EU law, that is the minimum mandatory eForm content. Tier 2 will concern the optional collection and exchange of a much larger volume of information concerning eg the entirety of tenders received, as well as qualitative information on eg specific policy goals embedded in a tender process. Of course, in the absence of coordination, a (large) degree of variation within Tier 2 can be expected. Tier 2 is potentially very important for (digital) procurement governance, but there is no guarantee that Member States will decide to implement eForms covering it.

One of the major obstacles to the broad adoption of a procurement data model so far, at least in the European Union, relates to the slow uptake of e-procurement (as discussed eg here). Without an underlying highly automated e-procurement system, the generation and capture of procurement data is a main challenge, as it is a labour-intensive process prone to input error. The entry into force of the eForms rules could serve as a further push for the completion of the transition to e-procurement—at least in relation to procurement covered by EU law (as below thresholds procurement is a voluntary potential use of eForms). However, it is also possible that low e-procurement uptake and generalised unsophisticated approaches to e-procurement (eg reduced automation) will limit the future functionality of eForms, with Member States that have so far lagged behind restricting the use of eForms to tier 1. Non life-cycle (automated) e-procurement systems may require manual inputs into the new eForms (or the databases from which they can draw information) and this implies that there is a direct cost to the implementation of each additional (voluntary) data field. Contracting authorities may not perceive the (potential) advantages of incurring those costs, or may more simply be constrained by their available budget. A collective action problem arises here, as the cost of adding more data to the eForms is to be shouldered by each public buyer, while the ensuing big data would potentially benefit everyone (especially as it will be published—although there are also possibilities to capture but not publish information that should be explored, at least to prevent excessive market transparency; but let’s park that issue for now) and perhaps in particular data re-users offering for pay added-value services.

In direct relation to this, and compounding the (dis)incentives problem, the possibility (or likelihood) of minimal implementation is compounded by the fact that, in many Member States, the operational adaptation to eForms does not directly concern public sector entities, but rather their service providers. e-procurement services providers compete for the provision of large volume, entirely standardised platform services, which are markets characterised by small operational margins. This creates incentives for a minimal adaptation of current e-sending systems and disincentives for the inclusion of added-value (data) services potentially unlikely to be used by public buyers. Some (or most) optional aspects of the eForm implementation will thus remain unused due to these market structure and dynamics, which does not clearly incentivise a race to the top (unless there is clear demand pull for it).

With some more nuance, it should be stressed that it is also possible that the adoption of eForms is uneven within a given jurisdiction where the voluntary character of parts of the eForm is kept (rather than made mandatory across the board through domestic legislation), with advanced procurement entities (eg central purchasing bodies, or large buyers) adopting tier 2 eForms, and (most) other public buyers limiting themselves to tier 1.

Ensuing data fragmentation

While this variety of approaches across the EU and within a Member State would not pose legal challenges, it would have a major effect on the utility of the eForms-generated data for the purposes of eg developing ML solutions, as the data would be fragmented, hardly representative of important aspects of procurement (markets), and could hardly be generalisable. The only consistent data would be that covered by tier 1 (ie mandatory and standardised implementation) and this would limit the potential use cases for the deployment of digital technologies—with some possibly limited to the procurement remit of the specific institutions with tier 2 implementations.

Relatedly, it should be stressed that, despite the effort to harmonise the underlying data architecture and link it to the Procurement Ontology, the Implementation Handbook makes clear that ‘eForms are not an “off the shelf” product that can be implemented only by IT developers. Instead, before developers start working, procurement policy decision-makers have to make a wide range of policy decisions on how eForms should be implemented’ in the different Member States.

This poses an additional challenge from the perspective of data quality (and consistency), as there are many fields to be tailored in the eForms implementation process that can result in significant discrepancies in the underlying understanding or methodology to determine them, in addition to the risk of potential further divergence stemming from the domestic interpretation of very similar requirements. This simply extends to the digital data world the current situation, eg in relation to diverging understandings of what is ‘recyclable’ or what is ‘social value’ and how to measure them. Whenever open-ended concepts are used, the data may be a poor source for comparative and aggregate analysis. Where there are other sources of standardisation or methodology, this issue may be minimised—eg in relation to the green public procurement criteria developed in the EU, if they are properly used. However, where there are no outside or additional sources of harmonisation, it seems that there is scope for quite a few difficult issues in trying to develop digital solutions on top of eForms data, except in relation to quantitative issues or in relation to information structured in clearly defined categories—which will mainly link back to the design of the procurement.

An opportunity about to be lost?

Overall, while the implementation of eForms could in theory build a big data architecture and facilitate the development of ML solutions, there are many challenges ahead and the generalised adoption of tier 2 eForms implementations seems unlikely, unless Member States make a positive decision in the process of national adoption. The importance of an ambitious tier 2 implementation of eForms should be assessed in light of its downstream importance for the potential deployment of digital technologies to extract data-driven insights and to automate parts of the procurement process. A minimalistic implementation of eForms would significantly constrain future possibilities of procurement digitalisation. Primarily in the specific jurisdiction, but also with spillover effects across the EU.

Therefore, a minimalistic eForms implementation approach would perpetuate (most of the) data deficit that prevents effective procurement digitalisation. It would be a short-sighted saving. Moreover, the effects of a ‘middle of the road’ approach should also be considered. A minimalistic implementation with a view to a more ambitious extension down the line could have short-term gains, but would delay the possibility of deploying digital technologies because the gains resulting from the data architecture are not immediate. In most cases, it will be necessary to wait for the accumulation of sufficiently big data. In some cases of infrequent procurement, missing data points will generate further time lags in the extraction of valuable insights. It is no exaggeration that every data point not captured carries an opportunity cost.

If Member States are serious about the digitalisation of public procurement, they will make the most of the coming year to develop tier 2 eForms implementations in their jurisdiction. They should also keep an eye on cross-border coordination. And the European Commission, both DG GROW and the Publications Office, would do well to put as much pressure on Member States as possible.

Some thoughts on the Commission's 2021 Report on 'Implementation and best practices of national procurement policies in the Internal Market'

In May 2021, the European Commission published its report on the ‘Implementation and best practices of national procurement policies in the Internal Market’ (the ‘2021 report’). The 2021 report aggregates the national reports sent by Member States in discharge of specific reporting obligations contained in the 2014 Public Procurement Package and offers some insight into the teething issues resulting from its transposition—which may well have become structural issues. In this post, I offer some thoughts on the contents of the 2021 report.

Better late than never?

Before getting to the details of the 2021 report, the first thing to note is the very significant delay in the publication of this information and analysis, as the 2021 report refers to the implementation and practice of procurement covered by the Directives in 2017. The original national reports seem to have been submitted by the Member States (plus Norway, minus Austria for some unexplained reason) in 2018.

Given the limited analysis conducted in the 2021 report, one can wonder why it took the Commission so long. There may be some explanation in the excuses recently put forward to the European Parliament for the continued delay (almost 2 and a half years, and counting) in reporting on the economic effect of the 2014 rules, although that is less than persuasive. Moreover, given that the reporting obligation incumbent on the Member States is triggered every three years, in 2021 we should be having fresh data and analysis of the national reports covering the period 2018-2020 … Oh well, let’s work with what we have.

A missing data (stewardship) nightmare

The 2021 report provides painful evidence of the lack of reliable procurement data in 2017. Nothing new there, sadly—although the detail of the data inconsistencies, including Member States reporting ‘above threshold procurement’ data that differs from what can be extracted from TED (page 4), really should raise a few red flags and prompt a few follow-up questions from the Commission … the open-ended commitment to further investigation (page 4) sounding as too little, too late.

The main issue, though, is that this problem is unlikely to have been solved yet. While there is some promise in the forthcoming implementation of new eForms (to start being used between Nov 2022 and no later than Oct 2023), the broader problem of ensuring uniformity of data collection and (more) timely reporting is likely to remain. It is also surprising to see that the Commission considers that the collection of ‘above threshold’ procurement data is voluntary for Member States (fn 5), when Art 85(1) places them under an obligation to provide ‘missing statistical information’ where it cannot be extracted from (TED) notices.

So, from a governance perspective (and leaving aside the soft, or less, push towards the implementation of OCDS standards in different Member States), it seems that the Commission and the Member States are both happy to just keeping shrugging their shoulders at each other when it comes to the incompleteness and low quality of procurement data. May it be time for the Commission to start enforcing reporting obligations seriously and with adequate follow-ups? Or should we wait to the (2024?) second edition of the implementation report to decide to do something then — although it will then be quite tempting to say that we need to wait and see what effect the (delayed?) adoption of the eForms generates. So maybe in light of the (2027?) third edition of the report?

Lack of capability, and ‘Most frequent sources of wrong application or of legal uncertainty’

The 2021 report includes a section on the reported most frequent sources of incorrect application of the 2014 rules, or perceived areas of legal uncertainty. This section, however, starts with a list of issues that rather point to a shortfall of capabilities in the procurement workforce in (some?) Member States. Again, while the Commission’s work on procurement professionalisation may have slightly changed the picture, this is primarily a matter for Member State investment. And in the current circumstances, it seems difficult to see how the post-pandemic economic recovery funds that are being channeled through procurement can be effectively spent where there are such staffing issues.

The rest of the section includes some selected issues posing concrete interpretation or practical implementation difficulties, such as the calculation of threshold values, the rules on exclusion and the rules on award criteria. While these are areas that will always generate some practical challenges, these are not the areas where the 2014 Package generated most change (certainly not on thresholds) and the 2021 report then seems to keep raising structural issues. The same can be said of the generalised preference for the use of lowest price, the absence of market research and engagement, the imposition of unrealistically short tendering deadlines implicit in rushed procurement, or the arbitrary use of selection criteria.

All of this does not bode well for the ‘strategic use’ of procurement (more below) and it seems like the flexibility and potential for process-based innovation of the 2014 rules (as was that of the 2004 rules?) are likely to remain largely unused, thus triggering poor procurement practices later to fuel further claims for flexibilisation and simplification in the next round of revision. On that note, I cannot refrain from pointing to the UK’s recent green paper on the ‘Transformation of Public Procurement’ as a clear example of the persistence of some procurement myths that remain in the collective imagery despite a lack of engagement with recent legislative changes aimed at debunking them (see here, here, and here for more analysis).

Fraud, corruption, conflict of interest and serious irregularities

The 2021 report then has a section that would seem rather positive and incapable of controversy at first sight, as it presents (laudable) efforts at Member State level to create robust anti-fraud and anti-corruption institutions, as well as implementations of rules on conflict of interest that exceed the EU minimum standard, and the development of sophisticated approaches to the prevention and detection of collusion in procurement. Two comments come to mind here.

The first one is that the treatment of conflicts of interest in the Directive clearly requires the development of further rules at domestic level and that the main issue is not whether the statutes contain suitable definitions, but whether conflicts of interest are effectively screened and (more importantly), reacted to. In that regard, it would be interesting to know, for example, how many decisions finding a non-solvable conflict of interest have led to the exclusion of tenderers at Member State level since the new rules came into force. If anyone wanted to venture an estimate, I would not expect it to be in the 1000s.

The second comment is that the picture that the 2021 report paints about the (2017) development of anti-collusion approaches at Member State level (page 7) puts a large question mark on the need for the recent Notice on tools to fight collusion in public procurement and on guidance on how to apply the related exclusion ground (see comments here). If the Member States were already taking action, why did the (contemporaneous) 2017 Communication on ‘Making public procurement work in and for Europe’ (see here) include a commitment to ‘… develop tools and initiatives addressing this issue and raising awareness to minimise the risks of collusive behaviours on procurement markets. This will include actions to improve the market knowledge of contracting authorities, support to contracting authorities careful planning and design of procurement processes and better cooperation and exchange of information between public procurement and competition authorities. The Commission will also prepare guidelines on the application of the new EU procurement directives on exclusion grounds on collusion.’ Is the Commission perhaps failing to recognise that the 2014 rules, and in particular the new exclusion ground for contemporaneous collusion, created legal uncertainty and complicated the practical application of the emerging domestic practices?

Moreover, the 2021 report includes a relatively secondary comment that the national reports ‘show that developing and applying means for the quantitative assessment of collusion risks in award procedures, mostly in the form of risk indicators, remains a challenge’. This is a big understatement and the absence of (publicly-known?) work by the Commission itself on the development of algorithmic screening for collusion detection purposes can only be explained away by the insufficiency of the existing data (which killed off eg a recent effort in the UK), which brings us back to the importance of stronger data stewardship if some of the structural issues are to be resolved (or started to be resolved) any time soon.

SMEs

There is also little about SME access to procurement in the 2021 report, mainly due to limited data provided in the national reports (so, again, another justification for a tougher approach to data collection and reporting). However, there are a couple of interesting qualitative issues. The first one is that ‘only a limited number of Member States have explicitly mentioned challenges encountered by SMEs in public procurement’ (page 7), which raises some questions about the extent to which SME-centric policy issues rank equally high at EU and at national level (which can be relevant in terms of assessing e.g. the also very recent Report on SME needs in public procurement (Feb 2021, but published July 2021). The second one is that the few national strategies seeking to boost SME participation in procurement concern programmes aimed at increasing interactions between SMEs and contracting authorities at policy and practice design level, as well as training for SMEs. What those programmes have in common is that they require capability and resources to be dedicated to the SME procurement policy. Given the shortcomings evidenced in the 2021 report (above), it should be no wonder that most Member States do not have the resources to afford them.

Green, social & Innovation | ‘strategic procurement’

Not too dissimilarly, the section on the uptake of ‘strategic procurement’ also points at difficulties derived from limited capability or understanding of these issues amongst public buyers, as well as the perception (at least for green procurement) that it can be detrimental to SME participation. There is also repeated reference to lack of clarity of the rules and risks of litigation — both of which are in the end dependent on procurement capability, at least to a large extent.

All of this is particularly important, not only because it reinforces the difficulties of conducting complex or sophisticated procurement procedures that exceed the capability (either in terms of skill or, probably more likely, available time) of the procurement workforce, but also because it once again places some big question marks on the feasibiity of implementing some of the tall asks derived from eg the new green procurement requirements that can be expected to follow from the European Green Deal.

Overal thoughts

All of this leads me to two, not in the least original or groundbreaking, thoughts. First, that procurement data is an enabler of policies and practices (clearly of those supported by digital technologies, but not only) which absence significantly hinders the effectiveness of the procurement function. Second, that there is a systemic and long-lasting underinvestment in procurement capability in (most) Member States — about which there is little the European Commission can do — which also significantly hinders the effectiveness of the procurement function.

So, if the current situation is to be changed, a bold and aggressive plan of investment in an enabling data architecture and legal-commercial (and technical) capability is necessary. Conversely, until (or unless) that happens, all plans to use procurement to prop up or reactivate the economy post-pandemic and, more importantly, to face the challenges of the climate emergency are likely to be of extremely limited practical relevance due to failures in their implementation. The 2021 report clearly supports aggressive action on both fronts (even if it refers to the situation in 2017, the problems are very much still current). Will it be taken?

Reflecting on data-driven and digital procurement governance through two elephant tales

Elephants in a 13th century manuscript. THE BRITISH LIBRARY/ROYAL 12 F XIII

I have uploaded to SSRN the new paper ‘Data-driven and digital procurement governance: Revisiting two well-known elephant tales‘ (21 Aug 2019), which I will present at the Annual Conference of the IALS Information Law & Policy Centre on 22 November 2019.

The paper condenses my current thoughts about the obstacles for the deployment of data-driven digital procurement governance due to a lack of reliable quality procurement data sources, as well as my skepticism about the potential for blockchain-based solutions, including smart contracts, to have a significant impact in public procurement setting where the public buyer is extremely unlikely to give up centralised control of the procurement function. The abstract of the paper is as follows:

This paper takes the dearth of quality procurement data as an empirical point of departure to assess emerging regulatory trends in data-driven and digital public procurement governance and, in particular, the European Commission’s ambition for the single digital procurement market. It resorts to two well-known elephant tales to send a message of caution. It first appeals to the image of medieval bestiary elephants to stress the need to develop a better data architecture that reveals the real state of the procurement landscape, and for the European Commission to stop relying on bad data in the Single Market Scoreboard. The paper then assesses the promises of blockchain and smart contracts for procurement governance and raises the prospect that these may be new white elephants that do not offer significant advantages over existing sophisticated databases, or beyond narrow back-office applications—which leaves a number of unanswered questions regarding the desirability of their implementation. The paper concludes by advocating for EU policymakers to concentrate on developing an adequate data architecture to enable digital procurement governance.

If nothing else, I hope the two elephant tales are convincing.