This is a blog about the use of emerging technologies to boost the governance of public procurement. It used to be a blog on EU law, with a focus on free movement, public procurement and competition law issues (thus the long archive of entries about those topics). I use it to publish my thoughts and to test some ideas. All comments are personal and in no way bind any of the institutions to which I am affiliated and, particularly, the University of Bristol Law School. I hope to spur discussion and look forward to your feedback and participation.
The recording and slides for yesterday’s webinar on ‘Tech fixes for procurement problems?’ co-hosted by the University of Bristol Law School and the GW Law Government Procurement Programme are now available for catch up if you missed it.
I would like to thank once again Dean Jessica Tillipman (GW Law), Professor Sope Williams (Stellenbosch), and Eliza Niewiadomska (EBRD) for really interesting discussion, and to all participants for their questions. Comments most welcome, as always.
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.
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.
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.
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.
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).
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.
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.
I have just started a 12-month Mid-Career Fellowship funded by the British Academy with the purpose of writing up the monograph Digital Technologies and Public Procurement. Gatekeeping and experimentation in digital public governance (OUP, forthcoming).
In the process of writing up, I will be sharing some draft chapters and other thought pieces. I would warmly welcome feedback that can help me polish the final version. As always, please feel free to reach out: a.sanchez-graells@bristol.ac.uk.
In this first draft chapter (num 6), I explore the technological promise of digital governance and use public procurement as a case study of ‘policy irresistibility’. The main ideas in the chapter are as follows:
This Chapter takes a governance perspective to reflect on the process of horizon scanning and experimentation with digital technologies. The Chapter stresses how aspirations of digital transformation can drive policy agendas and make them vulnerable to technological hype, despite technological immaturity and in the face of evidence of the difficulty of rolling out such transformation programmes—eg regarding the still ongoing wave of transition to e-procurement. Delivering on procurement’s goals of integrity, efficiency and transparency requires facing challenges derived from the information intensity and complexity of procurement governance. Digital technologies promise to bring solutions to such informational burden and thus augment decisionmakers’ ability to deal with that complexity and with related uncertainty. The allure of the potential benefits of deploying digital technologies generates ‘policy irresistibility’ that can capture decision-making by policymakers overly exposed to the promise of technological fixes to recalcitrant governance challenges. This can in turn result in excessive experimentation with digital technologies for procurement governance in the name of transformation. The Chapter largely focuses on the EU policy framework, but the insights derived from this analysis are easily exportable.
Another draft chapter (num 7) will follow soon with more detailed analysis of the feasibility boundary for the adoption of digital technologies for procurement governance purposes. The full details of this draft chapter are as follows: A Sanchez-Graells, ‘The technological promise of digital governance: procurement as a case study of “policy irresistibility”’ 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=4216825.
This is a post in two parts. The first part addresses my methodological concerns with research on digital technologies and public procurement (and public governance more generally), as exemplified by a recent paper. The second part collects the response by the authors of that paper.
This pair of points of view are offered together to try to create debate. While the authors found my comments harsh (I cannot judge that), they engaged with them and provided their own counter-arguments. In itself, I think that is laudable and already has value. Any further discussion with the broader community, via comments (or email), would be a bonus.
When I started researching the interaction between digital technologies and procurement governance, it was clear to me that a technology-centered legal method was required. A significant amount of the scholarship that is published fails to properly address the governance implications of digital technologies because it simply does not engage with their functionality—or, put otherwise, because the technology is not understood. This can lead to either excessive claims of what ‘technology fixes’ can achieve or, perhaps even more problematic, it can generate analysis that is based on a misleading, shallow and oftentimes purely literal reading of the labels with which the technology is described and referred to.
A recent paper on smart contracts and procurement clearly exemplifies this problem: N.A. Sava & D. Dragos, ‘The Legal Regime of Smart Contracts in Public Procurement’ (2022) Transylvanian Review of Administrative Sciences, No. 66 E/2022, pp. 99–112.
From the outset, the paper is at pains to distinguish blockchain and smart contracts, and proposes ’a needed conceptual distinction that would fit the public contracts theory: before a contract is signed, it is logical to refer to blockchain technology when discussing digital means of awarding the procurement contract. As a result of this award, the concluded contract could be a “smart contract”’ (at 101).
The trap into which the paper falls, of course, is that of believing that blockchain and smart contracts can be distinguished ‘conceptually’ (in a legal sense), rather than on the basis of their technological characteristics and functionality.
Blockchain is a type of distributed ledger technology (DLT). In some more detail: ‘A DLT system is a system of electronic records that enables a network of independent participants to establish a consensus around the authoritative ordering of cryptographically-validated (‘signed’) transactions. These records are made persistent by replicating the data across multiple nodes, and tamper-evident by linking them by cryptographic hashes. The shared result of the reconciliation/consensus process - the ‘ledger’ - serves as the authoritative version for these records’ (M Rauchs et al, Distributed Ledger Technology Systems. A Conceptual Framework (2018), at 24). Blockchain is thus a ‘passive’ digital technology in the sense that it cannot perform any sort of automation of (decision-making) processes because it simply serves to create a data infrastructure.
In turn, smart contracts are a type of ‘active’ (or automating) digital technology that can be deployed on top of a DLT. In more detail: ‘Smart contracts are simply programs stored on a blockchain that run when predetermined conditions are met. They typically are used to automate the execution of an agreement so that all participants can be immediately certain of the outcome, without any intermediary’s involvement or time loss. They can also automate a workflow, triggering the next action when conditions are met’ (IBM, What are smart contracts on blockchain? (undated, accessed 1 July 2022)).
What this means is that, functionally, ‘smart contracts’ may or may not map onto the legal concept of contract, as a ‘smart contract’ can be a unilaterally programmed set of instructions aimed at the automation of a workflow underpinned by data held on a DLT.
Taking this to the public procurement context, it is then clear that both the management of the award process and the execution of an awarded public contract, to the extent that they could be automated, would both need to be instrumentalised via smart contracts plus an underlying blockchain (I would though be remiss not to stress that the practical possibilities of automating either of those procurement phases are extremely limited, if at all realistic; see here and here, which the paper refers to in passing). It does not make any (technological/functional) sense to try to dissociate both layers of digital technology to suggest that ‘blockchain technology [should be used] when discussing digital means of awarding the procurement contract. As a result of this award, the concluded contract could be a “smart contract”’ (Sava & Dragos, above, 101).
This is important, because that technology-incongruent conceptual distinction is then the foundation of legal analysis. The paper e.g. posits that ‘the award of public contracts is a unilateral procedure, organized by state authorities according to specific rules, and that automation of such procedure may be done using blockchain technology, but it is not a ‘“smart contract” (sic). Smart contracts, on the other hand, can be an already concluded procurement contract, which is executed, oversaw (sic) and even remedied transparently, using blockchain technology (sic)’ (ibid, 103, emphasis added).
There are three problems here. First, the automation of the procurement award procedure carried out on top of a DLT layer would require a smart contract (or a number of them). Second, the outcome of that automated award would only be a ‘smart contract’ in itself if it was fully coded and its execution fully automated. In reality, it seems likely that some parts of a public contract could be coded (e.g. payments upon invoice approval), whereas other parts could not (e.g. anything that has to happen offline). Third, the modification of the smart contract (ie coded) parts of a public contract could not be modified (solely) using blockchain technology, but would require another (or several) smart contract/s.
Similarly, the lack of technology-centricity of the analysis leads the paper to present as open policy choices some issues that are simply technologically-determined.
For example, the paper engages in this analysis:
… the question is where should the smart public contracts be awarded? In the electronic procurement systems already developed by the different jurisdictions? On separate platforms using blockchain technology? The best option for integrating smart contracts into the procurement procedures may be the already existing digital infrastructure, therefore on the electronic procurement platforms of the member states. We believe this would be an optimal solution, as smart contracts should enhance the current electronic procurement framework and add value to it, thus leveraging the existing system and not replacing it (at 103, emphasis added).
Unless the existing electronic procurement platforms ran on blockchain—which I do not think they do—then this is not a policy option at all, as it is not possible to deploy smart contracts on top of a different layer of information. It may be possible to automate some tasks using different types of digital technologies (e.g. robotic process automation), but not smart contracts (if the technological concept, as discussed above, is to be respected).
The problems continue with the shallow approach to the technology (and to the underlying legal and practical issues), as also evidenced in the discussion of the possibility of automating checks related to the European Single Procurement Document (ESPD), which is a self-declaration that the economic operator is not affected by exclusion grounds (see Art 59 Directive 2014/24/EU).
The paper states
In the context of automatized checks, the blockchain technology can provide an avenue for checking the validity of proofs presented. The system could automate the verifications of the exclusion grounds and the selection criteria by checking the original documents referenced in the ESPD in real time (that is, before determining the winning tender). The blockchain technology could verify the respect of the exclusions grounds and rule out any economic operator that does not comply with this condition (at 104, emphasis added).
This is a case of excessive claim based on a misunderstanding of the technology. A smart contract could only verify whatever information was stored in a DLT. There is no existing DLT capturing the information required to assess the multiplicity of exclusion grounds regulated under EU law. Moreover, the check would never be of the original documents, but rather of digital records that would either be self-declared by the economic operators or generated by a trusted authority. If the latter, what is the point of a blockchain (or other DLT), given that the authority and veracity of the information comes from the legal authority of the issuer, not the consensus mechanism?
There are also terminological/conceptual inconsistencies in the paper, which does not consistently stick to its conceptual distinction that blockchain should be used to refer to the automation of the award procedure, with smart contracts being reserved to the awarded contract. For example, it (correctly) asserts that ‘When it comes to selection criteria, the smart contract could also perform automatic checks on the elements listed in the contract notice’ (at 104). However, this can creates confusion for a reader not familiar with the technology.
Other issues point at the potentially problematic implications of analysis based on a lack of in-depth exploration of the technologies. For example, the paper discusses a project in Colombia, which ‘created a blockchain software that allowed for record keeping, real time auditability, automation through smart contracts and enhanced citizen engagement’ (at 105). After limited analysis, the paper goes on to stress that ‘Our opinion is that the system in Colombia resembles very much the regular e-procurement systems in Europe. For instance, Romania’s SEAP (Electronic Public Procurement System) insures exactly the same features — non-alteration of bids, traceability and automatic evaluation of tenders (price). So, the question is whether the smart contract system in Colombia is anything else than a functional e-procurement system’ (ibid). This reflects a conflation of functionality with technology, at best.
In the end, the lack of technology-centered (legal) analysis significantly weakens the paper and makes its insights and recommendations largely unusable.
To avoid this type of problems in much-needed legal scholarship on the impact of digital technologies on public governance, it is necessary to develop a technology-centric legal methodology. This is something I am working on, in the context of my project funded by the British Academy. I will seek to publish a draft methodology towards the end of the year. Comments and suggestions on what to take into account would be most welcome: a.sanchez-graells@bristol.ac.uk.
Dear Professor,
As a first-year PhD student, being read and offered feedback, especially in the incipient phase of the research, is an amazing learning opportunity. Not all PhD students have the chance to exchange on their topic, and even more with a revered name in the doctrine of public procurement like yourself, therefore am I am very grateful for this debate (Sava).
The co-author Dragos also shares the respect and gratitude for the scholarly critique, although considers the comments rather theoretical and lacking an alternative constructive conclusion.
Concerning the need to conduct a ʻtechnology-centered legal’ research, I fully agree, and I will try to integrate more technology-centered research into the thesis.
However, being lawyers, we believe that technology-centered research does not take into account the established concepts from law and especially public procurement law, therefore an interdisciplinary perspective is needed.
Now we will address the arguments you formulated.
Concerning the definitions of blockchain and smart contract that you offer, we are of course familiar with them and agree with them.
We agree that blockchain-based smart-contracts could automate certain aspects of the procurement procedures, both in the award and in the execution phase. In our paper, we acknowledge the fact that ʻsmart contracts could automate any process that can be presented as an IF+THEN formula’ (p. 100-101). In this sense, like you noticed, we give the example of automating the check of the selection criteria: ‘When it comes to selection criteria, the smart contract could also perform automatic checks on the elements listed in the contract notice’ (p. 104).
However, beyond these two concepts (blockchain and smart contracts), there is a third concept, that of a ʻsmart legal contract’.
DiMatteo, L., Cannarsa, M. and Poncibò, C., in The Cambridge Handbook of Smart Contracts, Blockchain Technology and Digital Platforms (Cambridge: Cambridge University Press, 2019, p. 63) draw attention to the inadequacy of the terminology: ʻFor blockchain-based smart contracts, a useful dichotomy can be drawn between the ‘smart contract code’ that is, the computer code that is ‘– stored, verified, and executed on a blockchain and the ‘smart legal contract’ - a complement (or maybe even a substitute) for a legal contract that applies that technology. In essence, a ‘smart legal contract’ is a combination of the ‘smart contract code’ and traditional legal language.
'The LawTech panel recently decided that (...) smart contracts could still be legally binding provided that they include the typical elements of a contract.’ (https://juro.com/learn/smart-contracts, consulted on the 2nd of July 2022). Like you mention, ‘functionally, ‘smart contracts’ may or may not map onto the legal concept of contract, as a ‘smart contract’ can be a unilaterally programmed set of instructions aimed at the automation of a workflow underpinned by data held on a DLT’.
Therefore, the correct conceptual distinction would be between ʻsmart contract code’ and ʻsmart legal contract’. In the paper, we tried to focus on the smart legal contract, and discuss its compatibility with public procurement contracts. Through the conceptual distinction, we actually wanted to point out the fact that it would be difficult to imagine a smart legal contract (legally binding) exclusively in the award phase. On the other hand, concerning the ʻsmart contract code’ we agree that it could be applicable to both the award and the execution phase, although the terminology remains debatable.
We state that ʻThe best option for integrating smart contracts into the procurement procedures may be the already existing digital infrastructure, therefore on the electronic procurement platforms of the member states. We believe this would be an optimal solution, as smart contracts should enhance the current electronic procurement framework and add value to it, thus leveraging the existing system and not replacing it’ (p. 103).
Of course, we do not believe that the current system works on blockchain (in the paper we explore why this would be a difficult task), but we did discuss the integration of emerging technologies in the existing context of e-procurement tools. However, this would be an integration among the e-procurement tools, not on top of the existing tools, as adequate infrastructure would be needed.
Actually we mean exactly what you pointed out in your conclusions, so we are in agreement here: some aspects of the procedure could be automated, yet the rest of the procedure could function based on the rules already in place. By the idea of not replacing the e-procurement system, we mean automatizing some punctual aspects, but not replacing the entire system.
The idea was that smart contracts could automatically check certain documents, such as the ones referenced in the ESPD.
In our text, we only discuss the idea of a verification, we do not describe in detail how this should be performed and we do not state that the DLT should capture on its own ʻthe information required to assess the multiplicity of exclusion grounds regulated under EU law’. Of course, these documents would need to be uploaded to the DLT and the uploaded documents would have a digital form. By ‘original document’ we refer to the document per se, the reference document and not the simple declaration from the ESPD.
An analogy of this idea could be made with the Canadian ‘Supplier information registration system, which facilitates the registration of supplier information on blockchain to validate it against different records and to validate it in an automated way’ (NTT Data Presentation at EPLD Meeting, May 2022).
We could not understand your critique here. The referenced example described a system for selecting economic operators in public procurement (for more information: https://www.weforum.org/reports/exploring-blockchain-technology-for-government-transparency-to-reduce-corruption/), which we believe is comparable with a regular e-procurement portal.
Through our analysis, we intended to raise the following question: would automating some aspects of the public procurement procedure through “smart contracts” ensure the same characteristics and guarantees as the ones offered by an e-public procurement system of an EU member state? In that case, what is the added value of “smart contracts” in public procurement? It is a research question that we will try to focus on in the future, we merely pose it here.
This paper is an exploratory and incipient one. For the moment, our goal was to raise some questions and to explore some potential paths. Apart from theoretical “what ifs”, it is hard to find specificities of assertions that new digital technologies will definitely have numerous and game-changing applications in the procurement process, as long as the procurement process is still managed unilaterally by public bodies and entertains a public law regime.
The intention is to challenge a rather theoretical assumption on the role of digital technologies in public procurement and subsequently trying to find real, practical examples or applications, if any.
In no circumstance did we state that we are formulating policy recommendations, this was misunderstood. Only after extensive research conclusions may lead to policy recommendations but we are still far from that moment.
However, we believe that in order to actually draw some conclusions on the use of such technologies in public procurement, scholars should delve in more depth into the topic, by critically assessing the current literature in the field and trying to have an interdisciplinary (legal, technological and managerial) look at the topic. As of now, the literature is too theoretical.
In other words, in our opinion, the exclusive tech-centered approach that you suggest would be equally harmful as an exclusively legal one.
Thank you for this chance of a constructive dialogue, we are looking forward to future exchange on the topic.
Magic; Stage Illusions and Scientific Diversions, Including Trick Photography (1897), written by Albert Allis Hopkins and Henry Ridgely Evan.
As the dust settles in the process of reform of UK public procurement rules, and while we await for draft legislation to be published (some time this year?), there is now a chance to further reflect on the likely effects of the deregulatory, flexibility- and discretion-based approach to be embedded in the new UK procurement system.
An issue that may not have been sufficiently highlighted, but which should be of concern, is the way in which increased flexibility and discretion will unavoidably carry higher corruption risks and reduce the effectiveness of potential anti-corruption tools, in particular those based on the implementation of digital technologies for procurement oversight [see A Sanchez-Graells, ‘Procurement Corruption and Artificial Intelligence: Between the Potential of Enabling Data Architectures and the Constraints of Due Process Requirements’ in S Williams-Elegbe & J Tillipman (eds), Routledge Handbook of Public Procurement Corruption (Routledge, forthcoming)].
This is an inescapable issue, for there is an unavoidable trade-off between flexibility, discretion and corruption (in procurement, and more generally). And this does not bode well for the future of UK procurement integrity if the experience during the pandemic is a good predictor.
The trade-off between flexibility, discretion and corruption underpins many features of procurement regulation, such as the traditional distrust of procedures involving negotiations or direct awards, which may however stifle procurement innovation and limit value for money [see eg F Decarolis et al, ‘Rules, Discretion, and Corruption in Procurement: Evidence from Italian Government Contracting’ (2021) NBER Working Paper 28209].
The trade-off also underpins many of the anti-corruption tools (eg red flags) that use discretionary elements in procurement practice as a potential proxy for corruption risk [see eg M Fazekas, L Cingolani and B Tóth, ‘Innovations in Objectively Measuring Corruption in Public Procurement’ in H K Anheier, M Haber and M A Kayser (eds) Governance Indicators: Approaches, Progress, Promise (OUP 2018) 154-180; or M Fazekas, S Nishchal and T Søreide, ‘Public procurement under and after emergencies’ in O Bandiera, E Bosio and G Spagnolo (eds), Procurement in Focus – Rules, Discretion, and Emergencies (CEPR Press 2022) 33-42].
Moreover, economists and political scientists have clearly stressed that one way of trying to strike an adequate balance between the exercise of discretion and corruption risks, without disproportionately deterring the exercise of judgement or fostering laziness or incompetence in procurement administration, is to increase oversight and monitoring, especially through auditing mechanisms based on open data (see eg Procurement in a crisis: how to mitigate the risk of corruption, collusion, abuse and incompetence).
The difficulty here is that the trade-off is inescapable and the more dimensions on which there is flexibility and discretion in a procurement system, the more difficult it will be to establish a ‘normalcy benchmark’ or ‘integrity benchmark’ from which deviations can trigger close inspection. Taking into account that there is a clear trend towards seeking to automate integrity checks on the basis of big data and machine learning techniques, this is a particularly crucial issue. In my view, there are two main sources of difficulties and limitations.
First, that discretion is impossible to code for [see S Bratus and A Shubina, Computerization, Discretion, Freedom (2015)]. This both means that discretionary decisions cannot be automated, and that it is impossible to embed compliance mechanisms (eg through the definition of clear pathways based on business process modelling within an e-procurement system, or even in blockchain and smart contract approaches: Neural blockchain technology for a new anticorruption token: towards a novel governance model) where there is the possibility of a ‘discretion override’.
The more points along the procurement process where discretion can be exercised (eg choice of procedure, design of procedure, award criteria including weakening of link to subject matter of the contract and inclusion of non(easily)measurable criteria eg on social value, displacement of advantage analysis beyond sphere of influence of contracting authority, etc) the more this difficulty matters.
Second, the more deviations there are between the new rulebook and the older one, the lower the value of existing (big) data (if any is available or useable) and of any indicators of corruption risk, as the regulatory confines of the exercise of discretion will not only have shifted, but perhaps even lead to a displacement of corruption-related exercise of discretion. For example, focusing on the choice of procedure, data on the extent to which direct awards could be a proxy for corruption may be useless in a new context where that type of corruption can morph into ‘custom-made’ design of a competitive flexible procedure—which will be both much more difficult to spot, analyse and prove.
Moreover, given the inherent fluidity of that procedure (even if there is to be a template, which is however not meant to be uncritically implemented), it will take time to build up enough data to be able to single out specific characteristics of the procedure (eg carrying out negotiations with different bidders in different ways, such as sequentially or in parallel, with or without time limits, the inclusion of any specific award criterion, etc) that can be indicative of corruption risk reliably. And that intelligence may not be forthcoming if, as feared, the level of complexity that comes with the exercise of discretion deters most contracting authorities from exercising it, which would mean that only a small number of complex procedures would be carried out every year, potentially hindering the accumulation of data capable of supporting big data analysis (or even meaningful econometrical treatment).
Overall, then, the issue I would highlight again is that there is an unavoidable trade-off between increasing flexibility and discretion, and corruption risk. And this trade-off will jeopardise automation and data-based approaches to procurement monitoring and oversight. This will be particularly relevant in the context of the design and implementation of the tools at the disposal of the proposed Procurement Review Unit (PRU). The Response to the public consultation on the Transforming Public Procurement green paper emphasised that
‘… the PRU’s main focus will be on addressing systemic or institutional breaches of the procurement regulations (i.e. breaches common across contracting authorities or regularly being made by a particular contracting authority). To deliver this service, it will primarily act on the basis of referrals from other government departments or data available from the new digital platform and will have the power to make formal recommendations aimed at addressing these unlawful breaches’ (para [48]).
Given the issues raised above, and in particular the difficulty or impossibility of automating the analysis of such data, as well as the limited indicative value and/or difficulty of creating reliable red flags in a context of heightened flexibility and discretion, quite how effective this will be is difficult to tell.
Moreover, given the floating uncertainty on what will be identified as suspicious of corruption (or legal infringement), it is also possible that the PRU (initially) operates on the basis of indicators or thresholds arbitrarily determined (much like the European Commission has traditionally arbitrarily set thresholds to consider procurement practices problematic under the Single Market Scorecard; see eg here). This could have a signalling effect that could influence decision-making at contracting authority level (eg to avoid triggering those red flags) in a way that pre-empts, limits or distorts the exercise of discretion—or that further displaces corruption-related exercise of discretion to areas not caught by the arbitrary indicators or thresholds, thus making it more difficult to detect.
Therefore, these issues can be particularly relevant in establishing both whether the balance between discretion and corruption risk is right under the new rulebook’s regulatory architecture and approach, as well as whether there are non-statutory determinants of the (lack of) exercise of discretion, other than the complexity and potential litigation and challenge risk already stressed in earlier analysis and reflections on the green paper.
Another ‘interesting’ area of development of UK procurement law and practice post-Brexit when/if it materialises.
Thanks to the UK’s Procurement Lawyers’ Association (PLA) and in particular Totis Kotsonis, on Wednesday 6 March 2019, I will have the opportunity to present some of my initial thoughts on the potential impact of complex technologies on procurement governance.
In the presentation, I will aim to critically assess the impacts that complex technologies such as blockchain (or smart contracts), artificial intelligence (including big data) and the internet of things could have for public procurement governance and oversight. Taking the main risks of maladministration of the procurement function (corruption, discrimination and inefficiency) on which procurement law is based as the analytical point of departure, the talk will explore the potential improvements of governance that different complex technologies could bring, as well as any new governance risks that they could also generate.
The slides I will use are at the end of this post. Unfortunately, the hyperlinks do not work, so please email me if you are interested in a fully-accessible presentation format (a.sanchez-graells@bristol.ac.uk).
The event is open to non-PLA members. So if you are in London and fancy joining the conversation, please register following the instructions in the PLA’s event page.