When you take a course with IACA, you know you will get state of the art knowledge about the field from diverse guest lecturers who are proven specialists in their respective trades. During one such course at 2019 Regional Summer Academy, I had the opportunity to participate in a roundtable discussion, where a guest from Singapore was invited as one of the panelists. He presented the recent development in Singapore related to identifying corruption risks in public procurement using purchasing data.
I immediately asked questions about his experience with the approach and process of analyzing procurement data. My thinking behind my questions was “How do you do this? Is it difficult? Does it require cutting edge technology or method?” His reply was encouraging to say the least. The majority of methods used in analyzing procurement data were simple tricks of statistics such as finding mean value, deviance, and comparing the calculated values based on certain parameters. Which means everyone could implement it in his/her respective country, but one might need a solid database to do so.
As Mongolia rolled out its e-procurement system in 2017 I had the hope to introduce this data tool to my country’s anti-corruption practice. Since this discussion I was constantly on the lookout for additional knowledge and inspiration about my new found interest. Through much processing, long delay and numerous iterations, I finally managed to piece together procurement data using specific indicators with the help of colleagues in State Public Procurement Agency in June of 2021.
Displayed below is part of my early analysis of procurement data concerning two of the biggest State-Owned Enterprises (SOEs) in Mongolian mining Industry. Let me breeze through it to give you more complete picture. Since the main data contains sensitive information, I decided to use code words to present it below.
For context, two SOEs in question are mining companies of different pedigrees. SOE-A is one of the biggest tax paying entities in the economy, whereas SOE-B is comparatively smaller in its size and contribution in state budget. The graph below perfectly summarizes the dissimilarity.
In 2020, SOE-A organized 1755 procurement activities whilst SOE-B only managed 597 tenders for the same period. One concerning figure here is the number of direct contracting method employed by the SOE-B. Even though the SOE-B is much smaller in size, it procured 306 goods and works without competitive procedure compared to 124 of SOE-A. Law usually describes scenarios where one can utilize direct contracting method, but one must always try to avoid such procedure as it stifles competition and is prone to corruption risks.
The roll out of e-procurement system was a huge milestone in Mongolia’s fight against corruption. It brings the transparency and accountability of a public procurement to a new level. However, the e-procurement system is as good as the data it is supplied. Ideally, to ensure transparency of the public procurement, public institutions must supply its tender related data as soon as possible once the tendering procedure is over. The thinking behind my next analysis is, unless stated by law otherwise, that public institutions shall not act negligently in disclosing its data to the public in a timely manner. Below are the number of fields of the e-procurement system that have missing or overdue entries.
|Overdue Entries as of inspection||206||149||28||201||17||7|
|Missing Entries as of inspection||29||28||4||28||4||–|
In 2020, SOE-A was very lax in entering its procurement data to the system with 149 overdue entries compared to 17 overdue entries by SOE-B for the same period. Overall, SOEs are less prone to neglecting the data fields of the system altogether, however, disclosure of the data through the system leaves much to be desired.
My last piece of analysis relates to the number of tenders organized just under the statutory floor price. The Procurement Law of Mongolia provides statutory floor price for goods, works and services. According to the Law, if the goods and works are of value under MNT 50 million (~ USD 17,500) and MNT 80 million (~ USD 28,000) respectively, the public organization is clear to proceed with direct contracting. The rationale behind my last point is, many public institutions use the floor price to split goods and works for the purpose of circumventing competitive procedures.
The graph shows SOE-A organized 149 tenders just below the floor price in 2020. Compared to SOE-B, SOE-A chose non-competitive procedure more often, but one must factor the fact that SOE-A is much bigger in size.
For the purpose of this study, we needed to determine what is “just below the floor price”. Through numerous exchanges with colleagues and analyzing raw data, the following consensus was reached that it ranges between MNT 48-50 million (~ USD 16,800 – USD 17,500) for goods and MNT 75-80 million (~ USD 26,300 – USD 28,000) for works.
I had the opportunity to present my full analysis and discussed the findings with upper-level managers of both SOEs last June during e-meeting. One can see practicality from this analysis as it equips one to see the whole picture using only data. It also pinpoints risks or red flags for potential corrupt practice in public procurement if used wisely. However, I believe the analysis would generate much more impact, if conducted methodically and at a full scale. This is the aim I am working to meet as my next step.
I hope I will meet you again with my next impact story after I finish implementing step just mentioned, maybe on the 15th anniversary of IACA. Until then, fellow alumni!