A brief overview of the open data sources - opportunities and challenges. Anton will present a bird’s eye view of public procurement and outline main trends and possible uses of this dataset. The presentation will also put public procurement in the context of inequality analysis and social network analysis (SNA), using Gephi.

2. 2
Agenda
UPDATE REVEAL HIDDEN PATTERNS THE MIC IS YOURS

3. Networked Public Procurement
Anton Gerunov, Ph.D.
CCO @ LogSentinel & Ass. Prof. in Risk Management @ SU

4. Planfortheday
Have a look at
public
procurement
Consider
Network
Analysis
Enjoy the cool
graphs

5. Remarksonthe
DataSet
 Publicly available data on all public
procurement in the last decade on the
open data portal
 Data is actually surprisingly clean and
detailed, and relatively up-to-date
 A few quirks – format changed in 2016
because of new legislation

6. Statisticsonthe
Dataset
 Dataset spanning 2007-2016, 10 years
 Includes all public procurement, or a
total of 193,051 contracts
 21,558 unique firms

7. TheBird’sEye
View [CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE][CELLRANGE][CELLRANGE][CELLRANGE][CELLRANGE][CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE][CELLRANGE][CELLRANGE]
[CELLRANGE]
[CELLRANGE]
0
2,000,000,000
4,000,000,000
6,000,000,000
8,000,000,000
10,000,000,000
12,000,000,000
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
National Budget EU Funds Unspecified

8. MoreandMore
Procurement
OntheFringes
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Ministries and Agencies Municipalities Other Procuring Entities

9. High
Concentration
AmongTop50
0%
10%
20%
30%
40%
50%
60%
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

10. Little
Competition
1
participant,
24.6%
2
participant,
19.2%
3 participants,
15.5%
More than 3,
40.0%
Unspecified,
0.7%

11. Amotivating
question
 How would the network analysis of
public procurement look like?
 Let us focus on central administration
alone.
 Using

12. Adjacency Matrix:
Representing
Networks
1
2
3
45
0 0 0 0 0
0 0 1 1 0
0 1 0 1 0
0 0 0 0 1
1 1 0 0 0
A =

13. Pivoting Public
Procurement into
Adjacency Matrix

14. Andseeingthe
underwhelming
result…

16. Coloringthe
Network

17. TheNetwork

18. AFew Statistics
 Number of Nodes: 4,063
 Number of Edges: 6,852
 Graph Density: 0.001
 Average Degree: 1.686
 Maximum Degree: 427

19. Zoominginto
theNetwork

20. Understanding
theNetwork
Topology
And surely enough, the Ministry of
Labor and Social Policy

21. ThreeIdeasfor
Applications
1. If two (or more) contractor use the same
firms, they may benefit by bundling up
their purchases.
2. Network topology allows firms to see
potential customers in the public sector.
3. Network analysis may be used for
enhancing accountability and
transparency.

22. Discussion Time
Anton Gerunov, Ph.D.
CCO @ LogSentinel & Ass. Prof. in Risk Management @ SU