Data Governance in Guanajuato State

Gerardo Guerrero Martinez, Chief Data Officer (CDO), Gobierno del Estado de Guanajuato

First of all, we think that data is one of the principal organizational assets. In a free and sovereign state government in México, we have different agencies with a lot of normativity and laws and different ways to visualize, define, read, store and use data.

Data governance in Guanajuato is an attempt to define a common language to allow data to travel transversely with the same meaning for all. Focus on data related to government acts that generate public value.

We need to answer immediately when, where and how much. Do we have evidence? How many people benefited from those acts, and what processes were improved? Etc.

We found other efforts in the U.S. (Federal Data Strategy), Colombia (Data Strategy) and Spain (Spain 2015). Those efforts are related to digital transformation for the benefit of people.

This is not a technology project; it is a technology-enabled project. However, the real challenge is cultural issues.

The Challenges

a)Difficulty in following up on planning instruments at different levels and dimensions.

b)Difficulty integrating information from different transversal processes.

c)Duplication of efforts making different products

d)We use specialized technological tools, disjointed from each other at different levels of information detail.

e)Problems integrating information with the same approach and with intersectoral scope.

f)Technological gaps between agencies

The Achievements

Homologation and standardization of data for different purposes:

a)Inter-secretary Commission for the Prevention of Violence and Crime

b)Planet Youth – Addiction prevention

c)Focus on programs like childhood, social aid, ecological impact and infrastructure creation.

We have collected a lot of data from agencies and analyzed them in a heat map format as follows.

This map shows people helped compared with the amount of money applied.

This dashboard shows all budget codes showing different things at the same time:

a)Ball size is the amount of money contained in that budget code.

b)Balls go up depending on the budget spending. It is documented with evidences, like beneficiaries, location, description, classification, even photograph evidence.

c)The indicators go right when the budget is really compromised or paid.

Obviously, the ideal dashboard situation is that all budget codes (balls) are in the green quadrant.

"Data governance in Guanajuato is an attempt to define a common language to allow data to travel transversely with the same meaning for all"

We can say that we have only one version of truth. All data with public value passes through data governance tools and falls into a repository used to make reports, maps, heat maps, and graphics.

The main goal is monitoring public policy results and impacts with accuracy and opportunity.

Another achievement is transparency in citizenship, with information on web portals and open data sharing with society.

We have been awarded several times for transparency, monitoring and accountability.

This is the base of a digital transformation. We have other departments that use AI and machine learning. We only deal with data quality and criteria homologation transversally among agencies.

Guanajuato government is working on several projects going to a digital transformation:

a)Data Governance

b)Infrastructure for all (Red GTO) is oriented to take free wi-fi internet to every city, school, hospital, etc.

c)Data analytics, AI, Machine Learning

d)Cultural (re-education)

Transparency

We are proud because Guanajuato has been awarded for transparency in financial management. You can see our transparency and open data portal at:

https://presupuestoabierto.guanajuato.gob.mx

You can consult and download financial information, geographic information on government acts with public value, different data sets, etc.

What Did We Do?

Diagnosis Phase

First, we work very hard to define what, why, and for what impacts people’s benefit.

We went to the biggest agencies (based on budget size) and small agencies with some focus different from the others. We analyzed the way they get, register and store data and the infrastructure they use. How they call every single thing and concept, and what kind of criteria was used to do this. We identify talent, too, because citizens don't see an agency; they see a government, and they don't care if your name is a financial or economic agency. Identifying this talent was a strategy to involve all talent possible in this project.

Data Analysis

After visiting those agencies, we collect a lot of information, structures, criteria, points of view, etc. Gigabytes of data were analyzed from different points of view and from different dimensions. We realized that a lot of data didn’t have a clear definition or origin; there was no consistency in requirements and papers used in different processes in the same agency, among other things. We define an organizational and technological maturity level for each agency.

Scope Definition

Political times are complicated. We needed to know what we really can do in one, two and three years. We needed to create a data normativity that is easy to understand for all people and all levels of government. To accomplish this, we analyzed normativity mainly in the U.S., Colombia and Spain, and we strongly reviewed DMBOK (dama.org).

We think that a DMBOK implementation is justified if you are in a ‘compliance’ project, if you are a bank for example. We use DMBOK like a guide.

Practical uses of that normativity were also defined in the scope based on problems we experienced in the past. So, this was a cycle of defining normativity and building solutions with it.

Implementation

All data normativity and data catalogs and criteria are published in:

https://gobiernodedatos.guanajuato.gob.mx  (Only Spanish version for now)

You can get main catalogs with different formats (JSON, Excel, API) and consult our normativity in two documents:

a)Data governance model.

b)Data governance Implementation guide.

Conclusions

What is Data Governance in Guanajuato?

a)Standardization, homologation, and continuous improvement of strategic information assets, which generate public value (Government Acts), which have some tangible or intangible benefit to citizens.

b)Always consider the nature of the public policy that gave rise to those acts (Traceability).

c)Describe in detail the nature, location, and investment made, as well as their beneficiaries and profiles (Geolocation and evidence).

Data Governance Model Objectives

a)In a holistic approach, no one can stay out of this kind of initiative.

b)Generate an ecosystem focused on data.

c)Promote the creation and use of master data.

d)Assist in the identification of cross-cutting and focus issues, which allow for monitoring regardless of the sector or agencies involved.

Financial

Digital Transformation

Machine Learning

AI