In this article, the company Aquarela Inovação do Brasil SA presents the Case of the Public Security Secretariat of Santa Catarina (SSP), an organization that directly/indirectly impacts the lives of 6.7 million people and that seeks to be a national/international reference in security management supported by data and artificial intelligence.
The case study showed how the SSP has progressed in the Data Analytics Culture Levels from level 2 to level 3, presenting relevant insights to organizations of similar size that seek structure your analytics processes with less risk in the shortest time, leveraging opportunities with the use of Artificial Intelligence.
What will I find in this article?
1 First challenges
2 Project activities
3 Results and current situation
4 References
First challenges
Sharing and interpreting information are essential aspects of australia whatsapp users and effective public management. Public and/or private organizations have traditionally been compartmentalized and one of the most basic challenges is therefore to connect the “silos”.
Silo in this context refers to self-contained information with little or no communication between units of the organization. In the context of SSP, a task that is repeated in much of the work of area managers, In addition to connecting silos, it alleviates problems of various natures.
It could be a lack of communication between sectors and team members, little time to think strategically, poor distribution of information or low agility in routine tasks.
The relationship between the organizations began in 2017 in Aquarela's introductory Data Analytics culture courses and also in the various interactions that took place in Florianópolis innovation ecosystem .
The implementation of the project brought a great challenge: to have an ideal decision support tool, we need all data to be integrated and up to date.
At the time, the department already had several data collections and some specific success stories with the implementation of BI.
Data Analytics maturity level 2 refers to a situation where various data were already collected in some way, but decoupled from an architecture focused on Data Analytics. In an analogy, it is as if the materials for the house were all on the land, but the house itself was not ready to move into.
This lack of analysis architecture has created great difficulties in mining data within the SSP. For example, someone asks about a piece of data and no one knows who the right person is who has the reliable and accurate information. When this happens, in addition to wasted time, it generates stress for teams.
One problem was the alignment between the agencies, as many sectors did not know information about the others, even though they worked together on some actions. The Analytics project was created with the aim of concentrating and sharing this information.
Another important issue to be resolved was timeliness. Much of the data was unstructured, which required a great deal of effort for managers to compile and use. It was necessary for all data (or most of it) to be integrated and up-to-date.
Storing information is easy, but making sense of it is hard. This is especially challenging when you are hampered by technological limitations, which was the reality of the institution. Information and knowledge are free, but insights were rare and difficult to prove.
Project activities
Unlike traditional project management, which is highly deterministic, Data Analytics projects, on the other hand, challenge managers by demanding an orchestration of extremely specific actions for each case.
Throughout the project period, several internal and external interactions between SSP teams were necessary until version 1.0 of the analysis office was established. Below we list some of the main activities:
Definition of Data Analytics roles for project management, process management, security and data integration levels;
modeling of integrated data dictionaries (What are data analytics dictionaries?);
acquisition of licenses for the BI tool – Qlik Sense. SSP found a solution to deal with these problems by adopting a single Business Intelligence (BI) technology tool, called the Analytics project;
generation of rapid prototyping linked to SSP areas, always in compliance with the 3 basic analysis requirements (business objective, available data and administrative processes);
definition of the analysis architecture by breaking down processes by areas of activity and segmenting access security;
data integration and large-scale testing;
creation of the data office brand called Analytics;
partnership with HUBSSP – the first Public Security innovation laboratory in Brazil;
agree on more effective information flows with the agencies and we work to ensure that the most up-to-date version of the data is always available;
Results and current situation
The Analytics Project has been connecting SSPSC from the roots to the top of the tree and has been an absolute agent of change in the institution, transforming the organizational culture and increasing the efficiency of public management.