One System That Optimizes Many Government Processes in Canada
Do you have any questions? Contact us!
I agree the Terms of Service
published April 8, 2020
Since May 2017, we have been developing and improving the Canadian startup product. Our task was to automate and simplify business processes by creating a secure tool that collects reliable and complete data on social investments' returns using detailed reports.
Since May 2017, we have been developing and improving the Canadian startup product. Our task was to automate and simplify business processes by creating a secure tool that collects reliable and complete data on social investments' returns using detailed reports.
Companies and government in Canada demonstrate their impact on the community through regular reporting, but quantifying the social returns on their investments is very difficult. The traditional social performance reporting methods used by investing companies were previously labor-intensive. Often, they had to use several data sources, a large number of spreadsheets or paper media to generate one necessary report, and it took several hours or even days to create a report on one initiative. There was a very complicated process involving a vast amount of human resources and the likelihood of a mistake.
To receive grants and contributions, recipients of funds must create and coordinate a system for evaluating the effectiveness of their initiatives. At the start of the project, the documents' recipients documented the tools and methods for collecting data that each project should use to measure progress towards their short-term results.
By the contribution agreement, recipients of the funds were required to submit reports with data collected during the project's implementation. The government program employees provided report recipients with report templates in Word, Excel, or PDF format. Recipients received and analyzed data within their project using various methods and entered them into report templates, after which they sent reports by e-mail.
After receiving reports from the recipients of funds, government employees had to transfer progress data from the submitted reports to the general system of government grants and contributions. Depending on the completeness of the reports, this information was entered with different levels of detail.
The government system at that time did not support work on data analysis, and therefore it was manually performed by government analysts.
Analysts often had problems because the data was difficult to find or was not in the right place. In such cases, the analyst had to correct the data independently and enter it into the database. This process was laborious and inefficient, during which the report data could be distorted, and errors were made in them.
By the contribution agreement, recipients of the funds were required to submit reports with data collected during the project's implementation. The government program employees provided report recipients with report templates in Word, Excel, or PDF format. Recipients received and analyzed data within their project using various methods and entered them into report templates, after which they sent reports by e-mail.
After receiving reports from the recipients of funds, government employees had to transfer progress data from the submitted reports to the general system of government grants and contributions. Depending on the completeness of the reports, this information was entered with different levels of detail.
The government system at that time did not support work on data analysis, and therefore it was manually performed by government analysts.
Analysts often had problems because the data was difficult to find or was not in the right place. In such cases, the analyst had to correct the data independently and enter it into the database. This process was laborious and inefficient, during which the report data could be distorted, and errors were made in them.
We have developed many microservices for Canadian startups - a centralized authentication service, a report designer for collecting data and statistics, a logical model building service, and a service for de-identifying user personal data.
Using a microservice for data collection, recipients of funds can enter their data collected in various ways into one repository. Instead of sending reports with social performance data via e-mail, they send them to their project within the system.
The primary way to collect data for companies is through surveys. That is why, in the first place, it was necessary to create a convenient and functional tool for creating and managing survey forms.
The form designer has a full set of functionality that allows you to create various survey forms with multiple options for filling them out, posting answers, pictures, and input fields. But, in addition to the usual functions, the system allows you to create a hierarchy. Many forms must contain mandatory questions from the government or the investor. Some nesting creates questions in the forms, and each subsequent participant in this process can add a series of questions to questions already created from another structure. The system is bilingual and allows you to enter data directly into the forms received by mail, by reference, or from paper.
It is also possible to download large amounts of data from CSV and Excel files, automatically converting them into forms with answers. This function is implemented based on parsing data from tables that were prepared in advance in excel.
Gathering information in some surveys requires respondents' anonymous responses accurate data from respondents, and you still need to identify them somehow and not allow them to answer again. To do this, we implemented a question-identifier function and a unique way of identifying a user by first and last name or contact information or respondent's birthday in a microservice with de-identification of data to the system. When filling out the fields, the system can understand what kind of person responds to the survey. These data are converted and reflected in the answer list as a unique encrypted code consisting of characters and numbers after submitting the form. The system automatically generates and remembers, preventing you from filling out the survey again.
After the data is collected to provide a report, it is necessary to analyze and present it in the form of visual graphs, charts, or lists and build a calculation of the future return on investment. To do this, we created a unique tool for creating logical models.
It is also possible to download large amounts of data from CSV and Excel files, automatically converting them into forms with answers. This function is implemented based on parsing data from tables that were prepared in advance in excel.
Gathering information in some surveys requires respondents' anonymous responses accurate data from respondents, and you still need to identify them somehow and not allow them to answer again. To do this, we implemented a question-identifier function and a unique way of identifying a user by first and last name or contact information or respondent's birthday in a microservice with de-identification of data to the system. When filling out the fields, the system can understand what kind of person responds to the survey. These data are converted and reflected in the answer list as a unique encrypted code consisting of characters and numbers after submitting the form. The system automatically generates and remembers, preventing you from filling out the survey again.
After the data is collected to provide a report, it is necessary to analyze and present it in the form of visual graphs, charts, or lists and build a calculation of the future return on investment. To do this, we created a unique tool for creating logical models.
The logical model designer automates the previously manual process of creating analytical models and calculating data based on the collected data in a microservice for data collection. These are the critical functions of a performance measurement system required by socially-oriented programs and government departments. The service we developed centralizes vital indicators, which allows us to carry out standardization between different projects. The logical model builder enables non-expert users to create complex analytical models using the recommendation engine. Users are invited to fill out a user profile that describes their level of knowledge in impact reporting, the project from which they would like to start. Based on this profile and specific information about the program, the application will offer indicators that correspond to the program under consideration and calculations that correspond to the organization's potential.
Logical model building, data collection, and standardized reporting are indispensable for reporting impacts, which, being manual processes, are incredibly burdensome in terms of time, effort, and data integrity. The software significantly reduces the workload and simplifies the impact reporting process, allowing users to perform calculations, often at the enterprise level, and using a recommendation mechanism to simplify the configuration process. User testing showed that using the application allows users to spend 65% less time developing a logical model, collecting data, and creating reports.
The application developed by us allows us to solve the full life cycle of reporting on social impact. Budget recipients no longer have to bother with spreadsheets, third-party survey products, and special reports.
Instead of providing a one-time static report on one initiative, the system optimizes and automates data collection, allows real-time analysis of relevant performance indicators for programs, and helps our customers to understand the big picture of how their investments benefit.
The system is located in a production environment and continues to be developed; integration with artificial intelligence, machine learning, and additional services is planned.
Our professional development team is ready to implement any solution for your business using advanced technologies. Let's discuss!
The application developed by us allows us to solve the full life cycle of reporting on social impact. Budget recipients no longer have to bother with spreadsheets, third-party survey products, and special reports.
Instead of providing a one-time static report on one initiative, the system optimizes and automates data collection, allows real-time analysis of relevant performance indicators for programs, and helps our customers to understand the big picture of how their investments benefit.
The system is located in a production environment and continues to be developed; integration with artificial intelligence, machine learning, and additional services is planned.
Our professional development team is ready to implement any solution for your business using advanced technologies. Let's discuss!
Did you like this article?
Share article on social networks
Worked on the article:
Maria Ilchenko
PR and Event Manager
