Training organisations and guidance professionals can now obtain data on the skills required in working life. At the same time, SECLE can monitor the effectiveness of its funding and make its activities more transparent for members of the public. “The traditional practice in the central government has been to monitor how much money was distributed and to whom. In this model, we focus on what was achieved with funding. We monitor the impact of our activities on society at large,” says Kirsi Heinivirta, Director of SECLE.
Established in 2021, SECLE sought modern knowledge-based management solutions. SECLE aims to respond quickly and flexibly to any mismatches in working life.
The goal was to improve the development of training and competence services through anticipation data and enable the effectiveness of funding to be monitored efficiently. SECLE now monitors the effectiveness of granted funding using pre-defined metrics. At the same time, scattered anticipation data have been compiled and processed for further uses.
What does all the money buy?
Through the use of data and analytics, SECLE is leading the way in reporting operational effectiveness in the central government. SECLE saw that it is important for a new organisation to be transparent from the get-go and communicate what can be achieved with tax revenue.
“What has been particularly valuable is that, while initiating our activities, we have simultaneously been able to develop such a monitoring system. The demand for accountability is constantly growing in society. Many organisations start to build systems to measure effectiveness and efficiency retrospectively. We have done everything right from day one, as we started this system project while we were still taking our first steps,” Heinivirta says.
A modern and reproducible data warehouse solution
SECLE bridges the gap between the needs of the employment market and employees’ skills. It provides funding for training and competence services, as well as disseminates and produces anticipation data. The goal of the partnership was to build a system in which data can be compiled, analysed and distributed. Anticipation data are used in planning the funding SECLE provides for training and competence services. Data help identify the most significant competence needs among Finland’s working-age population.
Solita built a new data platform for SECLE and analytics solutions on top of it. Three use cases were completed during the project, two of which are related to analysing anticipation data, while the third helps SECLE monitor the effectiveness and allocation of the funding it provides.
The partnership resulted in a new scalable data lakehouse solution based on the AWS cloud. It merges the best parts of a data lake and a data warehouse such as conventional databases, cloud services and data integration into a single system. These properties help build a strong understanding of business, accelerate decision making and improve operational efficiency. The data lakehouse also enables operational expansions without any major investments in infrastructures.
“How can people get educated for hot industries such as wind power? From what parts of Finland do graduates come from? How can we respond to changes in business and work structures through additional training? These are but a few of the questions to which SECLE can now find answers,” Karppinen says.
“While this was a technically challenging project, it was also very educational and rewarding,” she continues.
On the way towards knowledge-based management
The project was a success, and all business-related goals were achieved. SECLE can now comprehensively analyse its funding process and the effectiveness of the funding it provides. Openly communicating the criteria for receiving funding to stakeholders on the SECLE website is also part of the modern way.
SECLE is a new organisation with ambitious goals. Various approaches had to be explores along the way, and plans had to be adjusted based on what data were actually available and how different data sources could be combined. Information flowed constantly in both directions. Because the project progressed concurrently with SECLE building its own data system, it was possible to make SECLE’s data collection processes compatible with the data models.
