“Data challenge” platform and methodology

To encourage data-driven decision making in public sector, University of Latvia and Microsoft Innovation Center developed a “Data challenge” platform and methodology. Aim of the initiative is to bring together teams of public sector officials and data analysts and in few weeks to create several AI solution prototypes for a specific public sector challenge giving the organisation an opportunity to explore innovative, data-driven solutions that they eventually can develop and implement in practice

Innovation Summary

Innovation Overview

Nowadays there is an immense pressure on public sector organisations to increase efficiency, decrease administrative burden on citizens and businesses, make wise data-based decisions while being cost effective and innovative all at the same time. From citizen perspective such demands make sense since government spends their tax money, thus they should work in the citizens’ best interests.
At the same time, public sector institutions have many legal and legislative restrictions hindering development and implementation of new, innovative yet sometimes less explored ideas, methods and programs. To invest money wisely in new ideas the institution has to be sure that the solution is worth it, yet they don’t have an opportunity to test it beforehand. This creates vicious circle and institutions get stuck.

Being an active part and one of the main facilitators of the innovation ecosystem in Latvia, the University of Latvia and Microsoft Innovation Center created a platform and a methodology called “Data challenge” to address the above-mentioned challenge. Data based problem solving and decision making is one of the challenges in public administration. It is therefore essential that both public sector professionals and data analysts exchange knowledge and gain experience in data analysis and data-driven decision-making. Every workshop is built around one well-defined public sector institutions problem. Teams of data analysts then try to create a solution various data analysis approaches, ranging from interactive data analysis to Machine Learning and Neural Networks

The target audience are the representatives from public sector and local business, data analysts and researchers from universities. During the seminar they are teaming up, working together to develop potential solutions for the defined task. At every event there is one public sector institution presenting a problem that they hope to be solved by creating a smart, data analytics-based solution. Teams comprised of data analysts, technology experts and enthusiasts then have a couple of weeks to explore available datasets and other relevant information and to create a solution prototype.
Then, the teams present their ideas and working prototypes at the next event where data analysis expert evaluates the model from technical point of view, and the organisation’s representatives give feedback on how useful and applicable the solution would be in the real setting.

Such platform and method give freedom and sparks enthusiasm to every involved party as it is set up as a challenge and a visionary method while still solving real life problems. Also, it is important that the holder of the platform is a neutral organisation building trust among everyone involved. The public sector organisations can see and assess the prototype before deciding to invest the funds in the solution development.

The “Data Challenge” seminars have already produced successful results. The Court Administration of Latvia participated in the “Data challenge” looking to improve efficiency of their processes. They provided data about the third category civil cases examined in the first instance in 2017. Using a variety of data analytics tools, a model (based on a neural network) was developed that could predict and determine the potential length of the court proceedings. The results provided by the data-driven test model were compared to the predictions of the judges about the same court proceeding cases, and it turned out that the judges were way more optimistic (and less precise than the test model) about how much time it takes for them to proceed the case. This solution now allows them to optimise their operations and organise their workflow much more precisely.

Similarly, Rural Support Service of the Republic of Latvia wanted to optimise the process of classifying images that local landowners and also their own employees take and use to evaluate the status of territory – whether the grass is mowed and removed or not. Based on the situation, Rural Support Service makes decision whether to grant support for the farmer. They receive huge number of photos and have to manually go through all those photos and mark each of them in one of the categories. It takes a lot of time and is not effective. Therefore, “Data challenge” teams used image recognition to offer a solution for this task. Now, Rural Support Service is considering the implementation of such solution that will save them time, money and will increase precision eliminating human error. Ultimately, landowners would be able to receive their state support faster improving their cashflow.

The “Data Challenge” platform and methodology can be applied to solving different problems – not only data-based ones. In future, this will be applied to different scenarios for public sector organisations on all levels.

Innovation Description

Innovation Development

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Year: 2017
Level of government: Other


  • Identifying or Discovering Problems or Opportunities - learning where and how an innovative response is needed
  • Generating Ideas or Designing Solutions - finding and filtering ideas to respond to the problem or opportunity
  • Developing Proposals - turning ideas into business cases that can be assessed and acted on
  • Implementation - making the innovation happen
  • Evaluation - understanding whether the innovative initiative has delivered what was needed
  • Diffusing Lessons - using what was learnt to inform other projects and understanding how the innovation can be applied in other ways

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