Impact on business ROI

AI competition has the following benefits which has a direct impact on business ROI:

1. Reduction in personnel costs for machine learning model development:

Typically, hiring dedicated machine learning engineers is necessary for developing machine learning models. In recent years, there has been an increase in the application of machine learning within companies to improve services and streamline operations. Additionally, the commercialisation of data science has expanded. Acquiring and retaining machine learning engineers involves significant costs. Furthermore, models built by these engineers may carry the risk of not being the best possible models developed at that time, as they are influenced by the resources available to the engineer and their own experience. Conversely, if data collection and preprocessing for building machine learning models have already been completed (bitgrit provides consulting services from data selection for competitions to data collection and preprocessing), organizing a competition immediately can allow for the development of the best model from a large number of participants compared to development by in-house dedicated engineers. This enables a significant reduction in the costs associated with hiring machine learning engineers and managing resources, while also obtaining the best model.

Additionally, conducting interviews with developers of models adopted through competitions as a secondary effect allows for gaining insights into the process of model development and acquiring knowledge for future in-house model development.

2. Recruiting machine learning engineers:

Data science competitions provide a platform to connect with and potentially hire engineers who rank highly on the competition leaderboard. Being ranked among the top performers in a competition with numerous participants indicates a high level of quality and makes it easier to screen for qualities required in potential hires, such as their areas of interest and technical knowledge.

Hackathons, which often involve engineers competing against each other to solve specific problems, are commonly held for the purpose of recruiting engineers who excel in certain domains. In this sense, data science competitions can also be seen as a platform for gathering engineers well-versed in specific fields of machine learning. Additionally, many competition participants include competition achievements on their resumes, which can facilitate the hiring process as there is alignment of interests between the sponsoring company and the winners.