Team + Value Management Center < Inquiry Count Forecasting> How many users’ inquiries do we need to treat for each LINE service every month? Every day? Every hour?
of predictions required every month for different departments - High project communication cost - Limited number of Data Scientists - Relatively similar data structure - Many repetitive operations of data pre-treatment and model training
and non-Data Scientist users from LINE biz/operational service department - For non-DS(non-Data Scientist) users - Let users do the forecast by themselves - For DS(Data Scientist) - Automate repetitive steps Motivation for Developing a Forecasting Tool
– for non-DS User - Supports different kind of data sources (CSV, MySQL, Presto, Spark SQL etc.) - Connects to internal DB - Provides anomaly detection and imputation function
– for non-DS User - Different types of models (Prophet, LSTM, ARIMA, Temporal Fusion Transformers etc..) - Hyperparameter Tuning - Model Explanation - Model Evaluation (RMSE/MAPE/WAPE etc..)
project communication cost VS Limited number of Data Scientists Repetitive operations of data pre- treatment and model training DS can take advantage of the API & advanced functions and can run batch jobs easily Non-DS Users can do predictions by themselves with the UI and functionalities developed Use Case with Value Management Center
- Use case – Inquiry Count Forecasting - After the usage of this tool, the work time has been reduced by 83% - The accuracy of prediction is higher and more stable, regardless of seasonality and personnel change. Source :https://linefukuoka.blog.jp/archives/20210630_01_news_plan_and_op.html
- Improve UI - Support more types of data visualization - Allow users to select weather/holiday common features - Support multi-horizon forecast Future Prospects