IMPLEMENTING PREDICTIVE ANALYTICS MODEL FOR NEW PRODUCT DEVELOPMENT IN MICRO, SMALL AND MEDIUM ENTERPRISE

• Main Author: Angela, Tessa
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/38894
• Institution: Institut Teknologi Bandung

The ever-rising level of competition and change in customers’ taste and preference push food service businesses to be innovative by offering new products in order to meet customers’ expectations. Unfortunately, those innovations often do not fulfill the market’s demand as the decisions made disregard accurate information. The failure rate is significantly higher for Micro, Small & Medium Enterprises (MSMEs) which are yet to realize and have the ability to optimally manage their data. Therefore, this research is aimed to implement a method of data management using predictive analytics for the decision-making process regarding new product developments. Using predictive analytics, historical data owned by MSMEs can be converted into valuable information, which provides an overview of current and even future business outlooks. Moreover, the predictive analytics model provides recommendations on relevant strategies with regards to new product sales. The implementation of predictive analytics model for MSMEs follows a modelling framework known as CRISP-DM, which is combined with V-model. Macro-Excel is used as a tool to develop the model due to its wide availability, high affordability and ease to implement. Lastly, the information produced is displayed in the form of a dashboard so that it is easy for users to understand. The results have successfully passed a series of testing and proved to have an accuracy of more than 93%.