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The Implementation of Business Analytic Solution in PROTON Holdings Berhad
- 1. PRESENTED BY WEI ZHEN, MENG CHUAN & JIUNN KAI The Implementation of Business Analytic Solution in PROTON Holdings Berhad
- 2. Introduction of Company Background ▪ Proton Holding Berhad established in Malaysia on 1983 ▪ Distribute task to department (Branch) ➢ Engineering Service ➢ Manufacturing ➢ Sales and Distribution ➢ Financial Service ➢ Property ➢ Other Equity Investment ▪ Proton Holding Berhad is an automotive industry, they manufacturing the car and sale to customer ▪ Proton Holding Berhad provide car service (after sales service)
- 3. Team of The Project Project Manager Business Analysis Team Analytical Development Team Data Scientist Statistician Business Analyst Project Sponsor Technical Architecture Team Database Administrator Data EngineerData Architect Sales & Distribution Department Manufacturing Department R&D Department Finance & Accounting Department Business Analyst Business Analyst Business Analyst Business User Business User Business User Business User
- 4. Problem Statement ▪ Bad customer feedback problem ➢Untrusted relationship is created between Proton and customer cause Proton sales decreasing ▪ Need is to re-energize the confidence of the customers to their products. ➢They need to improve the product’s quality and aim with the requirement that most customers want. ▪ Geely investment brings an opportunity to Proton for getting shared car technology from Geely. ➢Geely latest developing technology, EV car or Self-driving car, which technology to choose and invest by Proton?
- 5. Scope of Proposed Analytic Solution ▪ Studying the customer feedback ▪ Forecasting the impact of customer feedback to Proton’s sales ▪ Identifying for the right Car market and what the customers actually need. ▪ Proton may analyse on the sales data of the past 10 years. ▪ Identify the EV car interest in Malaysia people and market. ▪ Discover the potentiality of EV car in Malaysia market and aspect to be focused.
- 9. Data Mining Methodology • Fayyad’s KDD is used.
- 10. ▪ Studying of customer feedback ➢ Clustering algorithm is suitable for grouping the similarity of the feedback ▪ Forecasting the impact of customer feedback toward the Proton company sale ➢ Classification algorithm is suitable because customer feedback including ‘big data’ ▪ Identifying for the right car market ➢ clustering method is chosen – Group the sales data in certain pattern. ▪ Studying of EV car potentiality in Malaysia market ➢ Descriptive Analytic – Clustering algorithm – gather the same set data together. Eg, public interest & government offered policy ▪ Predicting of the future of EV Car trend and market potentiality in Malaysia ➢ Predictive Technique – Regression algorithm – forecast the continuous value changes. Eg, EV car focused aspect & market demand Data Mining Techniques for The Purposed Solution
- 11. Impact of The Purposed Solution ▪ Studying customer feedback ➢ Understand the reason of bad feedback, do improvement on particular reason ➢ Problem can solve if Proton’s take proper solution ▪ Forecasting impact of customer feedback to Proton’s sales ➢ Know the future sales through customer feedback, identify the impact (Big/Small) ➢ Problem could not be solved if the impact is small ▪ It helps the company to find the correct direction to do their sales. ▪ Able to give support to Proton in identified the EV car current & future market potentiality ➢ Neither solved or unsolved, prediction future EV trend might be inaccurate. ➢ Lacked of testing data & changes that take place in reality.