The Application of Business Intelligence and Analytics to Drive Better Business Outcomes in BSSB
A Small Tissue Paper Converting Establishment
Keywords:
Business intelligence, data analytics, manufacturing, productionAbstract
BSSB faces many uncertainties in its manufacturing, such as production targets, rejects and parent rolls' sources. Exposing business intelligence and analytics to BSSB will assist them in making wise choices and decisions. This study attempt to establish an output benchmark, analyse and suggest the manufacturing rejects rate and determine the best source of parent rolls. The definition of BSSB is a tissue paper converting company that has been in operation for four years. This study indirectly promotes sustainable development goals related to decent work, economic growth and innovation, and creating new jobs and business opportunities. The hypotheses tested the elements impacting output and rejects, such as basis weight (gsm), the TAPPI forecasted calculation (TFC) and weight. The chosen method is the CRISP-DM. Stages of CRISP-DM involved business understanding, data understanding, and data preparation divided into data cleaning, data verification, data exploration and selection, data transformation and construction. The data mining process included selecting the test models under classifications and clustering. Based on the test results, weight, actual output (ACTL), basis weight, and the TFC have positive relationships. The results that portrayed BSSB manufacturing operations as "superbly efficient" was inaccurate. BSSB needs to rectify its production to ensure the finished product meets its specifications. It should implement a rejection rate of 3% while improving its production and collecting new data. In addition, the source of parent rolls should be from batches named AA, BB, CC and DD. The result of output consistency, basis weight, and productivity were the criteria used to formulate recommendations. Also included were suggestions for a specific data collection and recording area to facilitate further analysis. Business intelligence and analytics may have discovered the facts about the production of BSSB, but the decision to improve and implement lies at their management discretion
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