Academic Journal
A Business Analytics Approach to Lean Six Sigma for Improving Operational Efficiency and Organizational Performance.
| Τίτλος: | A Business Analytics Approach to Lean Six Sigma for Improving Operational Efficiency and Organizational Performance. |
|---|---|
| Συγγραφείς: | Sanikop, Shrilaxmi1 shrilaxmisanikop@gmail.com, SABAT, KALI CHARAN1 kalicharan-mba@dayanandasagar.edu |
| Πηγή: | International Scientific Journal of Engineering & Management. Jul2026, Vol. 5 Issue 7, p1-6. 6p. |
| Θεματικοί όροι: | *Business analytics, *Continuous improvement process, *Process optimization, *Statistical decision making, *Organizational performance |
| Περίληψη: | In today's competitive business environment, organizations continuously seek methods to improve operational efficiency, minimize process variation, reduce waste, and enhance customer satisfaction. Lean Six Sigma (LSS) has emerged as a powerful continuous improvement methodology by integrating Lean principles of waste elimination with Six Sigma's statistical approach to quality improvement. The present study aims to evaluate the effectiveness of Lean Six Sigma in solving operational problems and improving organizational performance through data-driven decisionmaking. A quantitative research approach was adopted by collecting responses from 127 employees working in manufacturing and service organizations using a structured questionnaire. Statistical techniques including descriptive analysis, correlation, regression, hypothesis testing, Linear Programming, and Markov Chain analysis were applied to evaluate the relationship between Lean Six Sigma implementation and operational efficiency. The findings reveal that organizations implementing Lean Six Sigma experience significant improvements in process efficiency, quality, customer satisfaction, and competitive advantage. Leadership commitment, employee involvement, and continuous monitoring were identified as critical success factors. The study concludes that integrating Lean Six Sigma with Business Analytics enables organizations to make evidence-based decisions, optimize resources, and achieve sustainable operational excellence. [ABSTRACT FROM AUTHOR] |
| Copyright of International Scientific Journal of Engineering & Management is the property of International Scientific Journal of Engineering & Management and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Business Source Index |
| FullText | Text: Availability: 0 |
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| Header | DbId: bsx DbLabel: Business Source Index An: 196188370 RelevancyScore: 1412 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 1411.61413574219 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Business Analytics Approach to Lean Six Sigma for Improving Operational Efficiency and Organizational Performance. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Sanikop%2C+Shrilaxmi%22">Sanikop, Shrilaxmi</searchLink><relatesTo>1</relatesTo><i> shrilaxmisanikop@gmail.com</i><br /><searchLink fieldCode="AR" term="%22SABAT%2C+KALI+CHARAN%22">SABAT, KALI CHARAN</searchLink><relatesTo>1</relatesTo><i> kalicharan-mba@dayanandasagar.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Scientific+Journal+of+Engineering+%26+Management%22">International Scientific Journal of Engineering & Management</searchLink>. Jul2026, Vol. 5 Issue 7, p1-6. 6p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Business+analytics%22">Business analytics</searchLink><br />*<searchLink fieldCode="DE" term="%22Continuous+improvement+process%22">Continuous improvement process</searchLink><br />*<searchLink fieldCode="DE" term="%22Process+optimization%22">Process optimization</searchLink><br />*<searchLink fieldCode="DE" term="%22Statistical+decision+making%22">Statistical decision making</searchLink><br />*<searchLink fieldCode="DE" term="%22Organizational+performance%22">Organizational performance</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In today's competitive business environment, organizations continuously seek methods to improve operational efficiency, minimize process variation, reduce waste, and enhance customer satisfaction. Lean Six Sigma (LSS) has emerged as a powerful continuous improvement methodology by integrating Lean principles of waste elimination with Six Sigma's statistical approach to quality improvement. The present study aims to evaluate the effectiveness of Lean Six Sigma in solving operational problems and improving organizational performance through data-driven decisionmaking. A quantitative research approach was adopted by collecting responses from 127 employees working in manufacturing and service organizations using a structured questionnaire. Statistical techniques including descriptive analysis, correlation, regression, hypothesis testing, Linear Programming, and Markov Chain analysis were applied to evaluate the relationship between Lean Six Sigma implementation and operational efficiency. The findings reveal that organizations implementing Lean Six Sigma experience significant improvements in process efficiency, quality, customer satisfaction, and competitive advantage. Leadership commitment, employee involvement, and continuous monitoring were identified as critical success factors. The study concludes that integrating Lean Six Sigma with Business Analytics enables organizations to make evidence-based decisions, optimize resources, and achieve sustainable operational excellence. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Scientific Journal of Engineering & Management is the property of International Scientific Journal of Engineering & Management and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.55041/ISJEM08385 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 6 StartPage: 1 Subjects: – SubjectFull: Business analytics Type: general – SubjectFull: Continuous improvement process Type: general – SubjectFull: Process optimization Type: general – SubjectFull: Statistical decision making Type: general – SubjectFull: Organizational performance Type: general Titles: – TitleFull: A Business Analytics Approach to Lean Six Sigma for Improving Operational Efficiency and Organizational Performance. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Sanikop, Shrilaxmi – PersonEntity: Name: NameFull: SABAT, KALI CHARAN IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 25836129 Numbering: – Type: volume Value: 5 – Type: issue Value: 7 Titles: – TitleFull: International Scientific Journal of Engineering & Management Type: main |
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