Retail Analytics Using SAS: Experience of Fresh Greens Pvt. Ltd., Bangalore.
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| Title: | Retail Analytics Using SAS: Experience of Fresh Greens Pvt. Ltd., Bangalore. |
|---|---|
| Authors: | Dasari, Shailendra1 shailendra.dasari@gmail.com, Kurhekar, Anil S.2 anil.kurhekar@gmail.com |
| Source: | IUP Journal of Supply Chain Management. Mar2011, Vol. 8 Issue 1, p7-22. 16p. 8 Black and White Photographs, 2 Charts, 2 Graphs. |
| Subjects: | SAS (Computer program language), Retail industry, Data analysis, Business models, Decision making, Fresh Greens Pvt. Ltd. |
| Geographic Terms: | Bengaluru (India), India |
| Abstract: | India is witnessing a retail explosion. Leverage of the enormously available customer data for aligning precious resources with customers' needs makes it imperative for retail managers to deploy advanced tools and techniques for data analysis and generation of reports for effective decision-making. While a host of analytical processes and tools are available, a retailer needs to invest selectively and adopt to those applications that are proven to be successful, and resulted in substantial savings in terms of money, time and shelf space. This paper, apart from highlighting the relevance and efficacy of analytics for retail industry in India, also deals with a live study undertaken at Fresh Greens Bangalore, where Market Basket Analysis (MBA) and advanced demand forecasting techniques have been used for understanding the demand associations of different fruits and vegetables and fine-tuning their operations. Based on the findings of this study, certain conclusions, not only specific to Fresh Greens, but generally applicable to fruits and vegetables retailers in India, have been drawn and suggestions are provided for enhancing the operational efficiency and effectiveness. [ABSTRACT FROM AUTHOR] |
| Copyright of IUP Journal of Supply Chain Management is the property of IUP Publications 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.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 59806888 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Retail Analytics Using SAS: Experience of Fresh Greens Pvt. Ltd., Bangalore. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Dasari%2C+Shailendra%22">Dasari, Shailendra</searchLink><relatesTo>1</relatesTo><i> shailendra.dasari@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Kurhekar%2C+Anil+S%2E%22">Kurhekar, Anil S.</searchLink><relatesTo>2</relatesTo><i> anil.kurhekar@gmail.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IUP+Journal+of+Supply+Chain+Management%22">IUP Journal of Supply Chain Management</searchLink>. Mar2011, Vol. 8 Issue 1, p7-22. 16p. 8 Black and White Photographs, 2 Charts, 2 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22SAS+%28Computer+program+language%29%22">SAS (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Retail+industry%22">Retail industry</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Business+models%22">Business models</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+making%22">Decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Fresh+Greens+Pvt%2E+Ltd%2E%22">Fresh Greens Pvt. Ltd.</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Bengaluru+%28India%29%22">Bengaluru (India)</searchLink><br /><searchLink fieldCode="DE" term="%22India%22">India</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: India is witnessing a retail explosion. Leverage of the enormously available customer data for aligning precious resources with customers' needs makes it imperative for retail managers to deploy advanced tools and techniques for data analysis and generation of reports for effective decision-making. While a host of analytical processes and tools are available, a retailer needs to invest selectively and adopt to those applications that are proven to be successful, and resulted in substantial savings in terms of money, time and shelf space. This paper, apart from highlighting the relevance and efficacy of analytics for retail industry in India, also deals with a live study undertaken at Fresh Greens Bangalore, where Market Basket Analysis (MBA) and advanced demand forecasting techniques have been used for understanding the demand associations of different fruits and vegetables and fine-tuning their operations. Based on the findings of this study, certain conclusions, not only specific to Fresh Greens, but generally applicable to fruits and vegetables retailers in India, have been drawn and suggestions are provided for enhancing the operational efficiency and effectiveness. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IUP Journal of Supply Chain Management is the property of IUP Publications 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: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 7 Subjects: – SubjectFull: SAS (Computer program language) Type: general – SubjectFull: Retail industry Type: general – SubjectFull: Data analysis Type: general – SubjectFull: Business models Type: general – SubjectFull: Decision making Type: general – SubjectFull: Fresh Greens Pvt. Ltd. Type: general – SubjectFull: Bengaluru (India) Type: general – SubjectFull: India Type: general Titles: – TitleFull: Retail Analytics Using SAS: Experience of Fresh Greens Pvt. Ltd., Bangalore. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Dasari, Shailendra – PersonEntity: Name: NameFull: Kurhekar, Anil S. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2011 Type: published Y: 2011 Identifiers: – Type: issn-print Value: 09729267 Numbering: – Type: volume Value: 8 – Type: issue Value: 1 Titles: – TitleFull: IUP Journal of Supply Chain Management Type: main |
| ResultId | 1 |
