A framework for measuring return on data investment

A framework for measuring return on data investment | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A framework for measuring return on data investment Debarag Banerjee, Kamlesh Kumar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8568367/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 17 You are reading this latest preprint version Abstract In the era of big data, organizations face unparalleled opportunities to harness extensive data resources for competitive advantage. This study underscores the importance of assessing the return on data investment (RODI) as a foundational element in data-driven decision-making. It examines the critical role of RODI evaluation in guiding data-related investments, addresses the inherent challenges of quantifying data value, and explores methodologies tailored to financial lending firms for measuring RODI. The research further highlights the strategic benefits of adopting a comprehensive RODI framework to enhance operational efficiency. Additionally, the analysis incorporates relevant scholarly perspectives that emphasize the significance of financial metrics in optimizing data-centric strategies. JEL Classification: L86, D81, D82, E51, G21 Data Financial data ROI Data investments Return on data Digital divide Digital services Document services Interest rate Credit risk Credit risk model Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 16 Mar, 2026 Reviews received at journal 11 Mar, 2026 Reviewers agreed at journal 03 Mar, 2026 Reviews received at journal 01 Mar, 2026 Reviewers agreed at journal 27 Feb, 2026 Reviews received at journal 19 Feb, 2026 Reviewers agreed at journal 13 Feb, 2026 Reviews received at journal 11 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers invited by journal 11 Feb, 2026 Editor invited by journal 29 Jan, 2026 Editor assigned by journal 20 Jan, 2026 Submission checks completed at journal 20 Jan, 2026 First submitted to journal 20 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8568367","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":591514686,"identity":"40811ac1-d207-4e32-9a39-3fb239e8b19e","order_by":0,"name":"Debarag Banerjee","email":"","orcid":"","institution":"L\u0026T Finance","correspondingAuthor":false,"prefix":"","firstName":"Debarag","middleName":"","lastName":"Banerjee","suffix":""},{"id":591514687,"identity":"098015bb-74a0-4a5b-b3d7-9c7d43362c1b","order_by":1,"name":"Kamlesh Kumar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIie3PMUvDQBjG8fcIJMtbXC9U6ld4y4FT0a9yILRLM7lk7HQurXP6LSKC84UDlxa7uZxDXLoVAi4Zong6OEiT0q3D/beD+/HcAfh8JxgHYBpA0++pSkfnEOiDBP4Iy9ZjxFAeQYKeModJfLeSumreBL2abYXhBq/DqIQ6fWolfUzyYqm2l2THIuNo3QoSm69tKxlAkpvezIzISgHEHbmYQ8BUBznb5aZpfsjkAyS9uJWo7CR97lYgNO5hUwFaakeAOkmc7fJioYyI7fSWzfQN4jNS0fUXvkkeyroxw3s7eQw+v64GkYreyzptJ/vTR973+Xw+37++AdHsXIQsjlDHAAAAAElFTkSuQmCC","orcid":"","institution":"L\u0026T Finance","correspondingAuthor":true,"prefix":"","firstName":"Kamlesh","middleName":"","lastName":"Kumar","suffix":""}],"badges":[],"createdAt":"2026-01-10 12:53:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8568367/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8568367/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103504336,"identity":"98fa6efe-683b-4f83-bcae-975fb4aa4298","added_by":"auto","created_at":"2026-02-26 13:19:17","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":253685,"visible":true,"origin":"","legend":"","description":"","filename":"RODIDRAFT.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8568367/v1_covered_badb3d93-797a-4c10-ac86-e2e9899b8e33.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A framework for measuring return on data investment","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-analytics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Analytics](https://www.springer.com/journal/44257)","snPcode":"44257","submissionUrl":"https://submission.nature.com/new-submission/44257/3","title":"Discover Analytics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Data, Financial data, ROI, Data investments, Return on data, Digital divide, Digital services, Document services, Interest rate, Credit risk, Credit risk model","lastPublishedDoi":"10.21203/rs.3.rs-8568367/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8568367/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the era of big data, organizations face unparalleled opportunities to harness extensive data resources for competitive advantage. 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