International Journal of Multidisciplinary Research and Growth Evaluation  |  ISSN (Online): 2582-7138  |  Double-Blind Peer Review  |  Open Access  |  CC BY 4.0

Current Issues
     2026:7/3

International Journal of Multidisciplinary Research and Growth Evaluation

ISSN (Online): 2582-7138 | Open Access

A Conceptual Forecasting Model for Operational Expenditure in High Growth Enterprises

Full Text (PDF)

Open Access - Free to Download

Download Full Article (PDF)

Alternative download link

Abstract

High-growth enterprises face unique financial challenges due to rapid scaling, dynamic market demands, and fluctuating cost structures. Accurately forecasting operational expenditure (OPEX) is therefore critical for sustaining profitability, optimizing resource allocation, and maintaining liquidity. This paper proposes a conceptual forecasting model designed to enhance the accuracy and responsiveness of OPEX prediction in high-growth organizations. The model integrates financial analytics, machine learning algorithms, and business process metrics to capture non-linear expenditure patterns linked to expansion activities, digital transformation, and workforce scaling. It emphasizes the incorporation of internal performance indicators—such as productivity ratios and cost elasticity—with external variables, including inflation, market volatility, and supply chain dynamics. By conceptualizing a hybrid framework that combines econometric modeling and predictive analytics, the study aims to bridge the gap between traditional financial forecasting methods and data-driven decision systems. Furthermore, it examines how the proposed model supports scenario planning and strategic cost optimization through continuous learning and adaptive calibration. The review synthesizes theoretical perspectives, empirical findings, and managerial implications to establish a foundation for future research in predictive financial management for high-growth enterprises. The model’s conceptualization offers actionable insights for finance leaders, data scientists, and policymakers seeking to improve expenditure predictability in fast-scaling business environments.

How to Cite This Article

Oluwaremi Ayoka Lawal, Titilayo Elizabeth Oduleye (2020). A Conceptual Forecasting Model for Operational Expenditure in High Growth Enterprises . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 1(5), 574-582. DOI: https://doi.org/10.54660/IJMRGE.2020.1.5.574-582

Export Citation:

BibTeX RIS EndNote

References

  1. 1. Abass OS, Balogun O, Didi PU. Apredictiveanalyticsframeworkforoptimizingpreventivehealthcaresalesandengagementoutcomes. IREJournals.2019;2(11\:497-503.
  2. 2. Abass OS, Balogun O, Didi PU. Amulti-channelsalesoptimizationmodelforexpandingbroadbandaccessinemergingurbanmarkets. IREJournals.2020;4(3\:191-198.
  3. 3. Abass OS, Balogun O, Didi PU. Asentiment-drivenchurnmanagementframeworkusing CRMtextminingandperformancedashboards. IREJournals.2020;4(5\:251-259.
  4. 4. Adebiyi FM, Akinola AS, Santoro A, Mastrolitti S. Chemicalanalysisofresinfractionof Nigerianbitumenfororganicandtracemetalcompositions. Pet Sci Technol.2017;35(13\:1370-1380.
  5. 5. Adenuga T, Ayobami AT, Okolo FC. Layingthe Groundworkfor Predictive Workforce Planning Through Strategic Data Analyticsand Talent Modeling. IREJournals.2019;3(3\:159-161.
  6. 6. Adenuga T, Ayobami AT, Okolo FC. AI-Driven Workforce Forecastingfor Peak Planningand Disruption Resiliencein Global Logisticsand Supply Networks. Int JMultidiscip Res Growth Eval.2020;2(2\:71-87. doi:10.54660/IJMRGE.2020.1.2.71-
  7. 877. Adesanya OS, Akinola AS, Okafor CM, Dako OF. Evidence-informedadvisoryforultra-high-net-worthclients: Portfoliogovernanceandfiduciaryriskcontrols. JFront Multidiscip Res.2020;1(2\:112-120.
  8. 8. Adesanya OS, Farounbi BO, Akinola AS, Prisca O. Digitaltwinsforprocurementandsupplychains: architectureforresilienceandpredictivecostavoidance. Decision-Making.2020;33:34.
  9. 9. Adeyoyin O, Awanye EN, Morah OO, Ekpedo L. AConceptual Framework Linking Financial Strategyand Operational Excellencein Manufacturing Firms.2020.(Publisher/detailspending; conceptualpaper.\
  10. 10. Agyapong D, Obeng F. Predictingoperatingcostsofhigh-growthfirmsusinghybrideconometricapproaches. JBus Res.2018;93:188-198. doi:10.1016/j. jbusres.2018.08.
  11. 2111. Ahmed KS, Odejobi OD. Conceptual Frameworkfor Scalableand Secure Cloud Architecturesfor Enterprise Messaging.2018.(Publisher/detailspending.\
  12. 12. Ahmed KS, Odejobi OD. Resource Allocation Modelfor Energy-Efficient Virtual Machine Placementin Data Centers.2018.(Publisher/detailspending.\
  13. 13. Ahmed KS, Odejobi OD, Oshoba TO. Algorithmic Modelfor Constraint Satisfactionin Cloud Network Resource Allocation.2019.(Publisher/detailspending.\
  14. 14. Ahmed KS, Odejobi OD, Oshoba TO. Predictive Modelfor Cloud Resource Scaling Using Machine Learning Techniques.2020.(Publisher/detailspending.\
  15. 15. Akinola AS, Adebiyi FM, Santoro A, Mastrolitti S. Studyofresinfractionof Nigeriancrudeoilusingspectroscopic/spectrometricanalyticaltechniques. Pet Sci Technol.2018;36(6\:429-436.
  16. 16. Akinola AS, Farounbi BO, Onyelucheya OP, Okafor CM. Translatingfinancebillsintostrategy: Sectoralimpactmappingandregulatoryscenarioanalysis. JFront Multidiscip Res.2020;1(1\:102-111.
  17. 17. Akinrinoye OV, Umoren O, Didi PU, Balogun O, Abass OS. Designandexecutionofdata-drivenloyaltyprogramsforretaininghigh-valuecustomersinservice-focusedbusinessmodels. IREJournals.2020;4(4\:358-371.
  18. 18. Akinrinoye OV, Umoren O, Didi PU, Balogun O, Abass OS. Strategicintegrationof Net Promoter Scoredatainto International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com582feedbackloopsforsustainedcustomersatisfactionandretentiongrowth. IREJournals.2020;3(8\:379-389.
  19. 19. Akinwale YO, Odufuwa BO. Financialforecastingtechniquesforemergingmarketenterprises. Int JEcon Finance Stud.2018;10(2\:123-137.
  20. 20. Amini-Philips A, Ibrahim AK, Eyinade W. Proposed Evolutionary Modelfor Global Facility Management Practices. Int JMultidiscip Res Growth Eval.2020;1(5\:180-195.
  21. 21. Asata MN, Nyangoma D, Okolo CH. Strategic Communicationfor Inflight Teams: Closing Expectation Gapsin Passenger Experience Delivery. Int JMultidiscip Res Growth Eval.2020;1(1\:183-194.
  22. 22. Asata MN, Nyangoma D, Okolo CH. Reframing Passenger Experience Strategy: APredictive Modelfor Net Promoter Score Optimization. IREJournals.2020;4(5\:208-217.
  23. 23. Asata MN, Nyangoma D, Okolo CH. Leadershipimpactoncabincrewcomplianceandpassengersatisfactionincivilaviation. IREJournals.2020;4(3\:153-161.
  24. 24. Asata MN, Nyangoma D, Okolo CH. Benchmarking Safety Briefing Efficacyin Crew Operations: AMixed-Methods Approach. IREJournals.2020;4(4\:310-312.
  25. 25. Atere D, Shobande AO, Toluwase IH. Frameworkfor Designing Effective Corporate Restructuring Strategiesto Optimize Liquidityand Working Capital. ICONICRes Eng J.2019;2(10\. ISSN:2456-8880.
  26. 26. Atere D, Shobande AO, Toluwase IH. Reviewof Global Best Practicesin Supply Chain Finance Structuresfor Unlocking Corporate Working Capital. Int JMultidiscip Res Growth Eval.2020;1(3\:232-243.
  27. 27. Ayanbode N, Cadet E, Etim ED, Essien IA, Ajayi JO. Deeplearningapproachesformalwaredetectioninlarge-scalenetworks. IREJournals.2019;3(1\:483-502.
  28. 28. Babatunde LA, Etim ED, Essien IA, Cadet E, Ajayi JO, Erigha ED, Obuse E. Adversarialmachinelearningincybersecurity: Vulnerabilitiesanddefensestrategies. JFront Multidiscip Res.2020;1(2\:31-45. doi:10.54660/JFMR.2020.1.2.31-
  29. 4529. Balogun O, Abass OS, Didi PU. Amulti-stagebrandrepositioningframeworkforregulated FMCGmarketsin Sub-Saharan Africa. IREJournals.2019;2(8\:236-242.
  30. 30. Bankole FA, Lateefat T. Strategiccostforecastingframeworkfor Saa Scompaniestoimprovebudgetaccuracyandoperationalefficiency. Iconic Res Eng J.2019;2(10\:421-441.
  31. 31. Bankole FA, Davidor S, Dako OF, Nwachukwu PS, Lateefat T. Theventuredebtfinancingconceptualframeworkforvaluecreationinhigh-technologyfirms. Iconic Res Eng J.2020;4(6\:284-309.
  32. 32. Barrow CJ, Khanduja P. Machinelearninginfinancialforecasting: Comparativemodelaccuracyanddatagovernance. JAppl Econ Bus Res.2019;9(4\:255-269.
  33. 33. Basu S, Srinivasan K. Integratingmachinelearningwitheconometricforecasting: Ahybridapproach. JForecast.2019;38(6\:512-530. doi:10.1002/for.
  34. 256434. Behrens K, Mion G. Productivity, markups, andaggregatedynamics. Rev Econ Stud.2017;84(1\:440-471. doi:10.1093/restud/rdw
  35. 4335. Bukhari TT, Oladimeji OYETUNJI, Etim ED, Ajayi JO. Aconceptualframeworkfordesigningresilientmulti-cloudnetworksensuringsecurity, scalability, andreliabilityacrossinfrastructures. IREJournals.2018;1(8\:164-173.

Share This Article: