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Measuring Return on Investment in International Student Recruitment: A Working Model Advanced Session at the NAFSA Annual Conference in Denver, 31 May 2016

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Measuring Return on Investment in International Student Recruitment:

A Working Model

Advanced Session at the NAFSA Annual Conference in Denver, 31 May 2016

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Co-PresentersCheryl DarrupBoychuck, USjournal of Academics

[email protected] Kacenga, University of Colorado Denver

[email protected] Rigos, Merrimack College

[email protected]

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Caution: Advanced ContentAdditional Resources (listed on handout)

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Learning Objectives1. Define ROI metrics, as they pertain to your campus environment 2. Explore “quantifiably-elusive” factors, balancing ethical issues and practical realities 3. Play with the model, to evaluate your institutional ROI as it changes over time

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Advanced Session: Be prepared to assign values to these INPUT variables

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Advanced Session: Be prepared to assign values to these OUTPUT variables

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Brief Overview

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Managing Expectations

* ROI metrics are complicated

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Managing Expectations

* ROI metrics are complicated* Risk: Oversimplifying complex scenarios

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Managing Expectations

* ROI metrics are complicated* Risk: Oversimplifying complex scenarios* Each user = Master of the outcome

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Managing Expectations

* ROI metrics are complicated* Risk: Oversimplifying complex scenarios* Each user = Master of the outcome* Be consistent over time

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Two-Asset Portfolio

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Portfolio Strategy

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ROI – Definitions and Usefulness

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Quantifiably Elusive Variables (QEVs)

Both Input and Output Variables

Currency fluctuationsVisa policy fluctuationsSufficient budget

Input Variables that can be quantifiedInput Variables

Top-level supportWell-defined strategyWord-of-mouth referralsAcademic relevanceFaculty involvementEfficiency of operations

Diversification of studentsAlumni engagementPrestige factorPartnerships

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A few QEVs can be quantified…

Exchange Rates over time

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QEVs within the modelQuantifiably-Elusive Variables Importance Type

1 to 13 China Gulf States Brazil1 Top-level support 13 input 5 7 32 Sufficient budget 11 input 5 3 -53 Well-defined strategy 10 input 5 5 34 Prestige factor 5 both 5 5 55 Word-of-mouth referrals 7 input 5 8 36 Currency fluctuations 2 input -1 0 -37 Visa policy fluctuations 1 input 5 3 58 Academic program relevance 8 input 7 7 79 Faculty involvement 3 input 3 3 3

10 Partnerships 9 both 8 5 011 Alumni relations 4 both 0 3 012 Efficiency of operations 12 input 7 7 713 Diversification of student body 6 both -1 3 814 Other n/a n/a

Performance: -10 to +10

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Qualitative ROI* Useful for comparing markets

- Based on the performance of key variablesExchange RatesVisa FluctuationsStrength of Partnerships

* Most useful for developing market-specific strategies

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Quantifiably-Elusive Variables Importance Type1 to 13 China Gulf States Brazil

1 Top-level support 13 input 5 7 32 Sufficient budget 11 input 5 3 -53 Well-defined strategy 10 input 5 5 34 Prestige factor 5 both 5 5 55 Word-of-mouth referrals 7 input 5 8 36 Currency fluctuations 2 input -1 0 -37 Visa policy fluctuations 1 input 5 3 58 Academic program relevance 8 input 7 7 79 Faculty involvement 3 input 3 3 3

10 Partnerships 9 both 8 5 011 Alumni relations 4 both 0 3 012 Efficiency of operations 12 input 7 7 713 Diversification of student body 6 both -1 3 814 Other n/a n/a

Performance: -10 to +10

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Quantifiably-Elusive Variables Importance Type1 to 13 China Gulf States Brazil

1 Top-level support 13 input 5 7 32 Sufficient budget 11 input 5 3 -53 Well-defined strategy 10 input 5 5 34 Prestige factor 5 both 5 5 55 Word-of-mouth referrals 7 input 5 8 36 Currency fluctuations 2 input -1 0 -37 Visa policy fluctuations 1 input 5 3 58 Academic program relevance 8 input 7 7 79 Faculty involvement 3 input 3 3 3

10 Partnerships 9 both 8 5 011 Alumni relations 4 both 0 3 012 Efficiency of operations 12 input 7 7 713 Diversification of student body 6 both -1 3 814 Other n/a n/a

Performance: -10 to +10

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Model Development* More data => Better model

- Multi-year data is critical for partnerships…* Differentiate time and money

- According to markets and typesPartnershipsSponsorsOther / Nothing

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Questions and AnswersCheryl DarrupBoychuck, USjournal of Academics

[email protected] Kacenga, University of Colorado Denver

[email protected] Rigos, Merrimack College

[email protected]