Predicting Financial Vulnerability in Nonprofits

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Predicting Financial Vulnerability in Nonprofits

• Roger A. Lohmann, Ph.D.
• Nancy Lohmann, Ph.D.
• Division of Social Work
• School of Applied Social Science
• Eberly College of Arts Sciences
• West Virginia University

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Age of Financial Uncertainty for Nonprofits

• Cutbacks of programs
• Machinations of accountability
• Refusal of many funding sources to acknowledge
  need for long term operating support

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Situation in WV Getting Worse

• NP Crises in Kanawa Valley
• Multi-CAP scandal/bankruptcy
• Shawnee Hills bankruptcy
• Etc.
• DHHR De-funding Juvenile Retention
• DHHR Contract Terminations
• 70 agencies
• 5-600 jobs

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Is Prediction of Vulnerability Possible?

• No cure for mismanagement
• Multi-CAP Officer said After 26 years in the
  business, hed never heard you couldnt commingle
  funds!
• If any of you are in doubt You cant!!
• No present way to predict actions of others
• Will DHHR cancel more contracts?

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Some Vulnerability is Predictable

• NPs are part of a fairly stable political
  economy
• Deliberate introduction of risk
• Managers feel vulnerable much of the time

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Background

• Small group of accounting researchers working on
  this problem.
• First, in commercial settings
• More recently, in nonprofits
• Produced and tested a predictive model of
  estimating financial vulnerability that should be
  of interest to all nonprofit administrators.

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Background Accounting Statements

• Three standard nonprofit financial statements
  relevant to prediction
• Balance Sheet (Position)
• Statement of Income and Expenditures (Performance
  Over Time)
• Changes in Fund Balance (Changes in Position Over
  Time)

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Background Expenditure Types

• NASB recognizes three main types of expenditures
• Administrative
• Fund Raising
• Program

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Background Revenue Sources

• IRS 990 recognizes five types of revenues
• Contracts, gifts and grants
• Program revenues (earnings)
• Membership dues
• Sales of unrelated goods (UBITs)
• Investment Income

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General Approach Ratio Analysis

• Built from standardized information from
  financial statements
• Ratios are just Fractions
• Numerator and denominator from different places
  on financial statements
• E.g. current ratio is
• current liabilities / current assets
• Normally, 1 or less
• Greater than 1 should raise questions about
  long-term asset coverage of debt.

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Three kinds of Financial Distress ratios

• Seat of the pants (practice- or experience-based
  wisdom)
• Practice wisdom validated by empirical research
• Reliability, validity and generalizability
• Can you trust the measure?
• When does it apply?
• How widely does it apply?
• Published Industry Standards

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Defining Financial Vulnerability

• ( Beaver, 1966) financial vulnerability is
  probability of filing for bankruptcy.
• Gilbert, et. Al. (1990) found many vulnerable
  companies do not file for bankruptcy.
• Franks Torous (1989) Companies that file may
  not be vulnerable (may be due to labor disputes,
  etc.)

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Underlying Idea

• Financial Vulnerability ability to recover from
  sudden financial shocks.
• Sudden and unexpected loss of income
• Sudden and uncontrollable increase in
  expenditures
• Examples
• Loss of a grant/contract
• Sudden decrease (or increase) in clients
• Discovery by EPA that your building is full of
  asbestos

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Research Measures of Financial Vulnerability

• Actual or anticipated filing for bankruptcy
• Three consecutive years of net losses (negative
  net income)
• (Nonprofit) Reduced program expenses

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The Tuckman-Chang Model

• Financially vulnerable nonprofit Likely to
  reduce its program services following a financial
  shock.
• Study of 4,730 501(c)3 organizations filing IRS
  990s in 1983.

FOR MORE INFO...

• Howard Tuckman and Cyril Chang. A Methodology for
  Measuring the Financial Vulnerability of
  Charitable Nonprofit Organizations. Nonprofit and
  Voluntary Sector Quarterly. Winter, 1991. 445-460

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Tuckman-Chang Ratios

• Inadequate Equity Balances
• Revenue Concentration
• Low Administrative Costs
• Low Operating Margins

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Inadequate Equity Balances

• Ratio of total equity (fund balances) to total
  revenues
• Lower ratio means less able to replace lost
  revenues following a financial shock
• Lower ratio greater vulnerability
• Negative ratio unlikely (Neg. total revenues
  means real trouble!)

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Tuckman-Chang Ratios

• Inadequate Equity Balances
• Revenue Concentration
• Low Administrative Costs
• Low Operating Margins

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Revenue Concentration

• Sum of revenue sources / total revenues squared
• (24/328,000) .000073
• .000073.000073 .0000000053
• Organizations with fewer revenue sources are more
  vulnerable to financial shocks in any one of them
• Fewer sources greater vulnerability

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Tuckman-Chang Ratios

• Inadequate Equity Balances
• Revenue Concentration
• Low Administrative Costs
• Low Operating Margins

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Low Administrative Costs

• Ratio of Administrative Expenses/Total Revenues
• Contrary to conventional wisdom Lower ratios
  greater vulnerability
• Lower administrative costs almost always
  translate into decreased flexibility.
• Diminished ability to reduce administrative costs
  in a crisis
• More limited management problem solving
  capabilities
• E.g., fewer mgrs., supervisors or support
  personnel to draft to 1)solve problem or 2)
  provide services in meantime.
• Reminder Conclusion based on random sample study
  of 4,730 nonprofits!

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Tuckman-Chang Ratios

• Inadequate Equity Balances
• Revenue Concentration
• Low Administrative Costs
• Low Operating Margins

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Low Operating Margins

• Ratio of (total revenues less total expenses) /
  Total Revenues
• Lower ratios greater vulnerability
• 300,000 in revenues and 200,000 in expenses
• 30-20 10
• 10/30 .33
• 500,000 in revenues and 200,000 in expenses
• 50-20 30
• 30/50 .60

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Tuchman and Chang standards

• Any score in second quintile at risk
• Lowest quintile on all four variables severely
  at risk
• Quintile ratios for four measures
• Equity Balances
• Revenue Concentration
• Administrative Cost
• Operating Margins

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Tuchman and Chang Insights

• Inverse relationship --gt revenues and risk
• Low equity levels an indicator of risk
• Higher long-term debt to long-term assets ratios
  another sign of trouble
• Vulnerable nonprofits are less liquid (current
  ratios)
• Higher program service reliance --gt greater
  vulnerability

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Two Major Research Problems

• Extent of Program Services not fully captured by
  accounting system.
• Difficult to determine independently which
  nonprofits experience financial shocks

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Prediction Equation

• Greenlee and Trussel (2001) develop a prediction
  equation
• Useful for exact estimation of financial
  vulnerability within a set of norms for
  interpreting it.
• Useful for comparing vulnerabilities

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Greenlee-Trussel Equation

• Yields the probability of financial vulnerability
  
• Probability greater than 10 is a strong
  indication of financial vulnerability
• Probability less than 7 is a strong indication
  of no vulnerability
• Probability between 7-10 are indeterminate.

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Greenlee-Trussel Equation

• 1/(1e-z) where
• ZConstant (3.0610) EQUITY CONCENT ADMIN
  MARGIN
• The four ratios of Tuckman-Chang

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Almost Ready for Prime Time

• In the absence of other information, this
  approach is solid enough that nonprofit managers
  might begin to make use of it to test their
  hunches about the financial vulnerability of
  their organizations.
• Probably not a good idea to rely on totally.
• Certainly better than anything else currently
  existing.

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Some general guidelines for more intuitive use of
ratios

• Greater the body of data you have more meaningful
  it will be.
• Year-to-year comparisons are more momentous than
  month-to-month
• Cross-organizational comparisons of programs with
  similar names can be very risky. (E.g., All home
  health programs are not created equal).

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Different Approaches

• Self-Norming
• Compare a single organization at different
  periods
• Pick most secure and most vulnerable periods and
  compare
• Peer-Comparisons
• Compare Groups of related organizations
• Compare community systems
• Information on ranges

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Limitations of the Model I

• Not all nonprofits file 990s
• Risky to generalize about non-filers.
• Ratios limited to data IRS 990 collects
• E.g., IRS doesnt collect data on outputs

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Limitations of the Model II

• The Greenlee-Tressel model (GTM) only tested on
  organizations four or more years old.
• Could be that newer organizations (1-3 years old)
  behave differently.
• The GTM only tested on charitable organizations
  to date.
• Further research needed using alternative
  definitions of financial vulnerability.

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