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"I'd rather be approximately right than exactly wrong."

-- John Maynard Keynes

Research - Finding and Using Data

  • It is critical to remember that you are not trying to convince yourself -- you are already a true believer. You need to move policymakers who have different agendas, other distractions, different ways of learning, and much less time to devote to your issue than you have. A fact that may be extremely meaningful to one person may be irrelevant to another. You are looking for the fact/story/whatever that will move your target(s).
  • Based on a Connecticut survey, policy makers trust information from legislative staff and state agencies the most. Start there searching for information. Even if the staff quote another source, use the more trusted citation in your work.
  • Search federal sources next, such as the Census, Centers for Disease Control and Centers for Medicare and Medicaid Services (CMS). Next use journals, academic institutions and trusted non-profit sources, such as the American Foundation for the Blind or National Organization on Disability. Advocacy organizations, provider and professional organizations are moderately trusted. Media and industry organizations are least trusted.
  • Use your own information - both statistics from your program and stories from your experience. This is very powerful.
  • Remember to cite your source. "Consider the source" is often repeated at the Capitol. Information from a disinterested party is sometimes more persuasive. Nonpartisan organizations that take great pains to remain neutral carry more weight.
  • Be creative in finding sources of information. Wider searches of the state website or a general search engine may find your information in a place you never would have thought to look.
  • Supporting information from an unlikely source can be very persuasive. For example, May 23, 2000 the Wall Street Journal (not a consumer oriented publication) ran a front-page article describing how Merrill Lynch lowered their health care costs by expanding benefits for employees.
  • DO NOT SKEW INFORMATION - Do not take quotes out of context. Do not use "fuzzy math" to make a point. Eventually you will be found out. You can never get your reputation back.
  • Be careful in using small numbers or data from very small populations. That is not a reason to exclude the data, just frame it clearly. For example, "While his patient list is not long, a local pediatrician estimates that the number of uninsured patients in his practice increased 25% last year."
  • Be certain that definitions are the same when making comparisons. For example, one survey may label a respondent as uninsured for answering no to "Do you have health insurance now?" while another survey may frame their question, "Have you been without health coverage in the last year?" Do not assume that because two numbers are from the same source, that they are comparable. Another example: From the Census you can get a figure for the number of disabilities reported AND a figure for the number of people who have disabilities. Since many people have more than one disability, the second number will be smaller than the first. The number of PEOPLE who have disabilities is usually the statistic you need, but when the other data is used, it is important to accurately describe it.
  • Make reasonable adjustments. For example a dollar of health care in 1950 would cost far more now - spending would increase in a program that was just keeping services level. Also, adjust for population. Ten infant deaths in one year would be far different in a small town than in a big city.
  • Pay attention to information that does not support your position. It is critical to know what your opponents are going to say and to be ready to respond.
  • Contact friends and follow up on their recommendations. People often know where to find things that are not available on the web or not easily accessible. Or they may know someone else who knows.
  • Check your numbers three times. Have someone else check your work.
  • Don't overanalyze, if it will delay the work. Too many great reports - beautifully formatted, perfect research - are released too late to make a difference.

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