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Assumptions to Unravel the Tangle of Complexity, Values, and Cultural Responsiveness

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Assumptions to Unravel the Tangle of Complexity, Values, and Cultural Responsiveness Working with Assumptions to Unravel the Tangle of Complexity, Values, and Cultural Responsiveness Session 1: How can assumptions be recognized? Apollo Nkwake Katrina Bledsoe Jonny Morell Presenters Jonathan Morell, Ph.D. Katrina L. Bledsoe, Ph.D. Principal, 4.669 Evaluation and Apollo M. Nkwake, CE. Ph.D. Research Scientist, Planning/Editor, Evaluation International Technical Education Development and Program Planning Advisor, Monitoring and Center/Principal Phone: (734) 646-8622 Evaluation, Education Consultant Katrina Email: [email protected] Development Center Bledsoe Consulting Website www.jamorell.com Email: [email protected] Email: [email protected] Blog:https://evaluationuncertai nty.com/ YouTubeTinyurl.com/morell- YouTube Session 1: How can assumptions be • Facilitators walk through scenarios that illustrate applications recognized? 1/14/19 and use tools and processes that are designed to help reveal and monitor the use of assumptions. We will help participants learn to gauge the tools' and processes' appropriateness, their strengths and limitations, and when to use which tools. • This session will cover assumptions about how programs work Session 2: The role of assumptions in the and relationships among outcomes; assumptions about program design and conduct of evaluation. 1/28/19 logic; assumptions about evaluation and assumptions about program purpose. • Discuss the intersection of cultural responsivity and values Session 3: Assumptions, Values and Cultural assumptions in program design and evaluations. Reflect on Responsiveness. 2/11/19 case studies and scenarios. Session 1 Outline • Propositions to frame the discussion • The tangle of complexity, assumptions, values and responsiveness • Tools and processes for examining assumptions • Diagnostic assumptions focused tools/processes • Prescriptive Assumptions focused tools/processes • Causal Assumptions focused tools/processes • Findings from an Assumptions survey • Principles • Next steps One program’s overelaboration is Carol Weiss – evaluator another program’s theory. All models are wrong but some George Box – statistician are useful. Propositions to frame the discussion 03. Assumptions have 01. Definition consequences • Assumptions are what we • It is one thing to make assumptions, it believe to be true (implicit, is something else miss the explicit, examined, consequences of making them. unexamined). • It is impossible to make wise choices • It’s hard to exclude assumptions about invisible assumptions. from what we think we know • Unexamined assumptions can be a risk to program success and useful evaluation. 02. Inevitable and 04. Caution: prioritize necessary • Assumptions are not only • Use with caution, pick the few unavoidable but necessary assumptions that matter and be because without simplification, comfortable ignoring the others. it is hard to discern relationships among elements that matter. What is a tacit assumption? A tacit assumption or implicit assumption is an assumption that includes the underlying agreements or statements made in the development of a logical argument, course of action, decision, or judgment that are not explicitly voiced nor necessarily understood by the decision maker or judge. Often, these assumptions are made based on personal life experiences, and are not consciously apparent in the decision-making environment. These assumptions can be the source of apparent paradoxes, misunderstandings and resistance to change in human organizational behavior . https://en.wikipedia.org/wiki/Tacit_assumption Where do assumptions live? Single Portfolios of Whole programs similar organization programs People’s heads Funding proposals Theories of change Organizational culture Requests for proposals Mission/goal statements Makeup of human capital History of previous activities Schedules (of varying timeframes) The tangle of complexity, assumptions, values and responsiveness LOGICS/frameworks › Simplification creates assumptions ASSUMPTIONS COMPLEXITY › Values influence typologies prioritized/examined › Logics for simplification are › Feedback prioritized in adaptive value laden program delivery VALUES TOOLS AND RESPONSIVENESS PROCESSES FOR EXAMINIG Values influence feedback that’s ASSUMPTIONS prioritized and the actions taken › Values influence tools Think about programs that you have reviewed in the past… • How did you navigate assumptions: What types of assumptions were articulated or not articulated? • How did these assumptions affect program success or evaluation quality? • Post a brief response in the chat box Examining Program theory Assumptions External assumptions Causal : What are the assumptions Prescriptive factors outside of : How are the the stakeholders' assumptions control that are Diagnostic intervention's : What's the most outputs expected critical to the Assumptions to translate into success of the Normative appropriate : What are the strategy? desired long intervention? Assumptions root causes of the term outcomes? : A problem or problem/opportu opportunity nity? exists and we should respond to it Tools/processes for examining assumptions • Diagnostic assumptions focused • Prescriptive assumptions focused • Causal assumptions focused Diagnostic assumptions focused tools • Assumptions underlying what’s believed to be the root cause of issues (or opportunities) • The alternative causes approach process • Alternative Causes Matrix High infant mortality rate Children are malnourished Insufficient Diarrheal Poor quality food disease of food Contaminated Unsanitary Need for water practices improved health policies Flies and Do not use People do not rodents facilities wash hands correctly before eating From Jim Rugh Alternative causes matrix (for each root) Stakeholders’ beliefs Past program experience Research and evidence Very Likely Somewhat Likely Unlikely Prescriptive assumptions focused tools • Alternative strategies approach • Strategic assumptions surfacing and testing • Assumption Based Planning (RAND) To achieve impact all of these need to address the same target population. Program Goal: Reduce childhood malnutrition Food Health Nutrition Production Project Project Project Goal: Goal: Goal: Increase Decrease Improve availability diarrheal quality of of food to disease food fed to households among children children ASSUMPTION OUR project (that others will do this) PARTNER will do this Program and project goals at impact level From Jim Rugh Alternative Strategies Matrix Criteria for prioritizing Strategy Option 1 Food Production: Strategy Option 2: Health Project: Strategy Option 3: Nutrition Project: Reduce strategies Reduce child malnutrition Reduce child malnutrition by child malnutrition by improving quality of food by Increasing availability of food decreasing diarrheal diseases among chi fed to children to households ldren Effectiveness Arguments Arguments Arguments Relevance Arguments Arguments Arguments Feasibility Arguments Arguments Arguments Sustainability Arguments Arguments Arguments Fit/Complementarity with other Arguments Arguments Arguments strategies being implemented Strategic assumptions surfacing and testing (SAST)/Assumptional analysis 1. Once a problem 2. Review the list of 3. Search for 4. With this full list 5. Create a “best” and initial treatment assumptions and supporting data to of strategy options, strategy from these strategy have been reverse the bolster the counter negotiate a set of assumptions that is identified, note the arguments for each, assumptions and, acceptable supported by data to support the creating counter- where validated, assumptions that relevant data. strategy and the assumptions. create counter will serve as a base underlying strategies. moving forward. assumptions made in developing that strategy. (Mitroff and Emshoff, 1979) Assumptions rating Most Certain ???? Least Important Most Important ???? Least Certain Leeuw, 2003:12 Illustration-US Census Bureau • U.S. Bureau of the Census dealt with the problem of accuracy of its census and in particular with the problem of undercounting population numbers. • Undercount Adjustment Workshop - assumptions underlying different adjustment procedures were addressed. • Four working groups on different adjustment plans, identified the assumptions that were necessary for each group’s particular plan of action to be made feasible • assumptions were ranked for their importance and certainty • A list of about 20 measures was generated (Leeuw 2003) Assumption Based Planning Developed by RAND for the U.S. Army to adjust its plans toward the end of the Cold War. Systematically identify and assess vulnerabilities of explicit and implicit assumptions underlying policy options to improve strategic planning. 1) Identify load-bearing assumptions (assumptions that, if broken, would require major revision of the course of action) 2) Identify vulnerabilities of those load-bearing assumptions. 3) Develop: • Signposts – explicit signals that may provide early warning of the vulnerability of load-bearing assumptions; • Shaping actions – actions that attempt to control the vulnerability of loadbearing assumptions; and • Hedging actions – actions that attempt to better prepare the organization for the potential failure of a load-bearing assumption. Illustration-US Counter-terrorism strategies (RAND study) Area of Assumption Current U.S. Plan Enhanced Law Disengagement (Reduce (offensive operations Enforcement (Defeat American political against terrorists, deny terrorists with improved intervention in them sanctuary, spread intelligence and law contentious
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