Boubakari GANSONRE’s Post

I have been thinking again. This time about the role of people in evaluation. When talking about evaluation, the focus is often on data, outcomes, and systems. But at its heart, evaluation is profoundly human. People are central to every step. Intervention Designers: Behind every programme or initiative is a team of people aiming to address a need, solve a problem, or create change. Their intent and understanding of context shape what is possible. Programme Recipients: The people impacted by interventions are not just "beneficiaries" or data points; they are experts in their own lives. Their experiences, voices, and feedback are essential to understanding what works and why. Evaluators: Evaluation is as much about relationships as it is about rigour. Skilled evaluators must balance objectivity with empathy, cultivating trust while navigating complex systems. Policymakers/decision makers: At the decision-making table, it’s people interpreting the findings, weighing trade-offs, and deciding what to scale, adapt, or stop altogether. In evaluation, we often ask "What works?" But I prefer the Realist Evaluation question: "What works: for whom, in what context, and why?" This question helps inform data collection, analysis and evaluation criteria that are inclusive, equitable, and reflective of lived realities. He aha te mea nui tea o? He tangata he tangata, he tangata! (What is the most important thing in the world? It is people, it is people, it is people!) #Evaluation #HumanCenteredDesign #DataWithHeart #PolicyMaking #EquityInEvaluation

The biggest Problem is, trying to find a #solution to a #problem on the first attempt itself. This general approach is #motivated by our #cognitive thought, #influenced by numerous #biases. Project #valuerealization fails not because of technology, but due to #valueproposition. #Curiosity and #logic guide us to #innovative solutions at work, but do we seek sufficient outside #perspectives when solving tough problems? Are we keeping our minds open, putting aside the selective approach of shortlisted solutions? Do we recognize the importance of #data in #decisionmaking, or do we solely rely on gut feeling and #pastexperience to solve a problem? While navigating a complex problem scenario, #criticalthinking ability is essential for exploring potential paths ahead. To approach this, we must be able to hold our #hypotheses and #assumptions loosely, #observe and analyze all aspects of a situation, be open to new and contradictory information, and use both quantitative and qualitative research to support the right choice. We often move forward too quickly in #reactive mode, considering and relying on the same behaviors and solutions that worked in the past in identical situations. Consequently, we become victims of #blindspots and miss new, potentially better opportunities. #Criticalthinking enables us to use reasoning and data-centric logic to navigate the most challenging issues, whether a difficult problem, a tough decision, or a #complex scenario. It requires us to look at the situation from multiple #perspectives and #viewpoints and choose a well-informed and effective path forward.

Day 3: Analytical Dissection - Unveiling Insights in Complex Problems Article: Welcome to Day 3 of our "7-Day Series: Mastering Critical Thinking in Complex Problem-Solving" journey. Today, we embark on the critical role of analytical thinking in dissecting complex problems and uncovering hidden insights. Analytical Dissection: Peeling Back Layers Analytical thinking involves breaking down complex issues into manageable components and examining them systematically. By dissecting problems methodically, we can identify patterns, relationships, and underlying causes that may not be immediately apparent. Key Elements of Analytical Dissection 1.Identifying Components: Begin by deconstructing the problem into its fundamental elements. This involves identifying relevant factors, variables, and interdependencies that contribute to the complexity of the issue. 2. Examining Relationships: Explore the connections between different components of the problem. Analyze how changes in one aspect may impact others and identify potential causal relationships. 3. Uncovering Patterns: Look for recurring themes, trends, or anomalies within the data or problem scenario. Identifying patterns can provide valuable insights into the underlying dynamics at play and guide the formulation of effective solutions. 4. Detecting Assumptions: Challenge assumptions underlying the problem or existing approaches to addressing it. By questioning assumptions, we can uncover biases, limitations, or overlooked perspectives that may influence decision-making. The Power of Analytical Dissection By employing analytical dissection, we gain a deeper understanding of complex problems and are better equipped to develop innovative solutions. This structured approach enables us to navigate ambiguity and uncertainty with clarity and confidence. Stay Tuned for Day 4! Tomorrow, we'll explore the transformative potential of creative thinking in problem-solving, unlocking new possibilities and pushing boundaries. #criticalthinking #problemsolving #analyticalthinking #complexproblems #innovativesolutions #businesssuccess

Well, each method presents unique advantages and limitations, and each will contributing differently to the evaluation process...

A failure to build build confidence in a methodology runs the risk of truly innovative going head to head with a stakeholders gut feel. Here Leigh Caldwell discusses how you can get round the issue. https://hubs.ly/Q02wwrVR0

How success is defined and measured drives what and how we do things. From education to business, health, and environment etc. From there, it influences how organization and hence society operates, what is valued, and how learning happens. Can new ways of evaluating (and learning) re-define success? In the last few months, I have been having conversations with Michael Q Patton on development and generative evaluation. Where are the openings or cracks where change can occur, Michael Patton and I asked ourselves? Perhaps this question takes us closer to re-defining success of an initative. That’s in context and it's in relational data we reflected upon. Evaluation can help us to reflect where things are fixed, and where things are fluid, and to discover what's amenable and not amenable to change.

Developing a practical impact measurement framework is critical to driving meaningful change. Start by defining clear objectives and mapping out a theory of change to establish causal links between activities and outcomes. Prioritize significant outcomes and choose evidence levels that balance rigour with available resources. Select appropriate data sources and tools, and focus on collecting meaningful data. Analyze the data to validate your theory of change, benchmark against similar services, and track improvements over time. This structured approach ensures valuable data for learning and reporting, ultimately enhancing the impact of your interventions. Investment Impact Index: Impact Management and Measurement #ImpactMeasurement #DataDriven #ContinuousImprovement #SocialImpact #MakingADifference

THE BRAIN OF ANALYST The complexity of many organisational/social problem situations defeats attempts at defining a problem: in many such situations the problem is 'what is the problem?'. Soft Systems Methodology (SSM) provides a framework for analysts to tackle such situations. Analysts can attempt to foster learning and appreciation of the problem situation between a group of stakeholders rather than set out to solve a pre-defined problem. There are two main modes within SSM, real world activities and systems thinking about the real world. Initial work involves interviews and meetings to gain an understanding of the problem situation, which is represented by the use of #richpictures. Systems thinking uses concepts of hierarchy, communication, control, and emergent properties to identify 'relevant systems' which may provide useful insights. These relevant systems are logically defined by constructing 'root definitions' which are then used to generate 'conceptual models' of the selected systems. Different conceptual models representing different viewpoints are then used as the basis of a debate, which through an 'appreciative process' can lead to feasible and desirable change and then to action. Soft Systems Methodology has been developed over twenty years by Peter Checkland of the Department of Systems at Lancaster University, and others. References: Checkland and Scholes (1990), Naughton (1984), Eden and Radford (1990) Source: https://lnkd.in/gAn99udv

In a world driven by data and metrics, we often hear, “If it can be measured, it can be managed.” But is this always true when dealing with living, complex systems? Living systems—whether ecosystems, societies, or organizations—are dynamic, interconnected, and adaptive. They are shaped by relationships, feedback loops, and emergent properties that resist easy quantification. While defining a metric provides clarity, it also risks oversimplifying a system's complexity. Metrics, by design, highlight certain aspects while obscuring others, potentially leading to narrow interventions that ignore the broader context. Dark Matter Labs explores these dimensions and offers a framework 👇 Let's discuss #ComplexSystems #SystemsThinking #Metrics #BeyondMeasurements #Postreductionism #CriticalComplexity