People conduct interviews in research to gather in-depth, qualitative insights directly from participants. Interviews allow researchers to explore experiences, opinions, and motivations in detail, providing richer context than surveys or numerical data. They enable flexibility, allowing follow-up questions for deeper understanding. Additionally, interviews help capture nuances, emotions, and personal perspectives, making them valuable for studies in the commercial sector, social sciences, healthcare, business, and anywhere where you need to find out how people experience your product or service.
Pros & Cons of Interviews
Interviews are a valuable research tool, providing rich, qualitative data that helps uncover emergent theories, build relationships, and gain a deeper understanding of a topic or community. They offer a way to grasp the bigger picture and lay the groundwork for effective change. However, interviews can be time-consuming, resource-intensive, and expensive, with challenges such as participant reluctance, interviewer bias, and the need for specialised training in thematic coding and analysis. SenseMaker® is a smarter way to capture real experiences and enjoy all the benefits of real interview-led research without the associated time, training and energy costs all while reducing the risk of bias.
Read on to learn more about the benefits of SenseMaker®, or skip ahead to the table comparing SenseMaker® versus Traditional Interviews.
SenseMaker® isn’t just another survey tool – it’s a revolution in how we gather real-life experiences. Instead of rigid questions and rehearsed answers, SenseMaker® allows people to share their own stories in their own words. Using predefined labels, respondents categorise their own experiences, making analysis faster, more accurate, and free from interviewer bias.
SenseMaker® is a Smarter Way to Capture Experiences because
With digital access via mobile apps and online surveys, SenseMaker® reaches a wider audience than traditional interviews ever could. The anonymity and convenience encourage openness – no more polite or pressured responses. Instead, you get insights straight from the source.
SenseMaker® is a Large-Scale & Accessible Data Collection Tool that
Traditional interviews rely on note-taking, transcription, and interviewer interpretation—all of which introduce bias and risk losing key details. Interviewers may unintentionally influence responses, shaping narratives instead of capturing them. SenseMaker® removes the middleman, letting respondents frame their own experiences in ways that truly reflect their perspectives.
By using structured signifiers, SenseMaker® ensures responses are categorised consistently. No more sifting through transcripts and guessing themes – patterns emerge naturally, giving you richer, more reliable insights without the hassle.
So Why is SenseMaker® more reliable than Traditional Interviews?
Traditional interviews require painstaking manual coding and subjective interpretation. SenseMaker® streamlines this process by automatically identifying themes, emotional tones, and shared experiences across large datasets. Decision-makers get actionable insights faster, with a clearer understanding of emerging trends and potential challenges.
If you Analyse Themes & Patterns with SenseMaker® you get
Forget messy filing systems and endless spreadsheets. SenseMaker’s digital platform stores every response in an organised, searchable format. Built-in visualisation tools generate charts, graphs, and reports with a click – so you can present findings clearly without spending hours formatting data.
Easy Storage & Instant Visualisation with SenseMaker® includes
More authentic stories. More accurate insights. Less bias. Less manual work. If you’re still relying on traditional interviews, it’s time to upgrade. SenseMaker® delivers deeper understanding and actionable intelligence – faster and more efficiently than ever before.
| Feature | SenseMaker | Traditional Interviews |
|---|---|---|
| Primary Purpose | Identifies patterns in narratives through participant self-interpretation. Your theories can be tested against what the data is showing. | Varies. Typically develops theories inductively from gathering qualitative data. |
| Approach | Combines qualitative and quantitative analysis by using structured signifiers (Triads, Dyads, etc.). | Purely qualitative and exploratory; may include iterative coding of data if the interviewer has received training. |
| Data Collection Process | Participants submit self-signified narratives via structured digital tools. | Researchers conduct interviews and may also make observations and take field notes. |
| Type of Data Collected | Short narratives, micro-stories, and structured responses. | Interviews which will vary in degrees of structure. Some interviewing processes will allow open-ended responses and allow observations by the interviewer. |
| Sample Size | Scalable (hundreds or thousands of responses). | Smaller samples due to time/resource cost. |
| Speed of Analysis | Fast (automated dashboards & self-signification). | Slow (manual writing, interpretation, and analysis). |
| How Data is Analysed | Pattern detection through visual dashboards, heatmaps, and statistical tests. Automated coding via Triads & Dyads. | Either through informal methods or the interviewer can receive training in manual coding processes through thematic coding (open, axial, selective coding). |
| Statistical & Visual Analysis | Automatically generated heatmaps, cobweb diagrams, word clouds, cross-data correlations. All downloadable as graphics. | Analysis must be done manually by a trained interviewer, for example, manual thematic clustering, memos, and comparison. |
| Bias Reduction | Minimises researcher bias by having respondents interpret their own stories. | Higher risk of bias, as the researcher codes and interprets responses. |
| Role of Interviewer | Minimal intervention; participants categorise their data. | Interviewer-driven. Formal training in coding and categorisation is required for theme analysis to be effective. Coding needs to be done extensively by hand. |
| Output | Identifies patterns, clusters, and trends in narratives – allowing you to focus on generating theories of change. | Interviewers generate theories based on emerging patterns in data. Data collection risks being biased or even incomplete leading to premature decision making. |
| Survey Tools | Triads, Dyads, Open-text, Image-based prompts. | Interviews, focus groups, and field notes. |
| Scalability | Can process large volumes of responses. | Typically not scalable. High time and resource cos, so best for small studies. Requires significant expertise and cross-checking. |
| Cost | A single cost that is fixed no matter how much data you collect, the price for a 3 month NFP licence: i.e £900 only | Varies. Can be difficult to predict ahead of time. The time cost of the analysis stage can increase exponentially with the amount of data you collect. |
Macro and micro-cultures are everywhere. It’s in our nations, our office space, our work departments, our neighbourhoods, family systems and friendship groups. Cultures create rules that shape our daily lives. Yet, when it comes to evaluation, analysis of the culture is often neglected. Dominant narratives and assumptions can be so large that, like the fish in the sea, we are not aware of them. So, how do we truly understand the cultures that shape our decision making? That’s where SenseMaker® CultureSense comes in.
Evaluation methods should always be wary of oversimplification. We can’t categorize things into neat little binaries: good/bad, success/failure, right/wrong. People’s day to day reality is messy and interdependent. Constantly in flux and changing. Simple, linear, causal relationships don’t always hold.
SenseMaker® helps us move past binaries and embrace the rich complexity of human experience. Instead of imposing external interpretations, it allows respondents to interpret their own stories. This shift removes researcher bias and puts the power where it belongs: in the hands of the people sharing their experiences.
Culture isn’t just about nationality—it’s also about workplace culture, community dynamics, and those inevitable culture clashes that come from groups with differing expectations. When we bring these hidden cultural assumptions into awareness, we can ask:
Are these assumptions still serving us? Do they reflect the perspectives of the many or just a privileged few? By addressing these questions, we create space for more meaningful and culturally informed evaluations.
Here’s a common pitfall: institutions often evaluate people or communities using their own narrow definitions of success. This is a huge barrier to the deeper understanding that leads to progress. Imagine someone coming into your space and telling you what “progress” looks like—without asking for your input. It’s demoralising, isn’t it? This happens all the time in evaluation.
By measuring only based on externally imposed standards, we risk erasing the knowledge of those on the ground. We can’t afford to undermine what they know about what truly creates barriers to working effectively or where opportunities for growth lie. SenseMaker® ensures that those being researched and evaluated actively participate in shaping the evaluation process.
Let’s talk about targets. On the surface, they seem like a great idea—set a goal, track progress, and boom, success! But the reality? Targets often distort behavior rather than improve outcomes.
During British rule in India, the government wanted to reduce the number of venomous cobras, so they offered a bounty for every dead cobra brought in.. Seems logical until you realise that some enterprising individuals started breeding cobras just to collect the reward. When the government realized this and scrapped the program, the now-worthless snakes were released, leading to even more cobras in the wild.
This is what happens when we focus too much on numbers without thinking about how they influence behaviour. SenseMaker® avoids this trap by moving beyond rigid targets and instead exploring systemic patterns—giving us a clearer picture of what’s really happening.
We’ve all heard the saying: “History is written by the victors.” But in evaluation, history is often written by those with power – leaving out voices that don’t fit the dominant narrative. This is called epistemic injustice – a situation or dynamic where some perspectives are valued while others are dismissed before their merits can even be assessed. Even when diverse voices are included, people often feel pressured to shape their words to fit the dominant culture. That’s not a real fair hearing or real representation.
SenseMaker® ensures that everyone’s voice carries weight by prioritizing collective patterns over a handful of selected stories. This means we don’t just hear the loudest voices—we hear all voices.
Many evaluation methods rely on quantitative metrics—Likert scales, KPIs, and statistical averages. And while numbers have their place, they can’t capture everything. People aren’t machines; their lives aren’t reducible to data points.
Daniel Yankelovich perfectly summed up this issue:
This kind of methodological reductionism strips away the richness of people’s experiences. SenseMaker® avoids this by combining stories with data, ensuring we capture both scale and depth—without losing sight of context.
Have you ever started a project with good intentions, only to realise it had unexpected side effects? That’s the nature of complex systems—every action has ripple effects, some predictable, others chaotic.
Most traditional evaluations focus on predefined outcomes, making it hard to spot these unintended consequences. SenseMaker®, on the other hand, is designed to pick up on emerging insights, helping us understand the full impact of an intervention in its positive and negative aspects. It also helps us avoid research where the distinction between targets and questions are blurred. When people know what an evaluation is looking for, they often naturally seek to game the system leading to the aforementioned ‘cobra effect.’SenseMaker® reduces this risk by allowing respondents to frame their own narratives, making the evaluation process harder to manipulate.
SenseMaker® isn’t just another evaluation tool—it’s a shift in thinking. It moves beyond rigid targets, numbers, and imposed narratives to uncover what truly matters. By centering respondent voices, embracing complexity, and respecting cultural contexts, it provides a richer, more authentic way to understand change. In a world where evaluation often feels disconnected from real experiences, SenseMaker® brings the human element back into the equation. And that is what leads to the deeper understanding that grounds meaningful progress. An essential post that will enhance your knowledge about how SenseMaker® operates effectively: How to use a new generation data collection and analysis tool?
The Cynefin Framework and Estuarine Mapping (Estuarine Framework); Frequently mentioned, but what are they and how are they related?
Most people who will come across this blog will probably be familiar to some extent with the Cynefin Framework, and increasingly more people are becoming familiar with Estuarine Mapping, but how are they related, what is different about them and how to integrate them?
Effective decision making is crucial for the success of any organisation. So is strategic thinking, which translates to on-the-ground, in-the-moment tactics. In today’s complex and rapidly changing environment, traditional models often fall short. The Cynefin Framework and Estuarine Mapping offer alternative approaches to understanding and navigating complex environments, each with a distinct focus and application.
Understanding the Cynefin Framework
In its simplest form, The Cynefin Framework is a decision-making tool that helps decision makers establish in what kind of system(s) a problem or decision exists within, in order to know how to respond accordingly.
Clear, Complicated, Complex, Chaotic, and Confused/Aporetic. Each domain requires a different approach to decision-making:
The primary function of the Cynefin Framework is to establish which type of system or context you are dealing with and make decisions accordingly. Subsequent decisions will include elements such as what kinds of processes to follow, what kind of tools to use or actions to take, and a recognition of the dynamics that exist between the domains and navigating between them. This involves understanding whether the situation is clear, complicated, complex, or chaotic (or which parts of the situation are clear, complicated, etc…), and then applying the relevant decision-making strategy.
When introducing the Cynefin framework, I like to use it for identifying what I call “Domain dissonance” – when we are acting in one type of system, but according to the principles of another. It can become a very useful individual and team exercise to reflect on whether you may be making any decision or acting in an environment in a way that is dissonant to the actual issue at hand.
Compared to Estuarine Mapping…
While the Cynefin Framework focuses on identifying the nature of the system to inform decision making, Estuarine Mapping is specifically geared towards applied complexity theory in order to create a strategy or take action in a complex system.
Estuarine Mapping:
Estuarine Mapping is a way of understanding a system or context and then initiating micro changes that reduce the risk and cost of taking action, to create the best environment for solutions to emerge. Just as with the movement of the tide in an estuary, complex problems in a system are non-linear, multi-directional, and have multiple effects. They can’t be solved by tracing an issue back to its root cause, as with simple problems. Instead, we need to adjust how the system is set up to increase the chances of good results and reduce the chances of bad ones.
Estuarine Mapping identifies the things that shape and influence a system. Once these are identified, they are plotted onto a chart, mapping them against how much energy and time they would each take to change. This chart of energy against time is called the Estuarine Framework. This allows us to see what can be reasonably changed and allows for a portfolio of micro-interventions to be designed in order to stabilise, change, or monitor, where appropriate.
If we make micro-interventions at this level, they can have surprisingly significant effects on a grand scale. In fact, they can even affect whether the problem exists in the way we think it does. The result is a clear, physical picture of where we are, what we want to change, and what we realistically can’t change, with a spectrum of actions that we could take to enable the strategy to become reality.
Estuarine mapping is about working with the substrate of a system rather than attempting to change people or tackling individual problems head-on in a direct, linear fashion. The Estuarine Mapping process is conducted to generate a portfolio of actions. The portfolio of actions can each be mapped back onto the Cynefin Framework to categorise the action types in order to develop and roll them out according to the domain they occupy and the relevant change management process for that domain.
In Summary…
When starting with the Cynefin Framework and establishing that a context or issue falls within the Complex Domain, Estuarine Mapping of said context or issue can provide a practical and structured approach for developing both a strategic and operational response through establishing a map of the substrate of the system, developing a range of interventions; these can then be mapped back to the Cynefin Framework and delivered and managed accordingly to the domain they relate to.
Utilising the Cynefin Framework and Estuarine Mapping enhances decision-making and strategic application by providing structured approaches to handle different types of challenges. The Cynefin Framework aids in identifying the nature of the system and determining decision-making strategies, while Estuarine Mapping focuses on applying these decision-making strategies in practical ways, with applied complexity theory baked into the method. Together, these frameworks help organisations improve their agility, decision-making processes, and strategic resilience.
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