Back to session 1’s two axes

• In session 1 we classified research along two axes; today we take up one end of the first
• Qualitative research works with words, images, and observed behaviour — data not easily reduced to numbers
• It is usually descriptive rather than experimental: the researcher observes the world rather than manipulating it
• Its reasoning is characteristically inductive — building understanding up from observations, rather than testing hypotheses fixed in advance (Babbie calls this field research)
• A qualitative researcher seldom starts with a precise hypothesis; more often, the task is to make sense of an ongoing process that cannot be predicted in advance

Naturalism and meaning

• Two commitments define the qualitative outlook
• Naturalism — study social life where it actually happens, not in the artificial settings of the survey or the laboratory
  • Behaviour in a store, a warehouse, or a team meeting is best understood in that setting, shaped by its pressures and routines
• Meaning — take seriously the actor’s own point of view
  • What does the rota mean to a shift worker? What does “engagement” mean to the people being scored on it?
• By going directly to the phenomenon and observing it as completely as possible, researchers can notice nuances of attitude and behaviour that escape every other method

Small samples, chosen on purpose

• Qualitative studies work with small numbers — a dozen interviews, three teams, one organisation
• Participants are selected purposively, not randomly: chosen because they are informative
  • the longest-serving employee, the store that bucks the trend, the customer who left
• Small size is a consequence of depth, not a defect: an hour-long interview generates more material than a hundred questionnaires
• The trade-off is explicit: qualitative samples do not statistically represent a population, and honest qualitative researchers never claim they do
• Collection often stops at saturation — the point where new cases keep telling you what you already know

Inductive discovery

• Qualitative inquiry typically runs from data to theory: observe, look for patterns, build concepts up from the ground
• This makes it the natural approach when a phenomenon is new, sensitive, or poorly understood — when you do not yet know enough to write the right closed questions
• Its findings often become the hypotheses that later quantitative work tests — recall session 1’s cycle between induction and deduction
• It also challenges preconceptions: immersion in a setting confronts researchers with their own assumptions
• Creswell & Creswell treat this as a hallmark of the qualitative worldview: design stays flexible and emergent, adapting as understanding grows

When qualitative is the right choice

• Topics that defy simple quantification — attitudes and behaviours best understood in their natural setting
• Processes unfolding over time — how a reorganisation, a conflict, or a new system settles in, watched as it happens rather than reconstructed afterwards
• Babbie’s inventory of field-research topics translates directly into organisational life:
  • practices and encounters — how handovers, briefings, and customer interactions are actually done
  • roles and relationships — how “team leader” or “new manager” is performed and received
  • groups and organisations — shift cliques, departments, whole firms
• Whenever the question is how or why rather than how many, the qualitative family deserves a look

Five approaches, one logic

In-depth interviews

• A one-to-one conversation designed to gather detailed information about experiences, motives, and interpretations
• Interviews sit on a spectrum of structure:
  • Structured — fixed questions in fixed order; uniform, quantifiable, but shallow
  • Semi-structured — a topic guide plus the freedom to probe and follow up; the workhorse of organisational research
  • Unstructured — open and exploratory; the participant’s narrative leads
• What they suit: individual experience, sensitive topics, expert insight, reconstructing decisions — “how would you describe the work culture here, and what experiences shaped that view?”

Interviews: strengths and limits

• Strengths
  • Depth — topics explored in detail, in the respondent’s own words
  • Flexibility — questions adapt to the answers; unexpected themes can be pursued
  • Clarification and rapport — misunderstandings fixed on the spot; trust invites candour
• Limits
  • Time-consuming and costly — scheduling, conducting, transcribing, analysing
  • Interviewer effects — the interviewer’s presence and phrasing shape responses
  • Accounts, not behaviour — you learn what people say they do, which is not always what they do
• For organisational diagnosis: unbeatable for individual meaning; weak evidence for how common a view is

Focus groups

• Five to fifteen people brought together in a comfortable setting for a guided discussion of a topic, led by a moderator
• The distinctive data is the interaction: how views are voiced, challenged, defended, and revised in front of peers
• A staple of market research — groups evaluating a product or reacting to a proposal before launch
• Participants do not statistically represent any population; the purpose is to explore, not to describe or explain definitively
• Typically more than one group is convened, because any single group of five to fifteen people may be idiosyncratic

Focus groups: strengths and limits

• Strengths
  • Diverse perspectives in one sitting, and efficient — several participants at once
  • Interactive — participants react to each other, surfacing agreements and fault lines a one-to-one interview cannot show
  • Rich data — emotions, group norms, even body language
• Limits
  • Group dynamics — dominant voices can silence others; minority views may go unspoken
  • Conformity and caution — people say less, or say safer things, in front of colleagues
  • Less control and complex analysis — discussions wander; many voices make intricate data
• For organisational diagnosis: excellent for testing reactions and surfacing shared understandings; risky for sensitive topics where hierarchy is in the room

Observation and ethnography

• Observational research — watching and recording behaviour and interaction in natural (or controlled) settings, without manipulating the environment
• Variants differ by the researcher’s position:
  • Non-participant observation — the researcher watches without joining in
  • Participant observation — the researcher takes part in the life of the group
• Ethnography extends participant observation into long-term immersion — weeks or months inside a setting, to understand it from the inside
• What it suits: routines, workarounds, and informal norms — the gap between the process manual and what actually happens

Observation: strengths and limits

• Strengths
  • Captures behaviour, not accounts — what people do, not what they remember or admit doing
  • Context — behaviour is seen embedded in its real pressures and routines
  • Well suited to processes over time and to groups who cannot or will not articulate their practice
• Limits
  • Observer effects — being watched changes behaviour, at least initially
  • Subjectivity — findings pass through the observer’s interpretation; multiple observers and careful design mitigate this
  • Slow, local, and hard to generalise — deep knowledge of one setting, silence about all others
  • Ethical care needed: consent and privacy are harder to manage than in an interview

Case studies

• An in-depth examination of a single instance — one store, one team, one merger, one crisis — using multiple sources of evidence in combination: interviews, observation, documents, and numbers
• The case is chosen purposively: because it is typical, extreme, deviant, or revelatory
• One of Creswell & Creswell’s five core qualitative designs; the natural home of the question “what is going on in this particular place, and what can it teach us?”
• What it suits: understanding how many factors combine in context — and learning from outliers
• Limits: boundaries blur, depth is costly, and a single case supports only cautious generalisation

Document and qualitative content analysis

• Organisations write constantly: policies, emails, announcements, meeting minutes, exit forms, reviews, complaints, chat logs
• Document analysis treats these texts as evidence about the organisation that produced them
• Content analysis does so systematically: define the question, develop a coding scheme of themes or categories, apply it consistently, and look for patterns
  • classic example: coding a year of press coverage to see how women in leadership are portrayed
• Unobtrusive: nobody is interviewed or observed, so nobody reacts to being studied; the past is as accessible as the present
• Limits: documents record the official trace, not the lived reality — and what was never written down is invisible

Matching approach to question

Can we trust it? The quality problem

• Sceptics ask: small samples, no statistics, interpretation everywhere — isn’t this just anecdote?
• The honest answer: bad qualitative research is exactly that; good qualitative research is not, and there are criteria for telling them apart
• Session 1’s criteria — validity (measuring what you intend) and reliability (getting the same result again) — were built with quantitative measurement in mind
• Babbie’s verdict on field research: compared with surveys and experiments, its measurements typically have more validity but less reliability
  • watching real behaviour in context gets closer to the truth of this setting — but another observer might see it differently
• So qualitative researchers use a parallel vocabulary for quality, asking the same underlying questions in a form that fits the method

Credibility and transferability

• Credibility — the qualitative counterpart of validity: are the findings believable as an account of this setting?
  • strengthened by prolonged engagement (enough time in the field), triangulation (multiple sources, methods, or observers pointing the same way), and member checking (do participants recognise the account as true to their experience?)
• Transferability — the counterpart of generalisability: could these findings illuminate other settings?
  • the researcher does not claim statistical generalisation; instead, thick description — rich detail about the case and its context — lets readers judge how far the findings travel
• Note who does the work: in a survey, the sampling design carries generalisation; in qualitative work, the description does

Dependability

• Dependability — the counterpart of reliability: was the process consistent, transparent, and traceable?
• Since the study cannot be exactly repeated — the setting moves on, the researcher is part of the instrument — the standard becomes an audit trail:
  • documented decisions about who was selected and why
  • recorded and carefully transcribed data, systematic notes separating what you observed from what you inferred
  • a coding process another researcher could follow and check
• The discipline is the same as in session 1: explicit, transparent, repeatable-in-principle procedure is what separates research from impression

Quality criteria compared

Why did the engagement score fall?

• Meridian’s annual engagement survey (CAWI, all 450 staff) reports store-employee engagement down from 3.8 to 3.2 out of 5
• The score is genuinely useful: it is comparable across years and stores, and it triggered the alarm
• But it cannot say what “engagement” means to a shift worker, which of a hundred possible causes is at work, or what to change
• The qualitative follow-up: semi-structured interviews across stores and roles, sampled purposively — long-servers, recent joiners, leavers
• This division of labour is the standard pattern: quantitative monitoring detects; qualitative inquiry diagnoses

How teams actually work

• Every organisation has two structures: the formal one in the org chart and process manuals, and the informal one in daily practice
• Diagnosis usually needs the informal one — and people cannot fully report it, because routine practice is largely invisible to those inside it
• Observation and mini-ethnography answer questions like:
  • where does the shift handover actually lose information?
  • who do people really go to when something breaks?
  • which rules are followed, bent, or quietly ignored — and why?
• Field notes should record both observation and interpretation — what you know happened and what you think it means — kept clearly apart

Customer experience research

• The same logic applies outward: Meridian’s customer satisfaction scores are falling, and the scores alone cannot say why
• The qualitative toolkit maps directly onto customer experience:
  • interviews with lapsed customers — what does switching away mean from their side?
  • focus groups reacting to the store refit or the loyalty scheme before rollout
  • observation of real shopping trips — where do customers hesitate, queue, give up?
  • document analysis of complaints and online reviews, coded for recurring themes
• Market researchers have used every one of these for decades — qualitative methods are not academic luxuries but standard commercial practice

What qualitative evidence cannot do

• Choosing qualitative approaches honestly means knowing their limits
• They cannot provide statistical descriptions of large populations — no percentages, no margins of error, no “23% of staff intend to leave”
• They cannot establish how widespread a discovered pattern is: ten interviews can find a mechanism, not measure its prevalence
• They are labour-intensive, and their conclusions depend on interpretation that must be documented and defended
• The remedy is not to abandon them but to pair them: qualitative work to discover and understand, quantitative work to measure and generalise — in the next session we turn to the quantitative side

Conclusion

• Qualitative inquiry rests on a coherent logic: naturalism, meaning, small purposive samples, and inductive discovery — depth bought at the price of breadth
• The family offers five main approaches — interviews, focus groups, observation and ethnography, case studies, document analysis — distinguished by what they gather and therefore by the questions they suit
• Quality is judged by credibility, transferability, and dependability — the same underlying demands as validity and reliability, translated for a different kind of evidence
• For organisational diagnosis, qualitative methods answer the questions dashboards raise: not whether the score fell, but why — and what to do about it
• Sessions 12 and 14 return to this family for technique: how to interview well, and how to analyse what you gather
• Questions and discussion are welcome

Exercise

Study guide