Fuzzy Logic is good! As is Binary. There would be no computers without binary logic and there would be no decisions without fuzzy logic! A quote from the deck I used for a Faculty Development Program (FDP) for Management Professors in Mumbai some time ago.#GivingBack. Many slides are common to other decks uploaded , but the weave and additional material provide the relevance.
2. Have you participated in a PTA meeting?
How would the embattled Account Manager desire to be evaluated?
Muder Chiba
3. Market
Complexity
Decisions
Information
Complexity
I have concluded that the essence of wisdom is to hold the attitude that
knowledge is fallible and to strive for a balance between knowing and
doubting Psychologist John Meacham quoted in Hard Facts , Dangerous Half-Truths andTotal
Nonsense, Profiting from Evidence-Based Management
muder.chiba@gmail.com
6. The business of
insights is at the
core , the
business of
truths (with a
small t).The
Tagore poem
referenced here :
http://www.poe
mhunter.com/po
em/where-the-
mind-is-without-
fear/
Muder Chiba
10. Muder Chiba
In a world where quantitative is privileged over qualitative,
many (mis) perceptions have been built up around qualitative
research.
To really get qualitative , it is necessary to get past those barriers
to understanding.
14. ...with sympathy
for all my Qual
brethren who have
been asked for
tally distribution
for the 32 people
who attended the
Groups as "30 is
the sample at
which you can do
the Student'sT
test !
Muder Chiba
15. Qual is the seemingly soft fluffy area of MR.
There is a lot more of the eclectic mix of a range of the Social
Sciences here than in Quant though!
And hard decisions using words instead of numbers per se as
data.
Fits well into the modern Big Data world .
Muder Chiba
22. Qualitative view Quantitative view
Muder Chiba
The Quant researcher needs a ready structure whereas the Quali
compatriot spins structure out of context!
26. Data Collection questions ,photos , videos
DataTranscription to provide cogent analysis base
Content analysis to reduce data to manageable
chunks whilst retaining flavour of context
Chunking the analysis into a model to
explain/decide
Muder Chiba
27. Muder Chiba
Techniques are data collection agnostic
f2f ,
online ,
Mobile ,
Social media feeds
Analysis is human+ machine.
28. IDI
Dyads
Triads
Mini Groups
Focus Groups
Extended Focus Groups
Accompanied Shopping
DILO
Extended Ethnography
ObservationalTechniques
Muder Chiba
Decision based
on :
Objective,
Confidentiality
requirements
Respondent
accessibility,
Taboo topic or
not,
time and cost
30. Paint purchase decision for home
Paint purchase decision for office
Ideation for a creative brief for a toilet soap
brand
Market estimation for a new to market
innovation
Muder Chiba
32. muder.chiba@gmail.com
Qualitative and Quantitative Perspectives
With the Information Deluge ( think
IoT , Big Data, Engagement
Economy) , it does not require
crystal ball gazing to determine that
Qual and Quant approaches will
need to cross-fertilise- with Quant
learning to deal with fuzziness and
context and Qual with huge sets of
data and structure
#2: If you are a researcher , qual or quant but do not possess a sense of humour- do Not proceed ! The Qual/Quant divide has been a part of life as we know it and the stress involved in getting the twain to meet has prematurely greyed many managers !!
#9: Quali perceives quant to be shovelling tons of data as throughput! Quant sees itself though as the steady ,solid Thinker!
#10: Quali perceives quant to be shovelling tons of data as throughput! Quant sees itself though as the steady ,solid Thinker!
#12: Quali perceives quant to be shovelling tons of data as throughput! Quant sees itself though as the steady ,solid Thinker!
#13: The Quant researcher sees the Qual as a diva holding forth ;The Quali sees self as hard-working ,have-to-do-everything-myself
#14: This is where self-view and others view of self possibly coincide!
#33: With the Information Deluge ( think IoT , Big Data, Engagement Economy) , it does not require crystal ball gazing to determine that Qual and Quant approaches will need to cross-fertilise- with Quant learning to deal with fuzziness and context and Qual with huge sets of data and structure