T Ho M.Mindset Analytics.200901.Slideshare.V2

The Mind-set Prior to Analytics
(Perspective of The House of Marketing)

January, 2009

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The House of Marketing (THoM)
Customer orientation present in all four functional
areas we specialize in
Functional expertise
Corporate and business unit strategy
Growth and innovation strategy
Strategy Business plan, modeling and scenario building
Market and competitive analysis

Marketing strategy and marketing plan
Customer insights and intelligence
Customer segmentation and value proposition
Marketing Sales and channel management
Customer relationship management
Branding and pricing
Product management and new product development

Organization design and development of new organizations
Program management and change management
Organization
Core process mapping and developing reference process models

Communication strategy and plan
Communication
Marketing (communication) efficiency and effectiveness

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THoM.Mindset Analytics.200901.Slideshare.v2.ppt

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Objective of today’s presentation

Using data intelligently has already been around for decades …
So are the related issues…

The analytics market is offering an abundance of solutions to gear up
your data abilities…
And customers/companies are increasingly more willing to deploy
data in some way…

But are they really ready to turn their minds to data ?

This presentation provides the view of The House of Marketing on
how companies should gradually structure their analytical
perspectives and pace the required transformation in the
organization.

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Agenda

1. Kondratieff’s case

2. The Kondra-stages

3. The Kondra-quences

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Kondratieff
Macro-economic analytics ‘avant la lettre’

Professor Nikolai D. Kondratieff – Social Sciences
• Publishing in 1926 (that is 3 years prior to the ‘crash of 1929’)
• Analyzing the capitalistic economy
• “Die langen Well der Konjunktur”, Archiv für Sozialwissenschaft
und Sozialpolitik vol.56, no.3, pp.573-609

Renown for building a macro-economic theory, amongst many …

Still subject to discussion today: Believers vs. Non-Believers, despite
• Scientific study
• Data proven study (descriptive)
• Historically proven (post-study)

We’ll focus on the original way of working of Kondratieff in 1926
We’ll focus on the original way of working of Kondratieff in 1926

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Ambitions at the start of Kondratieff’s study

Initial objectives of the study:
• Unravel or structure the complexity of capitalist dynamics (i.e.
find the main driving factors)
• Analyze for trends or movements in the long term (i.e. economic
shifts)
- No prejudice on cyclical character

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The analytical issues were no different than ours today

The issues: Sounds familiar ? Comments

Identifying what’s relevant (i.e. which Only interest rates and gold reserves as
macro-economic factors to include) readily available macro factors

Long/short observation time Maximally 140 years of data, eventually
representing only 2,5 cycles

Data availability Only some French and English data going
back to 1800’s

Data reliability Missing data (wars), different sources or
collection methods within the same sample

Data representativeness US proxying for England for some data;
coal consumption proxying for industrial
activity

Normalization Divide by population data (if available) for
comparison

Mitigating short-term distortions Using new statistical techniques of 1919-
1920

Contextual issues Territory changes…
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Results versus acceptance …

• Revealing a likely high risk of depression (1929)
• Cycles of 50 years (48-60yrs), on top of the known 7-11 yr
Some results
and 1,5yr cycles
• Multiple options of concurring factors to trigger change

Shedding light on relevant and less relevant factors
•
Cyclical character of mankind
•
The merits Denying linear behaviors
•
Gold production is not a determinant
•
…
•

• ‘He’s not so sure, is he?’
• ‘Cycles… really? Not a
surprise’
• ‘We knew it was complex’
The comments • It falls short of clarifying
the nature and types of the
wave-like movements
(cause vs. consequence)
•…

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What happened?

Where did Kondratieff go wrong?

Or did his audience?

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Agenda




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All analysts risk having a ‘Kondratieff experience’

In our experience discussing analytics with customers, The House of
Marketing tackles the readiness and organizational understanding in
phases …

… as we often need to work around disconnects in
• Language used
• Perspective and interpretation
• Mutual understanding
between the analytical and the non-analytical individuals involved

There is a lot more to prepare and align prior to any important
analytical job, especially for an external provider

90% of a data mining job is data preparation …
… but at least 50% of the whole job is building a common (data)
mind-set of people

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Today’s stakeholders’ mind-set process on analytics:
Clearing out the clouds jointly
Kondra-stage 1 Kondra-stage 2 Kondra-stage 3
1 2 3

Convinced that there is Understood that you’re Comfortable in not always
(sufficient) data out there dealing with real life having the ‘why’
• Techniques • Ambiguity and • But there’s always more
• Approaches probability than you know
• Proxies • There’s no such thing
• Hypotheses as exact sciences Comprehended that
predictive is not descriptive
Understood that data Perfection has generated • A world of difference
needs to be ‘screened’ no results yet
• It’s not just input • It’s about an And even descriptive is
improvement vs. already more than reporting
Comprehended that you today
don’t have to wait for IT • You don’t need all Understood that your
• IT awaits you data organization requires a
multi-skilled (marketing)
Pre-defined what you Understood your data and team
want to DO in the end data processing
• Application / • It’s never just data IT solutions eventually help
implementation side • It’s never the right • Scaling
data • Integrating
• Automating

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Discussing the mind-set stages helps the non-analytical

Kondra-stage 1 Kondra-stage 2 Kondra-stage 3
1 2 3

Convinced that there is Understood that you’re Comfortable in not always
(sufficient) data out there dealing with real life having the ‘why’
• Techniques • Ambiguity and • But there’s always more
• Approaches probability than you know
• Proxies • There’s no such thing
• Hypotheses as exact sciences Comprehended that
predictive is not descriptive
Understood that data Perfection has no results • A world of difference
needs to be ‘screened’ yet
• It’s not just input • It’s about an And even descriptive is
improvement vs. already more than reporting
Comprehended that you today
don’t have to wait for IT • You don’t need all Understood that your
• IT awaits you data organization requires a
multi-skilled (marketing)
Pre-defined what you Understood your data and team
want to DO in the end data processing
• Application / • It’s never just data IT solutions eventually help
implementation side • It’s never the right • Scaling
data • Integrating
• Automating
Getting to data
Getting to information Getting to data usage
Getting started
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Agenda




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Analytics cannot (correctly) hold and prosper on
its own

Building
common
understanding Kondra-stage 1 Kondra-stage 2 Kondra-stage 3
1 2 3
of
stakeholders

Into the Getting to data Getting to Getting to data
analytics Getting started information usage
language

Goal-based data Competitive
Up to the
Analytical
management advantage
managerial
discovery
(not DWH) creation
side

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Why your audience is everything:
Professor Nickolai Kondratieff

After the Russian Revolution of 1917, he helped develop the first
Soviet Five-Year Plan, for which he analyzed factors that would stimulate
Soviet economic growth.

In 1926, Kondratieff published his findings.

His report was viewed as a criticism of Stalin's stated intentions for the
total collectivization of agriculture.
Soon after, he was dismissed from his post as director of the Institute for
the Study of Business Activity in 1928.

He was arrested in 1930 and sentenced to the Russian Gulag (prison).

His sentence was reviewed in 1938, and he received the death penalty,
which was probably carried out that same year.

Kondratieff's theories documented in the 1920's were validated with the
depression less than 10 years later.
Source: www.kondratieffwinter.com
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The end

Probably Kondratieff's greatest contribution to the science of
investment is not his observation the world economy operates in long
cycles

Cycles would suggest a repetitive nature to events. While the
underlying economic conditions will repeat over time due just to the
physical nature of our world, our reactions will always be tempered
by knowledge and experience. The history of man has been one long
climb higher. Kondratieff recognized progress as the irreversible
trend

Imposed upon our progressive nature are the physical limits of
life. It is the interaction of these physical limits with our dreams and
aspirations that creates the constant push pull of the economy known
as the Long Wave

Source: www.kondratieffwinter.com
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For more information on marketing analytics,
contact

Stijn Ghekiere
Stijn.ghekiere@thom.eu
+32 (0)474 94 60 15

The House of Marketing
www.thom.eu

Subscribe to our monthly Marketing Buzz newsletter
on www.mingle.be (register)

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