Presented at the Bitkom Big-Data.AI Summit on 14 September 2022 together with Kantar Public. We discuss how AI technology was used to automate survey analytics at Kantar Public Germany, and detail key business benefits such as improved efficiency, quick deliverables to the client, and advanced data validation and analysis. This work is part of Kantar Public's Public Data Innovation Hub (https://www.kantarpublic.com/de/Unsere-Expertise/daten-und-fakten/public-data-innovation-hub). Supporting write-ups are available at https://www.inspirient.com/case-studies/survey_analysis_automation.php and https://www.inspirient.com/case-studies/survey_quality_assurance.php Full abstract at https://big-data.ai/programme#Complementing-PoliticalSocial-Research-with-AI-for-a-Deeper-Understanding-of-Society

1. Complementing Political / Social Research
with AI for a Deeper Understanding of Society
Dr. Georg Wittenburg ▪ Inspirient
Martin Schniedermeier ▪ Kantar Public
Bitkom Big-Data.AI Summit
Berlin, 14 September 2022

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Bitkom Big-Data.AI Summit 2022, 14.09.2022 1
Dr. Georg Wittenburg
Co-founder and CEO at Inspirient
Martin Schniedermeier
Data & Operations Global Transformation Director
and Partner for Europe at Kantar Public

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Trust is central to political and social research
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Kantar Public works with clients across the world to improve public
policy, public services and public communication
• Partner of governments and multilateral clients in the collection and
curation of data for national and international statistics and linked
public information
• Manage global research programs using all types of data collection
methodologies
• World-leading experience in running high-quality, complex multi-
country studies using all recruitment methods working with a
multitude of public clients
– E.g. European institutions, Fundamental Rights Agency, Banks
(ECB, World Bank), country governments, foundations

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...and so is efficiency!
• On-time delivery, high-quality data and
results are based on:
– Experience (team)
– Effectiveness (processes)
– Efficiency (innovation)
• Each process step is linked to significant
manual work, e.g.:
– Survey scripting
– Fieldwork
– Data processing / analyses
– Data visualisation / report out
• Preparation, execution and processing of
projects delivers against defined timelines
and improves capacity utilisation
Bitkom Big-Data.AI Summit 2022, 14.09.2022 3

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We have our core processes - but can we do this even better? Can AI help?
Kantar Public launched its Innovation Hub:
• to link innovation (ideas, tools, algorithm platforms)
with our recent solutions and research approaches
• to improve both quality and efficiency
• to provide more comprehensive and relevant results
• to support data science and digital start-ups and
micro-enterprises active in data, technology and AI in
the provision of evidence for use in the public sector
And to rethink our core production process
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+ AI ?

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Building an AI to do statistics
and business math
Inspirient was founded on the idea that
reasoning about (semi-)structured data
can, and should, be automated
Our vision is that 10 years from now, AI
will handle typical and repetitive
human tasks autonomously, just like
microprocessors handle tasks of a 1950s human
computer
Consequently, businesses will be able to:
• Reduce the cost of their analytics operations
• Improve predictability of analytics projects
• Comprehensively look at internal and
external data
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AI-derived
Results

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Intuition: Analytical reasoning closely resembles a game of chess
Computer Chess Automated Data Analysis
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• Enumerate and score all valid moves, anticipating
opponents counter-moves
• Select next move based on best score
• Enumerate and score all valid analysis steps, e.g.:
 Data classifications, aggregations, regressions
• Visualize results as searchable slides
AI
Human nothing to do
• Select relevant results based on context specific to the
client and/or survey
Numeric?
Country?
ZIP code?
Likert Scale?
Aggregation?
Outliers?
String?

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Analytics is automated by orchestrating 420+ custom build classifiers to
emulate the reasoning process of a human statistician
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Inspirient’s Hybrid AI uses 420+ custom built classifiers
to autonomously apply human-level analytical reasoning

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For our processes, this means we can get now up to 80% of our client-
facing deliverables in less than 30% of the time
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1–2 minutes 5 mins – 2 hours
Data Upload
Analysis Guidance
(optional)
Review of
Generated Reports
Discovery of
Additional Insights
• Datasets in Microsoft Excel,
SPSS, CSV or from
SQL data sources
• One or multiple files
• Prioritising dimensions
• Guiding the analysis
 Survey meta information
 Multiple-choice variables
• Advanced customisation
• Survey quality assessment
 Straightliners and
interviewer effect
• Contingency tables and
cross tabulations
• Most significant multivariate
regressions
• Browsing all results
• Finding most significant
statistical patterns
• Finding something new
and unusual
• Compiling a custom report
• Sharing results and reports
Automated data scan Automated analysis

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What is more, we get to scale in-demand statistical capabilities
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• Advanced analytical methods are
applied automatically whenever data
meets defined prerequisites
• Core methods include multivariate
regression analysis, Average Marginal
Effects (AME), density-based
clustering, geographic data analysis,
and key phrase extraction from natural
language text
Enabling
Technology
New
Capability
• With classified input dimensions (e.g., as socio-demographic or survey
answers), analysis is applied to all valid combinations
• Prioritisation metrics help to statistically identify which results, for
example which contingency table, has the most significant patterns
Analytical deep-dives are
comprehensively applied to
data, guaranteeing that
most relevant results are
discovered
Client Benefit

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Our digital dividend is to run one of our core business processes more
than one order of magnitude faster
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Now With Inspirient
Manual analysis of survey data takes days to weeks Improved Efficiency – Deliver detailed analytical
evaluations in minutes, with more time for deep-dives
Results only available at the very end of research
projects, which can last days weeks or weeks
Quick Deliverables – Access results the moment they are
needed, with generated reports and prioritized insights
Limited visibility into results until data collection is done;
difficult to fix collection issues immediately
Preview Results during Data Collection – Preview
results to gather feedback in real time and steer project
Undetected data quality issues up to, and
including, rampant fraud
Advanced Data Validation – Collected data is more
thoroughly checked for data quality issues
Advanced analytical methods only applied selectively by
expert statisticians
Advanced Analytical Methods, Applied at Scale –
Valuable insights surfaced with automated methods
Limited audit trail of delivered results Paper Trail for Every Result – Detailed, audit-proof
documentation how each analytical result was derived

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Data analysis will become more and more commoditised, even for more
demanding deliverables
Mixed-mode Story Telling
• Prioritize and summarize
analytical results to compile
full presentations
• Generate supplementary
documents, e.g. detailed
Excel tables
Narrated Presentations
• Generate voice-over for
individual or sequenced
analytical results to further ease
consumption
• See example at
https://youtu.be/6hW9E0-OMpE
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Use Case Scalability
• 2017  1 dataset
Process mining and optimization
at Deutsche Bahn
• 2018  3 dataset + real-time
Fraud detection, cyber crime
prevention, AML at BNP Paribas
• 2021  All use case datasets
Survey analytics at
Kantar Public
• 2022  100,000s datasets
Full analysis of data.europa.eu
(talk this morning)

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Thank you for your time today
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Martin Schniedermeier
martin.schniedermeier@kantar.com
Dr. Georg Wittenburg
georg.wittenburg@inspirient.com