SlideShare a Scribd company logo
1 of 39
Download to read offline
Paul Laughlin, Host of Customer Insight Leader podcast & Founder of Laughlin Consultancy
The other Softer Skills analysts need
Beyond the importance of data visualisation skills for analysts
Client-side to Agency-side
Created and lead data & analytics
teams, for all general & life
insurance businesses across
Lloyds Bank Group, over 13 years.
Added over £11m incremental
profit to bottom line annually.
Developed team of 44 analysts &
mentored future leaders.
My Career Journey
“Helping exceptional teams master the
people side of analytics”
2
3
4
Customer Analytics delivers ROI
Research & my own experience confirm analytics delivers profit
5
To achieve that needs Commercial Focus
Data & Analytics leaders confirm relevance trumps sophistication
6
There’s a focus on developing skills needed
But all too often that focus is solely on Technical Skills
7
EDSF Release 2: Part 1. Data Science Competence Framework (CF-DS)
Table 4.2. Identified Data Science skills related to the main Data Science competence groups
SDSDA
Data Science
Analytics
SDSENG
Data Science
Engineering
SDSDM
Data Management
SDSRM
Research Methods
and Project
Management
SDSBA
Business Analytics
SDSDA01
Use Machine Learning
technology,
algorithms, tools
(including supervised,
unsupervised, or
reinforced learning)
SDSENG01
Use systems and
software engineering
principles to
organisations
information system
design and development,
including requirements
design
SDSDM01
Specify, develop and
implement enterprise
data management and
data governance
strategy and
architecture, including
Data Management Plan
(DMP)
SDSRM01
Use research methods
principles in developing
data driven applications
and implementing the
whole cycle of data
handling
SDSBA01
and Business
Intelligence (BI)
methods for data
analysis; apply
cognitive
technologies and
relevant services
SDSDA02
Use Data Mining
techniques
SDSENG02
Use Cloud Computing
technologies and cloud
powered services design
for data infrastructure
and data handling
services
SDSDM02
Data storage systems,
data archive services,
digital libraries, and their
operational models
SDSRM02
Design experiment,
develop and implement
data collection process
SDSBA02
Apply Business
Processes
Management (BPM),
general business
processes and
operations for
organisational
processes
analysis/modelling
SDSDA03
Use Text Data Mining
techniques
SDSENG03
Use cloud based Big Data
technologies for large
datasets processing
systems and applications
SDSDM03
Define requirements to
and supervise
implementation of the
hybrid data management
infrastructure, including
enterprise private and
public cloud resources
and services
SDSRM03
Apply data lifecycle
management model to
data collection and data
quality evaluation
SDSBA03
Apply Agile Data
Driven
methodologies,
processes and
enterprises
SDSDA04
Apply Predictive
Analytics methods
SDSENG04
Use agile development
technologies, such as
DevOps and continuous
improvement cycle, for
data driven applications
SDSDM04
Develop and implement
data architecture, data
types and data formats,
data modeling and
design, including related
technologies (ETL, OLAP,
SDSRM04
Apply structured
approach to use cases
analysis
SDSBA04
Use Econometrics for
data analysis and
applications
EDSF Release 2: Part 1. Data Science Competence Framework (CF-DS)
Table 4.3. Required skills related to analytics languages, tools, platforms and Big Data infrastructure 6
DSDALANG
Data Analytics
and Statistical
languages and
tools
DSADB
Databases and
query
languages
DSVIZ
Data/Applicatio
ns visualization
DSADM
Data
Management
and Curation
platform
DSBDA
Big Data
Analytics
platforms
DSDEV
Development and
project
management
frameworks,
platforms and tool
DSDALANG01
R and data analytics
libraries (cran,
ggplot2, dplyr,
reshap2, etc.)
DSADB01
SQL and
relational
databases (open
source:
PostgreSQL,
mySQL, Nettezza,
etc.)
DSVIZ01
Data visualization
Libraries
(mathpoltlib,
seaborn, D3.js,
FusionCharts,
Chart.js, other)
DSADM01
Data modelling
and related
technologies (ETL,
OLAP, OLTP, etc.)
DSBDA01
Big Data and
distributed
computing tools
(Spark,
MapReduce,
Hadoop, Mahout,
Lucene, NLTK,
Pregel, etc.)
DSDEV01
Frameworks: Python,
Java or C/C++, AJAX
(Asynchronous
Javascript and XML),
D3.js (Data-Driven
Documents), jQuery,
others
DSDALANG02
Python and data
analytics libraries
(pandas, numpy,
mathplotlib, scipy,
scikit-learn,
seaborn, etc.)
DSADB02
SQL and
relational
databases
(proprietary:
Oracle, MS SQL
Server, others)
DSVIZ02
Visualisation
software (D3.js,
Processing,
Tableau, Raphael,
Gephi, etc.)
DSADM02
Data Warehouse
platform and
related tools
DSBDA02
Big Data Analytics
platforms
(Hadoop, Spark,
Data Lakes, others)
DSDEV02
Python, Java or
C/C++ Development
platforms/IDE
(Eclipse, R Studio,
Anaconda/Jupyter
Notebook, Visual
Studio, Jboss,
Vmware, others)
DSDALANG03
SAS
DSADB03
NoSQL Databases
(Hbase,
MongoDB,
Cassandra, Redis,
Accumulo, etc.)
DSVIZ03
Online
visualization tools
(Datawrapper,
Google
Visualisation API,
Google Charts,
Flare, etc)
DSADM03
Data curation
platform,
metadata
management (ETL,
Curator's
Workbench,
DataUp, MIXED,
etc)
DSBDA03
Real time and
streaming
analytics systems
(Flume, Kafka,
Storm)
DSDEV03
Git versioning system
as a general platform
for software
development
DSDALANG04
Julia
DSADB 04
Hive (query
language for
Hadoop)
DSADM04
Backup and
storage
management
(iRODS, XArch,
Nesstar, others)
DSBDA04
Hadoop
Ecosystem/platfor
m
DSDEV04
Scrum agile software
development and
management
methodology and
platform
DSDALANG05
IBM SPSS
DSADB 05
Data Modeling
(UML, ERWin,
DDL, etc)
DSBDA05
Azure Data
Analytics
platforms
(HDInsight, APS
Source: EDISON Data Science Framework (2017)
Experienced leaders say otherwise
Like me they see the need to focus on “Softer” People Skills
8
So, I’ve developed a model
to explain the skills needed
Introducing a model to explain
the People Skills needed at each
stage for analysts or Data
Science teams to achieve impact
Sharing four pieces of that puzzle
In this talk I’ll introduce you to these parts of that Model
10
(1) Questioning to get to
the real business need
Socratic Questioning skills to get
beneath the request to what the
business really needs and how
what is delivered will be used.
The problem with requirements
12
Getting clarity on need not want
Practice using questions to get clarity on
what they need, not just what they want:
• Concept clarification questions
• Probing assumptions
• Probing rationale, reasons & evidence
• Questioning viewpoints & perspectives
• Probe implications & consequences
Socratic questioning
13
That’s all for now on Step 1
(3) Securing buy-in from
the key players
Identifying, prioritising and
managing stakeholder relationships
to ensure you manage expectations
& communicate/collaborate well.
Alexander Hamilton (American ‘Founding Father’ & abolitionist), 1755-1804
“Men often oppose a thing merely because they have
had no agency in planning it, or because it may
have been planned by those whom they dislike.”
16
Step 1: 360-degree MindMapping consider all those impacted
Focus using Stakeholder Mapping
17
IT
Developers
Business
Architect
Finance
BP
Compliance
Competitors
CMO
CEO
CIO CRO
NEDs
City
Analysts
Your
Managers
Chairman
Your
Analysts
CFO
Regulators
Market
Tech
Vendors
Gartner/
Forrester
Benchmarks
Consumer
Groups
Customers
COO
Finance
Peers
Risk
Peers
Marketing
Peers
You
Legal
Peers
Ops
Peers
IT
Peers
Teams
supplying
data
Teams
supporting
systems
External
data
suppliers
CX ManagersIT Managers
Finance
Managers
Risk
Managers
Legal
Managers
Finance
Teams
Risk Teams Legal Teams
IT
BP
Step 2: Prioritise those who need more of your time
Focus using Stakeholder Mapping
Step 3: Bring both tools together to decide where to act
Focus using Stakeholder Mapping
High Influence
Low Influence
High
Interest
Low
Interest
CMO
CEO
CIO CRO
CFO COO
Your
Managers
Your
Analysts
Business
Architect
IT
BP
Marketing
Peers
Teams
supplying
data
Finance
Teams
Compliance
Review all stakeholders
None on the Axes
Ruthless Prioritisation
Segment your stakeholders to better understand their styles
Flex your style to work for each Stakeholder
Spotting a Pioneer
Pioneer motto: Have
fun. It’s just work.
Spotting a Driver
Driver motto: And your
point is…?
Spotting an Integrator
Integrator motto:
Consensus Rules!
Spotting a Guardian
Guardian motto:
Changing the World, One
Spreadsheet at a Time
20 https://www2.deloitte.com/us/en/pages/operations/solutions/business-chemistry.html
How to map & segment your stakeholders to focus your efforts
Further guidance is available on my blog
21
That’s all for now on Step 3
(6) Generate insights to
understand behaviour
Generation of deeper insights
into motivation and triggers for
behaviour seen in analysis, using
structured questioning &
converging evidence.
Exploring further the context & considering what you don’t know
Generating Insight means asking questions
24
How do
Do we meetHow will we
How will we
communicate
Fig 2a
Datamine 7
How do
Do we meetHow will we
How will we
communicate
Fig 2a
Fig 2b
Converging evidence from four possible sources to spot themes
Generating Insight means convergence
25
Media and Technology Trends
Regulatory Environment
Socioeconomic Stats
Competitor Intelligence
Market Developments
Qualitative Research
Quantitative Studies
Tracking Studies
Meeting Customers F2F
Customer Complaints
Listening in at Call Centre
Those who meet customers
Sales, Customer &
Transactional data
Communication
Evaluations
Behavioural
Data
Environm
ent
Research
Custom
er
Connection
Customer Personas/Vox pops
Customer Experience Study
Market	Intel.	Team	
External	MI	Database
Data	Team	
Analysis	Team
Research	Team
Customer	facing	
Colleagues
Can use structured questioning techniques to build bridges
Customer Insight Generation workshops
26
Through the steps of an Insight Generation workshop, attendees are
building a bridge from the current customer behaviour to the desired
customer behaviour, via Analytical Thinking about deeper motivations…
BEHAVIOUR NOW
MOTIVATION
BEHAVIOUR THEN
WHY NOW WHY THEN
How to run an Insight Generation workshop
Further guidance is available on my blog
27
That’s all for now on Step 6
(9) Ensure action as a
result to deliver solution
Follow-up on recommendations and
influence key players to ensure
appropriate action that meets the
business need.
Plus, implement feedback loops so
you continue to learn from what
happens as a result of actions.
Ella Fitzgerald (American jazz singer), 1917-1996
“It isn't where you came from, it's where
you're going that counts.”
30
Where does your responsibility end?
A simple segmentation to consider adjusting your style
Face the Political Reality
32
CARR YING
READING
Politically aware
Politically unaware
Acting with
integrityPsychological
game-playing
Focus on action not outputs
Ensure request is for action
Design analysis to be actionable
Include recommended actions
Give progress updates on action
Measure effect of actions
Change your language
33
That’s all for now on Step 9
That’s your preview
Where might you need to
develop your People Skills to be
a more effective Analyst?
Take action in the next 2 weeks
Action-orientated learning
36
?
What one thing will you do differently (within the next 2 weeks) as a result of this webinar?
Further details are available
How to contact me…
37
@LaughlinPaul
+44 (0)7446 958061
linkedin.com/in/paullaughlin
paul@laughlinconsultancy.com
Any questions?

More Related Content

What's hot

Effective Staff Suggestion System (Kaizen Teian)
Effective Staff Suggestion System (Kaizen Teian)Effective Staff Suggestion System (Kaizen Teian)
Effective Staff Suggestion System (Kaizen Teian)
Flevy.com Best Practices
 
Best Practices - The Seven Most Important Success Factors
Best Practices - The Seven Most Important Success FactorsBest Practices - The Seven Most Important Success Factors
Best Practices - The Seven Most Important Success Factors
Richard Harbridge
 
The Datafication of HR: Graduating from Metrics to Analytics
The Datafication of HR: Graduating from Metrics to AnalyticsThe Datafication of HR: Graduating from Metrics to Analytics
The Datafication of HR: Graduating from Metrics to Analytics
Visier
 
Richard Harbridge: 7 SharePoint Success Factors
Richard Harbridge: 7 SharePoint Success FactorsRichard Harbridge: 7 SharePoint Success Factors
Richard Harbridge: 7 SharePoint Success Factors
SharePoint Saturday NY
 

What's hot (20)

A Playbook for Diversity Analytics and Strategy Development
A Playbook for Diversity Analytics and Strategy DevelopmentA Playbook for Diversity Analytics and Strategy Development
A Playbook for Diversity Analytics and Strategy Development
 
Building Partnership to Tell Great Stories
Building Partnership to Tell Great StoriesBuilding Partnership to Tell Great Stories
Building Partnership to Tell Great Stories
 
Effective Staff Suggestion System (Kaizen Teian)
Effective Staff Suggestion System (Kaizen Teian)Effective Staff Suggestion System (Kaizen Teian)
Effective Staff Suggestion System (Kaizen Teian)
 
People Analytics
People AnalyticsPeople Analytics
People Analytics
 
HR Analytics - A Pathway to Business Impact
HR Analytics - A Pathway to Business ImpactHR Analytics - A Pathway to Business Impact
HR Analytics - A Pathway to Business Impact
 
Workforce analytics, an introduction
Workforce analytics, an introductionWorkforce analytics, an introduction
Workforce analytics, an introduction
 
58 Quotes, Facts, Benchmarks, and Best Practices on People and Analytics
58 Quotes, Facts, Benchmarks, and Best Practices on People and Analytics58 Quotes, Facts, Benchmarks, and Best Practices on People and Analytics
58 Quotes, Facts, Benchmarks, and Best Practices on People and Analytics
 
People Analytics 2016 - Shareable
People Analytics 2016 - ShareablePeople Analytics 2016 - Shareable
People Analytics 2016 - Shareable
 
Best Practices - The Seven Most Important Success Factors
Best Practices - The Seven Most Important Success FactorsBest Practices - The Seven Most Important Success Factors
Best Practices - The Seven Most Important Success Factors
 
HWZ-Darden Konferenz: Building a Sustainable Analytics Orientation
HWZ-Darden Konferenz: Building a Sustainable Analytics OrientationHWZ-Darden Konferenz: Building a Sustainable Analytics Orientation
HWZ-Darden Konferenz: Building a Sustainable Analytics Orientation
 
A Primer on HR Analytics
A Primer on HR AnalyticsA Primer on HR Analytics
A Primer on HR Analytics
 
Today and how to succeed tomorrow
 - HR Analytics
Today and how to succeed tomorrow
 - HR AnalyticsToday and how to succeed tomorrow
 - HR Analytics
Today and how to succeed tomorrow
 - HR Analytics
 
Building higher quality explainable(XAI) models
Building higher quality explainable(XAI) modelsBuilding higher quality explainable(XAI) models
Building higher quality explainable(XAI) models
 
Hr analytics whywhathow
Hr analytics whywhathowHr analytics whywhathow
Hr analytics whywhathow
 
Toolkit For Security in the Enterprise
Toolkit For Security in the EnterpriseToolkit For Security in the Enterprise
Toolkit For Security in the Enterprise
 
Self-service Analytic for Business Users-19july2017-final
Self-service Analytic for Business Users-19july2017-finalSelf-service Analytic for Business Users-19july2017-final
Self-service Analytic for Business Users-19july2017-final
 
The Datafication of HR: Graduating from Metrics to Analytics
The Datafication of HR: Graduating from Metrics to AnalyticsThe Datafication of HR: Graduating from Metrics to Analytics
The Datafication of HR: Graduating from Metrics to Analytics
 
Ceb clc talent analytics quarterly q2 2017
Ceb clc talent analytics quarterly q2 2017Ceb clc talent analytics quarterly q2 2017
Ceb clc talent analytics quarterly q2 2017
 
Richard Harbridge: 7 SharePoint Success Factors
Richard Harbridge: 7 SharePoint Success FactorsRichard Harbridge: 7 SharePoint Success Factors
Richard Harbridge: 7 SharePoint Success Factors
 
Skills Management Best Practices Webinar
Skills Management Best Practices WebinarSkills Management Best Practices Webinar
Skills Management Best Practices Webinar
 

Similar to The Softer Skills that analysts need (beyond Data Visualisation)

Business analytics workshop presentation final
Business analytics workshop presentation   finalBusiness analytics workshop presentation   final
Business analytics workshop presentation final
Brian Beveridge
 

Similar to The Softer Skills that analysts need (beyond Data Visualisation) (20)

The Softer Skills analysts need to succeed in their careers
The Softer Skills analysts need to succeed in their careersThe Softer Skills analysts need to succeed in their careers
The Softer Skills analysts need to succeed in their careers
 
The Softer Skills Analysts need to make an impact
The Softer Skills Analysts need to make an impactThe Softer Skills Analysts need to make an impact
The Softer Skills Analysts need to make an impact
 
The People Skills analysts need to succeed in their careers
The People Skills analysts need to succeed in their careersThe People Skills analysts need to succeed in their careers
The People Skills analysts need to succeed in their careers
 
Data Leadership talk for CIIA March 2022.pdf
Data Leadership talk for CIIA March 2022.pdfData Leadership talk for CIIA March 2022.pdf
Data Leadership talk for CIIA March 2022.pdf
 
Do data leaders face unique challenges as leaders?
Do data leaders face unique challenges as leaders?Do data leaders face unique challenges as leaders?
Do data leaders face unique challenges as leaders?
 
Scanning of Business Analysis
Scanning of Business AnalysisScanning of Business Analysis
Scanning of Business Analysis
 
Everyday Data Science
Everyday Data ScienceEveryday Data Science
Everyday Data Science
 
Big Data LA 2016: Backstage to a Data Driven Culture
Big Data LA 2016: Backstage to a Data Driven CultureBig Data LA 2016: Backstage to a Data Driven Culture
Big Data LA 2016: Backstage to a Data Driven Culture
 
Success Through an Actionable Data Science Stack
Success Through an Actionable Data Science StackSuccess Through an Actionable Data Science Stack
Success Through an Actionable Data Science Stack
 
PPT1-Buss Intel Analytics.pptx
PPT1-Buss Intel  Analytics.pptxPPT1-Buss Intel  Analytics.pptx
PPT1-Buss Intel Analytics.pptx
 
Are you getting the most out of your data?
Are you getting the most out of your data?Are you getting the most out of your data?
Are you getting the most out of your data?
 
Fundamentals of Data Analytics Outline
Fundamentals of Data Analytics OutlineFundamentals of Data Analytics Outline
Fundamentals of Data Analytics Outline
 
Bersin by Deloitte - Demystifying Big Data
Bersin by Deloitte - Demystifying Big DataBersin by Deloitte - Demystifying Big Data
Bersin by Deloitte - Demystifying Big Data
 
My Mastery Journey Timeline
My Mastery Journey TimelineMy Mastery Journey Timeline
My Mastery Journey Timeline
 
Best Practices For GCC Analytics
Best Practices For GCC AnalyticsBest Practices For GCC Analytics
Best Practices For GCC Analytics
 
Structure Your Data Science Teams For Best Outcomes
Structure Your Data Science Teams For Best OutcomesStructure Your Data Science Teams For Best Outcomes
Structure Your Data Science Teams For Best Outcomes
 
How to sustain analytics capabilities in an organization
How to sustain analytics capabilities in an organizationHow to sustain analytics capabilities in an organization
How to sustain analytics capabilities in an organization
 
Giving Organisations new Capabilities to ask the Right Business Questions
Giving Organisations new Capabilities to ask the Right Business QuestionsGiving Organisations new Capabilities to ask the Right Business Questions
Giving Organisations new Capabilities to ask the Right Business Questions
 
Business analytics workshop presentation final
Business analytics workshop presentation   finalBusiness analytics workshop presentation   final
Business analytics workshop presentation final
 
Pluto7 - Tableau Webinar on enabling Organization to be Data Driven in 201...
Pluto7   -  Tableau Webinar on enabling Organization to be Data Driven in 201...Pluto7   -  Tableau Webinar on enabling Organization to be Data Driven in 201...
Pluto7 - Tableau Webinar on enabling Organization to be Data Driven in 201...
 

More from Paul Laughlin

Measuring your Marketing Effectiveness for Budget setting public
Measuring your Marketing Effectiveness for Budget setting publicMeasuring your Marketing Effectiveness for Budget setting public
Measuring your Marketing Effectiveness for Budget setting public
Paul Laughlin
 
Msms2015 adopting holistic customer insight public
Msms2015 adopting holistic customer insight publicMsms2015 adopting holistic customer insight public
Msms2015 adopting holistic customer insight public
Paul Laughlin
 
When customers don't act rationally v1.2
When customers don't act rationally v1.2When customers don't act rationally v1.2
When customers don't act rationally v1.2
Paul Laughlin
 

More from Paul Laughlin (17)

Big Data and Analytics in your Organisation talk.pdf
Big Data and Analytics in your Organisation talk.pdfBig Data and Analytics in your Organisation talk.pdf
Big Data and Analytics in your Organisation talk.pdf
 
Why Data Scientists are not the answer to your Customer Insight gaps
Why Data Scientists are not the answer to your Customer Insight gapsWhy Data Scientists are not the answer to your Customer Insight gaps
Why Data Scientists are not the answer to your Customer Insight gaps
 
Covid-19 dashboard 25 March 2020
Covid-19 dashboard 25 March 2020Covid-19 dashboard 25 March 2020
Covid-19 dashboard 25 March 2020
 
GDPR and Identity Management
GDPR and Identity ManagementGDPR and Identity Management
GDPR and Identity Management
 
How life-event data can improve & protect your marketing in a post-GDPR world
How life-event data can improve & protect your marketing in a post-GDPR worldHow life-event data can improve & protect your marketing in a post-GDPR world
How life-event data can improve & protect your marketing in a post-GDPR world
 
The Softer Skills that analysts need to help Creatives
The Softer Skills that analysts need to help CreativesThe Softer Skills that analysts need to help Creatives
The Softer Skills that analysts need to help Creatives
 
Softer Skills workshop for #DTS16 event in Edinburgh
Softer Skills workshop for #DTS16 event in EdinburghSofter Skills workshop for #DTS16 event in Edinburgh
Softer Skills workshop for #DTS16 event in Edinburgh
 
Customer Insight & Conduct Risk
Customer Insight & Conduct RiskCustomer Insight & Conduct Risk
Customer Insight & Conduct Risk
 
Presentation at Big Data & Analytics for Insurance 2016
Presentation at Big Data & Analytics for Insurance 2016Presentation at Big Data & Analytics for Insurance 2016
Presentation at Big Data & Analytics for Insurance 2016
 
Measuring your Marketing Effectiveness for Budget setting public
Measuring your Marketing Effectiveness for Budget setting publicMeasuring your Marketing Effectiveness for Budget setting public
Measuring your Marketing Effectiveness for Budget setting public
 
Msms2015 adopting holistic customer insight public
Msms2015 adopting holistic customer insight publicMsms2015 adopting holistic customer insight public
Msms2015 adopting holistic customer insight public
 
Less jargon, fewer bonuses, more loyalty
Less jargon, fewer bonuses, more loyaltyLess jargon, fewer bonuses, more loyalty
Less jargon, fewer bonuses, more loyalty
 
Behavioural economics for The Financial Services Forum members conference 2015
Behavioural economics for The Financial Services Forum members conference 2015Behavioural economics for The Financial Services Forum members conference 2015
Behavioural economics for The Financial Services Forum members conference 2015
 
Introduction to Laughlin Consultancy
Introduction to Laughlin ConsultancyIntroduction to Laughlin Consultancy
Introduction to Laughlin Consultancy
 
Marketing Effectiveness Measurement replaces Budget Envy
Marketing Effectiveness Measurement replaces Budget EnvyMarketing Effectiveness Measurement replaces Budget Envy
Marketing Effectiveness Measurement replaces Budget Envy
 
When customers don't act rationally v1.2
When customers don't act rationally v1.2When customers don't act rationally v1.2
When customers don't act rationally v1.2
 
Gain Deeper Insights: Using analytics and research to generate insights
Gain Deeper Insights: Using analytics and research to generate insightsGain Deeper Insights: Using analytics and research to generate insights
Gain Deeper Insights: Using analytics and research to generate insights
 

Recently uploaded

會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文
會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文
會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文
中 央社
 
Poster_density_driven_with_fracture_MLMC.pdf
Poster_density_driven_with_fracture_MLMC.pdfPoster_density_driven_with_fracture_MLMC.pdf
Poster_density_driven_with_fracture_MLMC.pdf
Alexander Litvinenko
 

Recently uploaded (20)

Andreas Schleicher presents at the launch of What does child empowerment mean...
Andreas Schleicher presents at the launch of What does child empowerment mean...Andreas Schleicher presents at the launch of What does child empowerment mean...
Andreas Schleicher presents at the launch of What does child empowerment mean...
 
philosophy and it's principles based on the life
philosophy and it's principles based on the lifephilosophy and it's principles based on the life
philosophy and it's principles based on the life
 
UChicago CMSC 23320 - The Best Commit Messages of 2024
UChicago CMSC 23320 - The Best Commit Messages of 2024UChicago CMSC 23320 - The Best Commit Messages of 2024
UChicago CMSC 23320 - The Best Commit Messages of 2024
 
Exploring Gemini AI and Integration with MuleSoft | MuleSoft Mysore Meetup #45
Exploring Gemini AI and Integration with MuleSoft | MuleSoft Mysore Meetup #45Exploring Gemini AI and Integration with MuleSoft | MuleSoft Mysore Meetup #45
Exploring Gemini AI and Integration with MuleSoft | MuleSoft Mysore Meetup #45
 
diagnosting testing bsc 2nd sem.pptx....
diagnosting testing bsc 2nd sem.pptx....diagnosting testing bsc 2nd sem.pptx....
diagnosting testing bsc 2nd sem.pptx....
 
How to Manage Closest Location in Odoo 17 Inventory
How to Manage Closest Location in Odoo 17 InventoryHow to Manage Closest Location in Odoo 17 Inventory
How to Manage Closest Location in Odoo 17 Inventory
 
Implanted Devices - VP Shunts: EMGuidewire's Radiology Reading Room
Implanted Devices - VP Shunts: EMGuidewire's Radiology Reading RoomImplanted Devices - VP Shunts: EMGuidewire's Radiology Reading Room
Implanted Devices - VP Shunts: EMGuidewire's Radiology Reading Room
 
會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文
會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文
會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文會考英文
 
Stl Algorithms in C++ jjjjjjjjjjjjjjjjjj
Stl Algorithms in C++ jjjjjjjjjjjjjjjjjjStl Algorithms in C++ jjjjjjjjjjjjjjjjjj
Stl Algorithms in C++ jjjjjjjjjjjjjjjjjj
 
Including Mental Health Support in Project Delivery, 14 May.pdf
Including Mental Health Support in Project Delivery, 14 May.pdfIncluding Mental Health Support in Project Delivery, 14 May.pdf
Including Mental Health Support in Project Delivery, 14 May.pdf
 
An overview of the various scriptures in Hinduism
An overview of the various scriptures in HinduismAn overview of the various scriptures in Hinduism
An overview of the various scriptures in Hinduism
 
Poster_density_driven_with_fracture_MLMC.pdf
Poster_density_driven_with_fracture_MLMC.pdfPoster_density_driven_with_fracture_MLMC.pdf
Poster_density_driven_with_fracture_MLMC.pdf
 
Book Review of Run For Your Life Powerpoint
Book Review of Run For Your Life PowerpointBook Review of Run For Your Life Powerpoint
Book Review of Run For Your Life Powerpoint
 
When Quality Assurance Meets Innovation in Higher Education - Report launch w...
When Quality Assurance Meets Innovation in Higher Education - Report launch w...When Quality Assurance Meets Innovation in Higher Education - Report launch w...
When Quality Assurance Meets Innovation in Higher Education - Report launch w...
 
24 ĐỀ THAM KHẢO KÌ THI TUYỂN SINH VÀO LỚP 10 MÔN TIẾNG ANH SỞ GIÁO DỤC HẢI DƯ...
24 ĐỀ THAM KHẢO KÌ THI TUYỂN SINH VÀO LỚP 10 MÔN TIẾNG ANH SỞ GIÁO DỤC HẢI DƯ...24 ĐỀ THAM KHẢO KÌ THI TUYỂN SINH VÀO LỚP 10 MÔN TIẾNG ANH SỞ GIÁO DỤC HẢI DƯ...
24 ĐỀ THAM KHẢO KÌ THI TUYỂN SINH VÀO LỚP 10 MÔN TIẾNG ANH SỞ GIÁO DỤC HẢI DƯ...
 
Đề tieng anh thpt 2024 danh cho cac ban hoc sinh
Đề tieng anh thpt 2024 danh cho cac ban hoc sinhĐề tieng anh thpt 2024 danh cho cac ban hoc sinh
Đề tieng anh thpt 2024 danh cho cac ban hoc sinh
 
The Ball Poem- John Berryman_20240518_001617_0000.pptx
The Ball Poem- John Berryman_20240518_001617_0000.pptxThe Ball Poem- John Berryman_20240518_001617_0000.pptx
The Ball Poem- John Berryman_20240518_001617_0000.pptx
 
Dementia (Alzheimer & vasular dementia).
Dementia (Alzheimer & vasular dementia).Dementia (Alzheimer & vasular dementia).
Dementia (Alzheimer & vasular dementia).
 
Benefits and Challenges of OER by Shweta Babel.pptx
Benefits and Challenges of OER by Shweta Babel.pptxBenefits and Challenges of OER by Shweta Babel.pptx
Benefits and Challenges of OER by Shweta Babel.pptx
 
Capitol Tech Univ Doctoral Presentation -May 2024
Capitol Tech Univ Doctoral Presentation -May 2024Capitol Tech Univ Doctoral Presentation -May 2024
Capitol Tech Univ Doctoral Presentation -May 2024
 

The Softer Skills that analysts need (beyond Data Visualisation)

  • 1. Paul Laughlin, Host of Customer Insight Leader podcast & Founder of Laughlin Consultancy The other Softer Skills analysts need Beyond the importance of data visualisation skills for analysts
  • 2. Client-side to Agency-side Created and lead data & analytics teams, for all general & life insurance businesses across Lloyds Bank Group, over 13 years. Added over £11m incremental profit to bottom line annually. Developed team of 44 analysts & mentored future leaders. My Career Journey “Helping exceptional teams master the people side of analytics” 2
  • 3. 3
  • 4. 4
  • 5. Customer Analytics delivers ROI Research & my own experience confirm analytics delivers profit 5
  • 6. To achieve that needs Commercial Focus Data & Analytics leaders confirm relevance trumps sophistication 6
  • 7. There’s a focus on developing skills needed But all too often that focus is solely on Technical Skills 7 EDSF Release 2: Part 1. Data Science Competence Framework (CF-DS) Table 4.2. Identified Data Science skills related to the main Data Science competence groups SDSDA Data Science Analytics SDSENG Data Science Engineering SDSDM Data Management SDSRM Research Methods and Project Management SDSBA Business Analytics SDSDA01 Use Machine Learning technology, algorithms, tools (including supervised, unsupervised, or reinforced learning) SDSENG01 Use systems and software engineering principles to organisations information system design and development, including requirements design SDSDM01 Specify, develop and implement enterprise data management and data governance strategy and architecture, including Data Management Plan (DMP) SDSRM01 Use research methods principles in developing data driven applications and implementing the whole cycle of data handling SDSBA01 and Business Intelligence (BI) methods for data analysis; apply cognitive technologies and relevant services SDSDA02 Use Data Mining techniques SDSENG02 Use Cloud Computing technologies and cloud powered services design for data infrastructure and data handling services SDSDM02 Data storage systems, data archive services, digital libraries, and their operational models SDSRM02 Design experiment, develop and implement data collection process SDSBA02 Apply Business Processes Management (BPM), general business processes and operations for organisational processes analysis/modelling SDSDA03 Use Text Data Mining techniques SDSENG03 Use cloud based Big Data technologies for large datasets processing systems and applications SDSDM03 Define requirements to and supervise implementation of the hybrid data management infrastructure, including enterprise private and public cloud resources and services SDSRM03 Apply data lifecycle management model to data collection and data quality evaluation SDSBA03 Apply Agile Data Driven methodologies, processes and enterprises SDSDA04 Apply Predictive Analytics methods SDSENG04 Use agile development technologies, such as DevOps and continuous improvement cycle, for data driven applications SDSDM04 Develop and implement data architecture, data types and data formats, data modeling and design, including related technologies (ETL, OLAP, SDSRM04 Apply structured approach to use cases analysis SDSBA04 Use Econometrics for data analysis and applications EDSF Release 2: Part 1. Data Science Competence Framework (CF-DS) Table 4.3. Required skills related to analytics languages, tools, platforms and Big Data infrastructure 6 DSDALANG Data Analytics and Statistical languages and tools DSADB Databases and query languages DSVIZ Data/Applicatio ns visualization DSADM Data Management and Curation platform DSBDA Big Data Analytics platforms DSDEV Development and project management frameworks, platforms and tool DSDALANG01 R and data analytics libraries (cran, ggplot2, dplyr, reshap2, etc.) DSADB01 SQL and relational databases (open source: PostgreSQL, mySQL, Nettezza, etc.) DSVIZ01 Data visualization Libraries (mathpoltlib, seaborn, D3.js, FusionCharts, Chart.js, other) DSADM01 Data modelling and related technologies (ETL, OLAP, OLTP, etc.) DSBDA01 Big Data and distributed computing tools (Spark, MapReduce, Hadoop, Mahout, Lucene, NLTK, Pregel, etc.) DSDEV01 Frameworks: Python, Java or C/C++, AJAX (Asynchronous Javascript and XML), D3.js (Data-Driven Documents), jQuery, others DSDALANG02 Python and data analytics libraries (pandas, numpy, mathplotlib, scipy, scikit-learn, seaborn, etc.) DSADB02 SQL and relational databases (proprietary: Oracle, MS SQL Server, others) DSVIZ02 Visualisation software (D3.js, Processing, Tableau, Raphael, Gephi, etc.) DSADM02 Data Warehouse platform and related tools DSBDA02 Big Data Analytics platforms (Hadoop, Spark, Data Lakes, others) DSDEV02 Python, Java or C/C++ Development platforms/IDE (Eclipse, R Studio, Anaconda/Jupyter Notebook, Visual Studio, Jboss, Vmware, others) DSDALANG03 SAS DSADB03 NoSQL Databases (Hbase, MongoDB, Cassandra, Redis, Accumulo, etc.) DSVIZ03 Online visualization tools (Datawrapper, Google Visualisation API, Google Charts, Flare, etc) DSADM03 Data curation platform, metadata management (ETL, Curator's Workbench, DataUp, MIXED, etc) DSBDA03 Real time and streaming analytics systems (Flume, Kafka, Storm) DSDEV03 Git versioning system as a general platform for software development DSDALANG04 Julia DSADB 04 Hive (query language for Hadoop) DSADM04 Backup and storage management (iRODS, XArch, Nesstar, others) DSBDA04 Hadoop Ecosystem/platfor m DSDEV04 Scrum agile software development and management methodology and platform DSDALANG05 IBM SPSS DSADB 05 Data Modeling (UML, ERWin, DDL, etc) DSBDA05 Azure Data Analytics platforms (HDInsight, APS Source: EDISON Data Science Framework (2017)
  • 8. Experienced leaders say otherwise Like me they see the need to focus on “Softer” People Skills 8
  • 9. So, I’ve developed a model to explain the skills needed Introducing a model to explain the People Skills needed at each stage for analysts or Data Science teams to achieve impact
  • 10. Sharing four pieces of that puzzle In this talk I’ll introduce you to these parts of that Model 10
  • 11. (1) Questioning to get to the real business need Socratic Questioning skills to get beneath the request to what the business really needs and how what is delivered will be used.
  • 12. The problem with requirements 12
  • 13. Getting clarity on need not want Practice using questions to get clarity on what they need, not just what they want: • Concept clarification questions • Probing assumptions • Probing rationale, reasons & evidence • Questioning viewpoints & perspectives • Probe implications & consequences Socratic questioning 13
  • 14. That’s all for now on Step 1
  • 15. (3) Securing buy-in from the key players Identifying, prioritising and managing stakeholder relationships to ensure you manage expectations & communicate/collaborate well.
  • 16. Alexander Hamilton (American ‘Founding Father’ & abolitionist), 1755-1804 “Men often oppose a thing merely because they have had no agency in planning it, or because it may have been planned by those whom they dislike.” 16
  • 17. Step 1: 360-degree MindMapping consider all those impacted Focus using Stakeholder Mapping 17 IT Developers Business Architect Finance BP Compliance Competitors CMO CEO CIO CRO NEDs City Analysts Your Managers Chairman Your Analysts CFO Regulators Market Tech Vendors Gartner/ Forrester Benchmarks Consumer Groups Customers COO Finance Peers Risk Peers Marketing Peers You Legal Peers Ops Peers IT Peers Teams supplying data Teams supporting systems External data suppliers CX ManagersIT Managers Finance Managers Risk Managers Legal Managers Finance Teams Risk Teams Legal Teams IT BP
  • 18. Step 2: Prioritise those who need more of your time Focus using Stakeholder Mapping
  • 19. Step 3: Bring both tools together to decide where to act Focus using Stakeholder Mapping High Influence Low Influence High Interest Low Interest CMO CEO CIO CRO CFO COO Your Managers Your Analysts Business Architect IT BP Marketing Peers Teams supplying data Finance Teams Compliance Review all stakeholders None on the Axes Ruthless Prioritisation
  • 20. Segment your stakeholders to better understand their styles Flex your style to work for each Stakeholder Spotting a Pioneer Pioneer motto: Have fun. It’s just work. Spotting a Driver Driver motto: And your point is…? Spotting an Integrator Integrator motto: Consensus Rules! Spotting a Guardian Guardian motto: Changing the World, One Spreadsheet at a Time 20 https://www2.deloitte.com/us/en/pages/operations/solutions/business-chemistry.html
  • 21. How to map & segment your stakeholders to focus your efforts Further guidance is available on my blog 21
  • 22. That’s all for now on Step 3
  • 23. (6) Generate insights to understand behaviour Generation of deeper insights into motivation and triggers for behaviour seen in analysis, using structured questioning & converging evidence.
  • 24. Exploring further the context & considering what you don’t know Generating Insight means asking questions 24 How do Do we meetHow will we How will we communicate Fig 2a Datamine 7 How do Do we meetHow will we How will we communicate Fig 2a Fig 2b
  • 25. Converging evidence from four possible sources to spot themes Generating Insight means convergence 25 Media and Technology Trends Regulatory Environment Socioeconomic Stats Competitor Intelligence Market Developments Qualitative Research Quantitative Studies Tracking Studies Meeting Customers F2F Customer Complaints Listening in at Call Centre Those who meet customers Sales, Customer & Transactional data Communication Evaluations Behavioural Data Environm ent Research Custom er Connection Customer Personas/Vox pops Customer Experience Study Market Intel. Team External MI Database Data Team Analysis Team Research Team Customer facing Colleagues
  • 26. Can use structured questioning techniques to build bridges Customer Insight Generation workshops 26 Through the steps of an Insight Generation workshop, attendees are building a bridge from the current customer behaviour to the desired customer behaviour, via Analytical Thinking about deeper motivations… BEHAVIOUR NOW MOTIVATION BEHAVIOUR THEN WHY NOW WHY THEN
  • 27. How to run an Insight Generation workshop Further guidance is available on my blog 27
  • 28. That’s all for now on Step 6
  • 29. (9) Ensure action as a result to deliver solution Follow-up on recommendations and influence key players to ensure appropriate action that meets the business need. Plus, implement feedback loops so you continue to learn from what happens as a result of actions.
  • 30. Ella Fitzgerald (American jazz singer), 1917-1996 “It isn't where you came from, it's where you're going that counts.” 30
  • 31. Where does your responsibility end?
  • 32. A simple segmentation to consider adjusting your style Face the Political Reality 32 CARR YING READING Politically aware Politically unaware Acting with integrityPsychological game-playing
  • 33. Focus on action not outputs Ensure request is for action Design analysis to be actionable Include recommended actions Give progress updates on action Measure effect of actions Change your language 33
  • 34. That’s all for now on Step 9
  • 35. That’s your preview Where might you need to develop your People Skills to be a more effective Analyst?
  • 36. Take action in the next 2 weeks Action-orientated learning 36 ? What one thing will you do differently (within the next 2 weeks) as a result of this webinar?
  • 37. Further details are available How to contact me… 37 @LaughlinPaul +44 (0)7446 958061 linkedin.com/in/paullaughlin paul@laughlinconsultancy.com
  • 38.