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Acting on Analytics

Building a Data-Driven Enterprise

Sept 11th, 2013

Mario Faria

http://www.linkedin.com/in/mariofaria/ www.slideshare.com/fariamario

Twitter : @mariofaria

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Who am I ?

•  MIT recognition as one of the 1st Chief Data Officers and Data Scientist

Leaders in the world (just Google “Mario Faria Chief Data Officer”) •  20+ years working with Information Technology, Management

Consulting, Financial Services, Retail, CPG and Private Equity •  Proven expertise in Data Management, Data Science, Analytics, CRM

and Supply Chain Management •  Speaker at several conferences on the subject in USA, Europe and Latin

America •  Contributor to magazines and publications •  Big Data Advisor at the Bill and Melinda Gates Foundation •  Member of the MIT Data Science Initiative •  Helping companies cross the Big Data Chasm

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Objectives

•  Clarify Analytics •  Present some analytics terms that will help professionals

do their jobs better •  Provide insights on how you should successfully create a

data & analytics organization •  Present some concepts to help you prepare to implement a

data-driven organization •  Bring some attention on how to properly use data •  Show a few options available for your professional future

in today’s world

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Where we stand today

•  Fragmented technology ecosystem •  Over usage of the Big Data term •  The “how to compete on analytics” is still

hard to achieve •  In most companies, data is still managed

with an IT mind set

Big  Data  will    fade  away    to  Analy1cs  

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Analytics is transforming data assets into

competitive insights, that will drive business

decisions and actions, using people, processes

and technologies

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People

Data Management

Domain Expertise

Statistics

On Analytics

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Data, Information, Analytics, Business Intelligence and Performance Management

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The Hawthorne Effect (1924-1933), at a Western Electric factory outside Chicago

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“Measurement drives behavior, and if we don’t understand how, it drives

behaviors in mysterious ways”

by Frank Buytendijk, Beingfrank Research, Sept 2012

1.  Understand the decision making process 2.  Understand what the many frameworks in

measurement do for us 3.  Understand what can go wrong 4.  Understand the culture

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Data is the oil of the 21st century

 Data  access  is  quite  easy  to  

achieve    

Transforming  data  into  something  useful  in  a  1mely  

manner  is  tough      

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The 5 Steps from Data to Decisions

Souce : Aryng Analytics Consulting

Data  Science      

The  process  of  taking  raw  data,  producing  informa1on  from  data,  and  using  this  informa1on  to  guide  ac1ons  that  will  bring  financial  benefits  to  business  

Data  Mining  is  the  explora1on  and  analysis  of  large  quan11es  of  data  to  discover  

meaningful  paCerns    and  rules  

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Source : Dr.Saed Sayad

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The Data Mining Goals •  Explain the past •  Predict the future

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The Data Mining Process

1.  Project definition 2.  Data exploration 3.  Data preparation 4.  Model creation 5.  Model deployment 6.  Model management

Machine  learning,  part  of  ar1ficial  intelligence,  is  about  the  construc1on  and  study  of  systems  

that  can  learn  from  data  

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Machine Learning is the "Field of study that gives computers the

ability to learn without being explicitly programmed"

Arthur Samuel, 1959

Machine  Learning  is  about  predic1on  and  learning  

from  data    

Data  Mining  is  about    finding  unknown  proper1es  

of  the  data    

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Deep X Operational Analytics

•  Deep Analytics –  Few users –  Complex queries –  Worried about response time –  Dedicated data marts

•  Operational Analytics –  Lots users –  Simple queries –  Worried about throughput –  Real time data flow

It takes more than just

data and analytics for results to be

achieved

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The 3 Architectures a Company needs to succeed

Business Architecture

Technology Architecture

Data Architecture

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The Data Value Chain

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Chief Data Officer / Chief Analytics Officer Data Architect

Data Quality

Data Scientist

Data Governance Data Operations

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The roles of an Analytics organization

A data scientist is the one who looks for insights

The insight is operationalized in BI/DW products, by data architects

The insight is shared with the enterprise The Chief Data/Analytics Officer is the

executive responsible and accountable for the data life cycle inside the organization, managing the people involved in the data activities, such as acquisitions, analytics,

processes, governance, quality, technology and budget

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A Chief Data/Analytics Officer is

the executive responsible to

manage these areas

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The Best of the Breed Data & Analytics Leader

•  Knows how to talk business with business people; technology with techies

•  Runs his/her team as a business unit

•  Has multi-discipline skilled people (technologists, mathematicians, statisticians, business people as well)

•  Manages quite well the back office and front office functions

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The checklist to hire data & analytics professionals

Chami Akmeemana Managing Director

Huntel Global

•  Where are they ? Think global •  What are they interested in ? It is not just

money, it is the possibility to “create” something new or transform

•  What are they going to do ? Gain clarity on

your business analytics strategy

•  What are they going to work with ? Set budget for technology tools, data acquisition and other resources needed

Link to download the full paper : http://goo.gl/Fc8Xl

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From good to great, an analytics team must have:

•  Passion for analytics and data •  Never stop learning •  Always be there for tough analytics

questions •  Ask questions until everything makes sense

and you are satisfied with the answers and analyses

•  Learn how to develop prototypes quickly •  Be an advocate for building a strong

foundation in corporate analytics •  Be a "bridge builder" between IT and

business users

How  to  promote  Business  Maturity  through  Analy1cs  ?  

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Analytic Maturity Curve

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The Four Types of Analytics

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Data and Analytics professionals are not helping others to understand it

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Is it possible to promote Business Maturity using Analytics, or is it the other way around?

•  Your company must have some Business Maturity to take a step and start using Analytics.

•  When you if take the path of using the right people, good technology, proven methodologies and changing the current processes, you will gain more Business Maturity.

•  After you have gained more Business Maturity, naturally you will start to evolve to more complex Analytics usage

•  It is a self-promoting system following exactly the Deming PDCA method

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The 3 ingredients to make Advanced Analytics work

•  Choosing the right data and managing multiple data sources

•  Having the capability to build advanced models that turn the data into insights

•  Management must undertake a transformational-change program so that the insights translate into effective action

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Managing an Analytics project

•  Focus on the execution •  Well-defined and realistic scope •  Put all activities on the schedule •  Budget control

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Technology alone will not change the previous results

To succeed in Analytics, an organization will be required to change some of its current internal processes

Good  KPIs  will  not  save  your  business,  but  they  will  be  able  to  tell  how  

screwed-­‐up  your  business  is  

Conclusions  

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Which companies will thrive in the near future ?

•  The ones which will understand how to adapt faster to this new scenario

•  The ones which will have successful Analytics implementations

•  The ones with great human capital, which understand how to leverage their resources and with proven methodologies to embrace this change

Is your company going to lead, influence or

follow when using data and analytics to drive results ?

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Lessons to Analytical Success

•  People •  Change Management (on going program) •  Culture •  Organization Model •  Processes •  Architecture •  and Analytics, of course

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“Successful people shoot for the stars, put their hearts on the line in every battle, and ultimately discover that the lessons learned from the

pursuit of excellence mean much more than the immediate

trophies and glory” Josh Waitzkin, The Art of

Learning

Q&A

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Thank you Mario Faria Chief Data Officer and Analytics Strategy Advisor http://www.linkedin.com/in/mariofaria/ Founder of the Digital Mad Men www.slideshare.com/fariamario Twitter : @mariofaria fariamario@hotmail.com +1 (425) 628-3517