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Using Lean Principles to Manage the Data Value Chain
Mario Faria Twitter: @mariofaria Head and Chief Data Officer CDO, Inc. http://www.cdo-inc.com/
Track: Data Quality, Data Governance Industry:
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About Mario Faria
• Mario was one of the first Chief Data Officers in the world
• Acting as a CDO for the last 5 years in North America, South America, Europe and Asia
• Passion : Bring order to the chaos
• Leader of teams working in Analytics, Data Monetization, Data Quality, Data Governance, Operations and Business Architecture
• Motto: “If you do not treat people, technology and data as economic assets, they will become liabilities”
Mario Faria Twitter: @mariofaria Head and Chief Data Officer CDO, Inc. http://www.cdo-inc.com/
Managing your most important asset to
drive business performance
In May 1915, The Boston Red Sox Babe Ruth pitching debut and his first home run, but …
The Rex Sox lost to the NY Yanks
Your data strategy is a journey
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The 3 Architectures a Company needs to succeed
Business Architecture
Technology Architecture
Data Architecture
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Data & Analytics Responsibilities • Data Strategy • Data Governance • Data Quality • Data Analytics • Data Insights • Data Architecture • Data Acquisitions • Data Operations • Data Policies • Data Security • Data Protection
A data & analyGcs team is responsible for transforming data assets into compeGGve
insights, that will drive business decisions and acGons, using people, processes and
technologies
Data teams build the bridge between business
and IT
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A data product allows an objective to be achieved using data & analytics
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More and more, leaders are being hired to think strategically about all the steps, from getting raw data and making it useful to the
business users
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Chief Data Officer (focused on data management)
Chief Digital Officer (focused on digital transforma8on)
Chief Analy8cs Officer (focused on decision management ini8a8ves)
The ul8mate leader who creates and executes digital, data and analy8cs strategies to drive business value
Copyright: Mario Faria 2014
The Chief Data / AnalyGcs / Digital Officer roles
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A few lessons I have learned to become a data and analytics expert
• Many problems with streamlining a data strategy • Major concerns with data management • How you can overcome the issues • What I have learned from several data journeys
The Data Life
Cycle
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The Data Value Chain
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A few problems in most organizations
• Data is fragmented and scattered • Silos of information hanging around • Like the truth, data has many versions • The Data Lifecycle is a complex process • Data projects being managed by IT • A formal process to data management is
a requirement in order to do Analytics
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Data is an abstract concept
Using Supply Chain Concepts and Techniques to manage your data assets
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Data & Analytics as a Production System
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The Deming Model : Production Viewed as a System
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What is Data Quality ?
• Quality is a customer perception • A few dimensions: freshness, coverage,
completeness, accuracy • It is a never ending job
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A Few Quality Programs
TDQM
TIQM
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Source: Dan Myers, The Value of Using the Dimensions of Data Quality, Information Management
Implementing Lean Best Practices that came from the
Toyota Manufacturing Process
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Toyota Production System
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Lean Goals
• Improve quality • Eliminate waste • Reduce lead time • Reduce total costs
It is about how behaviors, processes and actions can be changed for improving the
overall system
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The 8-Basics of Kaizen Based Lean Manufacturing,
by Bill Gaw
http://bbasicsllc.com/
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• Specify the value desired by the customer • Map the data value stream • Reengineer your data processes to eliminate waste • Introduce “pull” • Strive for continuous improvement
Source : Meghann Wooster, Beyond Fire Drills: Applying Lean Principles to Information Governance, http://www.cmswire.com/cms/information-management/beyond-fire-drills-applying-lean-principles-to-information-governance-023705.php
Applying Lean Principles to Information Governance
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• Data & Analysis are becoming products • Quality is key to success • Data explosion in volume, variety and
velocity • The number and value of external data
sets are rising fast • Focus your team efforts is crucial • Leverage technology to implement a
distributed data value chain initiative
Why Building a Distributed Data Value Chain is Critical
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The Predictive Analytics Factory Concept
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Data Value Chain Monitoring Centers
Right People Right Data
Right Technology
Without proper Data Quality principles, it is impossible to achieve the goals of increasing
revenue, reducing costs or gaining operaGonal efficiency in the
business areas
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Problems with Data Quality • Business people don’t understand it and don’t have time
or patience • IT people still have a technology mindset • Data & Analytics people make it more complex than it is
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Quality is about customer perception
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What you can do : Establish a customer oriented mentality within
your team
How did some
organizaGons change to a data driven culture ?
Make Everyone in the organization
feel responsible for Data Quality
How prepared is your business to have a lean data quality program in place ?
Time
People
Technology
Some bonus tips and
recommendations
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Start where it hurts the most
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Learn from mistakes
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Be flexible and adapt to changes fast
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Source : Leading Strategic Initiatives (www.leadingstrategicinitiatives.com)
Conclusions
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Data, Information, Analytics, Business Intelligence and Performance Management
“The Data Asset: How Smart Companies Govern Their Data For Business Success” - by Tony Fisher
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• A good CDO can implement a data organization with success
• A great CDO has the ability to turn raw data into new revenue streams for the business
• Components such as technology and methodologies are important, but they are just enablers
• The CDO focus is delivering enterprise value to the business (not writing code or SQL scripts)
From good to great CDO
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How leaders can benefit from using Lean for Data Quality programs
• Increase of productivity • Increase throughput • Improve of quality • Reduce of cycle times • Less fire-fighting • Smooth operation • Reduce costs
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Golden Rules to Success in Data Quality
• Find out the Why • Strategic vision and a plan in place • Strong Data Quality leader • Secure investments and budget • Always deliver results
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Future of Data Quality
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When was the last time ?
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“Continuous improvement is not about the things you do well — that’s work. Continuous improvement is about removing the things that get in the way of your work. The headaches, the things that slow you down, that’s what continuous improvement is all about.”
Bruce Hamilton , lean thought leader
Mario Faria http://www.cdo-inc.com www.slideshare.com/fariamario Twitter : @mariofaria [email protected] +1 (425) 628-3517