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Be Certain, Be Trillium Certain
© Harte Hanks Trillium Software 2012
Session 2
Lean Mean
Data Governance Machine
Kiran Gill, Senior Strategic Consultant, Trillium Software
1
© Harte Hanks Trillium Software 2012
Introduction and Overview
Waste Elimination – 7 Wastes
(TIMWOOD)
Transportation
Inventory
Motion
Waiting
Over processing
Overproduction
Defects
Turning an Approach into Reality
The Lean Mean Data Governance Machine
Overview
2
© Harte Hanks Trillium Software 2012
What is
LEAN Data
Governance?
5. Convergence
of 7 wastes, 5
Lean Principles
and 5 Data
Governance
Disciplines
1. Focus on the
Internal data
Customer
4. Delivery of
flexible,
perfected,
value added
outputs to the
internal
customers.
2. Optimisation
of Classic
Governance
using Lean
Principles
3. Minimise,
eliminate and
prevent waste
in Data
Management
3
© Harte Hanks Trillium Software 20124
© Harte Hanks Trillium Software 2012
Lean
Methodologies
5
© Harte Hanks Trillium Software 2012
Lean Data Governance
Waste Elimination
Taiichi Ohno’s 7 Wastes (TIMWOOD)
Example applications
Adopt and adapt the approach
Waste definitions unique to the business
No wrong/right definition
6
© Harte Hanks Trillium Software 2012
Lean Data Governance
Case Study: Luxury Fashion label
Existence of some governance processes – no definition
Data from multiple sources
Many risks as a result of bad practice
No ownership or awareness
Working in silos
Wastage occurring across the enterprise
© Harte Hanks Trillium Software 2012
Transportation:
Waste during transportation to end destination
Assess Transportation within Process, Technology, People and Data Management
T I M W O O D
Risk: Excessive transportation =
increased error and degradation
Map and Review
Assess tools and technology
Eliminate unnecessary data transfer –
refine the process
8
© Harte Hanks Trillium Software 2012
Inventory:
Responding to the pull of the customer ensures minimal Inventory
T I M W O O D
Risk: Using incorrect data to drive
decisions. Resource utilisation
Evaluate internal processes
Identify and eliminate excess data
Identify critical data
Avoid generating surplus data at source
Review roles and purpose
9
© Harte Hanks Trillium Software 2012
Motion:
Motion refers to the movement within a process.
T I M W O O D
Risk: Introduction of error during
transit. Resource/time wastage.
Process review - movement,
manipulation and interrogation
Reliable technology
Intuitive data management with less
stages
Assess people movement –
unnecessary process e.g. workarounds
10
© Harte Hanks Trillium Software 2012
Waiting:
Waiting is a common waste
This can be easily avoided
T I M W O O D
Risk: Introduction of
workarounds, errors and delays.
Tool functionality
Reliable technology
Review process and eliminate gaps
Prioritise resolution activity
Introduce new processes and eliminate
old ones. E.g. Issues Management tools
11
© Harte Hanks Trillium Software 2012
Over Processing:
Processes that do not add value
Correlates with the identification and creation of value streams in the 5 Principles of Lean
T I M W O O D
Risk: Deterioration of data quality
and integrity. Increased errors
Key stages of data journey by process.
Regular review of business rules -
central access to definitions
Establish schedule and scope of
cleanse
Build archiving rules and processes
12
© Harte Hanks Trillium Software 2012
Overproduction:
Excessive production of data or information
Wait for the internal data customer demand in order to prevent waste
T I M W O O D
Risk: Duplicated effort. Using
obsolete data
Define owners - manage outputs
Define process for creation of new
output
Review data capture
Introduce central tools - automate e.g.
dashboards
13
© Harte Hanks Trillium Software 2012
Defects:
Defects spread to the entire organisation
Defective data and processes have a negative impact on the business
T I M W O O D
Risk: Brand reputation,
compliance, costly
Reduce defects at point of capture
Identify workarounds - work
backwards to source
All defects to be logged and resolved
Effective monitoring of defects and
risks
14
© Harte Hanks Trillium Software 2012
T I M W O O D
Helps!
Suitable structure for data governance review
Waste definitions are adapted to suit the
business
Avoid missing crucial processes
Guides the business to key areas
15
© Harte Hanks Trillium Software 2012
Turning an Approach into Reality
Lean Data Governance is not just an approach - it is a way of
thinking.
•ELIMINATION - Taiichi Ono’s seven wastes - TIMWOOD
•PREVENTION - 5 principles of Lean – 5S
•Trillium’s 5 Data Governance Disciplines
= formula for Lean Data Governance.
16
© Harte Hanks Trillium Software 2012
The Lean Mean Data Governance
Machine
1. Avoid
batches and
queues -
Enable speed
and agility
2. Eliminate
and Prevent
waste in all
areas of data
governance
3. Automate,
standardise
and improve
processes e.g.
reporting
4. Meticulous
management
and
governance of
process flows
5. Data
Governance is
evolving –
continuous
changes and
updates to the
program
6. Deliver value
to the internal
customers
when they
demand it
17
Be Certain, Be Trillium Certain
© Harte Hanks Trillium Software 2012
Questions?
Suggested further reading:
Trillium White Paper: “Lean Mean Data Governance” Machine:
Available soon at http://www.trilliumsoftware.com/
To learn more about Lean: http://www.lean.org/
Contact: kiran.gill@trilliumsoftware.com
18

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Lean Mean Data Governance Machine Webinar Part 2

  • 1. Be Certain, Be Trillium Certain © Harte Hanks Trillium Software 2012 Session 2 Lean Mean Data Governance Machine Kiran Gill, Senior Strategic Consultant, Trillium Software 1
  • 2. © Harte Hanks Trillium Software 2012 Introduction and Overview Waste Elimination – 7 Wastes (TIMWOOD) Transportation Inventory Motion Waiting Over processing Overproduction Defects Turning an Approach into Reality The Lean Mean Data Governance Machine Overview 2
  • 3. © Harte Hanks Trillium Software 2012 What is LEAN Data Governance? 5. Convergence of 7 wastes, 5 Lean Principles and 5 Data Governance Disciplines 1. Focus on the Internal data Customer 4. Delivery of flexible, perfected, value added outputs to the internal customers. 2. Optimisation of Classic Governance using Lean Principles 3. Minimise, eliminate and prevent waste in Data Management 3
  • 4. © Harte Hanks Trillium Software 20124
  • 5. © Harte Hanks Trillium Software 2012 Lean Methodologies 5
  • 6. © Harte Hanks Trillium Software 2012 Lean Data Governance Waste Elimination Taiichi Ohno’s 7 Wastes (TIMWOOD) Example applications Adopt and adapt the approach Waste definitions unique to the business No wrong/right definition 6
  • 7. © Harte Hanks Trillium Software 2012 Lean Data Governance Case Study: Luxury Fashion label Existence of some governance processes – no definition Data from multiple sources Many risks as a result of bad practice No ownership or awareness Working in silos Wastage occurring across the enterprise
  • 8. © Harte Hanks Trillium Software 2012 Transportation: Waste during transportation to end destination Assess Transportation within Process, Technology, People and Data Management T I M W O O D Risk: Excessive transportation = increased error and degradation Map and Review Assess tools and technology Eliminate unnecessary data transfer – refine the process 8
  • 9. © Harte Hanks Trillium Software 2012 Inventory: Responding to the pull of the customer ensures minimal Inventory T I M W O O D Risk: Using incorrect data to drive decisions. Resource utilisation Evaluate internal processes Identify and eliminate excess data Identify critical data Avoid generating surplus data at source Review roles and purpose 9
  • 10. © Harte Hanks Trillium Software 2012 Motion: Motion refers to the movement within a process. T I M W O O D Risk: Introduction of error during transit. Resource/time wastage. Process review - movement, manipulation and interrogation Reliable technology Intuitive data management with less stages Assess people movement – unnecessary process e.g. workarounds 10
  • 11. © Harte Hanks Trillium Software 2012 Waiting: Waiting is a common waste This can be easily avoided T I M W O O D Risk: Introduction of workarounds, errors and delays. Tool functionality Reliable technology Review process and eliminate gaps Prioritise resolution activity Introduce new processes and eliminate old ones. E.g. Issues Management tools 11
  • 12. © Harte Hanks Trillium Software 2012 Over Processing: Processes that do not add value Correlates with the identification and creation of value streams in the 5 Principles of Lean T I M W O O D Risk: Deterioration of data quality and integrity. Increased errors Key stages of data journey by process. Regular review of business rules - central access to definitions Establish schedule and scope of cleanse Build archiving rules and processes 12
  • 13. © Harte Hanks Trillium Software 2012 Overproduction: Excessive production of data or information Wait for the internal data customer demand in order to prevent waste T I M W O O D Risk: Duplicated effort. Using obsolete data Define owners - manage outputs Define process for creation of new output Review data capture Introduce central tools - automate e.g. dashboards 13
  • 14. © Harte Hanks Trillium Software 2012 Defects: Defects spread to the entire organisation Defective data and processes have a negative impact on the business T I M W O O D Risk: Brand reputation, compliance, costly Reduce defects at point of capture Identify workarounds - work backwards to source All defects to be logged and resolved Effective monitoring of defects and risks 14
  • 15. © Harte Hanks Trillium Software 2012 T I M W O O D Helps! Suitable structure for data governance review Waste definitions are adapted to suit the business Avoid missing crucial processes Guides the business to key areas 15
  • 16. © Harte Hanks Trillium Software 2012 Turning an Approach into Reality Lean Data Governance is not just an approach - it is a way of thinking. •ELIMINATION - Taiichi Ono’s seven wastes - TIMWOOD •PREVENTION - 5 principles of Lean – 5S •Trillium’s 5 Data Governance Disciplines = formula for Lean Data Governance. 16
  • 17. © Harte Hanks Trillium Software 2012 The Lean Mean Data Governance Machine 1. Avoid batches and queues - Enable speed and agility 2. Eliminate and Prevent waste in all areas of data governance 3. Automate, standardise and improve processes e.g. reporting 4. Meticulous management and governance of process flows 5. Data Governance is evolving – continuous changes and updates to the program 6. Deliver value to the internal customers when they demand it 17
  • 18. Be Certain, Be Trillium Certain © Harte Hanks Trillium Software 2012 Questions? Suggested further reading: Trillium White Paper: “Lean Mean Data Governance” Machine: Available soon at http://www.trilliumsoftware.com/ To learn more about Lean: http://www.lean.org/ Contact: kiran.gill@trilliumsoftware.com 18