Lean Mean Data Governance Machine Webinar Part 2

Be Certain, Be Trillium Certain

© Harte Hanks Trillium Software 2012

Session 2

Lean Mean

Data Governance MachineKiran Gill, Senior Strategic Consultant, Trillium Software

1


� 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


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


Lean

Methodologies

5


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


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


Transportation:

�Waste during transportation to end destination

�Assess Transportation within Process, Technology, People and Data Management

T I M W O O DRisk: Excessive transportation = increased error and degradation

Map and Review

Assess tools and technology

Eliminate unnecessary data transfer –

refine the process

8


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


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


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

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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


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


Defects:

�Defects spread to the entire organisation

�Defective data and processes have a negative impact on the business

T I M W O O DRisk: 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

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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


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.

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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


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: [email protected]

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Lean Mean Data Governance Machine Webinar Part 2

Technology

Transcript of Lean Mean Data Governance Machine Webinar Part 2