I was delighted to attend in Ark Group’s annual Data Quality Asia Pacific Congress last
week, and privileged to be able to contribute on all three days of the
conference (expert panel discussion on Day 1, a presentation on MIS Strategy on
Day 2, and leading an interactive workshop on Information Asset Management on
Day 3).
The event featured participants from a diverse range of
organisations such as National Australia Bank (NAB), Telstra, Walgreens, SA
Water, Sydney Airport, State Bank of India (SBI) and the United Nations
Conference on Trade and Development (UNCTAD). Their though-provoking content provided
stimulus for a highly interactive forum with some great debate about data quality,
data governance, master data management and cultural change.
A wide range of topics and themes were touched upon during
the event, however some concepts were cropping up consistently throughout the
various sessions. I’ve captured my own personal “Top 10 Takeaways” from the
conference (not in any particular order):
1.
Branding.
Engaging with a whole range of communities requires visibility of the Data
Governance group. You’ve got to be actively marketing on a daily basis. Mike Jennings of Walgreens stressed the need to ensure
that the message keeps hitting home by having an easily identifiable logo,
pervasively used on all output from the Data Quality/Data Governance Unit.
This needs to be reinforced by a
clear Vision and Mission statement, as well as persistent and consistent
communication of the Data Governance agenda.
2.
It
doesn’t matter where in the organisational hierarchy the Data Quality function
sits. According to Nonna Milmeister of Telstra, the debate about “does Data Quality live in business or I.T.” is a
red herring – it just needs to exist somewhere!
While sponsorship is vital, the
function lives within whichever part of the organisation has the most ability
to sponsor and influence the uptake of data quality management.
3.
Crowd-source
your data quality. Open government initiatives are leading the way in
getting end-users of data sets to provide feedback and enrichment.
Tim Moon of RXC encouraged thinking about opening up access to the raw
data, new and innovative uses can be found which deliver additional value – to
the organisation itself, and to the wider community. (For further view on this,
see this excellent TEDTalk by Tim Berners-Lee.
4.
Metadata
needs to be accessible if it is to mean anything. Common definitions aren’t
of any value unless they’re accessible, in context, and directly relatable to
the data set being viewed.
Mark Bands from ANZ suggested that the “holy grail” is to have the
business meaning, calculation rules and lineage of a data element available in
real-time and in context with a single “Right Click”. The market-leading
Metadata Management tools can enable this capability.
5. Standards aren’t always so standard. Well-defined
standards, in conjunction with the right Governance models, can be a force for
continuous improvement. Consistency of approach drives quality of outcome.
Unfortunately, the current
application of standards & frameworks within the Geospatial Information
Systems (GIS) industry mean that the data managed by vendors of different
solutions are not necessarily interoperable. According to Jonathan Roach, there is no co-ordinating body to
enforce & certify GIS solutions, and the vendors can interpret what
frameworks do exist in their own way. A particular problem is variance in data
processing granularity, which means that transfer of geospatial data between
systems is lossy (64 bit processing for CADCorp, 32 bit for Esri, only 16 bit
for MapInfo).
6.
CRM
Integration through SOA. Ram Kumar from IAG showed how having a robust MDM
architecture helps drive integrity of the customer record, even in federated
environment.
For each attribute, one system is
designated the “master”, then all other transactional systems call that value
on request via the ESB. At IAG, the CRM system doesn’t even master any customer
details – its purpose is to manage interaction events.
7.
Set your Information
Principles first. Ram Kumar again. For IAG, the Information Principles were
first set of principles endorsed by the SBI Board, even before the Business
Strategy was endorsed.
IAG have gone beyond the standard
platitude of “right data, at the right time, to the right person”. Their
approach requires clear definition of:
a.
The right data
b.
In the right place
c.
For the right person,
d.
At the right time
e.
In the right format
f.
Of the right quality
g.
In the right context
h.
With the right security
i.
With the right governance.
Any information set is only under
governance when all of these have been explicitly addressed.
8.
Legal
& Compliance. Mike Jennings from Walgreens proposed involving Legal &
Compliance as an active part of the Data Governance structure, to ensure
appropriate guidance and assessment of legislative impacts (e.g. privacy,
security, integrity).
9.
Data
Governance needs benefit opportunities. Scott Jerome of SKM highlighted
that Data Governance can support management of risk, improved efficiency and
better effectiveness, while Clint Morrell from AGL identified specific
monitised benefits that have resulted from their Data Quality initiative.
Identifying the explicit links from
the Data Governance actions to the resulting business outcomes promotes the
value and establishes a platform for further investment in improving the
organisation’s data assets.
10. Map your Data Quality workflow. Andrew McAlindon from SA Water asked the following though-provoking questions: what process
and resolution path do you go through when an issue is raised? What are the decision
rules, who has authority to act, approve & signoff?
Mapping out the activities and responsibilities will help ensure the decision making process is clearly thought through, fit for purpose and visible.
Mapping out the activities and responsibilities will help ensure the decision making process is clearly thought through, fit for purpose and visible.
