Will reality ever live up to the hype? What to do about all that bad data? And how should a senior executive make smart choices about where to invest?

• The Not Too Distant Future: Data and Organization in Five Years Time.

• Big Data and other Competitive Strategies

• Data Quality: Improve or be Swamped By Junk, and

• Building Organisational Capability to Produce Better Information

There executive briefings will be led by Dr Thomas Redman, President of Navesink Consulting Group. Dr Redman, widely known as the Data Doc, quite literally “wrote the book” on these subjects (Data Driven: Profiting from Your Most Important Business Asset). Dr Redman’s extensive industry knowledge is sought after internationally and he had advicsed companies across the globe in all aspects of information management.

Secure your position at this event by registering on-line.

“And the winner of the 2012 Data Quality Asia Pacific award is . . . “.

The deputy CEO of SBI General Insurance, Rob Logie, stepped up to the stage to accept the Data Quality Award as part of the APAC Data Quality Congress in March 2012.  SBI Insurance was a new joint venture formed between Insurance Australia Group (AIG) and the State Bank of India (SBI).

I thought it would be worthwhile to have a look at what the benefits were that underpinned the award and what actions SBI Insurance took to implement a strong information quality culture in their organisation.

Some of the stated benefits of SBI Insurance measured during and after the rollout of their enterprise data quality program were:

• Significant long-term cost savings by efficiently handling  the data/information
• Ability to understand  and identify growth opportunities
• Greater efficiency in implementing and managing business and information processes through supporting technology
• More valuable, superior, high quality and powerful information for effective decision making
• Market leadership in information management through the creation of a high value quality asset
• Effective and efficient risk selection and product pricing
• Effective regulatory legal compliance

Here are some of the key things SBI Insurance established to drive these benefits:

• Deputy CEO was appointed the  Information Management Champion, thereby securing support from the top
• Aligned all of their information management activities to their Enterprise Information Management Framework (EIMF).  The EIMF answered some basic questions around:
• What information assets do we hold?
• What do we need to collect, store and manage to leverage our information effectively?
• What capabilities do we require to manage our information effectively?
• How do we manage and govern the Information Management Lifecycle?
• Through their Enterprise Architecture function they defined and implemented Information Management Policies, Principles and Standards
• They defined an Information Lifecycle model specific to the SBI business model and tied their policies, principles and standards to this model
• Developed an Enterprise Business Data Model (Conceptual, logical and physical) based on data requirements captured from the business processes and built these requirements into their IT Systems
• Developed an Enterprise Business Data Dictionary of all terms used in the organisation and identified owners of each term.  The definitions of which enabled the organisation to speak the same language.
• Defined and implemented an Information Management Governance Framework including  Charter, Roles, Responsibilites and RACI

It is clear SBI Insurance was committed to genuinely leveraging their information as a competitive differentiator and that focus and effort has paid off handsomely.  How does your organisation compare?

With ever increasing business demands and pressures from compliance regulations, financial institutions are pressured to make more effective use of their company data. With multiple departments maintaining siloed information, accurately meeting compliance reporting and analytical requirements proves difficult.

Regulatory compliance often occurs on a project-by-project basis with no standard approach and a high cost of people, time and money for each project  – sound familiar?  There are significant benefits in a quality data management approach which include;

Flexibility – quickly adapt to new or changed requirements

Responsiveness – standard approach exposes benefits in shorter time to compliance

Comprehensive – flexible and standardised approach allows for a single solution to most regulatory requirements

Trusted – provide timely and accurate information that is correct every time

The new regulations around FATCA (Foreign Account Tax Compliance Act ) and APS910 compliance requirements rely heavily on trusted information.

Under FATCA, U.S. taxpayers with specified foreign financial assets that exceed certain thresholds must report those assets to the IRS. This reporting will start this tax filing season in the U.S. FATCA requires Australian financial institutions to report directly to the IRS information about financial accounts held by U.S. taxpayers, or held by foreign entities in which U.S. taxpayers hold a substantial ownership interest.

This session will also discuss approaches to developing your Single Customer View in accordance with Australian Prudential Standard APS 910.

+ Register for this Workshop Right NOW!

Public Healthcare is spoiled for Data Governance at a Federal level.

Whether or not the industry realises it, there are 25 committees in Australian Institute of Health & Welfare (AIHW) alone to develop and work through data set specifications and information needs for our federal health statisticians. There’s a plethora of organisations that meet and discuss information agendas, policies, goals, standards, and metadata at the national level. We have a National Health Data Dictionary, standardised code sets and terminology, and National eHealth Transition Authority (NEHTA)’s Unique Health Identifiers (UHIs) amongst other initiatives.

But how does that translate to the state level? How does that trickle down to the individual institutions and in to the private sector?

How does the ward clerk or administration assistant know how you have defined an Occasion of Service by Mode of Telephone?

Therein lies the problem.

With such a top-heavy array of committees and healthcare reform programs how are the states, or even institutions, managing to keep up with it all?

So let’s focus on one big factor here – the Individual Health Identifier (IHI) brought in by NEHTA. The IHI is intended to be the one identifier that follows someone their whole life and is used by healthcare institutions to resolve identities. This provides the capacity to link health records across systems, institutions, or jurisdictions. In the event you have a patient presenting with a common name such as John Smith it will aid in ensuring you have the right ‘John Smith’ when prescribing a medication that does not trigger his allergic reaction.

NEHTA recommends  your organisation meets a minimum data quality maturity rating of 3 against their framework and maturity model, not to mention have also tackled managing the single view of patient across your systems through the use of a Patient Master Index (PMI) or similar. NEHTA has already had some pilot sites operating with the IHI but this has proven to expose the actual reality of underlying data quality issues – not a pretty sight!

So how are healthcare organisations handling this?  The answer is they’re still struggling to cope and have not yet tackled the real issue – effective Data Governance and Stewardship programs. The technology may be present, where are the people and process dimensions to accompany it? Some of the initial questions arising are:

• What data elements are necessary for your master data records?
• How has the organisation defined the Stewardship for each data element?
• Who has determined the correct classifications and what will be standardised?
• Who is accountable for the data at the source or once its hit their MDM solution?
• Who has the expertise to act as a Steward for such critical data?
• How will the organisation proactively manage upcoming initiatives or react to reform in relation to their data?

Is your organisation equipped with the people and processesto manage the technology across systems, business units, and facilities? Orwill you be balancing patient outcomes on the great unknowns? Healthcare reform initiatives bring an exciting road ahead for the industry, but it is a long and windy road.

“You can tell when they aren’t serious about data quality.” said Tom.

I was sitting in the lobby of a hotel in Adelaide, South Australia just prior to the kick off meeting for the International Conference on Information Quality in November 2011.  With me were Ken Self, IAIDQ Asia Pacific board member, and international author and expert on improving data quality, Tom Redman.

Tom was in the middle of explaining to us how some organisations simply aren’t serious about their data quality.  Tom’s point was you can sense this pretty early in the discussion when senior management is focused on more activities that make them feel like they can say that they are addressing the problem but in reality they are not committed to the cause.

I really liked the idea of characterising companies by those who are serious and those who are not.  The unfortunate truth is that while data quality has risen in prominence among the senior levels of many organisations, this can sometimes only be heard and not so much seen in the behaviours and actions of the organisation.

Sometimes we can be fooled into believing because the executives are talking data quality that the actions will follow.  There are executives who “talk the data quality talk”, but are looking for the silver bullet or path of least resistance to improved data quality.  Here’s a tip, there are no silver bullets.  If a company is serious about data quality then it takes good old fashioned, roll up the sleeves, down and dirty WORK to make things better.

In our next blog I will be using the example of a company who focused on building data quality into their organisation from the ground up.  Hey, it won them an award and had the side benefit of helping their business significantly – they were serious about data quality.

+ Register for this Workshop Right NOW!

Whether you are just starting your project or are already in production, it is not unusual to find that information quality issues prevent the company from realizing the full benefit of their investment in the new systems. You will learn practical approaches to improving the quality of information critical to your organization, satisfying customers, and achieving company goals.

If you working on real data quality-related projects that need real results, this is the seminar for you. What is presented applies to any kind of data in any industry. Those from all organizations – for-profit businesses, education, government, healthcare, and nonprofits – can benefit from what is learned here because all depend on information to support what they provide. Both foundational data quality concepts and practical instruction are included. Lecture, discussion, and individual and group exercises are an integral part of the course.

Come with your particular needs in mind and ready to participate as this is a highly interactive workshop. Learn how to apply to your situation and leave with realistic methods for improving information quality.

The course is based on the extensive experience of Danette McGilvray, trainer/author/consultant, and her book Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™ (Morgan Kaufmann Publishers, 2008).

Workshop Name:
Danette McGilvray’s Ten Steps to Data Quality

+ Register for this workshop NOW!

What You Will Learn at the Workshop

Who Should Attend the Workshop…

Individual contributors and team members responsible for or interested in the quality of data in their business processes, systems, or databases. This includes those in roles such as:

• Data analysts

• Data quality analysts

• Business analysts

• Data designers/modelers

• Data stewards

• Application developers

This class has also proven helpful for some managers and project managers as they also need to understand what is involved in data quality. They are the ones who hire and assign people’s time and are called upon to remove roadblocks to data quality work.

Register for Workshop Now:
Danette McGilvray’s Ten Steps to Data Quality

Workshop Registration Form Limited spaces available.