TRILLIUM SOFTWARE INSIGHTS

Rules and Standards Everywhere – But How Do You Govern?

By Michele Goetz, Vice President of Product Marketing, Harte-Hanks Trillium Software

Great discussion on DM Radio on March 31.  Aaron Zornes, coming back from an MDM/Data Governance conference in London, provided some interesting insight on where organizations think MDM solutions are falling short.  Top of the list: centralized management of rules and standards.  The request from attendees was to have a work center application for workflow and repository management.

Attendees felt that after years of outsourcing IT, there was a distressing lack of management tools as they bring things back in house.  And, in the development of MDM and enterprise data infrastructure, rules and standards were dispersed throughout a variety of technology tools and scripts. Aaron provided reasons for why these tools were dispersed, but his responses begged the question “is that really the primary problem with why MDM solutions are falling short?”

First, the outsourcing of IT wasn’t the issue so much as the fact that the business was not taking accountability and ownership of the data.  Why care about an easy-to-use console or application when all you need is processing capabilities and coding?  The challenge today is not IT so much as data stewards in the business who require easier ways to interact and manage data.

Second, the issue of rules and standards dispersed across the infrastructure is more a failure of best practices and the enablement of development silos.  The reality is, by better aligning data to the business, we are discovering this old way of doing things just isn’t going to cut it anymore.

My mantra has always been, just because you can, doesn’t mean you should. I think that is why we are in the position we’re currently in when managing our data and its quality. It is in the nature of people to solve problems the easiest way they know how, not necessarily the most effective way.  I agree, we need to centralize rules and standards and have personally felt that pain as a data steward.  But, is it that we need to add yet another tool or workbench to the stack, or is it that we need to look back into our practice and determine where it makes most sense to centrally manage? 

Data quality solutions with robust profiling capabilities, rules engines, and stewardship management tools provide that central platform for defining and enforcing data requirements. It is what they were built to do.  When thinking about aligning your data to the business process and need, consider:

•  What was the intended purpose of the technology?  Data movement, data quality, data hub, repository?

•  What is the breadth of capabilities in the technology that can simplify and reduce the overall cost and time to implement while improving the chances for success?

•  Is the technology aligned to best practices?

•  Has the technology taken into account the variety of skills and users that will need to utilize the capabilities?

•  Does the technology help the business and IT collaborate and speak the same language in the same environment?

If you truly want to centrally manage rules and standards within your technology platform, the first step is deciding where the best place is to centrally govern the data.  That will give you true data quality.

 

5 Observations from FIMA 2011 (Part 5 of 5)

By Jon Asprey, Director, Strategic Consulting EMEA, Harte-Hanks Trillium Software

Continued from my previous post, Part 4, I talked to many of the attendees from FIMA 2011 made 5 core observations:

Observation #5. Carefully consider outsourcing & the resource mix
I heard some discussion about the pros and cons concerning outsourcing data quality operations.  It is clear to me that beyond relatively simple data cleansing activities, outsourcing or ‘offshoring’ can introduce added complexity, although solving the immediate resource problems. It is also important to leverage the right resources for each particular task to ensure your data management efforts are effective. For example root cause analysis requires specialist product and process knowledge.  This usually necessitates dialogue with many individuals to establish the origin of a data defect, whereas, some data cleansing activities can be outsourced in a “clearing house” type model. Carefully consider whether you need this added management effort and how you will coordinate you outsourced resources.

The Opportunity
These observations present a huge opportunity (and a huge challenge) for those responsible for a company’s data governance and compliance initiatives. It will require and enormous educational push and cultural change to ensure information is captured accurately and treated appropriately as it is used in down-stream processes.

Efforts to improve communication and share knowledge will only benefit the company by increasing efficiencies and streamlining processes. My view is that a centre of excellence model does work as it allows a centralised team to build the skills and knowledge that will serve the wider business as a whole. And regardless of whether it’s the regulators or the executive arm driving the changes, I would argue that they will help you run a better business.

 

“You Were Always on my Mind.” But Data Quality Shouldn’t Have to Be

By Nelson Ruiz, Senior Product Manager, Harte-Hanks Trillium Software

The great hit song from Willie Nelson, “You Were Always on my Mind” is something you may recall singing to a high school sweetheart.  But, when it comes to managing data and improving business processes, data quality should not have to be on our minds.

Well, for some of us that live and breathe data quality every day, we can’t avoid it.  But for the ‘consumers of data quality applications,’ they shouldn’t have to worry about the accuracy of the data flowing through these systems and processes.  They shouldn’t have to concern themselves that data will adversely impact real business decisions.  They just need peace of mind.

For example, I have multiple credit cards which I try to use for different purposes. For that reason, I have different limit alerts on each one of them. That way I set the limits and forget about it.   If the limit is reached, then I receive an e-mail notification on it.  This “rule” allows me to focus on the bigger picture (what I’m buying and what purchasing decisions I need to make) and not have to constantly think about whether I’ve reached the limit on one of my cards. 

I have a busy life full of long days, and there are so many other things that I actually need to think about!  But, having enough money is extremely important to me, so you can’t just avoid a high balance.

As a data decision-maker or data steward, these types of rules and alerts need to be critical components of my Enterprise Data Quality environment.   One of my goals would be to deploy an Enterprise Data Quality solution that allows me to set business rules that can be reused, accessed from one library and deployed ACROSS my enterprise to identify data inaccuracies across repositories.  This way, business users can, instead, focus on revenue generating business opportunities and campaigns….and not the Data Quality aspects. 

So, business growth would be the only thing on their minds… and, maybe their high school sweethearts!

Why is Data Quality always on your mind?  Tell me.

 

5 Observations from FIMA 2011 (Part 4 of 5)

By Jon Asprey, Director, Strategic Consulting EMEA, Harte-Hanks Trillium Software

Another core observation, continued from Part 3, based on my conversations at FIMA 2011: 

Observation #4. Siloed efforts
While a number of firms at FIMA are well on the way to establishing an experienced data quality team with expertise in risk and pricing functions, there is still a disconnect between the many data “consumers” and those in the front office responsible for “producing” or “sourcing” data. Many companies I spoke with still struggle with governing how data originates and then subsequently used within a business as a trusted source.

Do data consumers and data ‘producers’ at your company communicate on a regular basis? What has worked? What hasn’t?

 

5 Observations from FIMA 2011 (Part 3 of 5)

By Jon Asprey, Director, Strategic Consulting EMEA, Harte-Hanks Trillium Software

Continued from part two, I talked to many of the attendees from FIMA 2011 made 5 core observations:

Observation #3. Profile the process
Many companies focus on business process and efficiency—and rightly so. However they have not fully considered how data profiling can support their efforts. Profiling helps to identify the “evidence” of process failure, which eventually results in more effectively targeting resources and remediation efforts.

Have you profiled your data? What did you uncover? If you haven’t, what’s stopping you?

5 Observations from FIMA 2011 (Part 2 of 5)

By Jon Asprey, Director, Strategic Consulting EMEA, Harte-Hanks Trillium Software

Continued from my previous post, I talked to many of the attendees from FIMA 2011 and made 5 core observations:

Observation #2. Regulators are still driving change
While the business still has data quality needs that aren’t being met, change is primarily being driven by the regulations and a firms’ ability (or lack thereof) to meet minimum requirements. Building a case for data quality initiatives based on ROI is a difficult task for many firms. One of the presenters even suggested that such ROI calculations would always be negative! (I will cover this in a future blog).

We’d love to hear what is driving change in your organization.

Observations from FIMA 2011 (Part 1 of 5)

By Jon Asprey, Director, Strategic Consulting EMEA, Harte-Hanks Trillium Software

I had the pleasure of attending the recent Financial Information Management Association (FIMA) 2011 conference in New York, where I participated in a panel discussion titled “Exploring the Current State of Data Management” and moderated a round table in the Data Quality and Risk Workshop.

Like the NY Knicks’ performance in basketball games that week, the results for data quality within financial firms is mixed to say the least. I did make a few observations that all point to big opportunities for those responsible for their company’s data management & governance initiatives. I’ll present these observations over the course of the next 5 blog posts and would love to hear your comments and opinions.

Observation #1. There is a need for executive level education & expectation setting
Senior executives are becoming increasingly aware of the need for robust data governance and information management. However, after talking to many attendees at FIMA, it is still clear that many do not realize the implications and resource requirements in proactively tackling data quality and governance “head-on.”

What does this look like at your organization? Do executives have a good picture of what it will take? If not, what are you doing to help them understand what needs to be done?