On October 7-9, I will be hosting a conference on The Future of Data Governance at the Mohonk Mountain House (www.mohonk.com) in New Paltz, NY. This event has been designed to explore the challenges and solutions of Data Governance organizations constantly ask about:
1. How do I transform data into an asset? Data isn't an asset until you make it one, and its not an asset like gold, stocks, or oil. Those assets have commodity values based on their scarcity and demand. Data is an asset with infinite availability, so its value can't be based on the amount you own or the amount someone wants. The value of data is purely perceptional, unless there is a market for that data. iTunes, DVDs, Newspapers, and cable TV are all examples of data with values based on market demand through external sales channels.Many organizations in the Data Governance Council have been successful in creating information assets, protecting them from risks, and organizing x-functional participation in Data Governance Councils. And they have achieved some stunning results.But internally, we have no market for data sales. So the best we can do within an enterprise is increase the perceptional value of data as an asset. It has a perceptional value to Business when IT can demonstrate incremental revenue obtained through data consolidation, aggregation, cleansing business intelligence, and new sales.
Your data either is producing new revenue or it isn't. But when it is, getting business and operations to take notice and care about how the uses of this data are to be governed is easy. At this conference, we'll hear from customers who are both struggling with these issues and also those who have solved them. And I think we'll see that there are indeed best practices in working horizontally with Trusted Information that is a cause celebre for governance.
2. What are the risks to data assets everyone in the organization should be aware of? There are so many risks and liabilities from working with data today. We read about data breaches, privacy violations, and compliance challenges so often we become inured to the issues. But when Data becomes a perceived asset in your organization, knowing which risks to mitigate, avoid, or transfer out is critically important. Because no one has infinite resources to protect against every exposure, new methods in risk calculation, embedded deep in business processes and decision-making, are needed. And risk calculation can only take place when past mistakes and losses are accurately recorded, trended over time, and integrated into BI applications.
At the conference, we will explore the increased scrutiny that risk is getting and some of the best practices available in risk calculation, risk taxonomies, and forecasting solutions. We'll hear from customers with real use cases and experiences, as well as some vendors with exciting new solutions.
3. Organizationally, how do we govern the use of data assets and protect against risks? Data is unorganized Information, and Knowledge is information digested by a human being. Data itself can't be governed. It is inert until organized into information and transformed by a person into knowledge. A person can create data and information assets or put them at risk, so therefore only a person can be governed. Governance is a political process for organizing behavior to achieve certain goals.
Data Governance can be called other things, but the political organization can't succeed without x-organizational support. Just as we seek to create information assets by overcoming data stovepipes, so too do we need to overcome organizational stovepipes and link Business, Operations, and IT to achieve Data Governance goals.
Five years ago, Mohonk was the venue where I hosted our very first Data Governance event. Back then we organized three tracks to focus on Policy, Content, and Infrastructure questions. We had a lot of questions and ran each track as an interactive forum to frame common issues, understand the dimension of Data Governance, and identify convergent areas our customers wanted to explore. We had long discussions about data supply chains, policies and rules, metadata and data classification, security and risk. The dialog was extremely interactive, and coming out of that meeting there were many who wanted to continue. That was the genesis for the IBM Data Governance Council.
We knew then that Data Governance would become an important field. Some early visionaries like Robert Garigue from Bell Canada, Christa Menke-Suedbeck from Deutsche Bank, Charlie Miller from Merrill Lynch, Ed Keck from Key Bank, and Richard Livesley from Bank of Montreal helped us all to see the dimensions of the emergent market. And it was those leaders who helped to shape the Data Governance Council Maturity Model, which in turn helped define the elements of the Data Governance marketplace.
Of course, what we couldn't see then is how failures in Data Governance would threaten the world economy itself. The Credit Crisis was caused by incremental policy failures in almost every stage of the mortgage data supply chain. Loose credit led to bad home loan underwriting decisions, which were masked by rising home values. Huge fees in MBS and CDO trading led to inside-deals with credit rating agencies and banks and vast amounts of poorly documented mortgages came to be regarded as Tier 1 assets on many balance sheets around the world. These instruments were insured by complex derivatives traded without clearinghouses and created interconnected obligations among the largest banks with huge exposures should any one of them fail.
The media has focused on the wide segment of the funnel, the derivative market failure. Credit Default Swaps in this market had a notional market exposure exceeding $100 trillion. But the failure was within a supply chain and poor underwriting standards in loan origination from 2005 to 2008 continue to pollute banks with Toxic Assets and the long tail of mortgage foreclosure haunts our economy. Our mortgage market remains heavily discredited around the world and new Data Governance solutions are needed to restore investor confidence in the US Mortgage Market.
I've been working with a range of policy-makers and thought leaders on providing concrete solutions to those challenges, and I will host a round-table discussion on US Housing Data as a use case example on the value of data, the terrible risks that can still plague our economy from data pollution in that supply chain, and the concrete steps that can be taken now to address these issues.
I think this conference will be thought provoking and practical. The market is looking for Data Governance solutions. Not just know-how and not just software. But know-how and software and examples how to apply them. That's what we'll do and I hope you can join us. I think it will be the best Data Governance Conference ever. The venue is fantastic, the room rate unbelievable, and the conference fee is a true bargain.
This agenda will continue to evolve, so come back often for updates.
Directions to Mohonk