On September 20-21, IBM is hosting The Big Data Governance Summit at the Ritz-Carlton Bachelors Gulch in Vail, Colorado.
This event is about Metadata, Stewardship, Security, Privacy, Data
Quality, and Big Data. We can reach to the skies, pull in petabytes of
relational tables, twitter feeds, video, audio, and documents, but its
all garbage in and garbage out without Data Governance. Velocity, Volume, and Variety without Veracity creates Vulnerability. Everyone
knows this, and its our task to do something about it. We have to show
how it can be done – how anyone can build vibrant, dynamic, Big Data
Ecosystems that use common standards, ontologies, and methods to tag
huge volumes of data, index its value and context at high Velocity, and
search across its variety to discover trends with large clusters of
computational power that deliver high Veracity and low Vulnerability. This
is the promise of Big Data Solutions, uniting disparate data sources
across our organizations, our cities, and our planet; leveraging data
sets based on purpose specification; searching for meaning and value
with brute force speed. I can see this promise. Its within our
grasp. We can bridge our stovepipes of data and non-standard behaviors
into lean, mean, transformation machines that yield incredible insights
and informational power. But this promise is only in reach with
Data Governance Solutions to provide metadata tagging, standards,
ontologies, purpose-based access protocols, audits, security &
privacy, data quality, discrete retention rules, and new tools and
technologies to automate how we do it. The purpose of this event
is to explore how we can bring these ideas forward to help the world
adopt Big Data Ecosystems more rapidly, more successfully, more
fruitfully. We are meeting at the Ritz-Carlton Bachelor's Gulch,
which is the wonderful venue where we first shared the IBM Data
Governance Council Maturity Model with the world in 2007. We will look
at real life examples of firms using Big Data, exploring ecosystems, and
developing standards to model and simulate them. This meeting is hosted by the IBM Data Governance Council but it is open to all. Join us as we move forward Big Data Governance.
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This morning, General Motors announced that it would no longer advertise its cars on Facebook. This announcement comes a day before the Facebook IPO, and casts a shadow on the business model of Facebook. GM said that they will continue to support their page and user community on Facebook, but that ads just weren't effective in helping consumers to make car buying decisions. Ford jumped on this announcement to say they would continue to buy ads on Facebook and that Social Media requires a consistent commitment to innovation and community development. Maybe. But I think GM's decisions does illustrate a key problem for Facebook and Twitter - the revenue model. Social Media grew up without dependencies on ad-based revenue. On Facebook, you aren't a customer. You are a product, and its your likes, dislikes, friends, photos, videos, and content that generate value. Selling products to products via advertising is hard. Members don't use Social Media to go shopping. There's no commerce platform there. They use it to be social. There are so many other outlets that are more effective for advertising than Social Media.
So how should Facebook and Twitter make money? My idea: make it collective. The value is in the data.
1. Make terms and conditions explicit that every member owns their own data via copyright. This does two positive things.
A. It indemnifies Facebook and Twitter for the crazy, infringing, and potentially libelous posts of their members by allowing them to claim that they are conduits of content rather than publishers or distributors.
B. Copyright establishes the rights to royalties for content created and posted on their networks, which enables the next step.
2. Allow members to opt-in to Big Data analysis by Social Media partners and intermediaries.
3. Charge Social Media for Big Data Searches by data volume.
4. Pay members royalties every time their data is used in Big Data Searches.
This simple model creates powerful incentives that transform user members from products into mutual social network content providers with an economic interest in posting content that will be used in Big Data searches. It establishes data property rights that insulate Facebook and Twitter from vouching for the content on their networks. Members will also discover that providing high quality data that companies want to search for means more royalties and so the system will produce better behaviors. And it creates a 2-tier royalty distribution model that will also pay Facebook and Twitter handsome revenue that will change online advertising and make every other content aggregater change too. Of course, Facebook and Twitter will have to sort our who's a person and who's a bot, and will have to provide content creation tutorials to help users/customers create content that has value by sharing the top 100 Big Data queries and sample results.
But this Business Model has something for everyone and is a true win:win. It benefits customers by establishing data property rights and royalties for content. It benefits organizations who want to do Big Data searches by providing ever richer data streams of high quality and availability. And it benefits Facebook, Twitter, and their investors by providing an enormous profit making engine selling Data.
The Data is the Value. The more there is, the more valuable it becomes. Pay your customers to create higher quality data and charge your partners to use it. Its a simple Business Model. Dick Costolo - @dickc - and Mark Zuckerberg - @finkd - are you listening?
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I use Big Data every day. I don't have Hadoop, a Data Warehouse, ETL, or a big analytical engine. But I use search engines, which are indexes of web-pages from around the world, to discover related and unrelated facts. I use Twitter and Linkedin, which aggregate the ideas of millions of people, to understand the sentiments of the people I follow. And I make decisions, and mistakes, with this information every day.
We all do. And in that context, we are all Big Data users and abusers, and we can identify with larger enterprises that are also confronting vast streams of information from every corner of the globe, created by individuals, communities, corporations, and governments. We as individuals never had industrial data management applications. We never had Data Governance Councils, Stewards, or Data Management professionals. So we've been selecting data streams first and using the ultimate analytical engine - our brains - to integrate that information, glean trends, and make decisions.
What's new about Big Data is that large enterprises are copying the information processes that We The People use every day. They are selecting streams first, aggregating them second, determining application third, making decisions fourth. Judging consequences of decisions... later, if at all. Organizations around the world are deciding to retain information much longer because there is a belief that latent, slow developing, trends may lie dormant in that information that can be discovered much later.
But with vast volumes of information, long retention cycles, high velocity decision-making has the potential to do enormous damage as much as enormous good. And we know from experience, that decision-making is often influenced by cyclical trends, personal prejudice, and national dogma. Counter-Cyclical views can be marginalized. Whistle-blowers can be fired.
But Big Data also offers an historic opportunity for Data Management. This industry for too long has been seen as back-office archivists recording the deeds and attributes of heroic business leadership in dingy databases in large glass-house mainframes and data warehouses. They have taken back seats to application developers and business analysts who first and foremost collect the requirements of business users for new applications, features, and functions.
But Big Data changes all of that. It makes information sources and streams more important than applications, features, and functions. It changes the emphasis in value creation and puts the onus on Information Management to produce better sources and streams, easier aggregation and integration, manufacturing information products any user can leverage in any application they wish.
Its large enterprises automating the way We The People use online information every day, and the power and consequences of this paradigm shift are profound and potentially quite scary.
We need Information Governance over every part of Big Data to assure that organizations can answer these fundamental questions:
1. Can we trust our sources?
2. Do we know where they came from?
3. How do we verify the authenticity of the information?
4. Can we verify how the information will be used?
5. What decision options do we have?
6. What is the context for each decision?
7. Can we simulate the decisions and understand the consequences?
8. Will we record the consequences and use that information to improve our Big Data information gathering, context, analysis, and decision-making processes?
9. How will we protect all of our sources, our processes, and our decisions from theft and corruption?
This morning, the Information Governance Community began discussing these issues in a global teleconference moderated by IDC. We have just scratched the surface of these issues and have much more to discuss. We have agreed to create a new category - Big Data - in our Maturity Model to provide organizations with new methods to benchmark their Big Data Governance maturity. But we also agreed that our existing Maturity Model categories also apply and we need to update them to include Big Data issues and questions.
I believe this is critical work. Big Data is an enormous opportunity to make information the arbiter of value creation in the Information Age. But it is also an enormous risk because the same solutions can be used to make dangerous and destructive decision-making a high volume, high velocity science.
Every new technology can be used for both good and evil. Join the Information Governance Community to help ensure Big Data serves the best possible uses.
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If you have a Data Governance program today you already know its easier to start one that do one. Real governing is not like a Hollywood movie. Its hard to know what's wrong, why its wrong, how to fix it, and how to get people to care or follow the fixes. And you have to do this every day and all the gurus tell you to get metrics and KPI's, build a framework and follow my process. But those gurus don't live your life, they don't work in your space, and they don't have to make tons of messy compromises to get things done.
But you do, and you know that Governance is tough stuff. In the Data Governance Council, we know that too and we want to help. We helped build the market with the landmark work we did on the Maturity Model. That gave you a way of knowing that what your already know isn't enough. You could use it to help others realize it wasn't enough too. And that gave you a place to start your program.
Well, now that you are in the thick of it, we think there's a way to communicate how your organization really works - to simulate your environment so you can help folks learn what's going on, how stuff gets done, and what would happen if you made some changes. We know you do that anyway, all the time. But we want to help you do it in a safe test environment before you put your ideas into production. We call this Predictive Governance - the SCIENCE of describing the world as it is to run simulations on how we'd like it to be. Normally, most folks do it the other way around... The simulate the way they think the world works so they can describe how they want it to be...
Now I could tell you all about how this new way of working is going to look, how its going to help you, and what its going to do. But its more powerful if you see it for yourself. What I'm sharing with you today is an early preview into the Predictive Governance Simulation we are building. Its not pretty or polished, but it works and you can play with it now. Have a look and let us know what you think: If you'd like to join the IBM Data Governance Council and help us do more with this, drop me a line.
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Does the European Union "promise to be true in good times and in bad,
in sickness and in health?" Will the Union survive the current Debt
Crisis and become more integrated or will it break apart under the
pressure and allow insolvent states to exit the common currency?
Can the United States maintain its high standard of living and reduce its debt burden at the same time?
You
may read these questions in the press every day and never believe they
have everything to do with Data Governance, but they very much do.
Governments make tactical decisions every day to increase debt amounts
by small fractions thinking that their incremental spending is nothing
in comparison to what others have done in the past - failing to see the
correlations between current consumption and long term systemic
instability.
With 7 billion people on the planet Earth, our
societies have become so complex it is impossible with past methods of
governance to foresee how policies impact even the smallest ecosystems.
So we rely on blunt cause and effect relationships to over-simplify our
options and fit our ideas into media soundbites. And the result is
non-correlated policies that are anything but smart or predictive.
We
seek to change this. We know that without new tools and techniques to
see beyond the next effect, every cause will yield policies that fail.
We are the IBM Data Governance Council and we see that Data is the raw
material of the Information Age and that effective Governance relies on
conceptual thinking, integrated approaches, correlated analysis, and a
relentless search for truth.
We call this Predictive Governance
and this meeting will explore what this means, how it works, and how we
as a Community can create predictive models that:
1. See the
Relationships between Data Quality and Security & Privacy and Data
Architecture and ILM and Metadata and Audit and Reporting and
Stewardship and Policy and Organizational Awareness and Business
Outcomes - the Forest and the Trees in our Information Ecosystems.
2.
Model and Simmulate how new integrated policies, people and
technologies are available to Govern in these complex Ecosystems.
3.
Understand and articulate these relationships to laymen who only see
the problems at hand and have no patience for larger integrated
discussions.
Please join us for this important two day event.
Participation is open only to members of the IBM Data Governance
Council. Organizations wishing to join the Council may sign up for this
event and execute a Council Agreement in New York at the meeting.
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Two years ago, I met Helmut Willke, the author of Smart Governance: Governing the Global Knowledge Society, at a hotel cafe near the great cathedral of Cologne. Professor
Willke is a sociologist who teaches Global Governance at the Zeppelin
University in Friedrichshafen, Germany. Late in 2009 I became
interested in Governance as a system of decision-making and Professor
Willke had written an excellent book exploring this topic. While the
Professor is German, he writes extremely well in English and his book
very well written and insightful. Like a lot of philosophical texts, it
is not an easy read. Dense descriptions, long sentences, and theory
backed by ample example make it a book you have to read at least twice
to fully comprehend.
I was in Cologne in late February 2010 to meet the CIO of the City and attend Rosenmontag at City Hall. I had already seen several days of Karnival, with the endless parades, costumes,
and candy strewn about the streets. For five or six days in February,
the staid and reserved city of Cologne becomes an endless drunken party
attracting visitors from all over the world who wear outrageous costumes
and march in parades on incredible floats and throw candy to the
bystanders. Its unlike any parade I have ever seen. Quite amazing.
It had snowed a lot that year. It was white from Brussels to Berlin,
and Cologne was still covered by eight inches. The square in front of
the Dom was clear, and I had spent the morning before our meeting
visiting the Roman museum across the square. Cologne is an ancient
Roman city and the ruins are collected in a fantastic museum right next
to the Dom. Of course there are columns and pediments, but also beautiful mosaic floors, jewellery, stained glass,
and decorative arts. There is a model of the Roman city and you can
see how the Germans built the city on the same street grid with walls
built on top of the Roman walls. Of course, much of this was destroyed
by allied bombs in WWII, but some remnants remain.
Looking back at Roman colonial rule of Cologne was an excellent
introduction to the systemic ideas of Governance Professor Willke and I
discussed over coffee that afternoon. He is not a tall man, mostly grey
late-50′s I would say, with bright blue eyes. He makes an immediate
impression, and is passionate about his book. I had used the book as
text for a class I taught at the Bucerius Law School on Data Governance
in Hamburg that January. My students did not entirely appreciate the
dense prose and abstract ideas, but through class conversation we did
ultimately appreciate the idea that Governance is a system of
decision-making that could be described and modelled. And we used
Social Networking metaphors to explore the idea of policy-making, human
behaviours in a system of Governance, and how to model potential
outcomes. Of course there is political science, which describes
political models of Governance – Democracy, Dictatorship, Monarchy, etc –
but what is unique and important about Professor Willke’s book is the
application of systems theory to Governance.
We had some coffee and talked mostly about how the Professor wrote
the book and why. As I had in 2007-8, the Professor had used the Global
Credit Crisis as a use case to describe failures in Governance. I had
covered this topic from a Data Governance perspective, arguing that
hundreds of incremental failures in business processes and data quality
had produced a domino effect that plunged the global economy into
Depression. He covered the topic from a decision-making perspective,
and while we approached this topic from different directions we arrived
at similar conclusions – policy-makers can’t possibly make the best
decisions without understanding the consequences of those decisions on
incredibly complex and interconnected global systems. And those
consequences are impossible to understand without new information
systems that render the complexity with software and illustrate how the
policies will be accepted and resisted.
In my class at Bucerius, my students complained that the Professor
had not done enough to provide solutions to the problems he had
identified, or that his solutions were too abstract. I presented these
criticisms to him at our meeting and he responded that it was not
possible to offer concrete solutions because every systemic problem
needs to be modelled to understand the variables and outcomes – that
there is no one size fits all. At the time, I thought this was a
dodge. It took me a few more years to understand that he was right.
There are no Governance Solutions that can auto-magically produce the
best outcomes for every decision. But it is possible for policy-makers
to use systems theory and software to construct decision-making models
that can plot many of the actors, objects, variables, and potential
outcomes to understand the impact of policies on complex systems made up
of hundreds, thousands, and even millions of human beings with unique
behaviours.
After my course, I synthesised concepts from the book with ideas from my students to create the Six Steps to Smart Governance.
It’s not meant to be a Framework. Frameworks and models are nice tools
to help people feel more secure about challenges they seek to overcome,
but they are not useful in making better decisions. The Six Steps are
meant to be a structure for decision-making that one would apply
iteratively; in which each of the six steps would involve different data
points and variables. Of course, it is highly summarised, flavoured
with marketing. And I would say in hindsight, its not really useful as a
practical or operational tool. It’s really just a theory, a
simplification of the better documented ideas Professor Willke writes
about in his book.
And I think we can do better. In the IBM Data Governance Council we
will soon begin to explore dynamic simulation models that go far beyond
the Six Steps to Smart Governance, and I recommend reading both the white paper and Professor Willke’s book:
Smart Governance: Governing the Global Knowledge Society
Today, thanks to really powerful simulation software, we can create
dynamic models that help demonstrate the impact of policy on people,
processes, and technology. The Data Governance Simulation Project will
revolutionise the field of Data Governance by applying theory, software,
and observed practices to an interactive model that will yield powerful
insights into Data Governance Value Creation and Risk Mitigation.
A lot of people ask me, “how do I show the value of metadata?” Some
say, “how do I make the business case for Data Governance?” Consultants
and Gurus will have a framework or process to offer you, a get started
guide with use-case examples, graphics, and legends about their
successes. But these myths won’t help you, because your challenges are
unique. Your politics are special, and your people are not machines.
Best practices are useful examples of glorified solutions that are very
hard to replicate outside the lab. And as many are already finding out,
people resist policies they don’t think apply to them and its really
tricky to understand how to change organisational behaviours on an
on-going basis without policies that dynamically change with new
circumstances.
Data Governance is, by nature, a systemic challenge and you can’t
solve systemic problems without systemic solutions. Projects and teams
that expect quick hits and 90-results are the reason you have systemic
Data Governance problems in the first place. But it is possible to
create software models that allow you to plot the goals, metrics,
policies, communications, outcomes, variables, and modifiers and
evaluate the impact of new policies and controls on your environment.
And that’s the lesson of Smart Governance: you can model complex
environments through Simulation and make better decisions. To learn
more about using Simulations to make better decisions, take a look at
the IBM Smarter Cities Demo.
In that demo, the complex interactions of human beings living in a city
are compared to the goals of human policies, the metrics measured by
interactions, and potential outcomes.
Many of our organisations are as complex as small cities. Policy and
Politics share the same ancient Greek root word – epolis. epolis is a
city, which itself is an aggregation of human beings who require
Governance to arbitrate their diverse interests and achieve better
outcomes for all. Today, we can simulate those interactions and help
Policy makers profile the impact of their policies before they are
deployed. Its a kind of Visual Risk Calculation.
If you would like to participate in the Data Governance Simulation
project, please read the Six Steps to Smart Governance White Paper, the book by Professor Willke, and join the IBM Data Governance Council by executing this membership agreement.
Only members of the Council will be able to participate in this
exercise and you don’t want to miss this because it will fundamentally
change Data Governance.
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My aunt Helen had an opinion on everything. She was an information junkie long before the Internet, consuming at least three newspapers a day and watching untold hours of news television. If she didn't know about an issue directly, she had enough reference points to issue an authoritative opinion. I spent many weekends in her ancient Cheshire farmhouse with the musket holes in the foundation to protect against indian raids and the secret spot behind the fireplace where slaves hid in the 1850's Freedom Railroad on their way north to Canada. Dusty newspapers from the 1960's clogged the front staircase that was never used. Every National Geographic since 1940 sat piled in closets and behind sofas. Photos and postcards sat in boxes everywhere. Nothing got thrown away. Even the dust had dust. Her home was a database, and her brain was the ultimate computational instrument, an informational repository without parallel in our family.
Helen's knowledge of the world seemed to extend way beyond the bounds of her 1730 home. When I was young, I sat in awe of her voluminous and expansive mind never daring to question or challenge any of her positions. But as I grew into adolescence I began wondering if some her statements weren't maybe a little made up, or at least extrapolations of things she knew into things she thought she knew or could know with just a little imagination. But woe to you if you challenged her without some backup because she sure did know a lot and her mind was so sharp you could be reduced to blabbering in a microsecond if you really didn't do your homework and researched a topic.
But when I got to about 20, attending college - the place you went to get important information before Google put it on our smartphones in the subway - I started to learn that lots of what Helen said wasn't quite the way she said it. It wasn't that it was completely wrong, its just that it wasn't really always black and white the way she presented it. There were lots of different ways you could see and interpret the information. And you could construct a perfectly valid and well thought out argument that tied her up in intellectual knots. And back at the farm that summer we had some great arguments. Fact is, Helen was often at least partially right and wrong about a lot of things. Not philosophically wrong, because that's a matter of belief.
Factually in error, but never in doubt.
Her conviction was the secret of her intellectual strength. We've all known people like Helen, and many of you who know me are probably already murmuring "ahh, that's where he got that..." But I didn't bring up this point to wax about my family heritage or personality. I brought it up because this characteristic is one we find every day in our organizations, in the newspapers, on the web, in our governments. People develop points of view and stick to them, and getting people to see beyond their point of view is really a challenge. It isn't that the information is wrong, its that the people interpret it the way they see the world.
Information itself is a human creation. The computer didn't put it there. It isn't immutable, dirty until cleaned, chaste, pure, imperfect until perfected. It is a reflection of us, and since we created it, its sometimes wrong or the truth is at best a mixed result.
But what's to blame for that? Your Metadata? Your Business Glossary? Data Architecture? Security & Privacy? Audit? Your Organization?
YES! All of the above. Everyone who creates and uses information is involved in its interpretation and implementation. You don't have to be a data architect to influence the way information is used in an organization. Any iPhone or Android user has a role in the information management today. Bloggers, vloggers, and photographers shape and shade their creations to effect a mood, sell a product, influence an outcome. Everyone with a data connection is a source and a target and we all must accept responsibility for how we govern the use of OUR information.
Those consultants who tell you how to "govern the data" with all those tools are not helping anyone but themselves. Tools like Business Glossaries, Metadata workbenches, Master Data Management, Data Quality Profiling, and Audit help us understand when our information is out-dated, inaccurate, partially true, or just plain boulder-dash. We use those tools to illuminate the dark corners where opinions and habits force difficult debates to unlock the truth because we know that Information is the only tool we have to change behavior.
Want to succeed with Information Governance. Get Aware. Know what's happening and share it. Use your Information Governance tools to build operational awareness.
People will change their opinions when confronted with a solid argument, and that's what you want - Change from Information.
Fact is, I learned a lot from my aunt Helen and I still hear her voice strong as ever. Sometimes wrong, never in doubt.
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The Winter Solstice is the time for Data Governance Predictions. And here are mine for 2011:
1. Systemic Risk Councils will proliferate. The Dodd-Frank Bill established a Systemic Risk Council in the Federal Government to aggregate financial data from across the economy to detect patterns of exposure that can impact macro-economic policy. All Financial regulated entities should follow the leader and do this themselves. Some, like JPMC and Goldman Sachs already do this. Everyone who is not doing it should get on the wagon and replicate.
The Federal Government will take eons to gather all the data and make sense of it. And even if they do it, their will be political considerations with regards to how the data is used and disclosed. And forget about counter-cyclical policy-making. So if you want your firm to escape financial ruin in the next Sub-prime, Sovereign Debt, Greek, Irish, Portuguese, or Spanish Debt Crisis, go and get a Risk Council and start sifting the data yourselves. Processors and storage are cheap, data is widely available, what you need is the organizational structure, decision-making system, and a sound Data Governance program. Get it going now, because with all the debt the world has accumulated there will be many more crises to predict.
2. Health care will join the Information Revolution - Today, many doctors use the Internet to look up symptoms, anatomy, and, of course, pharmaceutical remedies. Yet as an industry, there are so few information resources that document the comparative performance of doctors and hospitals in how they treat patients and the results. In 2011, thanks to US health care reform, this will start to change and I foresee a nationwide movement to aggregate vast amounts of health care data to analyze and report on what works, what hurts, and start building plans to make care more efficient and more effective so that people live longer. Data Governance will play a huge role in this effort, which will start next year and consume the next decade.
3. National Incident Detection - Like it or not, the days of the Internet Wild West are numbered. While the new Republican Leadership in the House is opposed to the Net Neutrality Bill, it seems certain that some form of national security oversight over Internet incidents and threats is going to happen. The government has been trying to corral business into sharing incident information since 9/11 and I predict they will succeed at some point because nation-sponsored cyber-warfare can not be resisted by private enterprise alone. In some as yet to be determined form, new information sharing regimes will need to be designed that aggregate threat information from businesses across the nation to develop early warning systems and protect national Internet assets.
4. Self-Governing Commons - Human beings can, in fact, govern the use of common resources more efficiently than hierarchical or proprietary solutions. The Information Governance Community is a demonstration of this fact, and in 2011, similar demonstrations will proliferate around the world and Social Networking itself will mature into online meeting places where people do more than talk - they will govern themselves to produce common work products. An aggregation of people without a deliverable is a media channel. Those same people collaborating on common ideas to produce work are self-ruling corporations and this phenomena will change how people are organized around the world. Any idea or project can be accomplished by self-organizing groups of people with common interests, a governance model, and an incentive structure designed to produce an outcome to effect change.
Five years ago, we formed a Data Governance Council to change organizational behavior and effect change. Achieving Semantic Consistency, Data Quality, Single Views of the Truth, Trusted Information, and Security & Privacy are all IT goals necessary to achieving any one of the above Predictions. Information is changing the world and with information we can change ourselves. However, without Governance, all we have is Data Management and none of what I described above is possible.
Happy Holidays.
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Fog. I thought we were in the clouds as the plane wheels hit the ground like a fighter jet landing on a carrier deck. Visibility was maybe three feet and the fog was so dense the plane parked on the tarmac and we were brought to the terminals in bright yellow buses. Kastrup is so efficient. Clean walnut parquet greets you as you climb up floors to reach the neatly organized passport control, where kind border control guards actually smile when you arrive at the window. In JFK they growl at you and treat you like a criminal begging for mercy to enter a dingy airport that feels more like a mid-50's bowling alleyl. In Copenhagen, the baggage is at the carousel when you arrive and the airport feels like a luxury shopping arcade. Mercedes taxis whisk you into the city, on a sleepy sunday when most of the city is just having brunch. My hotel room isn't ready when I arrive, but I'm happy to have some hours to relax in Vesterbro and wander the empty streets as the fog burns off into early autumn sun drenched splendor. The grass is green, the trees are yellow and red, the sky is bright blue. It takes me two hours to adjust and remember the life I led when I called this city home for 5 years in the 1990's. Bicycles wiz by on their own lanes next to the sidewalks. Late 19th Century apartment buildings hide hip modern interiors. Small, heavily taxed cars conceal a standard living that is the envy of most other nations. What a remarkable governance experiment. High personal income taxes (top rate is 52%), VAT (25%), car tax (220%), and all manner of other taxes are balanced by very low corporate tax rates (26%) and a free labor market, yielding universal healthcare, excellent pensions, and free education through PhD. This country is a net oil exporter, thanks to lucrative North Sea oil platforms, yet produces 60% of its energy needs from wind, solar, and geothermal. While America watched its bridges and roads deteriorate, Denmark built huge public works projects extending road and rail bridges to Sweden, Germany, and from Jutland to Zealand. They unified their rail system in Copenhagen, and deployed high speed rail to Hamburg and Stockholm. They made Kastrup into the logistical hub of Scandinavia, linking the Nordic countries to the EU mainland. It is a remarkable little country, and this week the weather is also wonderful. I'm here to speak at a conference - IBM Software Group Day. I'm in a Global Services track and have 35 minutes to go through some dense Data Governance content. The conference site is a mile from my hotel and I love the walk through Vesterbro, along many sleezy streets west of the Main Train Station that today feel quite a bit better than they were a decade ago when I lived nearby. The conference venue is an old slaughterhouse, now filled with 1200 IBM customers, and some fantastic art works on the walls. The conference organization is fantastic, and everything seems to run as efficiently as the rest of Denmark. My session is just after lunch, and my slides suffer some strange powerpoint virus which mixes them up just short of delivery. But the audience is wonderful and we had a great time going through the discussion. Somehow I finish on time, which is rare, and get some great questions after. Enclosed is what I presented. Its similar to the SIMposium 2010 deck with two new use cases. They worked well in Copenhagen and I have plans for something even better at IOD: Copenhagen SWG Day Presentation The rest of the week is full of customer meetings, but every day I'm here I'm reminded of the life I once lived in Denmark and the part of me that that lies dormant the rest of my life when I'm not here. Its the casualty of international travel, that you learn not only great things about the places you visit but also what you learn about yourself that is only evident when you are there again.
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On Tuesday, I gave a keynote presentation at SIMposium 2010 in Atlanta, Georgia. It was on the last day of a conference at 8:15am. On the best of days, I'm not a great morning person. The last day of a conference is not normally the best of days for a presentation. Normally, at least half the participants are in taxis on the way to the airport and the other half are often exhausted from the content and discussions on the earlier days. When I was first asked to speak, I was not inclined to do it. Keynote or not, 8:15 on the last day felt like a bad proposition.
I could not have been more wrong. First, the room, and it was a huge ballroom, was full with about 300 people. Second, they were awake, animated, and fantastic to talk to. We had a great conversation together, and I completely enjoyed the interaction.
Third, they were not the normal Data Governance crowd. In fact, when I asked how many had Data Governance programs at the start of my presentation not one hand went up. This is the kind of group I love talking to and they are the ones we most need to reach.
SIMposium, thank you for an excellent experience. Many have since requested my presentation and here it is in Flash format. Just click on the link below and it will launch in your browser.
SIMposium 2010: Change is Not Just a Word
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Last week I watched a video clip from President Obama's Town Hall meeting in which Velma Hart, a former Obama supporter living in Maryland, told the President about her disappointment with the lack of change since he took office. She told the President she had voted for change and things haven't changed. He responded by telling her about some aspects of the Healthcare Bill and Credit Card reform that have changed. The contrast between voter Macro expectation and Leader Micro response was fascinating. http://thecaucus.blogs.nytimes.com/2010/09/20/video-obamas-town-hall-meeting/
People around the Country are today unhappy with the 18% real unemployment rate, the spiraling deficit, and many feel they voted for change that they aren't getting. Obama for his part has a problem that confronts every organization implementing change - even the largest policy initiatives have only incremental impacts and the benefits only accrue over extended periods of time. But you can't sell that to voters or corporate executives. No one buys incremental progress (even if that's far better than the incremental deficiencies we all are used to living with). Every organization involved in Governance faces this dilemma - either build a business case for rapid improvement and explain incremental progress later, or train your organization to understand, measure, and report incremental progress and be happy with it. The latter is quite hard to do, completely impossible without technology that constantly reports the problems you are trying to fix and how your program is solving them. You can watch how the former unfolds in this year's Congressional elections and decide for yourselves which way you want to go.
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The IBM Information Governance Council Maturity Model is a model you
use when you don’t know what IG is. Its purpose is to encourage people
to start a program by learning the basics. That purpose remains
extremely valid. If you want to deliver trusted information to make smarter business decisions, this is a great resource.
But we want to build IG into all the projects that people do today
without IG - like getting to know your customers, mining data for
insights, protecting it from abuse, calculating operational risk, etc.
These are real world problems that companies solve today well and more
often not so well.
Often, people have to get things done today with fewer resources than they had yesterday and the best anyone can do is make the problem go away NOW. Information Governance in these solutions are an afterthought at best and therefore the outcomes are only sustainable
for a short time.
In this presentation, I am proposing that our Community work on
building Information Governance new maturity models based on the
business outcomes organizations commonly seek. By building these new
models with the wisdom we already have, we can help advance Information
Governance as a business enabler that helps every IT-based project
achieve sustainable results.
And that creates a business case for measuring maturity more often
and will help make our Community the go-to resource for the latest
know-how, thought leadership, and solutions.
I am sharing this presentation in advance to give the Community time to absorb it and respond with comments and ideas. If you want to comment, please join the Information Governance Community and post your comments to www.infogovcommunity.com. The ideas we generate in Tamaya will be broadcast live on this site and your comments will be incorporated into the meeting topics.
This is a flash file. Smart Governance Forum Introduction
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Please join us for an international crowdsourcing experience!  In May 2006, the IBM Data Governance Council used poster board and sticky notes in an oak paneled room in the Chateau Frontenac in Quebec City to create the categories, elements, and levels in the first version of the Maturity Model. About 35 people participated in that process in Quebec, and perhaps another 50 more in subsequence meetings. On September 14-16 2010, the Council will use social networking crowdsourcing technology to include a global community in a discussion about the Maturity Model - Live! Suggestions and comments from practitioners all around the world will be relayed to the participants in the room. Of course, this venue is awesome, and there is no substitute for live, face to face, communication. But if you can't travel to Tamaya, and spend three fabulous days with The Council in the Desert, you can still tune into the action by going to infogovcommunity.com.
In the room or in Rangoon, you can watch the ideas flow and chime in live or tune in later and add your views.
Either way, what you contribute will impact the community and change the Maturity Model. Synchronous or Asynchronous, this meeting is the beginning of a global dialog on Data Governance Maturity. What we do in the room will make a difference. And what you contribute from your own room will make a difference. Please join us in Tamaya or online at www.infogovcommunity.com to capture the best ideas from the Global Information Governance Community, contributed for the Community and published in an open-sourced IBM Data Governance Council Maturity Model. This is how we innovate!  Steven B. Adler Chairman IBM Data Governance Council
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Boston is America's most European City. Sorry San Francisco. Hills and Fog are not a substitute for Culture and History. The scale of Boston, with its rivers, sea, beaches just beyond the harbor, and easy access to fields, forests, and farms on the periphery make if feel like Hamburg or Stockholm. I've been to Boston a dozen times, but most often for just a day. I know Logan very well. Last week, I discovered Boston for more than a day. A great city! Who knew nice people lived in a civilized city North of New York?! <mock sarcasm> On Tuesday, we drove up from NY and discovered that Boston is a six hour drive up during rush hour and a 4 hour drive back before. On Wednesday, I was a speaker at the MIT Information Quality Industry Symposium in an afternoon session lasting 40 minutes. I arrived a lunch and found the event starting just after in a square building on Amherst Street on the Cambridge campus. About a hundred people filled a large tiered classroom. Many familiar faces and some old friends. We traded "what's up" stories in the lobby on low black sofas while chowing on salty sandwiches and chips. The US Army was the keynote speaker and some army chaps were in the lobby talking about Army things. Data Governance Aficionados were comparing the US Army to the British Army, who had just won a Data Governance Best Practice Award at the Wilshire Conference in San Diego last month. Funny coincidence...all ideas are derivative... My presentation was about www.infogovcommunity.com and The Six Easy Steps to Smart Governance and it was very well received. I like to present. Doesn't matter what mood I'm in before I stand up I always step up about three steps higher when I start talking. Its the audience that feeds me. Not the adoration, center of attention. I need the feedback. Every time I present I learn something new from the audience and its that interaction that makes presentations so much fun for me.  On Wednesday, my audience gave fantastic feedback and it took me all weekend to process what I learned. Information is a Tool. Wow. I can't tell you how many "Information is an Asset" presentations I've sat through where some IT Architect is trying to persuade the audience and herself that Information is an Asset with a value that can automagically be calculated. Someone out there is working on fantastic formulas that will produce THE ULTIMATE INFORMATION ROI CALCULATION and win a Nobel Prize. Ain't gonna happen. Here's why: 1. Value is dependent on price. Information has a value when there is a pricing mechanism and a market in which it buyers and sellers can interact. Movies, Music, News, and Software are all examples of INFORMATION that is sold with prices in markets. Economists have already developed pricing formulas for consumer behavior in markets. Cobb-Douglas Utility Theory captures these interactions nicely. In a market, both buyer and seller benefit so outcomes are equal. 2. Corporations have no internal markets. IT professionals are mostly eager to assign value to Information because Applications and Information are the primary work products of their lives and they want their life work to have meaning beyond their jobs and paycheck. But without internal markets for buyers and sellers to establish pricing mechanisms, Corporations can't assign anything but abstract values to information. 3. IT uses Unit Cost of Labor (Thank You Karl Marx) to assign the value of IT work products. The Unit Cost of Labor identifies the human contribution to value creation. Information is an Asynchronous Asset and it doesn't have to be right to be valuable. IT professionals are so hopelessly enamored with "The Single Source of Truth." IT is a belief system but that doesn't mean that verified information is always valuable. Fact is, quite often lies are just as valuable. Two examples: 1. In the old days, The Department of Labor compiled monthly unemployment data based on the percentage of the workforce that wasn't working. That made sense. Unemployment means "people who want to work but can't find work." But in the 1990's the standard was changed to include only the people filing for unemployment benefits each month. This rate excludes members of the workforce that are working less than 20 hours a week, people who have stopped filing their weekly claim for unemployment benefits, the elderly, and those who have dropped out of the workforce entirely. So naturally, the new number is much lower than the old number. How low? The current rate of unemployed is 9.5%. However, if you include those working less than part-time, those who recently stopped filing for unemployment benefits, and those who dropped out of the workforce entirely the real rate of unemployment is 22%. What's the difference? 9.5% is a recession. 22% is a depression. Information is a tool used by policymakers to achieve a goal and the outcome is not equal. 2. In May 2003, Ebay restated its earnings from 2000 and 2001 but didn't tell anyone. It appears that someone in the accounting department "discovered" a $127 million loss both years and retroactively restated earnings. They hid the restatement in their SEC filings. From a "Single Source of Truth" perspective, one could argue that the restatement demonstrates the value of trusted information. But I don't think that's the truth. I think the reporting of lower losses was a GOAL of ebay and the chart shows that the under-reporting had the effect of protecting the stock from significant declines during a recession. The truthful reporting of the losses during the bull market of 2003 had no negative impact on the stock. So it looks like ebay hid the truth when it benefited them and revealed the truth when it couldn't hurt them.  And who could blame them... after all using Information as a Tool to achieve policy goals is the whole point of Governance. And this is where I say to my IT friends that you won't be successful with Data Governance if you don't give up the hopelessly naive belief that a single source of the truth is a the goal of Data Governance. Data Governance is a Business Process The Goal of Data Governance is to achieve business goals - cutting costs, improving revenue, reducing risk. As we've seen above, the information doesn't always have to be "right" to achieve these goals. That's why Data Governance is a business process and not an IT process. Try to make Data Governance into an IT process like some sort of application development lifecycle and you will fail. Not because the process is wrong. Because the assumptions are wrong. Human Nature is at the Heart of it
This week, my wife and I visited the Bank. Its amazing how defensive retail bankers are these days when talking with their customers. And they should be! Money is free and these guys are charging nearly 5% for mortgages for the best rated buyers. But beyond the mortgage discussion, our friendly banker brought a good idea to us - Debit Cards for our teenage sons. It teaches them responsibility with money, he said, how to budget with what they have. And of course it gives the bank two new debit cards that earn small fees with every purchase, not to mention ATM fees at other banks... But of course, Debit Cards are fact of modern life and as much as we'd like to keep our kids kids and not indulge them in the consumer culture of America yet we need to be modern parents too. So we brought the idea home during the Saturday BBQ dinner in the backyard. "We went to the bank today..." the conversation began. "And we are thinking about getting you both Debit Cards..." At the banking bit, my kids started paying more attention to their burgers than us. Banks are boring. But as soon as the Debit Card idea surfaced, WOW! My kids know what Debit Cards are - its a BENEFIT. As soon as the conversation turned to a BENEFIT for them, they were alert, animated, inquisitive. They wanted to know how would it work, when would they get money, how much, how often, what happens when the money runs out, where can they spend it, how do they get it? How much was the big topic. Kids, all kids, are smart. They began negotiating from the getgo. My wife and I hadn't talked about how much, and they knew it. They wanted to hear what we were thinking. How much? Ben, the oldest, wanted to set the floor for negotiation. "Just what are you thinking?" Net: When benefits are at stake in any discussion, negotiations are competitive and you have to arbitrate between self-interest and the common good. Because you can't afford how much the other party WANTS because WANTS are infinite. That's where Governance comes in. You compare the situational needs of each party to sustainable goals of the program and you make a decision. Based on the goals. In a business process. With Six Steps. Information is a Tool. When you use it its an asset for YOU. Not always for the other guy. Thank you MIT.
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Manila is an ancient Spanish colonial city with American influences and a culture all its own on the rim of Asia. It takes several visits to appreciate that despite appearances and a host of American shops, businesses, and call centers, Manila is not a larger Honolulu, and the Philippine people are not just nicer Hawaiians. The culture, like the heat, is soft and pervasive and gently unique. The foreign influences, like the rain during the early June rainy season, hide behind clouds. Two weeks ago I made my third trip to Manila, and hosted a Data Governance Council Maturity Model workshop in a modern hotel conference room for 25 customers spread across 10 tables of round. In my 8 hour presentation, I integrated the Maturity Model into the Six Steps to Smart Governance using both OpenOffice and the IBM Application Roadmap Tool (ART). Customers used laptops with the ART tool running to score their respective levels of maturity and I explained how the Maturity Model provides benchmarks to assess current and desired states of Maturity from which the Six Steps can be used to govern the use of data in a more scientific and repeatable way. I've given these two presentations often, mostly in shorter conference presentations, but at least 12 times a year if not more. I constantly update my presentation with current examples and anecdotes to keep the material fresh but also to keep myself fresh and avoid the self-boredom of redundancy. But to each new audience, the material is fresh and I'm always amazed at how the Maturity Model transforms conversations from abstract theory to relevant practice. I present five to seven charts then go to the ART tool and we run through three to six sub-categories of the model. Organizational Structures/Summary, Data Quality/Processes, Stewardship/Accountability, Risk Management/Accountability. During these phases I read the content for each level of Maturity and simulate a to-be and desired state by moving the slider bars over. Most of the audience hears my words and ignores my gestures. They are engulfed in a personal assessment of their own Data Governance maturity. Huddled over the laptops, they discuss their perceptions of the model levels, argue about what the terms mean, relate the observed behaviors of 50 companies in North America and Europe to their own habits. It is fascinating to watch! They don't want to move forward to new categories, as each level brings forward painful memories of immature practices, problems long festering needing change, and the re-awakening that they too are immature and can change with an external assessment. Four years after its creation by a group of 50 visionary Data Governance Council members, the Maturity Model still inspires and provides fresh evidence of its value and relevance. It excites audiences all across the world, and as a benchmarking tool there is no comparison. Every time I do this I wonder to myself how this material can excite as it does. But it is the common awareness of ad-hoc, episodic, IT adventures, crises, and budget constrained fixes over decades that motivates people to realize that their situations are not unique and that only systemic solutions will work. After all these years, Data Governance is a real global market and the real work to make it a success just now begins. Thank you Manila.
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