Actually, this was a repeat of a conversation we’d had several times, but he didn’t remember that. It’s ok, we hear stuff when we’re ready to. And we’d been through a lot together, discussing what such a program would look like, and who would be involved, and what they would do. We’d also discussed several times before whether they actually SHOULD do it (after all, just because you CAN do something doesn’t mean you SHOULD.) Still, today he seemed surprised when I suggested putting the brakes on while they considered the political ramifications of starting and - gasp! - possibly failing.

He asked me to capture some of our discussion as conditions that need to be in place for a Data Governance program to be successful in delivering value. Asking whether they are in place is part of any Data Governance feasibility assessment; if the answer is “No, they are not in place,” then the conclusion might be to defer governance activities.

Following is an incomplete list of conditions.

1. A driving reason for Data Governance, supported by high-level sponsors.
Is there concensus about what needs to change, and why, and what will happen if it doesn’t? Are high-level stakeholders supporting the changes that will come with governance?

A sign you’re not ready: key stakeholders say they don’t see a need for Data Governance, and there’s no executive mandate to “trump” their opinion.

2. Political will.

The activities of data governance - setting standards, enforcing them, and resolving issues - are only needed because conflicts and disputes exist. What will happen if key data stakeholders insist that THEY don’t have to adhere to rules? What if they reject the rulings of roundtables, councils, or boards? Before you get to that situation, your Data Governance Sponsor should decide how they would react to stakeholders who reject being governed.

A sign you’re not ready: key stakeholders are not getting what they need from data, but they state they would not be willing to vote against a dissenter in a council meeting. Another sign: mid-level participants state they would not be willing to champion a standard unless their business sponsors provided “political cover” for them.

3. A commitment for participation.
Is there a commitment for time and support by those who will be triaging requests for support, setting standards, and resolving issues?

A sign you’re not ready: those whose attendance will be required at rule-making sessions are routinely double-booked or triple-booked, and cannot commit to being in attendance at required sessions.

4. Project Management/Documentation/Communication.
Someone has to “herd the cats,” facilitate sessions, create documents that summarize issues, draft rules and standards, and meet with stakeholders to mine their knowledge and address their concerns. Without this level of support, you’re likely to have a series of non-productive meetings.

A sign you’re not ready: You can’t get a commitment for enough hours from the right resource; instead, you might be assigned resources who can’t write well, aren’t strong faciliators/mediators, don’t understand the politics associated with data decisions, or are not regarded by participants as as politically-neutral, trusted brokers of information.

5. Knowledgeable data analysis.
Someone has to bring knowledge to governance sessions - knowledge about where data is, how it is actually used, undocumented but followed rules, and points of contact within the organization for understanding protocols, policies, and historical decisions.

A sign you’re not ready: If you can only assign a new hire to this role. Why? New resources (rather than seasoned veterans) are rarely successful in this role; even if they understand their discipline very well, they probably are lacking in tribal knowledge or even where to obtain it.

An important part of configuring a program is being honest with yourself about your organization’s readiness. Just because something is the right thing to do doesn’t mean that RIGHT NOW is the time to do it. 

Back in 2003, when I started the Data Governance Institute, a Google search on the term “data governance” yielded just 67 hits. I could count on one hand the number of people I could call to have a passionate discussion about this obscure subject. But look at the difference seven years can make. Now, it’s not a question of whether organizations need data governance.  Duh. Do they have data that flows across multiple systems and processes? Of course. Do they want rules to specify how the  data should be structured, shared, accessed, and used? Of course. Do they want controls to enforce those rules? Of course. Do they want clear rules of engagement that show how stakeholders make decisions about those rules and controls? Of course. Now, in 2010, it’s a given that organizations of a certain size want and need some form of formal data governance.

Now, the question is more about how much governance, and what form it should take. The focus is on making it actionable. The concern is about demonstrating value. The skill is in avoiding bureaucracies and bottlenecks. The vision is seemlessly embedding governance into projects, processes, and practices.

In 2010, I predict we will see new emphasis on folding governance into business processes and on highlighting the governance steps hidden within data management practices. We’ll see a new attitude toward accountability, as it becomes acknowledged that just most business roles have fiduciary, administrative, and security responsibilities, so do they contain stewardship and governance responsibilities. 

And we’ll see new opportunities to bring clarity and understanding about governance to our stakeholders. I think we should take advantage of these opportunities. We should create ”teachable moments” out of news stories and events in our work lives. I’ll start.

Hey everyone. You know how everyone’s talking about the way President Obama tore into twenty high-level officials about their inability to connect data points and avoid the attempted Christmas day airline bombing? You know how the press is using the word “silos” to describe the collections of unconnected data that held the clues about the bomber? Here’s our chance! Let’s remind everyone that good intelligence - good analysis of good information - takes more than a new policy. The data has to be shaped and structured and standardized in certain ways to be shareable. And that doesn’t happen on its own - it happens as a result of the rules and controls that are part of data governance. But its not enough for the data to be in a shareable format. The groups that manage that data have to agree on processes and practices for sharing it and resolving any issues about the data - another part of data governance. Here’s the bottom line, world. Good data governance alone won’t result in good intelligence. But you’re not gonna get good intelligence without good data governance. So here’s what Obama needs to tell the intelligence community: Keep on managing all those silos of data - they need it. But start applying better governance to the extended data environment. Lives depend on it. 

(For those of you who are trying to remember where you’ve heard Friedman’s name, he’s the author of ”The World is Flat: A Brief History of the 21st Century” and he’s won several Pulitzer Prizes.)

The metaphor Friedman uses is the different levels of commitment one brings to baby-sitting a child versus aogreeing to adopt the child. Friedman was talking about commitments between two countries - and I don’t want to go there in this blog. But I couldn’t help noticing how useful this metaphor could be to those of us who work with enterprise data assets.

We all face a similar framing situation on an ongoing basis, whether we’re asked to create/refine/review an enterprise data strategy, to implement a data governance program, to advise data stewards, or to help enterprise data management (EDM) or enterprise information management (EIM) programs build strategies, agree on tactics, prioritize efforts, or solve a particular problem.

Here are the questions inherent in all of the above situations as they have been historically framed: 

Who “owns” the data?    Who “owns” the problem?   Who “owns” the solution?

Two problems with this:

1. A conceptual problem - haven’t we all agreed, at least in theory, that the enterprise owns data with an enterprise impact (that is, Business owns data, not IT)!!!

2. A practical problem - even in organizations that agree to #1, I’ve still seen discussions grind to a halt as implications are explored. After all, there usually isn’t a budget line for “the enterprise.” Instead, one or more groups within the enterprise are going to get silo-slammed with negative impacts to their budgets, resources, applications, processes, etc.

So we have a natural tension here: a silo wants to “own” data when it’s to their advantage. But they don’t want to own every problem that is associated with that data. And you can’t blame them.

So the issue resolution framing metaphor of *ownership* is problematic when dealing with cross-functional data issues that impact one or more aspects of gaining access to usable information required to address business needs.

What about a *child care* metaphor?

What would happen if we posit that

• all data belongs to the enterpise

• certain data has been “adopted” by functional groups

• when that data “leaves the house to go to school or public areas, etc.” it is now part of additional systems & networks of activities and must agree to abide by their rules and  work within their protocols

• unless the journey has been “child-proofed” with strong controls, the data may require ”baby-sitters” in the form of data stewards, custodians, and others

• sometimes, additional facilitators are required for naturally chaotic environments such as field trips. (Now we’re stretching the metaphor to include issue resolution sessions, project prioritization analysis sessions, standards-building exercises, and the other types of “special events” that data governance teams get asked to facilitate.)

Now continue down the childcare metaphor path. As a parent, when I sent my children to school, or dropped them off at a babysitter’s house, I was not giving up my parental rights. I was expecting the school/babysitter to address issues that fell within the scope of their system, according to rights and responsibilities we had agreed upon. If an issue had a multi-system causes or impacts, then I expected to be apprised of it, and to be invited to a parent-teacher conference so we could agree on a solution that would have acceptable  impacts within all systems.

(yes, I know it’s more like networks than systems, and I really like the net-centric metaphor. but let’s save that for another discussion, ok?)

So… how would we address data-with-behavior-problems or data-we-can’t-find or data-that-won’t-answer-our questions if we were using a child care metaphor rather than an ownership metaphor?

What would we expect from ourselves and participants if we were invited (or invited ourselves) to take on the roles of 
those-who-plan-issue_resolution_sesions, or
those-who-align_and_prioritize-policies & standards & rules,
those-who-ensure-unbroken-chains_of_custody-for the child

You know, I’m going to have to give this a buncha thought.

- As a mom, I think I have a good idea of what good governance of my kids looks like.

- As an industry analyst, I get asked constantly by analysts/vendors/practice leaders/execs/program leaders/stewards/stakeholders  how we should be framing the next era of data governance in a way to make it operational and focused on performance and conformance and managing risk.

- As a practicing consultant, I know I’ve been willing to babysit other enterprise’s data, but I sure wouldn’t want to adopt it. I wonder if THAT is the sentiment I’ve been hearing from department/silo leaders who are hesitant about participating in data governance programs?  Hmmm…. 

Thoughts?

BTW, following is the quote from Friedman’s column that made me want to write this blog entry. I suggest you read it this way: change the topic under discussion (US levels of commitment within Afghanistan) with another topic (how should Data Governance help participants frame data-related discussions. Then let me know if you agree that we would be doing a service to mommy-and-daddy (the enterprise) if, before we accept a baby-sitting engagement, we ask them (or the silo leadership that has agreed to raise their data babies for them) the questions Friedman lists below.

“Before we adopt a new baby — Afghanistan — we need to have a new national discussion about this project: what it will cost, how much time it could take, what U.S. interests make it compelling, and, most of all, who is going to oversee this policy?” 

What does this have to do with Data Governance? Most programs I know have a three-part mission similar to the governmental model. One part of the program collects/makes/aligns rules (policies, standards, business rules, data definitions, etc.). Another governance mechanism deals with conflicts and non-compliance. And a third effort provides services to data stakeholders and works to embed rules and controls into business, IT, and data management processes.

It doesn’t really matter how big or small your program is, or what data you’re working with, or the ultimate goals of your program. Whatever your scope, you need to address all three missions if you’re going to create sustainable success.

Here’s a thought… do you think info-savvy President Obama just might “get” the concepts of Data Governance?

This is changing, thank goodness. And I am LOVING IT! After all, building rules (policies, standards, business rules, DQ checks, etc.) into processes and controls is key to sustainable success. And having technologies that can be used by non-technical Data Stewards as well as IT staff are key to making substantial improvements to data.

The fine folks from ComputerWorld and Kalido have asked me to join them on January 28th at 11 AM EST (GMT-5) to discuss this topic. We’ll be focussing on three uses of technology - to capture/define rules, to build those rules into workflows/processes, and to track changes to data in an audit-friendly way. Cool stuff. We’ll also take a few minutes to talk about the DGI Data Governance Framework and Data Governance processes.

You can get more information on the Data Governance Institute website or at the webinar registration page.

Had one of those moments today. Here I was, sitting in my sunroom in Florida, looking out the windows over my deck at the bougenvilla taking over the little building in my back yard, the brilliant orange fire vine creeping along the phone wires, the beautiful clear January sky behind my avocado tree. On the desk in front of me was my cell phone, on speaker.

On the line were Data Governance & Stewardship leaders in California, Minnesota, North Carolina, Virginia, other U.S. states, and even Scotland! How cool was this!

It was a weekly Knowledge Exchange of the Data Governance & Stewardship Community of Practice. The topic of the day was selling Data Governance to executives. What was interesting was that the dozen or so people talking came from a variety of verticals, but they all had the same challenges. And some of them had great tips to offer. (Topics: hard benefits versus soft benefits, story telling, making dollars quantifiable, measuring the value of work avoided, getting participants to go on the record.)

We’ve already scheduled a follow-up as well as a series of future discussions on organizing programs, setting roles & responsibilities, baking governance into processes, Data Governance communications, working in an SAP environment, and other topics. Probably some of the same folks will be involved, but we get a mix of folks, depending on the topic. Chances are, there will be multiple time zones involved in every discussion.

Me? I learn from every one of these I’m involved in. It’s cool to see what everyone has in common, as well as what makes one program unique, and another one especially successful.

And it’s waaaaay cool to have those moments where I realize I’m having a “small world” experience that was only possible on “Star Trek” when I was a little girl…

As memory serves, I wrote an ode to my dear friend and colleague Anne Marie Smith, PhD, who has been pondering a question that I know many of us have been wondering about. What are our obligations, as people who manage and govern data, regarding the usage of that data?

Yes, yes, we’re supposed to make it fit for use. But what if our users want to do something with it that violates a corporate policy, or an ethical principle, or a standard, or a process. What if they (or others from the business) don’t understand ramifications, but we do? Is it time for Data Governance workers to serve in some sort of advisory role?

Anne Marie will be sharing her ideas during a “Meet the Expert” session of the Data Governance & Stewardship Community of Practice (www.DataStewardship.com) on Tuesday, Jan. 27, at 11:00 AM EST (GMT-5). It’s free, but registration is required. I hope you’ll join us.

I know I have a few questions for Anne Marie regarding potential roles for people in our field as the world works its way out of the economic crisis. And I know she has some thoughtful ideas about other ramifications of knowing what we know.

By the way, if you’re wondering if this is “the” Anne Marie Smith - yes it is. Principal Consultant for EW Solutions. Many leadership roles in DAMA. Editor of the  Real World Decision Support journal. Involved in the EIM Institute. Presenter at many many data-related events given by MIT, DAMA, Wilshire Conferences, etc. Highly involved in the Data Governance & Stewardship Community of Practice. One of the most thoughtful people I know. I’m sure this tough concept is gonna seem more traversable after she speaks.

At every Data Governance conference I’ve attended, at the dinner tables, in the lounge and on break between  presentations and workshops, one question invariably pops up. It’s usually asked in the first person; some variance of “How do I sell Data Governance to our executive management.” Attendees are hungry to hear hints from the ‘I’ve been there’ people on this topic. I’ve even heard attendees announce after the resulting discussion, ” I’ve received more value from this conversation than from the rest of the conference put together.”

This is why I thought I might mention the up-coming Data Governance & Stewardship Community of Practice (DGS-COP) on-line event on this topic, coming up Thursday, Jan 22, 2009, 11:00 AM until 12:00 PM EST (GMT-5.)

This will be a discussion in the DGS-COP Knowledge Exchange series, and is one of the last events in this series open to non-members as well as members (available at no charge under the DGS-COP ‘Response to the Economy’ policy for events through January.)

I just looked at who’s registered to attend; I see several familiar names I know have a lot to contribute. Of course, Gwen will be moderating, she’ll chime in with some incites as well. If you are at all interested in developing your program’s executive support, I can’t urge you strongly enough to consider participating.

These events are limited in attendance, but as of this  blog posting, there are still some slots available.

BTW, if your organization’s policy restricts your participation in public forums, you are more than welcome to  email me at reese.thomas@datagovernance.com . I’ll be glad to ask your questions for you;  you can sit back and listen anonymously.

Here’s the link  for more information

So now thousands of us are working within our organizations to establish governance. We’re doing the right things, although maybe not at the pace we’d like. We’re agreeing on common activities and responsibilities. Frameworks are being used to help people communicate and stay in sync. Things are good.

So why don’t I feel great?

It’s because of the world’s economonic crisis and what we all might have done while it was all brewing. Yes, I understand there is much that none of us could have changed. We’re not in a position to stop fraud and crazy Ponzi schemes. We’re not in a position to stop leaders from taking crazy risks. We’re not even in a position to stop corporate leaders from taking calculated risks that might just turn out bad.

But we are - or should be - in a position to help leaders and other users of information to understand how well they should trust the information they’re using to make critical decisions.

The truth is that many of us know - and have known for a long time - about problems with the data we work with. We know when the data is polluted, or incomplete, or just wrong. We know when data quality hasn’t been tested (meaning that all we have are assumptions about how good it is). We know when users of information have all validated data definitions - and when they haven’t and instead are assuming they know what a particular report field means. We know where streams of information from various sources converge into a big repository, and we know when those data streams have been carefully sorted into trusted sets of information and when, instead, we really aren’t sure what we have to work with.

We know so much. And yet we haven’t made sure that the people making world-changing decisions understand whether they’re basing decisions on trusted information or on assumptions.

And that’s just not right.

Yes, I understand corporate politics. (Believe me, I have the scars.) I understand how hard it is to push information up the executive ladder. I understand what happens to people who break protocol.

But many of us do have access to executive users of information. (Or we have the ear of those who have access.) I propose that 2009 be the year of Proactive Data Governance. Let’s use our voices to make sure that leaders understand key facts about the information they rely on when they’re making critical decisions.

I suggest that we keep our messages simple. Let’s all tell our top-of-the-foodchain data users the same thing until they get it.

Let’s tell them that they need to know the answers to 3 questions concerning their data, and that we as Data Governance leaders are ready to help them get answers. Let’s tell them that they should know whether the information they’re relying on

1) Comes from trusted and controlled sources
(or the alternatives: we know that the source is suspect, or that nobody knows because lineage hasn’t been documented and analyzed)

2) Whether it means what EVERYONE thinks it means
(or the alternatives: we know there’s confusion, or that the data definition validation work just hasn’t been done)

3) Whether the data quality is “good enough”
(or the alternatives: we know it’s not, or that it hasn’t been tested, or that rules haven’t been established to say what “good enough” means).

Maybe we can’t do anything about the situation that got us all here. But we can be part of the solution. We can make sure that decision-makers know the right questions to ask, and we can help them get answers. We can help them understand whether they are basing their crisis-recovery decisions on trusted data or merely assumptions.

Now let me stop a few of you who are thinking that my three questions are too simple - you could probably add another half dozen to the list. And you could add a bunch of words to the simple questions:

1- Trusted source?
2- Agreed-upon definition?
3- “Good enough” quality?

Yes, you could cloak these with techno-speak, use words like “profiling” and “lineage” and “metadata repositories” and “taxonomies.” And when you’re talking to techies, you might want to do that.

But if you make this too complex, you won’t get executive attention.

So here’s my suggestion:

Let’s all tell our leaders the same simple message, and let’s use simple, non-technical language to get their attention, and then (if they respond with interest) let’s help them make the decision to proactively do/fund what it takes to get the quality of information they need.

Let’s all send the same message:
If you have answers to three questions about the information you need to make critical decisions
(1-Trusted source?   2- Agreed-upon definition?    3 - “Good enough” quality?), 
   then you’ll know whether you’re basing your decision on solid data, 
      and you can be more informed about the risks you’re taking.  

Right now, around the globe, leaders of corporations, governments, not-for-profits, educational institutes, and other organizations are trying to decide how to react to the current economic crisis. They’re trying to decide how to be proactive, to avoid making future mistakes. They’re pulling report after report after report, looking at their data while they ponder critical decisions.

What do you know about that data? Even more important, what should THEY know about that data? What questions should they ask?

Let’s do what we can, troops…

Back in the mid 90s, Bob and I worked for the same systems integration firm, CIBER. Although I was based out of Florida and Bob was based out of Pittsburgh, our paths crossed frequently as we consulted on national projects, contributed to the company’s infrastructure, and participated in communities.  

Bob and I discussed several shared interests other than data: parenthood, Knowledge Management, and publishing.  Bob, as many of you no doubt know, founded the amazingly successful TDAN (the Data Administration Newsletter) in 1997. In the late 80s, I’d co-founded a  magazine, so I was well aware of the workflows, stakeholder care, and information governance required to sustain a publication. It was fun to compare stories with Bob.

A few years later, Bob and I (along with Martha Dember, who also worked for CIBER at the time) joined forces to help bring formal Data Governance to a large theme park/resort in Orlando. Almost no one was doing formal Data Governance at the time, so it was great to have peers to exchange philosophies with as we helped this company address information governance, metadata, and data integration needs.

Since then, Bob and I have had many, many discussions about Data Governance. Generally we agree on guiding principles; sometimes we have different perspectives. But always, we’ve shared a belief in the value of good governance, and we’ve shared a passion for this growing field. I’m personally thankful for Bob’s countless contributions - articles, training, consulting, conferences. And I’m very thankful that for all this time, this cool guy has been my friend.   

Now, thanks to their efforts, practitioners, academics, and thought leaders have many opportunities to come together to discuss the growing discipline of Data Governance & Stewardship. Davida and Tony collaborate on a series of conferences such as the Data Governance Conference in Europe, coming up in Feb. 2009, and the Data Governance Annual Conference in the U.S., which will be held again next June in San Diego. And since their initial successes, others across the world have taken up the banner, also. So there are now many opportunities to get under one roof with your peers to discuss the ins-and-outs of this growing field.

But it wasn’t always so. Back when Davida had the forsight and courage to be the first program director for the industry’s first Data Governance conference, there wasn’t even concensus about what DG meant - much less what it did, and what it could accomplish. But Davida saw a need, and she had an extensive series of discussions with those of us working in the field (thought leaders and early adopters) to get a feel about what was going on and where efforts were headed.

Sure, now there are studies that show that 80-90% of organizations say they have or need formal Data Governance. But in the beginning there were no surveys. There was Davida, researching everything there was about Data Governance & Stewardship on the web, and connecting in person with many many people to identify trends, drivers, and best practices.

But I shouldn’t put this in the past tense. Davida continues to be one of the hardest-working people I know. Maybe you know her, too. Or maybe you’ve attended one of her events and haven’t said hello. (Next time, say hi!) Or maybe you participate in a different set of seminars or events put on by others. Regardless, there’s a good chance that something Davida has done has helped get you there.

So now I’m thinking about my paternal grandfather, who emigrated to the U.S. from Wales in 1929, followed shortly by my grandmother, father, and aunt. (Yes, I’m talking about “Scotty the Welshman” from my book.) Grandpa and Gramma Thomas became proud U.S. citizens and lived over 50 years in their new country, but they always retained their Welsh identity and menu preferences.

Grandpa loved his fish and chips. He and Grandma would talk about how they had to eat broiled fish and boiled potatoes because of the rationing during World War I, and how nice it was to have fried potatoes any time they wanted them.

But Grandpa never called them fried potatoes or even french fries. They were chips. And when a young waitress at a lunch counter asked him if he wanted chips with his ham sandwich, he always said yes. It was Gramma who would have to call the young waitress back and explain that he wanted french fries, not Lays potato chips. You see, even if Grandpa had just had an extended conversation with the waitress about how much he wished they had “fish and chips” on the menu, but he’d settle for a “ham sandwich and chips,” Gramma just knew that the waitress probably didn’t make the connection.

I think about them sometimes when I’m embroiled in a metadata discussion about how much documentation is really needed and how explicit data definitions need to be. 

Yes, even with a holiday coming up, I’m still talking about data and metadata most of the day. The past few weeks, many of my discussions tend to be with members of the Data Governance & Stewardship Community of Practice, and there tends to be an ocean between some of us. (I mean this literally - how cool it is to hear my grandparents’ accents in some of our community members… )

The answer to “how much documentation,” it seems, depends in part on whether the users/beneficiaries of those data definitions all have the same cultural background. It depends on whether their frame of reference includes two continents and and ocean between, or just a lunch counter and some familiar red vinyl stools.

And it depends on how they would react if they ordered french fries and got potato chips, instead.

Along the way, I discovered others with similar feelings and great passion. One of the coolest things about my life in the last few years has been getting to know many of them. And so, in the spirit of Thanksgiving, I’d like to send some shout-outs to people in the industry that I’m thankful for.

I’m going to start with the inimitable Jill Dyche for several reasons. One, because she’s an amazing writer. Boy, can she crystalize a thought! I absolutely love reading her blog.

The second reason is because of a certain blog entry she did recently, in which she fessed up to a poetry mishap in her youth. It inspired me to put together a little verse in response. I left it as a comment for her, but then I thought I’d print it here, also. Just be sure you read her blog, too, folks.

And the third reason I’m shouting out to Jill Dyche first is because we share that special, special bond that only comes when one of you (it was me) says something incredibly embarrassing (it’s too bad to ever print. trust me) in a very public place (you don’t want to know) and the other one (her) hears it, enjoys it, and then actually doesn’t repeat it in print! So when we run into each other at conferences, we sometimes have a little tweak at each other.  I didn’t really get a chance to hang out with her the last time I saw her, so instead, I thought I’d send her this little poem.

I think that I shall never say

Some things as well as does Dyche.

Her use of metaphor, you see,

And pithy points, and simile,

Provide a smile, a chuckle, laugh

That business folks and IT staff

Can use to bond while they review

Ideas - some old, and some brand new -

That help them manage information

From acquisition (or creation)

Through a lifecycle, to that feat

Where info’s archived or delete

-d.

(I know, I know, I sound like my gramma when she talked about the first time she stepped onto an airplane and how miraculous it was. I heard that story several times, back in the 1970s.)

Which brings me to the topic of saying No. 

I came of age in the 70s, a time when double standards were being challenged and we young women were receiving very mixed messages. “Just say no!” was the conventional wisdom we heard from our grandmothers and others. On the other hand, we were told, in this modern age it wasn’t a requirement to always say no. It was our choice.

But both sides agreed that it was sad if a girl couldn’t say no. That was a sign of a real problem.

Fast forward twenty years. I was learning to be a consultant from a very wise, very practical,  and extremely ethical man. Tony taught me that a consultant should rarely say no. (He was talking about work requests, of course. Get your mind out of the gutter.) Instead, Tony said, a good consultant learns the art of saying “yes, if…”

Q: Can I have this early?

A: Yes, if you’re willing to either spend more money or give up some functionality/quality.

Q: Can we skip user testing?

A: Yes, if you’ll give me a written statement that you’ll hold us harmless from all defects, and that statement is validated by your boss.

Q: Can you do twice as much work in the same time?

A: Yes, if you pay for extra resources to do the work (and by the way, it will be more than twice the resources, because there’s additional costs involved in bringing them up to speed and coordinating efforts).

Q: Can I jump off the roof?

A: Yes, if you’re ok with breaking your leg when you land.

I thought about saying no several times this last month. At the Data Governance and Stewardship Community of Practice<, I’ve been facilitating a series of Knowledge Exchanges, and a topic that keeps coming up is whether your program should say no to requests for help - and if so, when and how.

One participant had some sad “lessons learned” to share regarding a program that kept saying “yes” although they couldn’t get the resources to complete tasks.  Some other participants shared guidelines for saying no.

Me? I was torn. Part of me wanted to pass along Tony’s lessons about saying “yes, if.” Another part of me was busy trying to remember the name of the character in the musical “Oklahoma” that sings the song “I’m just a girl who can’t say no.”

And now I have that song stuck in my head. Oh, well.

Feel like listening to it yourself? Here’s a YouTube of Amanda Palmer with the Boston Pops.

Their discussion makes me think (for the hundredth time this past month) about things I wish I’d said more strongly. more loudly, more forcefully to corporate executives this past year.

Here’s what I wish I’d said in a way that everyone understood:

If you’re going to make critical business decisions based on information, then you’d better understand how ”fit for use” that information is. You should DEMAND good answers to 3 questions:
 
1. Do I know and trust the source of this data (that I’m using to make critical decisions)
2. Does the data mean exactly what everyone thinks it means?
3. Is the data “good enough” for what I’m using it for?

If you don’t have good answers to these questions, then you’re making decisions based on assumptions. So, if you still have decisions to make, then ask these questions. Demand answers. Don’t get distracted by the fact that answers may rely on complicated technology-centric efforts. Instead, maintain focus. Recognize where assumptions lie, and let your data management folks help you convert those assumptions to actionable knowledge.
 

Reese Thomas

Tom’s latest guest post certainly raises the question of what part did data practices play in this current situation. Bad decisions can, and do result from many other factors than the quality of information available. Data Governance could be viewed as an organization’s immune system.

A fully implemented and mature Data Governance program certainly will not protect an enterprise from risky management decisions; the healthiest immune system will not offer protection for risky behavior such as unprotected promiscuous sex. A compromised immune system will make it much more likely that even a casual contact with a flue carrier will result in transmission, a healthy immune system will help minimize both the rate of transmission, and the severity of the infection.

It could be argued that in many of these cases, plenty of warning signs were in place, I don’t know if the extent that data practices contributed to any one company’s demise could be determined, or how much were just bad decisions. 

Still Tom, in many of the cases I suspect you are right, data practices were a major factor in bad decision-making, and even for the cases that the data was not the (or even a) major factor…

Any physician knows, the better the overall health of any patient, the better the odds of survival for any cataclysmic health event. And that’s certainly where governance comes in. 

Guest poster Tom Jesionowski, Prime Data Consulting LLC

These days you cannot open a news portal, magazine, or turn around without hearing about the markets and the crisis in confidence in our markets. I can’t help but wonder what went on behind the scenes and ask what role poor data governance played? Mortgages being bought and sold three, four, or five times, and the data associated with them being merged over and over. Each time details getting dropped or obscured by undocumented ETL and data movement processes.

At the end of the information chain, the data was merged and aggregated forming the foundation for the derivatives sold and resold in the market. At the end of the day (and the boom) ultimately it was in data that we trusted. Data that was so far removed from the real assets that it became nearly impossible to fully evaluate the risk of what was held in the portfolios. The true magnitude of the risk was hidden behind poor data governance.  If the current crisis in confidence doesn’t make the case for data governance then what will it take?

 I’ve been thinking about this a lot. Surely the guy didn’t mean it - I’ve never seen a program where the goal was to keep users from getting the information they needed. Rather, it was about the responsible use of information - making sure that info presented to the world as complete, accurate, and fit for use actually was.

And don’t get me started on “The War on Drugs” - just don’t. 

But I will say that if I were to use a drug metaphor to discuss Data Governance, it would be more about the controls that you’d expect to be in place in a hospital, where the movement of a pill from the pharmacy to the patient follows a controlled path. The mission is to get every patient every drug they need, with the assurances that no one gets hurt along the way.

 After all, what would you think of a hospital that dumped all its drugs in a pile in the lobby and announced “Come and get it!” on the loudspeaker? (Actually, that would make a funny scene in a movie, wouldn’t it?)

 But in real life, we have horrible lessons to learn from recent events where babies died because the wrong strength blood thinner was administered to them. The drugs were lawfully administered, but what was in the vials wasn’t what medical staff thought it was. Terrible harm came from this.

 Well, terrible harm can also come from using information that means something other than what you think it does. Should you be prohibited from accessing it? Possibly, possibly not. Should there be controls so that you (and the people you’re feeding it to) can trust what’s in it? Absolutely! Is it ok to give you a key to the cabinet with the caveat to “use at your own risk?” Maybe - that is absolutely situational.

The real discussion here is how we serve the needs of patients when there is no pharmacy building (or no data mart, or not the data you need in the mart as it exists now). Do you let the patient die? I don’t think so. Do you turn them away, to find what they need in the dark alleys of ODBC territory? Risky business, that approach. Or do you set up a booth in the corner of the waiting room, where folks who understand medicine can hook up users with what they need, while keeping them from killing themselves.

Again, if this were a movie, that would be a funny scene. ”Doc, Doc, I need to mainline some customer data! Give me a hit, stat!” The only question I have is… what kind of data would be those little magic blue pills? 

If your name is Steve Jordan, and if you don’t want a surprise spoiled, stop reading.

For the rest of you, Steve is one of my dearest friends, and I happen to be bringing him a little gift from London, where I’ve been speaking at the DM&IQ conference. His gift is a mug with the words Mind the Gap - a phrase you see all over the London Underground (subway system). It’s printed on the platform and announced on the loudspeaker to remind riders to avoid stumbling on the gap between the platform and the subway cars.

“Mind the Gap” is also the name of a 2004 movie  by Eric Schaeffer that members of Steve’s and my Sangha watched together a few years ago. It’s a quirky film with seemingly unrelated plotlines and characters that finally come together. Fun and also thought provoking.

Steve and his wife Johanna Jordan (who is special to me beyond words) have had many thought-provoking conversations. We joke that we’re all in the same business: he’s a child psychologist, she’s a family therapist, and I work in Data Governance. Many of our discussions have been about Buddhist psychology.

The phrase “mind the gap” has meaning there. For about 2,400 years followers of this psychology (the idea that it is a religion is a modern invention) have known what brain imagers and scholars in cognitive studies have just started validating: there is a tiny but noticeable gap between when a feeling arises and when a person makes a decision to act on that feeling.

The ability to recognize this gap can help one choose a path other than the default, unconscious choice -  a path that might reduce suffering in the world (or at least in an individual).

So what does this have to do with Data Governance? Over time, organizations and individuals have chosen responses to data-related triggers such as issues, conflicts over standardization or integration, and opportunities to define or align business rules. Over time, if an organization chooses the same response repeatedly, it builds up a sort of “muscle memory” and that response becomes automatic - even when conditions change and it’s no longer the best choice.

So one thing that Data Governance professionals do is learn to recognize those situations. We learn to identify  the gaps between triggers and responses, and we help data stakeholders prolong the gap so that thoughtful, mindful analysis of useful options can take place.

Of course, to be successful, these leaders have to be mindful themselves. After all, when dealing with stakeholders who have inherent conflicts of interest (and human personalities), feelings such as irritation and anger are bound to arise occasionally. We have to mind the gap within ourselves so we choose personal actions in response to those feelings that won’t result in new sets of suffering.

Yikes. Emotional, passionate Gwen is still learning this. Now I’m thinking I should have bought a mug for myself, also, so I can fill it with a nice cup of chamomile tea to take into contentious meetings. Hmmm… maybe I can order one over the Internet…

Gwen’s currently on the way back from London, where she’s been cavorting, I mean interacting, with industry thought leaders at the Data Management & Information Quality Conference Europe 2008. She will undoubtedly gift us will some tales from ‘across the big pond’ when she returns, however…

I had to comment on an interesting, thoughtful, compelling and but somewhat disturbing article on BeyeNETWORK by John Myers, ‘Legalizing the Spread(Marts) of Business Intelligence. He draws a parallel between the thirst of power users for data, and the war on drugs. If you haven’t read it I’ll wait…

If you still haven’t read the article, let me give you a couple of excerpts that, while admittedly taken out of context, illustrate some of what I find disturbing. Please keep in mind this article is a thoughtful look at a very real and common situation, not a mindless rant.

“For many years, inflexible data governance organizations and IT departments have put a stranglehold on the development, distribution and consumption of analytical business intelligence applications – or at least they thought that they did.”

“Strident and driven, data stewards can be orthodox or inflexible in their definitions of and application of technologies.”

Wow.

Inflexible.

Stranglehold.

Strident.

Not very semantically flattering to the Data Governance practitioner, and not really evocative of the qualities that most of us would look for in a Data Steward.

It’s the fact that practitioners of a discipline that relies so heavily on communication skills to achieve objectives are regarded in these terms that I find disturbing.

Sometimes, your organization’s governance program may put limits and controls on users. How transparent or intrusive your program will be to the user will depend on many factors; your program’s focus, how the different types of stakeholders are represented, as well as how well the program was designed and implemented. If you happen to be a Data Steward, how stakeholders perceive your efforts to implement these controls depends on just one factor.

Communication.

Use your communication skills evangelistically, to educate and inform. It’s almost inevitable that at some point a stakeholder will be effected by a control; if you are the steward with whom they interact with, it would be nice if the stakeholder were cognizant of the reason for that control.

And not simply think of you as strident.

I admit that I wasn’t always crazy about all of Buffett’s early stuff, although “Come Monday” (see & hear  it on YouTube here) went to my heart the first time I heard it. Oh, the aching in that tune!

Swaying to the song, I’d try to imaging what it would be like to be a traveler, to be states away from someone I loved. I couldn’t really imaging at that time what a life with lots of travel would be like, but I (and millions of others), could certainly connect with the longing, with a feeling that “come Monday, it’ll be all right. Come Monday, I’ll be holding you tight.”

Fast forward to the mid nineties. Reese has been playing and singing for decades, building an exciting entertainment career where sometimes he’s the main attraction, and sometimes he’s supporting chart-topping stars. And me, I’ve started working in the world of data and IT, and I’m dating Bruce Cone, the man who would become my husband and stepfather to my children.

Because Bruce came across a bit formal at work, it surprised many people (including me) to discover he was a ParrotHead. Bruce loved Jimmy Buffett music passionately. So when my career in Data Governance exploded in its own little way, and I found myself on the road a lot, it was Bruce I was thinking about when I hummed “Come Monday,” when I was aching for the end of a gig and the holding tight that meant ”it’s be all right.” 

And it was those many times that Bruce and I had listened together to “Changes in Latitudes, Changes in Attitudes” that helped me pay attention to one of the real benefits of travel: the chance to experience changed perspectives.

Bruce passed away suddenly three-plus years ago (something I’m just now able to talk about). And when I travel now, it’s with my daughter, son, friend Gail, or - more often - alone.

It’s those trips when I’m on my own that I’m most sensitive to changes in attitude. For instance, today I’m about to start on my way home from London, having spent some time here for the DM&IQ conference. I got to spend lots of quality time with peers here - time to share facts, opinions, and attitudes. It is so very useful to hear about different approaches to information management and data governance. To compare notes on attitudes toward decision making, power versus persuasion, encouragement versus enforcement, and consensus-based activities versus command-and-control protocols.

I’ve come to treasure these exchanges. In the past 8 months, I’ve been at events in London, Berlin, Toronto, Minneapolis, San Francisco, San Diego, Raleigh/Cary, Chicago, Phoenix/Scottsdale, Boston/Cambridge, and Las Vegas (plus visits to client sites). I’ve had the privilege of talking in depth, in person with practitioners from every continent except Antarctica.

And guess what? With every  single change in latitude or longitude, I’ve found my own attitudes being adjusted in some way. Mostly I’ve felt myself becoming more inclusive, more flexible.

Maybe at one time I thought in absolutes - that there was one “right way” to do something. But rigid attitudes don’t make sense anymore when you hear success stories from around the globe that highlight polar opposite approaches that all succeed in meeting similar goals. Instead, you start “collecting” those approaches, and you concentrate on mapping them to the cultural and environmental factors that will influence what approach will work, and when, and under what conditions, for what types of organizations.

So what’s the moral of this story? I’m not gonna tell anyone to start listening to Jimmy Buffett. After all, you either think “Cheeseburger in Paradise” is funny, or you don’t.

But if you’re feeling like your own thinking is a bit rigid these days, you might consider a temporary change in latitude. If a virtual escape is all you can manage, please dial into one of our Knowledge Exchanges to exchange notes with Data Governance practitioners from around the world.

And if real-life travel is an option, Key West is always nice this time of year.

Dad was a good father and a good psychologist, who eschewed lucrative careers in Industrial Psychology and private practice to help thousands who came through the Florida Alcoholism Treatment Center in Florida, where we moved from Indiana when I was a kid. Dad was also an extraordinary teacher.

As anyone who knew him would attest, he was always ready to pull out a scrap of paper and pen, then diagram out the essence of a tricky problem, a  complicated concept, or an intricate idea. Dad told me on many occasions that “if you can’t describe something on the  back of a used envelope, you’re not ready to talk to others about it.”

If I’ve ever explained anything succinctly that has helped you or your program, you can thank my father and his back-of-the-envelope training. Here’s to you, Dad.

* * * * *

A postscript.

I wrote the above in a notebook, to transcribe into the blog software when I got back to my room. When I was done, I got involved in a discussion with a group gathered around the bar at the pub. One topic of conversation was what I’d been writing about, and of course someone wanted to know whether I’d written a book.

So wouldn’t you know it - we had a “small world”  moment. One man in the group runs very large SAP projects that rely on strong data governance. And, it turns out, he had a bone to pick with me about my book, Alpha Males and Data Disasters: the Case for Data Governance.  I was prepared to concede a few points right off the bat - yes, the book only addresses a few drivers for data governance. Yes, its provocative title was chosen to make a point. No, there’s no male bashing in it - it is simply using a recognizable term to talk about data-related risk and how to manage it. And yes, I do have newer thoughts than those from when it was first written, over three years ago.

But that wasn’t his point. And no, he didn’t take umbrage at the concept of Alphas. His point was that I hadn’t taken it far enough!

In his experience, there was a higher category - Uber Alphas - who were the key to successful data projects. An Uber Alpha, my new friend said, has the drive, focus, and skills of an Alpha. But the Uber Alpha has adopted Beta characteristics: the Uber Alpha is a system thinker, doesn’t let ego get in the way of reaching goals, is very willing to solicit advice from many sources, and values the support and contributions of less-aggressive Betas.

In our interconnected world, and with interconnected systems, this man said, a pure Alpha will self-destruct. But an Uber Alpha will come out on top.

It makes sense to me.

Go Obama!!!!!!!!!!!!!!!!!!!

Usually at these things, folks are careful to avoid such talk, but not this time. It may not come as surprise to those of you in the field, but nearly everyone I talked to (from the U.S. and from Europe) was passionately hoping Obama would win, and was very relieved when he did.

So of course some of us had to analyze this. Do you think it’s because we’re system people and used to looking at the big picture?

I’m in London speaking at the Data Management & Information Quality Conference Europe 2008. Having a great time. Lots of good sessions, and it’s great to meet up again with folks from the Netherlands (with whom I was “locked” in a conference room for 3 days at the IAP event last July) and folks from Great Britain that I see at events here in London. And of course, there are folks from the U.S. here that I seem to see only on the conference circuit. Had a great discussion with the inimitable John Zachman about the possibility of using humor to teach seriously needed concepts.

(I also made John blush - told him he was a big inspiration for me when I was trying to decide whether I was crazy or, yes-the-world-might-benefit-from-understanding-DataGovernance. Told him he was living proof of the power of one guy, one idea helping to change the world. Made me wonder why I waited to tell him for so long - why do we wait to tell people the important stuff?)

But I digress. Every evening I’ve been able listen to Big Ben from my hotel room. How cool is that? But it’s much more than cool. The sound, the certainty behind it, is so… comforting. The world is changing around us, but at least I know what time it is. I know where I am, and I trust the source of the information I’m getting.

How great is that. So here’s a question for all of you who are charged with creating roadmaps and change plans for our organizations? Where’s your Big Ben?