In this interview, Steve Adler of IBM answers questions relating to the InfoGov Community, a large and growing community resource that helps members mature their organisations approach to data and information governance.
Steve also answers a number of questions relating to trends in data governance and strategy.
As you probably know one of our aims with Data Quality Pro has always been to showcase other community resources that our members will find useful.
In this session, I want to introduce you to a very useful crowdsourced type community that I discovered recently, it’s the InfoGov Community, at http://www.infogovcommunity.com, created by IBM.
To help explain more about the community and how it can help, I have invited Steven Adler from IBM along today and he has kindly agreed to answer a few questions about the community and some other topics around Data Governance as well.
So, for those who don’t know Steve, he is the director of Data Governance Solutions at IBM and is the founder and chairman of IBM’s Data Governance Council, he is extremely active within the community and has directed IBM’s Data Governance Solutions since April 2004, he is a recognized authority and innovator on Data Governance, Security, Privacy and Operational Risk Management.
If you have any questions for Steve, you can post them using the link below the audio player on the webpage there and this will take you to the forum post for today’s session. So, if you post any questions in there, we will make sure that Steve sees them and he can respond.
I have also posted some screenshots below and some general information out there that illustrates some of the concepts that we will get into today, just some explanations around the community.
Dylan Jones: So, welcome Steve, thanks for joining us today.
Steven Adler: Well, thank you very much for having me. I am pleased to be here.
Dylan Jones: So, can you explain some of the history around the community, and when was it created, and what were the main aims for launching the community?
Steven Adler: Sure, we started the community almost a year ago today. We actually launched it on August 5th, 2010. It really started as a brainchild almost 3 years ago or two years before the launch date, in the Data Governance Council which we created, as you pointed out in the introduction, in 2004 as the thought leadership forum for customers who are looking at the convergent trends around Data Management, in Security and Privacy, in Compliance, in Operational Risk and there really wasn’t anybody in 2004 who was looking at all these different issues and seeing how they overlapped, and who was in charge of them and how they could be treated more holistically within a firm, because the customers were saying…you know, they have got the data and its really becoming a huge asset in the organization, but it’s also a source of increasing liability, because what’s valuable to us is valuable to others.
So, how do we govern the natural dichotomy that exists between an asset and its liability? Is, that you can think about a balance sheet, but there really aren’t balance sheet economics that apply to the management of the data.
So, we formed a council because we had a lot of questions in the market, our customers had a lot of questions. So, we thought, let’s work on these issues together and explore them together and perhaps come up with some solutions that were not obvious at that time.
As we did that, we built the maturity model, we’ve got a body of knowledge and a group of professionals who really were interested in this topic and their companies, benefitted from the process.
By 2008 or 2009, I began to realize that we are not only just discovering some interesting information but we are building a market and that there was a huge community of interest throughout the world in this topic.
I saw that from speaking around the world, but I didn’t have an easy way of including those voices in the dialog. So we started to explore the opportunity to open up the work that we’ve done privately and share it with the global audience, and the community really is the result of that idea, how can we take the time for the proprietary work for the idea that had led with 55 customers and turned into an open source resource to inspire others around the world, not only to take advantage of the resource but also to help contribute to it.
So, starting in February or March 2010, I brought the idea forward to the council and said, at that point we had a new partner in Chaordix, who was doing crowdsourcing social networking, and I said, this partner could help us develop a social networking website, where we could share the work we have done the last 5 to 6 years and encourage others around the world to contribute to it, and we would all get something valuable out of that. The council liked the idea and supported it.
So, we began working with Chaordix on the ideas and we went up to a beta test in June with the council in which we spent about 3 months working on the interfaces and the relationships and the scoring, and all what you see today is largely result of that collaboration which was launched in August and today we have about 1600 members.
Dylan Jones: Its quiet interesting to talk about the number of members and I was really impressed by just how easy it was to get into the sign and navigate around, you can see obviously a lot of thought has gone into that, it’s very commendable, you often see a lot of communities which are thrown up quickly to capitalize on latest industry trends so it’s really good to see that much depth going into it.
One of the things which did impress me looking around the site and getting into it was that crowdsourcing appears to be a key element, for example with the way the members are recognized for their contributions.
So, I think these things appear like a point scoring mechanism on that. It can visually see how people are being scored based on their contributions.
Can you explain for those who haven’t gone into the community yet, some of the other different ways in which members currently share knowledge within the community using that crowdsourcing model?
Steven Adler: We gave a lot of thought and we continue to give a lot of thought into “What inspires people to contribute knowledge?”
You have been to conferences and met lots of people that have inspired you, I am sure, in your life, and it’s easy to meet someone and to talk across the room, to get to know them and to see that you have common interests. It’s a different story if you are on the web and you are meeting people from around the world, virtually, that you can’t see their eyes, you can’t hear their voice and you are writing.
So, we thought very carefully how can we expose, first, this content we had created, which is the Data Governance maturity model, which is (the vast piece) of intellectual property.
So this was the major sort of contribution from IBM to the community. At the beginning we took this maturity model which has 11 categories and 5 levels of maturity and about 120 different benchmarking questions.
We had used that proprietarily to offer services and solutions to our customers. In 2010 we decided to publish it under an open source, Creative Commons Licence and allowed any organization around the world to take advantage of the resource by benchmarking themselves online.
We published the model in text form which is voluminous, it’s like a huge Wikipedia site, and then we also transformed it into a self assessment that any organization could use to benchmark themselves against the community median or average. That was the first decision was, let’s put this out there so that everybody can take advantage of it, because we think that’s the benefit to every organization looking Information or Data Governance today.
But, then let’s go further and not just put out there and say, “Here’s the Holy Grail, everybody come take advantage of it”, let’s put it out there as a hypothesis, because this is the way we created every new idea in the council, rather than just saying “We’ve got the best ideas and everyone should like them”, we’ve said “We have some ideas, we invite others to compare them, to criticize them, to improve them.”
So, we put our maturity model out there with the goal of inviting as many other voices around the world as possible, who could help improve it because we don’t know everything.
We were 55 to 60 data professionals working on Data Governance and since we did that work we learned so much more about E-Discovery and Unstructured Content and all variety of different things that we couldn’t possibly have built into the original model.
So, we posted this model on the site and asked new members who joined (logged in) to contribute new ideas on improving it for the benefit of the community. We did some work last year, adding some new sub-categories to Metadata and classification. We hope to do some more work this year on Data Quality.
So, the maturity model itself is slowly maturing and becoming more relevant today as the community grows and engages with it. So, that was the key consideration in developing a site, how can we get people to access this vast resource, understand it and contribute something to improving it?
That’s not an easy task because the model itself is vast, so we thought about game theory. If you are playing an online game, like if you play “World of War Craft” like my kids play it’s very clever the way they structure tasks in the game so that you have both short term, medium term and long term objectives and that keeps you constantly interested because you are constantly accruing recognition points, which is like love from your game.
It’s a sort of addictive interface that keeps you going because you keep getting rewards, and we thought about that in terms of the site that we didn’t just want to recognize people who contribute the text directly to the maturity model that was our goal, we wanted to recognize them for every contribution, large and small, so they constantly felt like they are being recognized for everything they put in, and that’s where you are seeing the point system on the leader board.
Every time you contribute any idea, you upload on a topic, you make a comment, you suggest a topic, you suggest a submission, you get points which go into the leader board and provides community wide recognition for your contribution and for many people that’s really motivating, because it allows them to establish leadership position in the global community which as we said is numbering today around 1600, we hope to get into the thousands.
Dylan Jones: I think it’s one of the most sophisticated I have seen, but also the simplest as well and that’s what you are really looking for in a social network type community environment. I was very impressed with that.
So, that was a very smart thing to do, because I think with all of these type of things… obviously there are other frameworks out there, 100s and 100s of people on there but you need to know who should I be connecting with, who should I be following, who should I be keeping an eye on unless you track that involvement sometimes, there can be a sea of people with no structure to it, so yeah I was very impressed with that [the gaming concept].
So, with the Creative Commons License, this is obviously open source. It’s not just open to IBM customers. I was able to sign in very easily and gather information. What does the Creative Commons License enable us to do?
For example, say I am a data management expert or head of information system of the company. I am listening to this webinar. What can I do with the Creative Commons License? What does that enable me to do with the resources on the site? How far can I use that information?
Steven Adler: One of the other prerequisites for the site was that we wanted to make it sure that it was open until we couldn’t post it on ibm.com, because that would create a vendor, a natural vendor environment in which some people might feel constrained in contributing.
So, we worked together with Chaordix [http://www.chaordix.com/], the company who created the interface, to host it on the http://www.infogovcommunity.com site, even though sponsored by IBM and we are the leading contributors, it is an open site so that was the first requirement. Anybody can join. I have no restrictions on membership whatsoever.
The Creative Common Share Alike License is specifically governing the contents of the maturity model itself, and it allows anybody to take advantage of the maturity model for non-commercial purposes, and if they make any derivative works out of it, they have to provide attribution of its original source.
Dylan Jones: So, people can use it. They can leverage it in their organization, but if they start to change it and modify it then they have to attribute. Could I, as an Information Manager, use it within my organization.
Steven Adler: Yeah, we encourage it actually and one other thing that we are looking at doing in the future, right now is that you can use the self assessment form, you can use the maturity model in one of the two ways.
You can look up the text and read it and its excellent, but it’s a long read, or you can go to the self assessment form which is what you see when you first click on the maturity model and you can self assess the maturity of your organization.
Now, right now, you can take it once and then you can retake it. In the future we hope to add options so that an organization can identify which department is taking the self assessment, you can journal different versions of the self assessment.
So in short, we want to make it a tool that has much more utilities for an organization where they can use the online version of the maturity model to benchmark like an audit or assessment on a periodic basis, the maturity of their organizations.
Dylan Jones: I guess the CIO could do this now obviously, so they can instruct 4 or 5 departmental heads of their business organization, and then they could get a very good overview of where some of the hotspots / danger spots are around the organization. So, it gives them a priority ranking around the organisation
Steven Adler: From the behavioural perspective, because what the maturity model does is that it descries different behaviours, and what we did when we created it was… we had 80 people who worked on it in total, and we had these 80 people, most of them were customers, banks, insurance companies and telcos to describe to us the different behaviours that they had seen in their organizations from a Data Quality perspective, ILM (Ed- Information Life-cycle Management), Security and Privacy, Data Architecture Stewardship, Metadata, Audit.
For each one of these behaviours, we then said, what level of maturity is that?
We went through a whole rigorous classification process and what you see in the maturity model then is the observed behaviours of other companies that are classified into different levels of maturity, so you can compare that to your own, and say, “Where do I stand?”.
So, it’s kind of an objective, subjective assessment and it’s really useful as an educational tool, educational for people who don’t usually think in these terms, who don’t think about it.
We’ve found that for many organizations, there’s usually some kind of a champion or heroic leader who sees the need for Data Governance and wants to bring it inside, but needs to persuade a lot of other people, “Hey you know this is important, we’ve got to do this and the maturity model is the fantastic tool for that”, because it provides that external benchmark but it’s not coming through a vendor, even though IBM is a vendor, we facilitated it, it’s coming from other companies, their observed behaviours. So, it’s got market validity.
Dylan Jones: Yes, it’s that crowd source benefit again, you can validate internally while you instruct different departments to get a trend completed. You can also compare it to the wider world out there to see how, overall what your score is.
I can see larger areas where that can be involved into comparing yourself against the sector, I mean different size of organizations, you know, there’re so many ways that you can take this through the power of open source and crowd source. I really like that.
So, I see emails about Data Governance Simulation, a feature coming out at some point in the future, could you explain a bit more about what’s coming down the line?
Steven Adler: So if you think about the maturity model as being a tool that you could use to benchmark your organization at the start of your learning process, and a lot of companies do have Data Governance programs today, if anybody who is collecting information and using it, intrinsically are making data handling policies and Data Governance program, it just may not be recognized, formalized or optimized.
So what we say is that those organizations are, you are doing it today, you are doing it badly, and with a little bit of work you could it well, but it’s not a project, it’s a governance program.
So, your data doesn’t die, so your governance program doesn’t die, and you want a governance program that’s going to constantly be comparing your goals to new projects and objectives that the organization creates, to make sure that at least there is some alignment. They may not always be perfect rule based alignment, but if you make exceptions of these to know what they are and you document them, you try to learn those experiences.
Well, to get on that road on maturity model the great tool, to create understand and over time, you can use same questions with the impact of new projects on your strategy or your goals, you can use it for audit questions, but it’s not really an Operational Decision Making tool.
You can use a maturity model everyday to figure out what policies you need to create or whether or not anybody is following those policies. That’s a different challenge. What we often find when we talk to the customers is that, within each organization there are vastly different constituents who care about different aspects of Data Governance. Like, it’s really rare to find a Data Governance structure that includes Data Quality, Metadata, Security and Privacy, ILM, Data Architecture, Audit, Reporting.
These different disciplines exist in specialized groups that often don’t communicate with each other and you don’t have to have them all in perfect alignment in harmony, but if you want to have a successful Data Governance program you want to think about how these groups should work together and whenever you get 2 or 3 groups together, you are always going to have semantic disagreements, substantive disagreements. Matching policies to all those requirements and needs is complicated.
So, we thought what if we could simulate how these different disciplines interact in an organization to get people a visual understanding of, well if I push here, if I increase my policy requirements here on Data Quality, how does that impact Security and Privacy? If I tighten my controls, if I insist upon greater monitoring across the organization to have persistent data logs on a data access, how does that impact the privacy of the organization or employees?
These are not hypothetical questions, they are real life policy questions that people think about when they work in Data Governance.
You think, for example, that poor Data Quality will impact organizational effectiveness, but it may also be that organizational ineffectiveness is impacting poor Data Quality and these causes or relationships are difficult for organizations to map.
So, we are looking at how we can build visual simulations of these types of policy challenges to help organizations get a better understanding of the inter-relationship, the correlation between many many different, distinct actors, parties, data objects, rules, policies, outcomes, etc.
It sounds complicated when you see it and we build from the simulations before in different areas where it’s just like a revolution, it’s just like an infinite bulb that goes off.
One of our smarter cities campaigns for a city in the US is to show them how different transportation systems can be optimized through policy and the impact on the population. It’s called the macro-micro economic model of a city that’s been simulated in software and I think that the city planners looked at it as the best thing they have ever seen.
I looked at it and I thought, I want that from a Data Governance perspective. I want my customers to understand the interrelationship between all these different disciplines and the impact on the organization so that they can do what if scenarios with different policy choices.
So, it’s not just feeling around in the dark about what we are going to do in the Data Governance program, but really matching our capabilities to our requirements.
Dylan Jones: I guess, using methods and techniques so that they can start to identify where the pain areas are, the simulation will give them more feedback around using “crowd resources” to get more and more data from more and more companies you can refine and improve and obviously help them so that…
Steven Adler: My customers often say what is the value of the Data Governance program? What’s the value of Metadata? How do I persuade my business people that Metadata is important? That every time we use it, it has a value, that when I show the lineage behind data usage that lineage has value.
That’s a complicated thing to illustrate, and we hope through simulating the use of things like Metadata and Data Quality tool and Profiling tools by providing a simulation of the use of these tools in a policy environment, we can illustrate quite clearly what the value of proposition is for doing Data Governance, and with every new hero and leader in an organization trying to excel the value of Data Governance, an easy step up.
Dylan Jones: In terms of timelines for that and, is that something that’s going to be offered through the community itself or through a council membership? How’s that being deployed?
Steven Adler: The development model is going to be similar to the way we develop the maturity model, which is not in the community for say, but we are doing as we still have the Data Governance Council which is the set, it was formed in 2004 and we are kind of going through a membership refresh in which we are opening up membership to community members who would like to participate in this project.
There’s a membership agreement that they have to sign and it contains certain clauses about the confidentiality and IP rights which members have to consider. It means that this project is being started in a more proprietary fashion to develop the intellectual property of the model and perhaps when we are finished, we may decide if we want to open this up to the community and publish it, but the development aspect there which I think would probably take about a year, will be done by the Data Governance Council and the information governance council in a more proprietary development environment.
Dylan Jones: Sounds good, so let’s talk about briefly, because something that comes up within our communities is collaboration, and I guess it’s hard to kick start any kind of collaboration and not least hundreds of organizations which you have obviously done. Many of who become competing in similar sectors.
But it’s clear within the forum discussions you got in there and the blog activity, the maturity model contributions and various sorts of community events that you are running within the Info Gov Community, you’re definitely winning the collaboration battle and the sharing battle and you are getting companies involved and people involved. People the right knowledge are contributing.
What lessons can you give to those who are maybe hoping to build a collaboration culture within their organization? So things like Data Governance and Data Quality, when you try to go across silos, you absolutely need that collaboration. So based on your current journey over the last several years with the council and more recently the InfoGov Community, are their lessons you can share from your experiences that would benefit our members?
Steven Adler: Well, you have to be opportunistic and you have to… if we’ve been successful it’s been through trial and error and a lot of error. We make a lot of mistakes. Getting people to collaborate is tricky and I try a lot of different things. I try a lot of different ideas. I put a lot of ideas out there, a lot of them don’t work, a lot of times council members think that’s a dumb idea, and then you know you have to just say, okay that’s a dumb idea and put it away.
Sometimes you have a dumb idea, it’s just the wrong time and you have to wait until the right time comes along and be persistent with it. So, I guess the rule is just to be incredibly flexible and also to realize that in communities, people get bored rapidly. I think if you useFacebook, my teenagers are getting bored of Facebook. There’s a short half-life with anything that’s new, in terms of interest and keeping the site lively and keeping people interested requires constant looking for new ways to incentivise people to participate.
So, I am really lucky because I work with a fantastic team of people at Chaordix who have just been so helpful. We have the symbiotic relationship about developing these interfaces and every time I come up with an idea, I find a receptive audience and within a few weeks we are able to test it out in our site and see how the members react to it and learn from that.
So, we have been very creative in terms of developing the interfaces and what you see in the site today is that when we started with it in August, it’s actually been a long evolution in getting to it as today and its going to continue to evolve in the next year.
Because, we have to think of new ways of getting people to collaborate and to contribute and in the future we will look at video and audio and new types of collaboration technology, that draw more insight from our really talented audience, but we are competing for their time with work that they have and family and other things in their lives and we can only get a small fraction of their attention so when they log on we want to grab that attention.
So, we are constantly looking for new ideas and new ways of getting people to interact on the site and you will see a lot of new features coming down over the next year so…
Dylan Jones: Fantastic, we will look forward to that and thanks for sharing tips on collaboration because I think that’s a key point for a lot of our members to learn.
I want to talk a little bit about Data Governance and Information Governance. What I always have at the back of my mind is that the people listening in might be getting in to this whole area for the first time and I guess it’s useful to define information governance.
So, does IBM have a core definition for information governance that we can possibly share with some of our listeners here who are just getting into this area and want to understand a bit more?
Steven Adler: We have a lot of definitions and I think there are a lot of definitions in IBM for data information governance. One that I like the best is that “It’s a system for coordinating people or collaborating to achieve common goals.” It’s a very nice sentence to say in a (massive), the huge amount of complexity. The complexity of course is coordinating people to collaborate, to achieve common goals. That’s not an easy thing to do, but you have to start at some place.
Now, some people make the semantic distinction between data and information, and I think that in the common vernacular that the distinction is correct. Data are like words in a sentence and information is the sentence, but we use data as “bits” and “bytes” to compose complete thoughts and that’s the information.
We consume that information and transform it and do something new with it. But, when it comes down to the data handling rules or the handling rules for data or information, then the distinction isn’t really useful, because when we put this information or the data in the computers, we structure it.
Whether it’s in a document or in a database, this is still structure, and we can apply common rules and policies to govern how that information should be used but the people on other systems, even if the execution of those policies might be different for an unstructured system as for a structured system, depending upon the repository, but if the rules and the behaviours of the people that were most concerned with, because the data or information itself is inert, its dead, it doesn’t have a bad day, it doesn’t have opinions, it isn’t created, it doesn’t make mistakes, but only people do that.
So, we can really only govern how people use information. We can’t govern information itself. So, we are primarily concerned with the policies and behaviours, the structures of an organization and how we achieve the business outcomes that we want.
Dylan Jones: Thank you for that, it’s a hotly debated topic, I think there is a big discussion on one of the forums at the moment, these things can get up into 100’s of comments. I do like the primary focus on the people side because I have seen on our site for example, it’s amazing when we launched, I thought all we were going to get was questions around technology, which tools to use etc. but we found the bulk of interest was the more governance, process and strategy type featured. We have seen activity around these articles, intensify around the change management, the shift in the organization, its perspective from data as a bi-product of IT to an asset… just changing the whole collective collaboration, things like that. So, I think it’s definitely a shift, it’s great that you are using a definition to tie into that.
So, are there any trends in why more companies are getting started with data governance now than in recent years? Obviously you are active within the community… are there any trends that you are spotting?
Steven Adler: Well, the biggest trend was of course the credit crisis, and the credit crisis or the sub-prime credit crisis that was caused from 2007 to 2010, and some people say we are still living with it, was such a big impact because Data Quality played such a favourable role in the underwriting notes of the sub-prime and poor loans or mortgages.
That not only in terms of its origin but in the direct aftermath, the regulatory authorities of the US, the central banks and the SEC started to asking banks, “Could you please report X, Y, Z? Could you show us your positional holdings today or tomorrow or the next month?” and when the banks actually started to demonstrate how still to pipe their own information and structures where they couldn’t actually readily produce this information, the authorities said, Aha, you guys need a Data Governance program, because you are really not in control of your own information. You are so balkanized and decentralized that you can’t report up information that we think that’s critical for managing your organization effectively, for managing your risk.
So that was a huge impedes for Data Governance. It wasn’t just US because the Federal Reserves in US was collaborating with ECB in Europe and with central banks around the world, and they were collaboration on common audit procedures and their findings, then they were having discussions.
That’s the bad how the catalytic affect are around the world and the central bank requirements that organizations have affect the Data Governance organizations, and that went from banks who were directly affected, to other organizations where directors on boards and they would ask to the insurance company, what are you doing by your Data Governance program?
So that was the first big catalyst. Catalyst that we are seeing today are increasingly in the security and privacy space where I think it’s becoming clear specially in the privacy area to many that the domestic privacy regulations haven’t really kept pace with the global nature of their flows. It’s increasingly difficult to assert data privacy protections on data flows, especially with regards to cloud computing in which the information is everywhere.
So there’s a growing concern about what types of data handling policies or rules we need in a cloud based computing environment. So, that’s becoming a key driver, and of course the latest incident in cyber security, you know the Pentagon being hacked recently etc. These all raise increasing concerns about the liability aspect of data management and they are also bringing new and also important trend in terms of Data Governance drivers.
Dylan Jones: Yeah, certainly in the UK there is a huge amount of activity around Solvency II and these insurance and banking timely initiatives that seem to be fueling a lot of the employment opportunities. I think Data Governance has really rocketed in this part of the world at the moment.
So, we’ve got people on this session listening in who are about to embark on Data Governance initiatives in their organizations. So based on your experience, what are some of the most common mistakes that you see organizations making as they take those first steps to Data Governance, trying to move forward?
Steven Adler: Short term focus, “What can I achieve in 90 days” type of things but it’s kind of interesting now looking at the market over the last 7 years, because the first 2 or 3 years, we spent a lot of time just persuading people that Data Governance was a real term, that it wasn’t just a provocative combination of an inert object with a political structure, that this was the real market that people should invest and do something about.
The maturity model helped a great deal in persuading people that the current practises were inadequate and that they needed something special to become adequate, but then the credit crisis happened and all of a sudden we have this big wind behind us.
Now, I think and almost like the majority says that the market in which there’s a vast number of organizations around the world were coming forward and saying, “I have heard about Data Governance, what is it good for? What problems does it solve? How do I do it? What can I get in 90 days?”
These companies are probably in the most significant danger or early burnout, in a hype-cycle if you will, because they are looking at it like another project. They are looking at it like okay it’s just another application I have to develop or just another widget I have to buy, and they are not thinking about what are the existing data management problems that I could solve by putting together a governance program which is sustainable, how do I achieve the results that I have always wanted from my information infrastructure, but haven’t gotten because nobody has actually been looking at it over time. When I deploy a data warehouse, how do I make sure that the integrity of the data warehouse doesn’t begin to evaporate the day I deploy it, but that I keep it over time?
These are the things that people should be thinking about.
The biggest mistake I see is that organizations either don’t have the facts about what’s currently wrong with the organization, with the problems that they have, that they want to fix and have a business case for making the fix or they don’t have the sustainable outlook e.g. I want to do this program not for 90 or 120 days but for years, so I want to institutionalize the roles, responsibilities and develop especially the BI infrastructure that gives me information about what’s happening today and how to use it.
So, I want to know when data elements change. I want to know when new databases are created. I want to know when new data marts proliferate. I want to have like an early warning radar system inside my organization that lets me know when these changes occur and what I should do about them.
If organizations aren’t thinking that long term about building a program that’s sustainable, that’s based on facts, that reports results, they are going to be disappointed. To do those things they are going to find that they are going to achieve sustainable results for the infrastructure investments that they make that more than exceed their business plans.
Dylan Jones: I think that’s really good advice. I think this is an issue we often see, they don’t plan to sustain or don’t plan for long term.
They have plans to manage this because it obviously has the executive churn, you have the leadership moving. All these things, I guess, you have to build in the solid bedrock that says we are going to do this long term and ride out any of these kind of changes internally, changes within organization structure, changes within sponsorship and things like that. So, great advice there, thanks for sharing.
Finally just in terms of the Info Gov Community, can you share any news on the future road map, are there any additional features or benefits coming that our members can look out for over the coming months?
Steven Adler: Well, there will be constant improvements coming to the site over the next few months. We hope to put into place new self assessment forms so that you can save your self-assessments in time, so you could take one today for Data Architecture and save it and then retake it next month and compare the retake version to the one you took so that you will be able to line up each one of yourself assessments in time and like a 3-dimentional spreadsheet, compare them so you can compare your result, it will give you an audit like capability for using the maturity model. So that’s one thing we look at.
Talking of the small changes coming to the site like the vote on comments, be able to express your like or dislike for comments for people post, or the ability to post videos onto the site from different members who would like to articulate their views in a medium other than text, a lot of things like that coming soon.
Dylan Jones: Fantastic, thank you so much for sharing your insights with our members. That was really good advice there for them. If anyone wants to check out the community, it’s infogovcommunity.com.
If you have any questions, follow the forum link and I will make sure that Steve gets to see them.
Thank you so much for coming on the session tonight Steve and best of luck as the community grows, it’s a fantastic resource, congratulations.
Steven Adler: Thank you very much. I really appreciate the opportunity. Great talking with you today.
Steven is the Director of Data Governance Solutions at IBM and is the founder and Chairman of IBM’s Data Governance Council.
He’s extremely active within the community and has directed IBM’s Data Governance Solutions since April 2004, and is a recognized authority and innovator on Data Governance, security, privacy and operational risk management.