 Welcome. And thank you for coming to this session this morning. I'll get kicking right away because I want to make sure you have time to get to the next presentation in a timely manner. And I do have quite a few slides. So the topic on this is master data management, big M, little M. And the reason that I feel like I can talk to you about this, I'll tell you a little bit on the next slide, some of the companies that I've worked for. Can you hear me all right in the back of the room? Okay. It sounds like it should be good, but it's like, okay, if I get it up too close, my fat neck will be bumping into it. And then it has a background noise. Okay, we'll let him come work on it and I'll see if I can extend my voice a little bit. So anyway, what I'm going to cover this morning is what master data management is and what it's not. A couple of ideas about how to assess your company's maturity and readiness. Some data governance as key levers because data governance is very critical aspect of master data management. The enterprise information framework, I'll talk a little bit about what I mean by that. And then lastly, some compelling business conversation about master data management. Thank you for working on that. See, I told you I had that peaceful voice. You could go to sleep on it. I felt it's important to explain my credentials. Besides the fact that I've spoken at 10 of the last 11 conferences, I believe in sharing what I've worked on and what I know about. I think one of the things is I was sitting at the table with someone the other day. They said, there's not very many old people or young people here. But if you look around, there actually is a fairly nice population of folks I'd say kind of in their 30s and their abouts. And I think it's important and it behooves those of us with more gray hair, although I color mine so you can't quite see it. To bring back what we do, what we know and share it with others, as well as help one another with lessons learned. So a little bit about my background. I do have diversity in company sizes. The most current company I'm with is Life Touch Portrait Studios. Most of you probably know them by your children's school photos being taken or your church directories. I happen to work for the Portrait Studios division, which coincidentally has Target Portrait Studios. I used to work for Target and JCPenney's Portrait Studios and recently Holland Mills. They're a small company. In fact, our I.T. shop in the division I work for only has 40 people and five of us are the data management slash B.I. group. So that's a much different experience than working for some of the larger companies ever for like Target Corporation, Boston Scientific, which was guided then, it's Boston Sign now, Fair Isaac, Minnesota Life Insurance and General Mills. So I do have a tapestry of small companies and large companies that I've worked for. And that's why I felt I could share with you a little bit the differences about how you get at master data management, whether it's with a big company or small one. And so I've also held several roles. I've been my current role as senior data modeler, but it's actually kind of Jacqueline of all trades. These are doing data model as well as B.I. design. I was one of us at Target. I was in the B.I. space there also. But my role was around strategy and data architecture and helping business understand why should we do data management in the B.I. space. And then one of the things that I like to do when I'm preparing to come to a conference is I usually pick a topic that's something I want to learn more about as it's relevant to the work that I'm doing at the time. Now ironically, I was working for Regis only for 10 months when they decided to lay off 20% of the staff, which just was very devastating to me because, you know, you get to a point in your life when you don't want to be getting laid off. And it was all about money. I didn't take it personally. But the reason I bring that up is I was preparing for master data management and data governance at Regis. So now when I switched to Life Touch, the focus is on something else, but here I was well on the way of digging in and hopefully I brought together some stuff that will help you out. I would like to know a little bit about you as an audience, though it kind of helps me tailor how much time I spend on certain slides. How many of you have a master data management program in place? Wow. Okay, very few. How many of you are just at the very beginnings of thinking about maybe trying to get one going? Okay, good. So that's a good reason to be here then when you're trying to figure that out. And then how many of you are just looking for maybe ways to enhance what you have a little bit? Okay, great. One other quick show of hands just because I marvel at it a little bit. How many of you feel that you've been in the data management space and a role of data architecture, data modeling, something like that for more than 15 years? Wow. Okay, how many for less than 15? Okay, it's a nice mix. So thank you for sharing that. And I'll try, like I said, not to labor too long in slides that might not be very important to you. And there's some very minor modifications I made, like for one thing I spelled assessing wrong. I think you might have noticed it on the lead slide and apologized for that too. For the force for the trees when you print it out, then you see your mistakes. First of all, let's start very simply about what is master data management? And you'll find people have different opinions about what it is. And one of the first things that you're going to be responsible for is declaring what you want to call master data management. But fundamentally, it should be centered around a critical element of your business's data. Something that really matters to the business is what makes the business run. And the very classical examples are customer product and location. So in the case of the retail industries I've been in, customer is a big deal. The location and the products that you're selling or the products that you're servicing with. There are some others, some more lightly glossed over ones I'll talk about shortly too. It also includes the processes and the tools to manage the data. So it's not just a matter of you data model it and you know what it is. It's how are you going to handle it? How are you going to keep it up to date? How are you going to document what exists? And if you're going to make changes to that information and leverage it across your organization, how are you going to manage that process? Governance of the data is extremely important. In fact, I'm going to be speaking at the San Diego conference in June about master data management and governance as it applies to that. Because without governance your master data management program will be kind of weak. And you might be sitting here thinking, how am I going to have governance if my organization only has five people in it? Well there is the business. And I was really interested and intrigued with the presentation I attended yesterday with the gentleman. My name is slipping me right now, I apologize for that. But he was speaking about Walgreens and that they had 89 business people and only three people who were actually in the IT aspect of their master data management or data governance and I just thought that was wonderful. It was fascinating and wonderful. So we'll talk some more about governance and the people involved. And then distribution and validation. And the validation piece kind of gets into the quality. So if you're wondering about how do you manage quality, it's around validating your data. And then lastly is maintenance. Maintenance is not to be trivialized. One of the things that I've been a little bit dismayed with over the last six, seven years is the lack of tools that have the real rigor to allow the business to update the metadata and keep track of it as well as because they're the ones that need to maintain the definitions. If they decide to add a new code, add a new product, change the hierarchies for their locations, they're the ones that understand what they're trying to do. And if they have to queue up with us every time they want to change their programming, change their understanding of the data, it can delay things quite a lot. So this definition, and you'll find throughout my presentation, I do reference things, but I do try to make sure the end in my references page any materials that I've used or leveraged that I've put their sites in there. But this Wiki site actually, I've seen this definition in lots of presentations and I think it's pretty much the industry standard. It's the set of processes and tools that consistently, and it's important consistently, defines and manages the master data. Non-transactional. And this, for those of you that are familiar with BI, quite often you could think of your master data as the dimensions. It's the lookup tables. It's the reference information that you'd be talking about. And of importance is what's important to the organization. And it can include reference data. Now some people will like to say reference data and master data are different. Some people will say that they're the same. You need to decide. You need to decide how you want to be the advocate for it in your company. And if one theme doesn't come out throughout this whole presentation, is that you need to be aware that you're the decision maker. You are the one that is going to help guide the mentality and thinking around master data management. One of the previous presenters that are talking about their topic is it's about marketing. And I'm going to share a couple of ideas about how you can put together your own sort of marketing plan if you were around master data. By the way, I talk fast midwesterner. I don't know if that's a midwester thing or not. But also, if you have questions, don't be afraid to raise your hand and ask. There's no dumb question. And if I can answer it, I'll try. And if you can't, I'll defer it till later. Now some common types of master data. And one of the reasons I brought these up is depending on what your business is, what your area of focus, some of these will be more relevant and useful to you. And they are intended to help you with ways to do some further research. So customer information management. The acronym quite often that you'll see around that is CIM. CDM is customer data management. And CDI is just customer data integration. So those are three other sort of frequently seen acronyms around customer information management. So that customer master data. Product information management. When I worked for Anderson Windows and Doors, that was a manufacturing company. And you might think that how much information can you have around Windows and Doors? I worked with the engineering group and they had a 32 tab Excel spreadsheet that they used for maintaining the information around the products. It blew me away when I got there. And I was kind of excited because we worked on a taxonomy and actually building out a database and they're continuing to extend that work. But product information management at PIM and product data management PDM. So when you're doing research and trying to understand how do you reflect product information for the master data, these are some subjects that you'd want to look into. Now supplier information. Supplier information might be relevant if you're manufacturing. It might be if you're in the healthcare industry and you're actually supplying medications and medical devices to people if you're in, like I said, manufacturing. And also in the retail industry, who are your suppliers? And there's a whole discipline around supplier information management. So SIM is another acronym to be looking for when you're doing your research. Location information management. You've got, of course, some of the classic things people are familiar with is GPS and which is your global processing. And then the RTLS, I always have to look at my acronyms because it's like an acronym soup. And I wrote it down and do you think I can find it? Shoot. Reference transportation. Oh, heavenly days. This is when you embarrass yourself when you're in front of the room and you can't remember your acronyms. It'll come to me and then I'll come back to you with it. Sorry about that. But anyway, when you're thinking about location information, you think of things like logistics and your transportation, your trucking, your movement of your goods from one location to another. This is why that area of data is important to your business. And then finally, financial information management, accounts payable, accounts receivable. There are whole disciplines and studies around how to manage the data for those particular areas. My background, even though I've worked for a couple of financial companies, I'm not big on accounting. And so this is an area where if you need a little bit more background and understanding, you make it some more help for yourself here, too. Now the classic one, you know, not to get too, to be lazy, but this is one that I probably worked with the most across all the companies I've worked for and that's customer information management. And when you think about the mastering your customer data, it's covering all of these focuses and maybe even more. So when you think about your company and you think about customer data, I'm just going to hit on the high points on these, not reading the slides to you. Some of the ones that are a little bit exciting and sexy like they say right now is the web activity and social media. So when a customer is talking about your company out on their Twitter and Facebook, capturing some of that information and deciding you and your company deciding how important is it to use that information and how are you going to leverage it. Most of that data comes in the form of blogs or blogs or free form text. So how are you going to cultivate that information and how are you going to store it? The kind of more typical ones are things like the customer data, like their name, address, phone number, the demographic information. You're generally trying to store things that are somewhat static, feedbacks and surveys. So if the customer calls up and says, you know, I don't like this product, I don't like the locations or I was really excited about this and I want this to go forward. Capturing that information and deciding is it customer data that you want to keep around for a long time or is it more point in time kind of observational things? You have to decide, is this part of the core master data or is it part of the just sort of extra information about your customer? Employee notes. So in the case of the Regis hair salon business, the stylist keeps notes about what's the customer's favorite hairstyle, maybe when did their daughter get married and so that sparks up a conversation and builds up an intimacy with that customer. You might not otherwise think it's very important, but that's how they build relationships and keep that customer coming back. Can you think of any others that maybe aren't listed here that you have experienced or used in customer data that is core and critical to your business? Sure, go ahead. Credit scores. Awesome example. Credit scores was brought up as one. So now credit scores, of course, you get into the whole Privacy Information Acts and I didn't spend very much time on any slides on this, but when you get into regulation around that, the processes that you have to put in place to protect yourself so you can keep that credit score information, but you might have to make it de-identified from the customer so that nobody else could pick up that information and know it belongs to the customer. In the business intelligence space, you might want to use the scores for some analysis, but you don't want anybody else to be able to say, oh, that's Dawn's score and so then they can track it back to her and bother her or whatever. Any other customer information? Thank you for that insight. That was a good example of an addition. So what isn't master data management? And one of my colleagues said you should really have a what is and what isn't and the what is part I was trying to talk to before this, but what it's not, it's not a technology and a typical behavior for IT folks in particular is to say, well, what tool can I throw at it and then say I have a master data management program at place? But that isn't the solution for it. It's very much a coupling of business behavior and IT approaches. It's not data management, although data management is a very integral part to doing a good job with master data, it is not the bullet that solves it all. Question? Yes. It's almost a dependency, I would say. If you don't have data management, it would be hard to deliver a good master data management program or master data program. But data management is the, I think a data management more around the data modeling, the metadata. A lot of the things that are on the DIMBAK wheel, how many of you are familiar with the DIMBAK wheel? Pretty familiar with that. So master data management is treated as its own separate sliver there, but the behaviors, the data management, the data modeling, the metadata, I feel those are other separates. So they're very interrelated, but not, it's not just data management, I think. Maybe that would have been a better way to say it, it's not just data management. It's not a silver bullet. So I've been at this about 25 years, and every year there's some new exciting thing. This year I think it's big data. So master data management is sort of starting to stand the test of time. It's not just a one-off thing people kind of do. It really has to be built out over time. It's not an IT problem. In fact, what I probably should say here is it is a business problem. Not an infrastructure solution, not just integrating your documentation. This is, but again, you could almost take, in fact I could take every one of these bullets and flip it and say it is part of a technology, it's part of data management, it's part of a silver bullet doesn't really work. But, and then the other thing and kind of sublimally stuck at the bottom here is it's not free. So when you're thinking about your corporate spend or your budget for the year or where you're going to slip this in, it's going to cost money and it's going to cost resources. So you'll need to keep that in mind. So thinking about assessing your company's readiness and the value proposition, this page is a little bit more on questions. But when you're thinking about having a master data management program, and as we go through this we're going to separate the big M and the little M, these questions will be answered slightly different depending on how big of an effort you want to put around it. How much would a new technical solution cost? If you're going to do master data management in spreadsheets or Microsoft Access database or just depended to your other processes, you might not be going out and spending more technology. You might also look at it and say we need to do a bigger job of it and therefore we are going to leverage some tools to do so. One of the hardest things about master data management is the distinction between hard dollars and soft dollars. Hard money, soft money, I'm sure you talk about it in your company. But what I find is sometimes the best way to get to that dollar thing is to look at the companies, we'll call it the skeletons in the closet or the dirty linens, and a lot of companies, not all, but a lot of companies will have some thing that happened but it was after the fact they went, oh man, if we would have had this data in place or we would have known this, I could speak to one instance where we were marketing to some hospital folks where in one part of the relationship they were actually filing a lawsuit against us but then another part, we were having the vice president out chamming them off to do more business with us because we didn't know from the front to the back what that customer relationship was like. Sometimes that's the best way to articulate the value proposition for doing a master data management program is to be able to say, okay, this is what happened, this is what it cost us. It might have cost us legally, it might have cost us in public face, it might have actually cost us in some lost revenue. If you can find those examples you could say, now if we would have had master data management in place we could have possibly saved this much money on this problem. Another thing to take into account is will it change your staff or your business processes? Most of the time I would say master data management ends up being extra, work on someone's plate, not necessarily a totally new job. And so then where I think it's been successful is if it's just another duties as assigned role for a person because most of the time people that are the knowledge workers on your master data management, they're in that job already. They already are the ones that are responsible for customer information. So they are the likely candidates to be the ones managing the master data. So it really becomes a matter of articulating what is the change on their roles when you're hiring new people that sometimes when you're a little bit more aware of the added bullets you need to put on a position description. And then some other things is could you provide better service? Could you have more accurate information about your customers so that you're serving them better or having a better intimacy with them? Now this is when you start to think about readiness and metrics. This is just a list but on another slide I've got a little bit more of a tool that you can kind of turn it into a spreadsheet if you will. But first thing to think about is do you have data definitions? Could you say, an easy one is do I know what my customer is? Do I know what measures or what information about that customer I need to be successful in my business? And then not only do I have definitions what are the quality of them? Is it just you know the customer is the person who buys product from us? Or is it a little bit more in depth than that? Like they have purchased from us in the past year or they have ever purchased from us. For some companies that matters. In the windows and door industry the lifetime value of a customer goes back like 30 years and they actually kept track of that because your guarantee for your window was the life of your house. So that had a relevance to keeping the information around that long. Do you have data migration standards in place? Moving from a big company to a small company you get a lot more of what I call the shoot from the hip kind of cowboy approach to things. And quite often those companies don't have things documented. It's just this developer knows where to get the data knows how to write the code to pull it out and uses this process to push it into the database. That's not very formal and it's certainly not a migration standard in place. So those are some things to look at. How reliable are your systems of record? Could you even decide which is the system of record? That's maybe one of the places to start is deciding what is the authority of data for your particular master data domain. Data governance. Do you have any? Now sometimes data governance will start long before you get into master data because there's some element of your business data that's important and enough people are taking it seriously that they've formulated just naturally around doing a better job. You may have already started a data governance program because of that need and not even realize that you're correlating it to some master data of importance. Maintenance of data. Is it all new refresh data? Is it something that you have and then you're updating it periodically? And then accuracy and the level of coupling to applications. One of the reasons I bring this up is if your use of your master data is so closely coupled to your application you have to have some sensitivity around that because what if the vendor changes the application? What does that do to your consumption of your data, to your maintenance of your data and those kinds of things? So think about that when you're deciding everything we do. I'm not to pick on the big ERP, but I think of SAP and when General Mills switched from being homegrown systems to SAP that had a big change on where our focus was around our customer information and around our financial information because then that became the system of record and you had to work around that. So I'm not saying you can't, I'm just saying you have to be aware that that will affect your approaches. So I have put together this little bit of a metric since somebody said it kind of looks like a CRUD diagram, but it really is intended to be used as a tool that you could leverage as a way to determine your company's readiness. And what I would say is, these that I had down the side, let me see if I can make my marker work here, these were just some things that I chose that were important with one of the companies I worked for to decide how ready they were or what their measures were around their, in this case product information. We also looked at customer and location at the time. So within your company you can decide which domains of data matter to you. Notice I left some generic ones here. And by the way, you are welcome to take this when you go back to your office and you can go copy paste or use the exact layout if you want, and I don't have any worries about that. But anyway, quality, number of sources. And you might look at these numbers and go, okay, well this one's marked as red, but here's 10 and that's marked as good. And that particular company, that particular subject area, it was okay that it came from a lot of sources because it was the nature of the business. Let's see what my shirt side was here. Where in the case of product and customer, we were really trying to minimize the number of locations of that data being available. So you have to decide with your business partners, you know, is it okay that we have 20 sources of this particular domain of data or should we really only have one? And then that would be one of the things to work towards. And the green, yellow, and red is really just your own somewhat subjective way of saying, okay, for customer data in this instance the number of sources of five was okay and it was a good thing. We originally had 12. So we were improving the environment over time. Then coming up with the name of a person, I just threw some, it's supposed to be Louise, Lousie. Didn't notice that before. Just the fact that there are names filled in does not necessarily mean that this is a good thing and you'll notice that I have a Mary here. No, the reason that Mary is in red is Mary was three weeks away from retiring. So that was a problem because in this organization then I was about to lose the person with the most subject matter expertise in that domain. So then when we started talking about are we ready to do master data around that area, we were kind of in a critical path here because we needed to get out of her head as much information as we could or get enough of it documented to be in a better place. To me personally, having been a data model or data architect for a lot of years, if there's not a conceptual model in place, I was really tempted to make these be red instead of yellow. But as you can see from a maturity standpoint, this company was not really very mature in master data management accepting in one area that we're doing better than another. So to me these were things that I was trying to say we have to have these in place in order to be successful. A logical model, physical model, some maintenance standards and analytics. Now you could take this list and you could say, okay out of these other things we'll talk about today, more of them should be on the list. Go ahead. Okay. On a conceptual model the way that I would describe it, in fact later on I have a framework picture that almost some people would call a conceptual model, very high level, some simple words for the term so like customer would be the box on a conceptual model, location, product, into some more subliminal things or subsets underneath that. That to me is the conceptual model. There won't be any cardinality about it. It'll just be those main business domains that the business thinks about. Business models in other way people will talk about it. Logical model you've actually started to call out what are the attributes that we care about. And they'll be in business words and then the physical model you're actually getting down to keys, indexes might be applied. So you start to get to how what I fit and then the data types are very specific. It would be how I would declare them. Yes, I'm sorry. I've got physical metadata. Oh, I'm sorry. You're right. In that particular case I was talking about physical metadata. In that company there wasn't any. Like we had no metadata for because if you don't have a logical model it's a good chance you don't have much for metadata either. Although some companies they actually will have spreadsheets or word documents with metadata in them. In that particular company they did not have any. Okay. All right. So, and then like I said you can tailor this to put whatever the key domains of data are for your company that might be relevant and you can break it down more. If customer, if you wanted to take customer instead of going customer product location across the top you decided to have customer demographic information. You could have customer web information. So that list off of the 360 picture. You might decide to take some of those particular groupings and actually apply those to the top of this grid and then decide where you're at as far as completeness. Okay. So just leverage it the way that it makes sense to you. I always have problems with these microphones. I hope that that's not too distracting to you when I turn my head and you get to listen to it louder. This is quite a busy chart but it is useful when you're trying to assess where you're at as far as master data management goes. And it's not a wholly complete list but it's pretty, it's pretty tidy one. No metadata, no master data. You don't have any definitions. You don't have any standards in place. You don't have any migration process in place. No data governance. When you start to move up the hierarchy or the, I'm sorry, the maturity level a little bit you start getting into things like you've identified your sources. You can just have a list of your sources somewhere and who's responsible for them? Who owns that information? That's the first nugget. I mean if you're starting to move along the pipeline that way a little bit, you're starting to make strides. The next piece is when you start getting into centralizing the information. That's kind of the next glimmer of hope that you're actually moving along the maturity model and that you've done some metadata establishment and you've done some integration. So you're starting to document those things. Not that documentation is the be all and all but if you're actually starting to document you're starting to move along the maturity model. Next, getting into data governance. So you've actually started to identify some people. They've put some rigor in place. They're meeting. They're making decisions about that data. That's an important next step along the continuum. If they're introducing the sole model here at this point is when we start thinking about do we treat this data as something that can be served up to different applications that we have. If service oriented architecture is what sole stands for, for those of you who aren't familiar with it. Have we set this data up in such a way that it can be served up to different applications in a somewhat streamlined form? And as I said this list is fairly long and I'm not going to read it all to you. When you start getting over into here you've actually moved into a realm of getting your users more involved. Data validations. You're starting to do some data quality checking and documentation. You've defined processes and those processes are expected to be lived up to. How many of you have a change control board or change board process? One of the things when you're in master data management if you're getting serious about it anytime you're going to change your data. You're changing your databases. You're changing even your models. That should be a part of your change control process. And it might need to be... Your DBAs might cringe at the fact that their CAB meetings are already fairly long and now you're going to introduce this. But if you're making it important and serious enough you want those folks to be a little bit of your gatekeeper that somebody doesn't come and ask for a change but it hasn't been identified anywhere in any of your documentation. So if someone's requesting a change on a table to the DBA straight away and you haven't been included in the conversation at all that's kind of an indicator that you're struggling a little bit with these processes here. Data governance and full swing. We'll talk a little bit about that more shortly. Having some kind of a hub. So a central place where all this information is stored. The solution with the businesses contributed. Can't underscore that enough. A lot of the things when you look at this list might seem pretty IT-ish in nature but it's really stuff that you want to have the business more involved in. So are they... Is it trusted information? Is there a validation process in place? The business are the ones that would be validating whether the data that you're using is good or not. Data quality here are listed. Governance processes. A little bit of redundancy in here. But again, by the time you're at that fully mature you have data governance in place. You have processes documented and maintained. You have change control processes in place. A lot of rigor. Question? I'm glad to see the SOA mention up there. My only question is do you need to be at a maturity level 4 to have effective SOA or at that level? It's interesting that you brought that up because when I was doing this with my home chapter SOA got brought up and that was the same concern. SOA in and of itself has its own maturity life cycle. So I would say you could introduce it in earlier than this but one of the things that can happen if you're so focused on that you may lose focus on master data. It's almost like pick which is the thing that you want to work the hardest for. Master data management will be its own whole program and SOA is kind of its own whole program. I would be careful that you don't end up having them compete with each other. But I would say you could start to introduce SOA earlier. It's not really to you get to this point that you have enough maturity around it to start to call it that and have it tightly coupled with your master data management. Does that make sense? This is where SOA has started by itself with no end in itself. And to that point he said he's seen places where SOA is introduced without master data management at all. That's when you're really into the technical side of SOA where the developers and the web developers as well as the programmers and the DBAs are thinking about how to deliver it from a technical perspective but they're not considering what the implications are from a business perspective as much. Yeah, so at that point we or we today part of my organization went ahead and implemented SOA and delivered some great services for common data delivery. So now we're common data delivery about unmanaged data. Interesting. Common data delivery and managed data. Okay, that's good. Unmanaged data. Unmanaged data. Oh, wow, wow, okay. One of the things that I think you'll find throughout the presentations this week if you don't walk away from here with anything else you should walk away with the empowerment to take from these presentations that which you can use and not feel like sort of overwhelmed that if I want to do master data I have to do all this stuff. It's more like figure out where you are and what are the battles that you want to work through and I hope that you'll get that from this. This is another kind of simple slide and I was looking all over the place I know that I got this out of a gardener slash IBM presentation but when I went back to try to find the resource I couldn't so I'll just tell you I know that it was from kind of a combination of their sites and it's really just sort of an overview highlight of the previous slide. Now the next piece here I'm going to jump off course and hopefully this will work all right. I'm a little tricky doing this. The next two slides, one's called Little M, simpler, I'm just going to flip here real quick and then this one's Big M and you'll go like I can't read these. I don't want you to sweat it and I'm going to show you why. I mentioned earlier that really all of this is about marketing. Here we go. If you go out to, and this is a little tip and this isn't really documented anywhere so if you want to write it down you might, www.google.com just straight go to Google and one of the choices is images. You type in images and here I just, this was what I chose to type in. You could type in the other number of things. Master Data Management Framework. You could do master data management you could do master data maturity but off of these images I'm going to just scroll here for you for a moment and show you how many different images there are to choose from. Okay. Good even there's Peter Akin. I'm not quite sure why Peter's in there. That one just threw me a little bit this morning. But my message about this is you know your organization. One of the things that happened at Target and I feel comfortable I can say this because I think it was fairly public. They brought in one of the big consulting firms with a group a former manager of mine and I were working with the business on master data management and it was kind of exciting because they had really gotten into it and they created their own data governance group it was the business running it and we were invited as guests from the IT part of the organization. Well then a year after that they decided they really wanted to really have a big powwow and they brought 90 people from the company across the business organization and this consulting company come in and look at master data management and how should we do this. And a fairly rigorous amount of time for the next six months after that was spent on building the marketing spiel. I mean literally they had a neat little glossy brochure and they had decided what parts of master data management they wanted to focus in on and had built teams around master data management. They didn't take the whole gamut they picked five or six that they really wanted to focus in on as a company. So my point about these slides and these different topics is when you're thinking about your company you're thinking about how do you want to deliver master data management. Okay now I've got to get back to where I was so just a second here to get back. Okay think about what works in your organization when somebody is launching a new program and you're really trying to get the message across. What's going to work? Something simple like this where you've got your policy audit controls process. One thing I did want to do is this particular one is provided by Informatica. This one came from Mindtree and the Galbraith one is kind of more of an industry standard. What's important about these if you leverage them realize they're coming from a vendor and these are all out on public domain some of them tell you they're copyrighted so like the Mindtree one that has a copyright on it some of the others don't. In fact it's funny I've seen some presentations lately where people are using this particular graphical image just because they like the way it looks it's got the glossy it's got the raised piece some of them are coming right out of using Microsoft's Vizio Say that again? The smart art or something like that and so the point isn't if one of these works better than the other the point is how do you simply illustrate the things that you want to focus on around master data management like I said for the little M maybe what you need to concentrate on is metadata the people the governance piece the rewards and benefits part is like if you want to do this how are you going to get it off the ground how are people going to be measured about it in your organization so then when you get to the more complicated ones and this is where I pick on Target but they had a very much more complicated rendering and I couldn't present that to you because I don't work for them anymore and it would have been in the kind of proprietary knowledge but the point is they needed to be able to see the rendering of what does master data look like so what I would tempt you to do is look at these different offerings these out of Google images and find one that kind of matches up with what your company needs to see now in the one engineering firm that I worked with they needed to see it like this really busy lots of eye charts but when they could see their stuff listed out here they talked about their business referenced here if your company has a lot more process going on you might need to look at one of these and be able to show the inputs and the outputs and the movement of the data that might be what's important so the reason for bringing this up is for a little M when you're just trying to get a small master data management initiative going on there maybe there's only one or two or three of you you need to keep the messages simpler and you need to find one that resonates with your company you might have a team of 15 20 you could even entertain as much as 30 or 40 people you have to figure out how would you illustrate that so that you get the kind of leverage and the kind of funding that you need to support that kind of effort does that make sense any thoughts or okay so that's the point of these two slides wasn't to try to give you like the perfect framework it was to really tell you where you could go look for some ideas about how to come up with a good framework and watch for them this week some other good ones as well I just liked these for the best yes one of the things that I have done personally and then when I come up to a framework picture here in a couple minutes what do we go till till 11 11 05 okay I don't want to lose this it's having the conversation with your business in fact one presentation I went to yesterday I really like to use that word so many times having the conversation listen to how they talk about their business and when you sit down with a business person you don't promise to deliver anything that's one thing I've learned it's not that I won't it just I tell them straight up I'm not here to tell you I'm going to deliver this I'm here to understand what your business is about what's important to you what keeps you awake at night what is how is it that you're measured for your success because that could be part of the problem if they're measured a certain way and what you're trying to deliver is contradictory to that measurement you'll be butt heads with them all the time but at least you understand that going into it and I was quite complimented by a peer of mine recently who said he appreciated my coming into life-touch and I've been this six weeks and I'm really trying to learn the business and went out and toured some of the plants and stuff he says you're learning about our business before you're coming in and telling us what we're doing wrong about it so if you can't have that kind of credibility with people they won't listen to you and they won't be your partners so it is important that you try to learn about their business and what matters to them then you're going to get to know that information this next couple of slides I'm going to go through a little bit quickly but when I talk about little m and this sort of like fundamental things you have to have in place if you want to do master data and that is some kind of a hub some kind of a persistent place that you're going to have your data stored figure out what that is and like I said pick your favorite database pick your favorite style of organizing that database but figure out where you want to store this information you do need to have some data in there if you bring your data from multiple sources and you're going to get it and this isn't just BI-ish I mean think about your operational systems you're pulling data from multiple places and you're going to have people looking for it in one place you have to figure out how you're going to integrate that come up with some kind of data quality measures even if it's even if all the measure is is the data populated or is it documented as being a valid value sometimes that is a big advance for your business that there's some crud data out there and you can help them figure out what needs to be done with it you may even need to seek some external data you may not be rich enough in a particular area your business might want more that can get into a cost feature but you can also it's funny my current boss I like he's got some favorite phrases one of them is our company likes to rub two nickels together make a quarter so I think that means that they're cheap but that's one of the reasons you're always watching how you spend your money but some simple things like going out to the the Census Bureau to pull down location information it's good data it's been validated by somebody else there's absolutely no reason not to use it and it's a good place for you to start when you want to extend the data that you have so keep it keep that in mind it doesn't external content doesn't necessarily have to cost you a lot of money you might have to just be the one that I could say it's the last one on the list but it is the most critical you need to be starting to think about how you're going to get governance because I would say if there is one absolute when it comes to master data is that if you don't have governance you might as well not bother and whether the governance is one or two people in the business who care about it and yourself that's a small place to start but if you don't have somebody who cares about it that what you how do they say that what you measure and if you don't measure it then you're not really going to be paying any attention or energy to it sure it kind of depends on what it depends and I'm not a consultant I can say that but depends on where you have the resources and the budget to spend on it you could at least document that you are depending on the quality as it comes out of your sources for those of you in the back room didn't hear the question is where should you determine your quality on the data from the source or in your integration point to your hub the biggest thing is decide where it is if you're if all you have for resources is pulling it from your systems of record and saying that's what we're going to call quality at least you know that if you want to enhance it then you're going to want to document what enhancements or what quality checks you put in place as it's being brought into the hub okay yes yeah in fact I would say if you're in the level five there's an assumption that you have a hub that you have quality in place that you have processes in place and you have data governance if you're on the earlier cycle you might just be identifying that you don't even have any quality checks it could be that simple okay good questions on the big master data there's a much longer list you'll see and here we start to introduce things like again identifying the sources of master data that might seem like a duh but you'd be surprised how many companies if you ask this person what's the source of record and you ask this person you're going to get two different answers guess what the resulting reporting or knowledge of the company isn't going to match either then you also at this point you're looking at gotten something going on your data modeling conceptual, logical, physical models starting to create metadata Big M is assuming that you're getting yourself lined up to be able to do more I think one of the things I want to emphasize too is don't just assume because you're a small company a small group that you can't do master data you just might not be able to do it with as much rigor as a bigger company with deeper pockets some myths, MDMs about implementing a technology this is kind of that nots thing again kind of the big ones in here though is that a myth is that metadata is the key to MDM I don't think metadata is the key I personally think data governance is the key to metadata I'm going a little quicker because I'm coming up short on time here some risks of failure and one of the important ones here insufficient executive and budgetary commitment now notice that doesn't say none or doesn't say it says insufficient so again depending on the size of your organization it might not take very much money it might take more than you have but figuring out what that looks like is part of what you need to accomplish the all-mind mentality this is where I have found that in organizations somebody either really wants to own the data or they don't want anything to do with owning the data it's not a lot off a lot of black and white there it's either a whole bunch of people want to own it and that's what the fight's about or nobody wants to own it and then you've got to work on that the again insufficient of data models I think is a critical piece and then lack of governance this last one lack of knowledge experts on the data that is seldom the case finding them is the problem it's there is somebody who knows that data otherwise you wouldn't be spending the money on getting it into your company but it's finding that person who's willing to be the owner and accountable for it is sometimes the challenge on the next couple of sides here data governance for the organization I have a what I call the oh I didn't want to miss with this one Gartner says that by 2016 20% of CIOs in regulated industries will lose their jobs for failing to implement the discipline of information governance successfully 2016 spending on governing information must increase to five times the current level to be successful and lastly only 33% of organizations that initiate an MDM program will succeed in demonstrating the value hopefully that's I don't like that last number that's to me like that sort of setting us up for failure but I think thinking about these things will help now this next two slides if you had a big organization and you could stand all of these layers and roles these are roles an executive sponsor somebody it might be the CIO of your company it could be somebody at the VP level of a business area that's actually the best if you're able to get that an enterprise architect if your company is big enough to have an enterprise architecture team I came from one that did have one and I've moved to one that doesn't so have to skip that one your data architect your data modeler might be the closest you get in that area business data stewards I'm going to just do this little cute thing here so I'm moving to the little M fundamental even if you're going to be a big M master data management program start with these three that you have an executive that you have business data stewards and you have data custodians who are responsible for the movement and the actual loading of the data that's where you start for your little M like I said the other one when you can start to grow your business or evolve it I'd start here and extend the picture but that's what I would recommend so I call that data governments light but start at least with these three in mind now that framework that I talked about and I said how do you get to know your business this was from a different company that I worked for but within the first few weeks of working for an organization I'm going through and I'm trying to identify what are their major domains of data and putting it in their terms you might look at this and go why do we have partner CRM separated I originally had a people slash organization box it fairly quickly became evident to me that it was really important to them that their people and their organizations and their CRM efforts were separated I wasn't going to fight that battle it's like I know it's people but they really wanted the CRM box separate so that's how I built it out similarly with the product and location and for those of you in the BI space these end up being your dimensions these end up being your facts and feel free to use this kind of a framework again I don't have any big deal about you but what you want to do is understand your business and put those pictures and it's what's really gratifying is to start to see this showing up in people's decks around the business creating the business case biggest messages on here don't do IT geek speak listen for those business terms listen for what their pain points are and how your data is going to help them be more successful thinking about things like profitability and accuracy and loyalty and retention and when you start showing those as the reasons for your doing this stuff it'll be more important to the business and useful key takeaways kind of got into hyper speed here sorry one size doesn't fit all companies identifying what master data matters to your business and like I said you might have three or four domains of data focus in on one so you can build out that reusability about how to do master data management determine the governance level of your organization again can you find those people that own the data and that are willing to work with you and ensure that you have sufficient leadership commitment and then lastly metadata metadata metadata and you know I find it one of the most challenging things but also kind of one of those golden nuggets metadata is laying all over the place you know it's in some picking up your corporate document that you publish that says how successful you're being there's metadata built in there you know off of the little cheat sheets people have hanging up in their office I've just started gathering things like that and ask can I get a copy of that hierarchy you're using is if it's hanging up in their office or it's glued to their desk they use it all the time so those are some things that you need to start paying attention to I have a whole bunch of resources on here and like I said I try to make sure if I copied anybody's stuff in the deck up above I'm here at least through to tomorrow and I'm glad to answer any of your questions I have a few of my business cards and I'd love it if you share yours with me and you can always reach out to me by phone or email and I'd love to share back so thank you for your time and I apologize for using up so much of it not leaving much time to check