Hello and welcome. My name is Shannon Kemp and I'm the executive editor of Data Diversity. We'd like to thank you for joining this Data Diversity webinar initiating a customer MDM data governance program sponsored today by Irwin. Just a couple of points to get us started. Due to a large number of people that attend these sessions, you will be muted during the webinar. For questions, we'll be collecting them via the Q&A in the bottom right-hand corner of your screen. Or if you like to tweet, we encourage you to share how these are questions via Twitter using hashtag Data Diversity. As always, we will send a follow-up email within two business days containing links to the slides and the recording of this session and any additional information requested throughout the webinar. Now let me introduce to you our speaker for today, Danny Sanwell, senior director of product marketing at Irwin. With more than 25 years experience in the IT industry, Danny has been with Irwin for 16 years. His industry experience includes various roles in data administration, database design, business intelligence, metadata management and application development. Danny is responsible for the strategy, messaging and strategic alliances for Irwin modeling. And with that, I will give the floor to Danny to get today's webinar started. Hello and welcome. Hey, thanks, Shannon. And thanks again to everyone that's joined us today. Thank you for taking the time. We really appreciate your interest in the topic. Also like to thank Data Diversity just for the opportunity to present and expose some of the success that we've had with our customers or at least our customers have had with us. And finally, I do have to shout out to Shannon to thank her for that fine, fine music that we got to listen to while we were waiting. So let's get into it. What are we going to talk about today? Really it's about underpinning your customer MDM and your data governance initiative using Irwin modeling. And this is based on a case study that we have of real customer experience. When we look at, hang on a second here, I'm going to get these slides to move. I know I am. I apologize for, there we go. So if we look at the agenda, we'll just do a quick overview on master data management. Look at what's going on in that space, why people are so interested in it and some of the challenges and success stories that are out there. Do a look at the case study that we have for today's presentation, understand why master data management was important to this organization and how they came to look to Irwin and a data discovery and analysis pilot using our technology to underpin and assure the success of that initiative moving forward. We'll go into some of the details of what they did using our technology to achieve this pilot and really kick start the road to successful MDM and then go through a summary of benefits followed by Q&A. So if we look at master data management, I've got a strange habit of starting every presentation with a Wikipedia entry. I thought it was a good overview. But really when we look at it, this is about mastering key elements and domains of your data so that you can have business agility through integration of strategic and shared information across the organization. There's a lot of ways that people have done master data management and continue to look to do master data management. A couple of them are listed here but as we get further and more capabilities in the area of data virtualization and cloud offerings in this space, we're seeing a lot of choices out there in terms of how to achieve this mastery of key critical data such as customer, product, vendor, there's a lot of other domains so that organizations can achieve the agility that they're looking and become that true data driven organization. What are they trying to get out of it? Agile analytics, real time analytics to drive their business both from a strategic planning perspective but also through sharper business execution and sharper and smarter operations in their business. Really understanding their customers so that the customer can be at the center of everything that they do because they understand strategically that's how they will be successful and grow as a business. When we put this in context, MDM doesn't stand alone as a, although it delivers direct value to the business in terms of delivering quality and accessible data, it really is one of the key pillars to successful data governance within an organization. You'll see that metadata management, data quality, information life cycle, there are lots of elements that go into a successful data governance initiative. Master data management is a key foundation to be successful in data governance moving forward so there's a lot of drivers to why people go and look at master data management as a solution for their organization. There's also a lot of key people in the organization that are looking to master data management to drive larger and bigger initiatives on that road to data centricity. Did a lot of research, worked with a lot of customers, this customer and many more and trying to understand what are the common keys to MDM's success moving forward. Through that research I actually ripped these pretty much for a paid amount of a white paper by a man I respect in this industry, Dave Lotion. You'll notice that the keys to success really are not skewed from a technology perspective. For MDM to be successful there's technology involved and technology may be the solution but in order to get the right technology and have that technology implemented properly there's some key things that are common across successful MDM's implementations and that's early consumer engagement. So who's using the data, what is the business data of that purpose and talking to those people understanding those expectations and requirements for the shared information because again it's not just a technical question of how do we get information there it's how is that information used and what are the expectations that come along with that information when we deliver it through a master data management solution. Data governance, master data management being a key pillar but data governance around master data management is equally important. You have to get the right amount of control and visibility to your master data management before you push it out there and actually have it start impacting different business processes within the organization and through that to get to that point metadata collaboration is key. Prior to exposing that view you have to make sure that people understand that data and that comes through metadata collaboration. Looking at the terms, definitions, usage from a business perspective that may be wide and varying across an application landscape and understanding where those things are similar, where those things are different, potentially synchronizing those things where applicable but if not rationalizing them and then making sure that the end result is harmonized to the business because again the business doesn't care what's going on underneath. They want data that serves their purposes in their terms and data that they can understand and actively participate with, basically trust the data that they have in their organization. So if we look at the case study and I'll be honest up front the names have been changed, in fact we're not using names to protect the innocent as have the models and I can guarantee that no data modelers or data sources were injured in making this presentation. So when we look at the organization that we're talking about today, very classic, classic scenario. It's a traditional brick and mortar business that started out basically selling their wares in a very traditional way. They are looking at and their industry is demanding that they start to grow that online presence and open up additional routes to market in order to be competitive and to satisfy the customer need. There's multiple lines of business in this organization. They deliver both products and services and they have a very large and very customer base. So you have individual consumers and consumer type products but they also have contracts with large corporations, large entities, both private and government to deliver their products and services.  They're not growing at the rate that they need to be successful in their organization. And along with that, not surprisingly, they've got declining customer satisfaction and retention metrics because their customers are changing just like the nature of their business and those customers have new and different demands and expectations in terms of the experience that they have with any organization.  They don't know the extent of my business. They don't know what they've offered and that I've turned down or they don't know what I'm interested in when I speak to them and it becomes a very siloed business and a very siloed experience for the customer and today's customer just will not be satisfied with that. So significant impact in terms of maintaining their revenues and the ability to take advantage of those relationships and move them forward into a position of growth. Their data management infrastructure, again, classic, you know, based on the length of time they've been in business, it spans the mainframe to the cloud. They've got lots of business systems and the backbone is based on some very traditional technologies and deployment methods but they're looking to new deployment methods and new capabilities that can be delivered in different ways to really enable their business and make sure that they have what they need to be able to meet the needs that they're trying to achieve. They had early MDM aspirations and it was a failed MDM initiative. So early on it came on and again looking at things from a technology perspective they saw MDM as something that would enable and solve some problems for them but they didn't necessarily approach it in the right way and the net net for them and a lot of organizations was, you know, round one didn't work out the way and that just makes round two even more difficult. One other key element to highlight, they didn't have a data modeling practice in place. There was a couple of people that would use data models in a limited way but there was no formal data modeling practice. There wasn't a tool in place or a process in place to integrate data modeling into the overall initiative, you know, to ensure its success. So what were the contributing factors to their initial MDM failure? It was, if I can nutshell it, they basically looked at it from a technology perspective. They saw it as a technology or a technical problem that needed to be overcome. They saw information across a wide landscape and they needed that to be integrated and rationalized. So instead of looking at what the business needed from MDM and really trying to get control and govern that initiative from the outgo with a business perspective, they really looked at it as just another piece of technology that they could bolt in, the problem would be solved. And what they found out was that they just couldn't support it, right? They didn't understand what they needed. They didn't understand what it was supposed to do. So it wasn't surprising when they implemented something that it didn't meet the needs. And then when they looked at what they'd implemented, they understood that they didn't have the buy-in or the sponsorship to maintain that and grow the resources that were needed in order to make this a reality within their organization. So if we can look at anything, it was, again, lack of business sponsorship and lack of business collaboration and accountability in the overall process that really stymied this thing before it started. So as this organization starts over, they're looking at it from a very different perspective. So now they're looking at their goals and driving those from the business. Technology is secondary. Technology is not what's going to drive this initiative. It's going to be what are the business requirements? How can they best meet the business requirements? And not just the requirements today, but the requirements for the future moving forward. So they want increased customer satisfaction and retention. They want to capitalize on those relationships. And they want to get new customers, understand who they've been successful with so that they can get more like that and get a better yield from those customers moving forward. So really it's about a 360 degree view and connection with their customer through the data that they have in the organization that runs the organization and the business from day to day. So what are they going to do? They want to deliver an MDM platform that's going to make sure that key domains of data are consistent, that they are of a high quality and that they're trusted. They want to promote this and promote data as the go-to way to doing business and to driving the business through governance and increasing the data fluency of all the stakeholders in the organization. They want to make sure that they have an agile, effective analytics platform and then drive operational excellence through data and effective and efficient integration of that data. And this is the foundation from which they went forward with the new approach to MDM. So this takes us to the pilot that they started looking for data discovery, analysis, and governance. Why did they decide to take a model-driven approach? You know, this use case is a great illustration of what we've been telling people about data modeling for years. Data modeling is much more than a way to automate the generation of data definition language or DDL. There's a lot of value in a data model that goes well beyond just saving time on IT-centric tasks or database or data asset-centric tasks. It really is that place where all the stakeholders can come together in an environment that's visual to allow them to understand and break down what are generally very complex topics into consumable and addressable bytes. It speaks to all of these folks in their language, with their perspective, in context of how they view data because we understand that a business analyst looks very differently at data than a DBA. And presenting data in one way is not going to satisfy either of those. So that ability of a model to be able to present the same information in multiple contexts allows people to become much more invested in the process of managing that data and leveraging that data for strategic advantage moving forward. And then there's the other elements of it, which is the ability to start to standardize and govern data within your organization, lots of capabilities to compare and analyze and collaborate.  There's lots of different types of data out there, big data, traditional data, cloud data, structured and unstructured. There's lots of different viewpoints. And given them one place to see all this, understand it, collaborate together, develop the acumen and knowledge required to be a valuable member of the team, but also in an environment where you're not going to break anything, right? You're not in a production environment. You're not potentially moving things around for scenario analysis. You're doing this in a place that's disconnected, but then easily reconnected to drive change for the business moving forward. And we look at that, really, we have top-to-bottom integration that breaks down silos and data management, right? You have taxonomy, looking at the business terminology, describing data in business terms, conceptual models, that business alignment, how does data interact with the day-to-day running, the processes, the organization, the services that are available out there in the business, what are the rules behind that, right? What are the business rules, how do we ensure that when we manage data, we don't just do it from a technical perspective, we implement those business rules so that the technology serves the business, it doesn't fight against the business, logical models, physical models, how is the data deployed? Again, understanding all of this conceptual and terminology is great, but if we don't know where it's deployed, how it's deployed, how are we going to manage and transform and synthesize those business requirements into actual technical deployments that work for the business? And then configuration models, how does this stuff hang together? How is data integrated? What feeds data? What consumes data? How is data transformed across all of those steps and those different elements of the enterprise that take and manage data in some way for the business? And having an integrated view, the combination of these views together is really the key to not just breaking down technology silos, as depicted in the slide, but breaking down organizational silos that different people that have a common goal but aren't sure how they can work together effectively in order to achieve it. So when we look at the pilot, we look at customer and their first domain, and this was one of the key elements was not trying to boil the ocean. They wanted to take one domain, be able to master that domain, and then through that mastery, establish a reusable facility and a repeatable process for doing it for the other key domains so that, again, they will get it right out of the gate and they will do it in the most effective and efficient way possible for the business. So in terms of the key steps at a high level, first, documenting your as-is-data landscapes, it still amazes me how many folks don't really understand the data that they have in their organization, how it's configured, how it's integrated, and how it feeds the business processes. So understanding that as-is-data landscape is job one, because how can you build something to transform that landscape if you don't know what it is? Second is making sure that you enable the stakeholders with awareness and collaborative analysis tools, ways that they can work together in a single place and effectively collaborate with all of the brethren that they have across all of the different organizational silos. Then take that knowledge and specify the MDM-2B architecture, because you can take that and draw the picture of what you need before you go out and start finding out where you can get it. A lot of problems come from engaging in MDM initiatives and engaging with MDM vendors without the real ammunition in the gun to understand specifically what you need, what they're going to provide, and what it's going to take for them to prove that they can provide it. So this gives you the ability to do build versus buy analysis. And if you do choose to go build, then you can specify what needs to be built and really scope that project appropriately. If you're going to buy, then again, you have a clear set of requirements and an architecture behind that that the vendor would then need to speak to and satisfy in order to win the business. Finally, establish data governance at the program initiation. Don't wait until it's built to say, okay, how does this fit and how do we control it? Make sure we understand the existing policies that apply and procedures so that they're supported out of the gate. And understand how we need to support that so that we can iterate that over time as that MDM program expands and changes based on emerging business requirements. So I think I've talked, which is my style, talked to some of this before, but really it's about capturing the structures, standardizing them, defining them, documenting those points of integration, and starting to understand, identify, and work on the differences that exist in your as is landscape. How do we enable the awareness and collaborative analysis? Well, we publish it in a place where they can get it. So web-based self-discovery for both technical and non-technical roles in a visual manner where they can see not just the visualization of any individual data source, but the visualization of how this hangs together in a metadata configuration or a data architecture. And then enable those managed feedback loops between the organizational silos. Give them a place to share things, get feedback, and do that under control so that we capture all of that tribal knowledge that's out there, and really look at managing the life cycle of the MDM from the get-go. How do we specify the 2B architecture? Well, you define your master record requirements based on the analysis of what data you have. So what are the data sources? Who are the consumers of that data? Capturing all that together, ensure that you've defined that semantic and data flow integration to get a full picture for harmonization. And then feed that into scoping documents, understand the impact of change so that that scoping is complete and comprehensive, and then be able to start taking that and understanding what phases and how am I going to get from point A to point B because it's generally not one step. There's a couple of steps to do that, and you can derive all of that easily using a modeling tool from the existing things that you document in Phase 1. And then, again, finally establishing that governance foundation. So through this process, capture and integrate business vocabulary and terminology. Make sure that you have clear lineage and impact analysis capabilities so people can understand and easily get answers to the questions so that they can participate. And then make sure that through that process you specify and align ownership accountability and ensure that you're attached and respecting all the policies and procedures that exist, and then identify the new ones that you'll need to instantiate as you move to this next stage in your data architecture. So let's get down to the tools and the steps. So when we look at discovering standardizing and document-relevant data, this is basically, it starts with reverse engineering your data sources. So Irwin has and provides support to reverse engineer all manner of data sources, whether they're traditional DBMSs, big data sources, unstructured data sources, anything going back even to things like COBOL copybooks and things that might be hanging around from your legacy. You can have access to that. You can have it read the structure from the catalog and then bring it into this visual environment. But there's a lot more to that. And some of the kind of features and capabilities that are listed under there are the ones that this organization really found valuable in terms of accelerating their analysis. The ability to either define and implement naming standards upon that reverse engineer, or to actually derive your naming standards and then finalize them from what you already have out sitting in a catalog. Same with data types, same with domains. The more you can standardize how things are described and how things are defined in your organization, the easier it's going to be for anybody to move from one area, one data source to another, and provide value in that process. Because the more they look the same, the easier they are to understand. Once you understand them, and we all have a relational mind, this is like that. And if this is like that, then this is what I did with that, and this is what I'll do with this. Other things that really made it valuable to them. The ability to import definitions and edit those in a bulk format. So they had a lot of definitions that were sitting out from different systems, a lot of them in Excel spreadsheets, we were able to grab those quickly and pull them into the data model so that people could start to work on them and collaborate on refining them in this optimized and visual environment. So layout features within the tool and active standard templates, the ability to figure out which were common data elements that needed to be in every model and then defining them in one place and have those become actively bound to the models so that if you manage them centrally, they would be reflected in all of the different modeling collateral that you were creating to support the initiative. Once you have the models in place, they leverage complete compare. Complete compare is our capability to take, do basically a left to right side compare of data models, so a model to a model, a model to a data source, or a data source to a data source. And really start to identify the gaps, identify the differences, analyze those, and then where appropriate, synchronize the metadata if it made sense through complete compare by dropping those things. But equally as important being able to mark and document those differences because sometimes there's a reason why things need to be different. There may be a different business purpose, a different perspective on elements in a data model, and you don't always want them synchronized, but at the same time you don't want them popping up in your face and bothering you every time you run a complete compare. So just that ability to mark and document differences, why they're being left in that fashion, and what the remediation would be outside of actually synchronizing the metadata was a key benefit to them as they went forward in their analysis. And just the ability to push out reports of individual compares to share with people that weren't necessarily using an urban data modeler and publish out into a collaborative environment was very valuable because it's not always the model itself. Sometimes it's the steps in the process and being able to capture those steps and show people what was done and why it was done is very, very valuable. Next, they centralized the models for data governance and metadata configuration. They did this using a product that we have called Erwin Data Governance. It's a web-based centralized repository that harvests Erwin models, quite frankly, it harvests data models of any source, so all of the leading providers as well as a lot of the legacy case tools and other tools that have been out there, and pulled in all of the data models related to their customer MDM initiative. So they broke it down, they pulled them in. They derived initial business glossary based on the definitions that they had in their data warehouse because those were pretty strong definitions. And then built a glossary and then started to publish that out to their stakeholders and iterating through refining those definitions and categorizing those definitions in a standardized glossary. So mappings between the models, mappings between the elements in the models was done very easily through drag and drop so that they could start to build the configurations of data models and how data hung together, how it flowed through the organization, and how the semantic definitions and standards that they had created applied to all of these varied and disparate data sources. Again, it's really building a full architecture, both from a real data perspective, but also from an equally important metadata perspective. And once that was done, your stakeholders had all of these tools available so that they could go out and discover data sources, educate themselves on what it is that exists out there, what the business purpose is, what the technical implementation was. Visualize those data sources through the web in their own terms on their own time, understand how these things hung together, and then drill down and leverage the mappings in these configurations so that they could understand, A, the lineage of key data elements in the MDM architecture, where they came from, what kind of transformations they went through. And then more importantly, as they start to pull out other systems that may have been managing the master data or doing a quasi-MDM in the current, as is architecture, understanding the impact on everything downstream. So if I change this, what do I need to change downstream? Because the last thing you want is the first view of your MDM to be something broken downstream that people didn't account for. This gives you the capability in a very strong visual and detailed way of understanding what is the impact of the changes that I plan to make, and I'm proposing when we put in this new technology, this new capability within our data management architecture. Finally, they used our model derivation to be able to take elements across all of the different models that they had documented in phase one, take the best of that, rationalize that, and pull out their customer MDM model. And as with all of the models, they ensured that they had a conceptual model, a logical model, and a physical model. And then, of course, as it was sitting in the data governance tool, they had their integration model or their configuration model. So now what they had was a conceptual model that they could validate with the business to ensure that it had all of the elements that were there and that it fit to the business requirements appropriately. They had a logical model where they could see the true business rules around this data in action for their proposed MDM solution. They had a physical model, so depending on which way they chose to go forward, whether it was a build or a buy, if they were building, they could actually deploy the MDM model in the technology of their choice, whether it's through straight DDL generation in the tool or through our multitude of bridges that will take all of the information and metadata that's stored in a data model in Irwin and share that and deploy that in all of the other metadata repositories in terms of downstream technologies and tools that needs to be in sync and governed in the same way. So if they were going to buy MDM technology, they could actually push this out. But most important, what they had was a true blueprint of their MDM 2B architecture that they could use to start driving out the documents in terms of scope, in terms of requirements to go to vendors and to really do a true analysis on the best solution for their requirements and for their needs as an organization from an MDM perspective. This was extremely valuable in elevating the confidence of the business to go forward with the budget and the buy-in to get to the next step, which is starting to visualize and understand and analyze how you're going to implement MDM that you've specified from a business perspective using Irwin. So the benefits, it accelerated and enhanced their analysis cycles. So there's a lot of information out there in terms of how much time and how much money out of any given data management initiative is spent just doing basic data analysis to understand the as is. They found that they were able to cut that time and expense in half based on the accelerators that were built into using a data modeling approach versus the traditional approaches that they had, which was going out, doing analysis through interviews with as much metadata as they could squeeze out of any given technology, and then generally using Excel to try to bind these things together. So it was the analysis in terms of those analysis cycles that cut the time in half based on their estimates and their results. From a more of a soft benefit, they found that the interactions and the willingness of stakeholders across all of the silos to engage together and the level of effectiveness in those interactions was increased significantly. So you had people that weren't used to being part of an initiative like this feeling much more comfortable and equipped to be part, a valuable part of that team. So the interactions and the value that they got out of those interactions was accelerated significantly. Specifying their MDM requirements, this was a byproduct of all the work that they did. So it was a natural byproduct. And having that analysis work done in an environment that could turn it into a specification of the 2B was very, very valuable to them. Because now they had in an environment that they could leverage to get as detailed as possible or as conceptual as possible, the same place where they understood and did all the analysis was now the place that they drove out those requirements and were able to reveal those to all of the different folks that they needed as they got on to the next step of the journey. Instituting accountability for proposed MDM elements and processes, the business was much more confident and much more committed to the initiative based on what they could see in terms of control, accountability, and ownership of MDM from all perspectives of the business. And then finally, what they'd done was created a repeatable process and a reusable facility so that as they get to stage two, stage three, stage four, and start going through those different domains that they wanted to master, they had an environment that they could build on. So the value will not just be realized in the initiative that they have today looking at getting control of customer, but the value is going to be repeatable and reusable. And the net result is a facility in which they can actually deploy governance across their entire data management infrastructure and business data consumption infrastructure and knowledge of what went right and what went wrong so that they can get more and more efficient and effective in ensuring that the discovery and analysis that's required for any major data management initiative will be successful and effective and efficient going forward. And this use case that I've just described, you could really take MDM out of it and put data warehousing in it or data lakes, data migration, legacy enhancement, all of the different use cases, anything that really has an impact on data management in your organization can easily be repurposed because basically those same steps will be the underpinning for all of those initiatives and creating that foundation provides a centralized source of the truth from an architecture, governance, and metadata perspective that will drive value in any initiative that you have the concerns data and strategic data in your organization. Before we get to the QA, I did want to basically give a shout out for one of the new and exciting features that Irwin now offers to the market. For those of you that aren't aware, Irwin became a privately owned independent company last April. So all of the Irwin technologies and the Irwin brand have moved and now we're in a very, very focused and agile company focused on architecture and governance. And the first step of fulfilling that vision and expanding our capabilities for our customers, we went out and acquired an enterprise architecture, model driven enterprise architecture tool that's delivered in a SaaS platform. So now beyond the deep dive that we have in terms of data modeling, data architecture and data governance, we now have a model driven solution that allows you to integrate that very detailed view of data into an information architecture, a business architecture application and portfolio architecture, infrastructure design and security architecture environments. So fully getting the big picture. So if you look at something like an MDM or data governance, most of those are not just pure technology. There's process integration. There's organizational integration as we've talked about. Now we have a solution that's going to be able to give you that full perspective and make sure that all of your key data management initiatives are not just going to be well aligned from a data management perspective, but from an overall enterprise architecture and organizational efficiency perspective and driving innovation in a much more agile way moving forward. The first instantiation of this is our Irwin Cloud Core, which is a cloud based or SaaS delivered data modeling and enterprise architecture bundle, where you can really start to get your arms around what's going in your organization and drive all of those strategic initiatives and make sure that they're well aligned to business strategy and can take advantage of the innovation that's just starving to happen in your organization. With that, I will take us to the Q&A. Danny, thank you so much and just a reminder and to answer one of the most popular questions, I will be sending a follow-up email by end of Thursday for this webinar with links to the slides, the recording of the session and anything else requested throughout. I'm diving right into the questions here, Danny. What is the most, you know, we get a lot of questions that are specific to industries. Is there a specific approach to different industries? Is it all the same? This specific question is regarding Minar Posse is saying in heavy chemical industries. You know, we've always, it's funny, there's a struggle always because we have a solution that crosses across all of the industry verticals and our value proposition in terms of what we can bring to that is, I would say, fairly similar. Obviously, you know, every industry has different and unique needs and challenges, but the real, you know, the real beauty of using a technology like Irwin is that it's agile and adaptable, right? It's not a solution for finance, it's not a solution for government, it's not a solution for, you know, petrochemical. It's a solution for data management and data management and data, you know, data centricity in an organization brings value to an organization no matter what it is. So, you know, you know, it is the same use case, it's the same value proposition because no matter what your business is, I believe that, you know, leveraging data as a strategic asset and leveraging the intelligence and the sort of answers to questions that exist in data that you have and use every day to run your business, I think is the key for transforming and growing any business no matter what the vertical. So, what, were there existing business processes that changed or were there required business processes to change as part of this method?  So, you know, understanding how to use the tools, what the tools could do, had impact on a lot of the, you know, data analysis processes that were in place. In terms of business processes, you know, external in the organization in terms of consumers of customer data, it hadn't got that far based on the, you know, the pilot that we ran, right? So, but what they did understand was what was going to change in terms of the data, the master data around customer, what were the implications to those processes and that's where they're now looking at taking the Agilier product and, you know, really understanding and doing the analysis on that and defining, you know, business processes today and business processes for the future. So they anticipate that there will be some impact but the real goal of the analysis was to harmonize all of the requirements to minimize the amount that you needed to change the business because of what was done with master data management. Business processes should be changed for business purposes and for business advantage. We really, really promote and enable organizations to get away from technologies or, you know, specific approaches to managing data, dictating business processes because that's just, that's a, I guess I think a little wrong headed. It's the wrong way. You don't want to have to do things in your business just because this is what the technology specifies. So what they did get was, you know, the true, you know, impact of this new technology and this new approach to managing and deploying customer across all of their systems and then they could do the analysis from there to understand what the impact might be on business processes but the overarching goal was to allow the business to change their processes and making sure that they had an agile foundation and backbone in their data architecture that would, you know, be able to support those changes in business processes that were driven from real business drivers and value to the business versus technological requirements coming from a data management infrastructure. You know, speaking of your clients and, you know, how long did it take to complete the pilot for the first domain for this client? Was that the first, what was the first domain and how long to repeat the process for the second domain approximately? How many entities defined for the first domain? Okay. So the first domain was customer and it's the only domain that they've attacked thus. So we haven't got the results in terms of the benefits on using the repeatable process. It took them basically a month to get everything documented, reverse engineered and in place to then start publishing for true collaboration and it took them basically three months to conclude the analysis and have the facility stood up with the information that was required in order for them to take the next step which is starting to look at, you know, what would be their master data management solution based on the analysis that was performed. So it was, you know, relatively quick process. In terms of entities, reverse engineered, I believe the number and I'm stretching my memory to a certain extent which is getting tougher and tougher all the time but we were looking at around I think 400 entities of information across multiple systems analyzed and then broke that down to I believe somewhere in the vicinity of 80 entities to really support customer from a centralized perspective. So from your experience and in your opinion Danny, what are the best fully integrated MDM tools today to centralize management and monitoring of the MDM data model across different MDM user types? That I would not say I'm an expert in and I'm definitely not in a position to, you know, to do a sort of overview of the technologies that are out there. You know, what my experience is is that there's different approaches for MDM and there's different organizations that have very different requirements and those requirements may be domain specific requirements. They also may be just a reality of how they're going to business in terms of building their IT infrastructure. You know, there's a lot of technologies out of there. Some are considered legacy at this point in the, you know, in the road to MDM perfection. There's new cloud offerings that are out there and as we said at the beginning there's a lot of different approaches. So, unfortunately, you know, one answer, there's a lot of good providers that have a lot of good messages, might, you know, answer to that would be make sure that you're well armed with your requirements and those requirements truly from a business perspective so that when you talk to these different ones you find out what is the approach that, or you have a good idea of what's the approach that's going to work best in the infrastructure that you have, what's your vision for this moving forward so that any technology you implement is, you know, agile and can iterate on those requirements and satisfy the needs of, you know, today, tomorrow and the day after that, you know, and again a lot of organizations are looking to the cloud to, you know, lessen the overhead and impact of, you know, maintaining this infrastructure within their organization. And that's a decision that every organization has to make in terms of, you know, where does it sit on the initial path and what is the risk of deploying one way or the other.  The trick is when you're going to make that choice, make sure that you have as much information and you are as fully armed as you need to get into that battle because everybody's going to tell you a story and tell you that they've got the right MDM for you. You have to understand and have a high degree of confidence, both from a technical perspective but even more importantly from a business perspective to ensure that you can enter those conversations and those negotiations and those, you know, deliberations, you know, as well, you know, as well armed as possible with as much information and a clear picture of what you need so that, you know, you can be an active and intelligent player in that conversation and people will be forced to show how they're going to support you today, tomorrow, and the day after that. You know, we see this next question quite a bit, you know, especially as companies take on big data, what role does no-sequel database play in an MDM solution? Are they required? In what solutions they may be better than traditional databases? Well, you know, MDM, you know, by its very definition is master data. The business doesn't care where the data is stored.    It's the business value of the initiative and how it impacts the bottom line of the business. So I'm probably, again, not the best person to talk about the differences between, you know, big data or no sequel type technologies. Again, it's really once you understand what are the requirements, you know, no sequel technology is great in terms of managing, you know, different types of data and data that doesn't necessarily lend itself to the structure of traditional business data, but a lot of the targets for MDM are traditional business data, like product, like customer, like vendor. And it's important to be able to implement, you know, rules associated with managing that data. And that's really what DBMS and relational DBMS technology has been very, very strong at.  And different vendors will have different technologies depending on what they want to deliver from an MDM solution. My game is not to really look and say one is better than the other. My game is to understand the business requirements and make sure whichever one people are proposing to you is going to meet those requirements and not impede those requirements in any way. Does Irwin have any metadata management tool or is there a best way to manage your metadata through Irwin? Yeah, that's a great question. So the product that I talked about, you know, in this presentation, so we talked about the Irwin data modeler, which is, you know, the active data modeling tool, the one that goes out and, you know, creates models, you know, syncs them up with data sources, gives you all of those different layers and ability to describe and standardize. The second tool that I talked about is what we call Irwin data governance. That is a metadata management tool. It's much more than a metadata management tool because it has governance constructs and capabilities layered on top, but it has a metadata foundation and the foundation is metadata driven out of Irwin models as well as additional metadata that we manage within that environment. So, you know, Irwin data governance is a metadata management tool. It's a data governance tool. It combines them together. It's also a data architecture tool. There's the element of managing the modeling process. We have Irwin data modeler work group addition, which has a modeling repository. And just like you would have an operational system and analytics system in your traditional business, we look at it very much the same way from an Irwin perspective. So that Irwin data governance is really, you know, the metadata repository for analytics publication planning. The Irwin data modeler work group addition is your operational data modeling. So looking at, you know, managing the life cycle of a specific model in your organization, version control, allowing people to work on them and, you know, reconciling conflicts, controlling who can change those models using an Irwin data modeler, who has access to them, what level of access that they have. So again, it's a distributed repository approach where we have a repository that's really fine tuned for the data modelers, the people that are actively creating and maintaining data models. And then we harvest from that into our warehouse of metadata and models and configurations where we then apply metadata management and governance in the data governance tool. I love it. And that puts us right at the top of the hour. I'm afraid that's all we have time for today. Thank you so much for this great presentation. As always, and thanks to our attendees for being so engaged in everything we do. We just have all the great questions coming in. I will just remind you I will be sending out a follow-up email by end of day Thursday with links to the slides of the recording, excuse me, with links to the slides and links to the recording. And there's a couple of questions in here, Dani, that I think we're going to have as well. How can I get a POC for the new Irwin product? So I'll include that in the follow-up email. As well, make sure you get that. So thank you, everyone, and I hope everyone has a fantastic day. Thank you, Shannon. Thank you, everybody.


Okay, so I'd like to start an interview with Greg Gavin. It is Wednesday, August 26th, 2015. We are in Oakville, Ontario, and the interviewer, as usual, will be William McCray. So we're going to start just with a few basic questions. So could you please state your full name? Greg Michael Gavin. However, I never use the Michael for anything other than a birth certificate. And your age? 61. And where were you born? Halifax, Nova Scotia. Didn't live there very long, though. And these guests are like me? And the usual problem is there is not much jobs there, so my parents were moving around looking for work. Okay, so when you were born they... I was in Halifax probably six months or so. Okay. And then we're off to the North Shore of the St. Lawrence up to seven islands, Settil, nowadays. And my father was working for the federal government and part time for the iron ore company of Canada. Okay. What did he do for the federal government? Sometimes he was in the weather office. Sometimes he was in the air traffic control office. And later on he ended up in... It's sort of like air traffic control, but it's more on the radar side, so radar instrumentation, maintenance. Okay. And you as a child, what were your pastimes or did you do for fun interests? We only lived up there for seven years, so that was an interesting place. We lived out at the airport. And it was always outdoors. Outdoors, in the woods, blueberries, swings, whatever. There was water down over the street and... Moved to Montreal, mostly for better educational opportunities for the children. And it was much the same. We lived in a place where it was fairly easy to hop on a bike and tear around the neighborhood. Of course we did that, but off into abandoned farmers' fields. And there was a river down there that we weren't supposed to go to, so of course we did. Climbing trees and just that sort. It was a lot of fun. Any interest in planes because you live next to the airport? We were always interested in planes. We see them going over, we go out to the airport with my father now and then, and sit there and watch them go and you had to know which ones they were and be able to say a few things about them. And did you develop at any early period in your life an interest for sciences in particular? We grew up always interested in sciences and education period.  I've got eleven brothers and sisters. So I'm saying a bunch. Wow, yeah, that is a bunch. So there was always books around. And there were always mechanical sets and Lego sets and stuff like that. And there was wood and string and you made your own kites and you had to figure out why they worked or how they worked and what to do about them. So science was a normal part of everything where we were. And going into school, what were your go-to subjects, your strengths or your interests? Math and science. Math and science. And so from high school, where did you go? High school was Riverdale, which is in West Island, Montreal. It's still there. And after that I went to McGill, downtown Montreal. And my brother had gone to McGill. That was half the reason I was going to McGill. He was also an engineer. He was a mechanical engineer. But the usual story was, so you pick something that's going to be hard and you try that first. You can always go down if you can't quite make it, but you'll never know if you can do the hard stuff. So try the hard stuff. So getting into McGill was hard. Okay, let's get into McGill. Engineering's about the hardest subject line there is there. Let's do engineering. Were you interested at least? Oh, it's got math and science and stuff in it. That's interesting to me. Okay. And specifically, so you got into engineering? Yes. What specific branch did you go into afterwards? I went into metallurgy. Okay. And on that one, that was more a matter of, call it almost mercenary. We're into the 70s. The 70s were not a good economic time. So my first look was, who's getting the jobs? Because I'm going to need a job at the end of this. This isn't just education for the fun of it. I'm going to need a job at the end of this. And the mining and metallurgy department had 100% placement every year. Okay, so where do you get to work? Anywhere from downtown Montreal to the middle of Pine Point up in the north, in the boreal forest. I kind of like that approach too. Oh yeah? Yeah. Okay. Because a lot of people, it's one or the other sometimes they tell me, they realize pretty quickly they don't like the constant traveling or the living out in the bush or the opposite. That they love it and that's what they want to do their entire life. So you like that? That it feel to you to live wherever or whenever? Yes. And I have to say that the cities are never as appealing to me as the trees and the birds and the rocks. I like Sudbury. I didn't stay there just because of the job. I liked Sudbury. Well, they call it one of the most beautiful cities, right? With how many lakes? Oh, there's hundreds. Yeah. I don't know because every time we change the boundaries, it changes. But it's 200 and some, you know? Yeah, yeah. So you got to have a kayak or a canoe and you wander around and you have a good time there. So what was your first, what would you consider your first official job? In the field was Brunswick Mining and Smelting summer job down in the Brunswick Bathurst in Brunswick. Oh, I'm from Camelton. There. Oh, we know where that is. Yeah, I actually live right outside in Pointland Inn on the way to Bathurst. So I was working at Brunswick Mining and Smelting actually two summers. Okay. That first summer was a little bit rougher going because when I started up working there, they were on strike. So that was definitely a different experience. But they settled the strike after a while and we moved along and I got to be a flotation operator. That was pretty good. Learned a few interesting things, not just the theory that you found in the classroom, this is the way it applies in the field. Pretty different. Yeah. And I went back there the second year and started up a pilot plant with them and I was back in the days before a bunch of the concerns about liability the way they are now, I was a foreman, replacement foreman in the summer for the flotation foreman, the crusher foreman after a while, the thickening dewatering foreman, and then I had a student labor gang for a while as well. You served as a replacement because they had their vacations in the summer? Right. That was it. And so now could you just, I guess, not quickly, but briefly kind of give an outline of your career, of your path from there? So the next place, when I graduated with the full degree, I went and I worked in Sudbury, starting off right away with INCO. And I stayed with INCO up until the day I retired. And I know that's unusual these days, but it wasn't the original plan either. But my father got sick during the final few years, so instead of going all the way to British Columbia or Northern Manitoba, I decided I'd be a little bit closer and Sudbury was actually the closest place I had applied to, period. Because I was ready to go off on some adventures. And it turned out to be a very good adventure. Sudbury had lots of variety in the metallurgy field. You know, the mining, the milling, the smelting, the refining, the environmental issues. If it was in metallurgy, Sudbury had something to do with it. Yeah, for sure. I figured it was going to offer lots of variety and interesting problems for years and years and years. And it certainly did. And what was your first position there? I joined what was called the pyrometallurgy group in the central technology group in Coppercliff. And that means I was doing some work. And it was a variety just because of the way they were set up for map processing, even though there's not a whole lot of pyrometallurgy in map processing, was doing work on flotation for them, grinding, some on the fluid bed roasting, some stuff on the converting cycles in the smelter, doing some stuff for the nickel refinery. They were having some interesting problems with some ammonium salts precipitating in their circuits and causing blockages in pumps and nobody could figure out. At this point the refinery had gone, I'm going to say maybe four or five years. So they hadn't figured everything out yet. It was a fairly new plan. So they were trying to come to terms with this. Where is it coming from? What are we going to do about it? So I was working on that project as well and ended up also doing some work with the copper refinery and the silver refinery in particular, which was within the copper refinery. That led to me eventually getting a job at the copper refinery in the silver refinery area. So that was sort of the next move. You tell me a bit about your work in the copper refinery. I went and worked at the copper refinery three times over the years. So the first was during the period where we were doing the silver refinery. And that was improving the refining cycle, some of the control points, but also we were trying to set up for changing the way the refining was done at the time. It was, I was going to say straight out of the 1950s, but no, that's way too modern for the way they were running. It was roasters for selenium removal where you manually rabble the charge around and dumped acid on top of it to sulfate it. It was a reverbitory style silver furnace. Everything was charged by hand and raked out by hand and raked out into these little two-wheeled carts that would only have a couple hundred pounds in a load unless it was actually the metal itself, but as far as the slags and such went. So it was a lot of manual handling, huge amounts, and the environmental exposures that the people were getting because of the dust. So these were sort of the final days for that, trying to work it out, but also paving the way to what are we going to do for a modern furnace to begin with, a modern charging system, not shovels. They already had what they called a sulfation reactor there. So working on the sulfation reactor to get it working better so that you weren't doing the manual part of the roasting, sulfation roasting in the open hearth sort of style roasters at the same time. So get that one working better so that it could take over the whole load. And then I also did work on the selenium plant, the tellurium plant, because they were all within the silvery finally at the time. This was earlier days, and so we were still making the platinum, palladium, rhodium, ruthenium, all that stuff right there.  The precious metals went off to actin. The gold eventually went off to the Royal Canadian Mint for final refining. Silver stayed with the copper refinery until the final days of the copper refinery. So that was round one. I was working primarily on the silver refinery. Left and worked at the iron ore plant, the acid plant. I came back when I was in charge of the technical department at the copper refinery, and at that point we're busy trying to improve the largely manual handling of anodes and cathodes. So that was, apart from the actual mines themselves, this was one of the areas most likely to injure workers. So it was quite a push on to do it better, use better equipment, protect the workers from exposure to the mechanical hazards. So eventually we got there, but it's expensive. That was the main thing, it was expensive and get it into the capital system and get it cut out of the capital system and get it actually working. And there's a few interesting things that happen along the way. One of the main things I'll say is quite memorable. We wanted to try and improve the starter sheet preparation. Now the starter sheets are just a piece of copper that we played onto a piece of metal and then we hang that one there to grow into the full-size cathode. We wanted to improve the operation of that because it was a very manual and sometimes hot job. It was never successful. People had tried it many times. It was never successful. It worked in many other companies. Why can't we make it work? And one of the guys who was doing the job actually said, we don't want it to work. If we don't want it to work, it's not going to work. They liked the job the way it was. We thought the job was labor-intensive in some ways it set a bad precedent because the copper refinery had a lot of time incentives. Do this job, go home. So these people would come in and they would work hard and consistently but by noon they're on their way home. They liked it that way. Even if you made the job easier if they weren't going to be going home at noon they weren't that interested. So this job was never going to work that way. Starter sheets I don't think we ever managed to get fully automated as a result of some of those issues. The cathode handling we did was probably at the end of the process and it's cleaning them up and inspecting them and packaging them up. And the most miserable one was the scrap handling.  That was the one that was hazardous because unless they corrode perfectly and they never do everyone is slightly different and it might break while you're trying to handle it. So getting a system to get that stuff out of the cells onto the racks washed and sent back for recycle without people getting very close to it. That was one of the most important things we were doing there. There was one other and that was at the time we were still large stationary anode furnaces very similar to the reverb furnaces with polling in the traditional polling as in take a tree and stick it in the melt in order to get the reactions going and as a result of that we made a lot of soot and we would get visible emissions out the stacks. We think they weren't that hazardous but they were visible emissions they were reportable emissions and it was certainly the number one item on the reportable emissions to the environmental ministry. You could see it and we did it many times a day. So trying to get something that would filter that out. Did you? We had something in the later days that would have done the job but it was going to be rather expensive. These were micro centered metal stainless steel in a tube form that we were going to pass the gas to and it was going to filter the soot out. It was a much better idea to move the anode furnaces over to the smelter where they were already making the copper so the transfer was molten copper in a torpedo car somewhat similar to what the steel industry was using. Shipped across a public highway over a bridge but still you're crossing Trans-Canada Highway for that matter at the time because the bypasses weren't around Sudbury and over to the copper refinery. There were enough troubles with that there. You really should just do away with that and so eventually they did. They put in rotary anode furnaces in the smelter much like most of the other people in the world had done and shut down the anode furnaces at the copper refinery. So before it's time the copper refinery was kind of behind? It was behind and the number one reason it was behind was because it didn't really have a lot of pressure on it. The copper refinery and keep in mind Sudbury you make about as much copper as you do Nickel so you're making a lot of copper but production had come down a little bit so the copper refinery was not stressed trying to keep up. They could guarantee that if you mine it we can refine it. So the system you had was fine? Right. So you were getting by and the ORC brand copper was we can argue but it was either number one or number two in North America. It had the lowest impurities the highest spiral elongation values available. It was top quality copper. So the system that we had might have not been the most modern but the product was the best. So you weren't under pressure to change a whole lot of things just to satisfy the marketplace. We were moving along. You wanted to satisfy the safety. You wanted to improve the environment. Absolutely. And then when Peter Jones was our chief operating officer he had come from I think it was Flynn Flawn and he was focused on the fact that if you look at the statistics because it was not being stressed we had amongst the lowest intensity of operation for refineries in the world. Meaning? Lowest current density the most cells being used to make that amount of copper a lot of people being used to make that amount of copper so to try and bring that more in line with the rest of the industry he was putting more pressure on to change things whether it was the best thing to do or not everybody will have an opinion if you were building a new refinery or you needed extra production you have to focus on that stuff because it costs money for a capital but where your capital is already sunk it's not quite as clear to me that you should be basically improving your intensity so that you can shut down more of the piece you've already got. And what about because in the late 70s and 80s in early 80s there was huge, huge downsizing. And was this before or what we're talking about right now? Some of this was in the middle of it. Okay, so there wasn't necessarily economical pressure or there was always economical pressure Sudbury went through I'm going to say 30 years of downsizing while I was working there a lot of it was economical pressure but the outside events were pretty much unrelated to copper. So copper still thrived? In fact some of the people on the copper side would tell you that you have to protect the copper and the copper market because even though you're not going to get double the price for it it's a commodity. You are going to get the top price for it and the inventory of our copper ever. So we went through periods like the late 70s where the nickel inventory, unsold nickel inventory went up to huge amounts and we ended up with these long shutdowns and strikes and everything else as we went through these painful adjustments. It never happened with copper. The copper was so good that it if it was available, people bought it. And I guess it's a very useful metal as well and it was cash flow for the company all the time, cash flow. It wasn't that you made it and you had to sit it. Nickel, there were times where we had an awful lot sitting in warehouses. Copper, it was such quality that if you made it it was sold. Now back to the downsizing and the harder times in the late 70s and such Kazinka was big it was a lot of things and how did it affect the region in general? There was absolutely nobody that was insulated from it. Everybody had a brother, a son, a cousin that was either kicked out the door had to go off some place else to find work or was force adjusted we call it force adjusted where you're not going to lose your job but you don't have the job you had last week you have to go and work at a plant or a different location entirely there were a large number of people who were put on layoff layoff is the same as fired except if you're lucky sometime in the next two years we'll give you a call and you come back to work so try and stay alive for those couple of years and maybe enough of your friends will retire that you get your job back we went through many layoffs in the late 70s early 80s and the mid 80s in the early 90s it was painful for everybody What was done to keep Sudbury growing, I guess your local businesses and such because there was a big kind of business community There was the business community and the governments don't forget the governments, the governments participated absolutely this was part of trying to diversify Sudbury's economy because it had become hugely reliant on Inco and Felco and Felcombridge was not doing dramatically different than us the same industry, same pressures same fundamental issues and a lot of the automation that was going on in the mines in particular to improve safety and improve productivity were not increasing production because we had enough production it was doing people out of work so you had more and more people who were coming up and either displacing some of the people on the surface of lower seniority or some of them going off we did try and help people start some other businesses but as far as the governments the federal government moved in with the taxation data center the provincial government moved in with the ministry of sort of like the ministry of mines quite called that there was a lot of support given for expansion of Cambrian college expansion of Laurentian University get more jobs there we gave people leave of absence to go and do education and maybe get jobs on place else, hopefully jobs on place else so they had a little bit of a safety string but pretty weak and we did also try to buy supplies locally where there was a reasonably close option you would buy your supplies locally your services locally I think I mentioned that in the late 90s and early 2000s that was changed to reduce the number of vendors you have in order to reduce the load on our purchasing department and all but in the 1980s in particular we were trying hard to support local businesses because that would employ more people locally the community needed it we thought it was good for us too so with all those efforts did Sudbury actually shrink in population size or no? Sudbury shrink absolutely Sudbury shrink I would suggest that Sudbury about now keep in mind we've changed the borders of the city but if you look at the population of Sudbury now as compared to 1975 it's probably about the same now you also worked at the Mississauga Research Lab what was that in your career? that was the tail end so I spent that was round two at the copper refinery went back to the nickel refinery ran the nickel foam plant then ran the technical department at that time we constantly redraw the borders it's almost like redrawing the borders of the countries in Africa you know so electro winning is a plant at the copper refinery that handles the residues from the nickel refinery and extracts the copper from them and makes a copper product sometimes it belongs to the copper refinery sometimes it belongs to the nickel refinery so when I got the last round of being in charge of the technical department at the nickel refinery that one was mine as well that part of the copper refinery was assigned to the nickel refinery so that was round three at the copper refinery and that was when we were moving along again trying to improve operations it was primarily a leaching so autoclaves leaching and electro winning but improving productivity that was one area where the copper refinery had trouble keeping up with the material coming to it and it basically amounted to whatever went through the nickel refinery and didn't end up going into nickel had to go through that plant and it was one of the plants that was built when the amount of material to design the plant on would probably fit in a saucepan so it was a lot of guesswork and on a number of the bits and pieces they guessed wrong that plant went through about four flow sheets before it even got to be halfway reliable so that was the tail end of my career up there was working on again characterizing some of the leeches or having some other people characterize some of the leeches and having the systems that would do the monitoring and figure out where we could optimize them a little bit more to increase you needed just a little bit more another 10% and you could not have the backlog staring at you all the time and about that time is when we shut down the copper refinery proper the part that was the electro refining tank house and started sending that product up to the horn smelter with falcon bridge and it was at that time that you made your way to the research lab or no I got to be the manager for process technology for Ontario so I moved over to copper cliff and got more of a desk job where I couldn't walk into the plants as often I did that for a few years before I came down to the research so that was more it had its very good points and some of the parts that I liked the best were bringing on and educating some of the younger engineers teaching them a few different ways to think and tackle problems they had some results that surprised themselves which is always the part that I liked the best get somebody to find out they can do more than they think they can after that then I came down two reasons really the first was I had had some interest in coming down but the timing wasn't right you get more international work down at the research centre Sudbury you're working on Sudbury down here well ok and Sudbury I was working on Clitic whales too but that was an exception that was when we were doing the foam plant and we were starting up the foam plant in Clitic as well as trying to run the one in copper cliff we came down here you get to work on Indonesia get to work on New Caledonia work on some of the projects in Brazil and would you consider to be some of your your best work in the lab or your groundbreaking work to stand out I don't think I had groundbreaking work in the lab groundbreaking work would have been the nickel foam up in Sudbury working very strongly with the people from the lab here but that was some of the stuff that we ended up doing that even the people in the lab they weren't sure it could be done when we were making the stuff for the fuel cells in particular it's an incofoam incofoam tell me a bit about that we were one of the first suppliers to Toyota for the Prius Battery substrates we do that through an intermediary called Panasonic Electric Vehicle so there were two issues that were major one was that Panasonic and for that matter Toyota wanted to have two suppliers can't say as we blame them two suppliers minimum that meant that no matter how good we made our foam it wasn't going to be it wasn't going to be exclusive if we had more for it than the price of the acceptable foam from Sumitomo so many ways we thought our foam was better many ways the results suggested our foam was better it was going to last longer and all the rest of that but you wouldn't get any more money for it so the best you could ever do was make it make lots of it for them reliably and when I got the plant it was behind on every single order that it was shipping we were making for General Motors Ovanek a competitor of Pevi we were making for Pevi we were making for a couple others one of the ones out in the Manitoba area forget the name at the moment but we had some fuel cell manufacturers in Canada too so some of the stuff was going in battery some going in fuel cells some going in filtration every single order was late their operation was not reliable so working on that and the people that were working there were just so interested in making it work as well that if you you really just had to help and figure out the way and they're all for doing it and when we were trying to start up the place in Clitik which was the next size up Carpaclub was the first thing bigger than something that would fit in your dining room basically so we got that one going and back fed the market enough to keep it alive while we built the plant in Clitik they had trouble starting up the stuff in Clitik and that was one of the first times that we had ever started shipping people these are unionized people from Carpaclub over to Wales to help the people over there figure out how to run the equipment and it was quite an adventure for everybody involved there was one guy in particular Jim McLaren he had never been on an airplane in his life but the guys who had been back and forth were of the opinion that we need Jim over here so work on Jim to get him convinced that you know you can do this and it will be an adventure that will last your lifetime and I think we gave those guys adventures that lasted every one of them their lifetime I think we ended up with about 15 of them on rotation going over to Clitik and helping out the guys there and making new friends and learning an entirely new country and starting up some process equipment that had never been invented before and having a great time at it how long did that last? we're probably doing that for about a year people in rotation over there meanwhile we had to keep our place running and keep the market full so that when they got theirs the market was there for them how long did the deal last with the Panasonic? I think it'd be fair to say that the deal changed more than it ended what happened was we were making the nickel foam by a vapor date position which gives very high uniformity higher than by electro deposition but electro deposition can use cheaper equipment and the Chinese had started doing it fairly reliably reasonably cheaply so what ended up happening was when it came time to decide what we were going to do first we were shutting down the carpet cliff plant because it was too small as I say it the price was going down 50% a year my production was going up 20% a year but that was about as much as we could manage we couldn't double it every year because we weren't building new equipment so my economics were terrible within a year I was guaranteed to lose money forever so that one was to be shut down Clitik wasn't going to have as long a lifetime as we anticipated either because the price was going down too fast and their productivity wasn't up to it so they weren't going to be able to stay in the market all that long Inco looked at it and said okay can't get more for it that kind of plant is very expensive we're going to go out and we're going to buy a couple of the Chinese foam manufacturers put them under the Inco brand and supply the market that way and so that's what they did with the same technique as the Chinese yes so electro plating okay so not quite as good reputation I guess it's not quite as good but it's good enough my parallel on that one is lumber if you're doing anything with lumber you walk into the lumber yard do you want economy grade do you want stud grade do you want the super wonderful extra kiln dried extra smooth well if you're going to put it inside the wall the answer is no stud grade that meets the requirement sold it's funny you say that I used to work at a lumberyard in high school for a while and that's the biggest thing people complain about yeah what the lumber looks like interesting and how's the the foam market now like where's it been taken I mean renewable energy and clean energy is bigger and bigger and bigger because I sort of got disconnected from that part I don't know what Inco's position is if they still have one I know that there were some lawsuits busy going back and forth about did you steal our technology did we steal your technology so I don't know whether we are still in that particular market but nickel foam is absolutely a market cleric is shut down looking by the vapor deposition nickel foam is absolutely made by the electrochemical deposition and it is the preferred substrate for most new battery plants that use a nickel nickel chemistry and that's because it takes a lot of the guesswork out of the people who are making the final batteries before that you had to use the nickel powders that we make in the nickel refinery and we do that well but you make a paste and you make a a plaque, you center it and try to get uniform porosity and it's not to say that the people who do it aren't good but there's a lot of variables and some of them are pretty darn hard to measure so the foam really helps the people who are making the batteries get into business quickly have something very predictable that they can paste their active mass into and make batteries out of the foam is pretty much the winner as far as the substrate for the batteries goes so it's still very much that now the ones for the fuel cells fuel cells have always been talked about as next year's technology and it's been next year's technology for decades and decades and that's basically it so yes there are fuel cells out there and some of them use nickel foam and fuel cells have a hard time here we are with another magic moment where hydrocarbons have become dramatically cheaper in price again and we think temporarily but here you are you've just made it cheaper for people to use their old style generators instead of going and spending money on newer technologies and fuel cells that's funny to say that because I was when I interviewed Bob Lee who's 91 now he had talked about how he had helped out a company in their startup phase and this would have been decades and decades ago and here we are you're saying the same thing now now there are some places where fuel cells are ideal backup power supplies in some of the parts of California are fuel cells out in the parking lots of some of these great approach up in the space station or the satellites it's hard to get some of the other stuff fuel cells own that but it's such a small market compared to all the other energy that we're consuming do you still work full time no when we're busy downsizing the last time at the lab here in a few other places they invited all of us to just all of us people that were already pension eligible to go away some of us thought that it would be good to preserve some jobs for the younger people turns out we didn't preserve any jobs for the younger people because the cuts were more like 80% it wasn't like 20% it was 80% and that was I was just retrenching and we've decided that some of these projects are going to take much longer than we've got so we're not working on them now and the nickel market has changed quite a bit with the advent of the nickel pig iron so that supplied a whole lot of nickel that didn't need to come from the usual refining sources the usual heavy duty processing through the smelters it goes through a less robust process but most of the nickel is not needed to be high purity if you're putting it in stainless steel and such like that it doesn't need to be the purity that you need for nickel foam or the high quality catalyst powders or the ones for the people in the oil refineries we use them for catalysts there they don't need to be that good so the nickel pig iron mostly developed by the Chinese folks is good enough and until Indonesia put a stop to exporting so much of the ore raw like that that became the route you took the ore from Indonesia you refined it in China and if you could sell it to the steel mill next door and that was a very economical item that's really changed a lot of the dynamics of the nickel industry right there and so what year did you retire or did you 2012 December was the last so you were there when INCO became or was taken over by Valet and you have some insight on the marketing issues that INCO Valet had in the copper nickel I have insight on yes I worked in close cooperation with the marketing people on the nickel side and on the copper side for many years part of what I did was put in the quality systems at the refineries both refineries matching the ISO 9000 series and that was very much driven by people in the marketing and the customers wanting this assurance that you are following reasonable procedures that your your quality of what you give us is not an accident it's not lucky we want to know that it's predictable, reliable and all that sort and that you have processes in place that are going to guarantee that next month will be the same and the year after will be the same so I had done that and as I say in conjunction with the marketing people I had worked with them many many years in fact were there any issues within the marketing or any big difficulties or challenges that you met? In particular I would say that that is one of the areas that Valet left predominantly alone the nickel marketing in particular Valet made some copper not much they made minimal nickel they had nickel projects that they were working on but they recognized that the people in the nickel marketing at INCO knew what they were doing had the contacts had the plans and they basically had them carry on as they were doing now they reported slightly differently but they operated much the same the copper group for reasons that are probably related to all kinds of other issues other than personal preference the copper group moved to Switzerland but again it was pretty much the same people working pretty much the same way and we'll switch topics right now you worked mainly in Sudbury but throughout your career how was how present or absent were women in the workplace or at least your departments I always had some women around sometimes the boss sometimes working for me, sometimes just co-workers but that was a technical department so we always had more qualified women than were in some of the other disciplines and keep in mind this is a very unionized workplace so on the floor the unionized workers there were fewer women absolutely and one of the reasons was we had this downsizing repeated downsizing so women had come into the workplace particularly in the 70's and the early 80's only to be laid off was there the first ones last seniority and they keep coming back and they keep getting laid off and some of them were absolutely as good as any of the guys no question about it but seniority rules in the union there was another time I'm going to imagine this one here because I don't know the exact dates but call it the late 80's where we ended up putting a bunch more women into the mines and they had low seniority but not as low and what happened there was as we were downsizing this was the first time that we had given the clerical workers the people who were doing the paperwork the office routines all that we were doing them out of a job but this was the first time we had given them the choice of okay you can have this package and you're on the street or you can sign up to go into the other union and run a drill or a skip and a number of them opted to do that and you can see a whole bunch of the subsequent interviews and stories there was I'd say at least a 50% success rate on that and probably a little bit higher some of them fit right in and loved the work they were doing and all of a sudden you know alright, you guys think that you're the only ones who can do this I'm going to show you a thing or two and there were some of them who got there and I'm going to get back on top as soon as I can I don't like this particular work but it was a mix were any of those women met with adversity when they started those new positions those more physical guy classical positions I guess yes, but so did other people it didn't matter, keep in mind this is Sudbury this is not downtown Toronto so in Sudbury the cliques are just different every place has got cliques but in Sudbury sometimes it's the finlanders sometimes this area is dominated by the French heritage these guys over there if you're not Italian you don't fit in if you're not a guy you don't fit in that was just one more they used to tell me and I didn't personally experience this because it died down a little bit but years before I got there they said, oh we've got divisions if you want to be in that plant you should be in the Knights of Columbus if you want to be in that one you should be in the Masons there were those divisions and subdivisions all over the place and from that point of view it's not that dramatically different from inco to other places yes there are entrenched groups sometimes they're men sometimes they're a religion sometimes they're an ethnic group now looking looking back not necessarily at your career but you've had a a lengthy career and looking back at I guess not just your career but Canada in general the natural resources world in Canada are there any specific innovations, improvements, changes people that jump out at you and really you think they've affected Canada for the better I look at them and to me it's a continuation of every single one of them some of the innovations are small and some of them are large but every one of them is a step along the way and we might not have been as successful in commercializing for example our inco flash furnace but we sure showed people a whole lot about how to contain some of the SO2 gases after we figured out that they were a problem and how to deal with them and how to stop having some of the adverse effects and I see that one from coast to coast when I was in Brunswick one of the things they were struggling with and it was new to them seemed to be new to everybody they were misbehaving and causing upsets downstream they were unexpected they were working on learning to understand them everybody across Canada in the mining industry was working with the National Research Council on this sort of stuff we worked with a number of them in CANMET and Natural Resources on many of these issues and I've got a friend who's a lawyer in Pennsylvania Saskatchewan I met him on some vacations and one of the things that he liked to tease me about was us miserable minors despoiling the environment oh my god you people I sue you you know and you're such easy prey and I just turned around to him and I said so Ron, you're old enough in 1972 were you driving a car? yeah did it meet today's emission standards? well no well that's awfully unreasonable of you why weren't you why were you despoiling the environment? and people are trying to do the best that they know how and the companies generally are exactly the same they're trying to do what they know how to do if they know it's going to be a huge problem they're not walking down that road and a lot of the times it's a matter of yeah we thought we solved that problem caused another one over here we're looking for a way to fix that we're having that issue right now in Alberta and my usual message to all the people who want us to not despoil the environment and not mine the oil sands if you guys would stop burning the energy nobody would have to mine it absolutely but if you want to have the energy it's got to come from somewhere so yes we want people to do it as responsibly as they can but these are processes that we improve year by year by year as we figure out what works what works better what can we do to fix whatever we did wrong the first time technology keeps changing we have to keep changing with it actually you answered a question I often ask as well and that's that's are the natural resources for the general public is there a disconnect between both of them you answered it pretty well and his car probably didn't meet the standards it did today it was also made of mainly mined metals yes absolutely there you go we'll finish up here what would you consider to be the proudest what are you proudest of in life we can go professionally professionally or both in life and professionally just generally period I keep my standards I have always kept my standards I've been accused or awarded depends on your point of view I've been told that I am gender blind I've had women work for me they get to meet the same standards as everybody else there is no preference and there is no discrimination it's the same with any of the other call them minorities within our male working groups because I've had a number of them who are in particular minority groups sexual religious whatever it's got nothing to do with the work that we're doing here unless it's impacting the work that's off the table we're just going to get along and carry on and do what we came here to do I've been very consistent at that I've been recognized at very consistent at that a number of the young engineers that I've brought on and given their start have very much appreciated the fact that it was like that it was they would come to work and they would be judged on how they were working not whether they were short, tall or had green hair it didn't matter and if you were speaking to someone much younger like a student for example what would be the one piece of advice or most important life lesson you could give them you can do a lot more than you think you can get out there and try short and sweet I like it and never stop trying is there anything else you'd like to add only that it's been so far hugely interesting hugely rewarding it's been fun along the way which is one of the things we always try to get a little bit of fun along the way absolutely oh Mr. Guy, thank you you're welcome


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