 Hello, my name is Tony Zanders. I'm the founder and CEO of SkillType. And I'm joined today by Johnny Bersico, our Chief Technology Officer. We're excited to share an update on identifying global expertise in the modern library economy with the CNI community. So allow us to start with the problem that we set out to solve a couple of years ago. There is a global talent problem in libraries. A few markers to kind of define the problem for us. Number one, libraries as organizations, but also information professionals, both struggle identifying in-demand skills. On the one hand, you have the organizations that are trying to keep up with changes and what universities need, changes in what patrons are expecting. Some describe this as the fourth industrial revolution that is bringing new technology and new ways of work, which imply new skills that are needed. And so organizations are struggling on that front to understand what are the skills that are in-demand and professionals are as well. Even once identifying what these new skills are with the help of professional associations and conferences, acquiring those skills is its own separate challenge. And for the organizations, that means using recruitment to bring new people on board, but also re-skilling individual employees is a challenge. Personally, for individuals, it's a struggle to acquire those if you don't have budget or funding to fly to certain conferences or to pay for coaching in certain areas. Most employees working in the library profession don't have clear pathways to acquire those skills individually. And to make matters worse, this knowledge gap organizationally and individually is not slowing down. Each year, there are new skills to be learned, new technologies to be adopted, new ways of work to be embraced that is just keeping this sort of ever-evolving as we look to the next decade. Some of the underlying causes of this that we've identified over the past couple of years, one is information asymmetry inside of every organization. So what we mean by this is on the one hand, organizations and the leadership or the administration has a good picture of the skills that are needed based on the strategic plan and what the university or the provost, the direction they're taking the university in. But employees don't oftentimes have that same level of understanding. And so employees are sort of grasping for straws in terms of what types of training should I be doing to benefit my organization? And so there's some asymmetry on that front. Whereas on the other hand, employees have a clear understanding of what they know and what interests they have personally as employees, but organizations oftentimes don't realize what expertise is lying within their organization or what their employees are interested in learning. So there's a symmetry on that side of the equation as well. Across the industry and the profession at large, there's very poor visibility into the supply and demand of library expertise. And so each organization produces a job posting saying, hey, we're looking for this type of person to come and join. We're looking for this set of competencies. But to do that at that organizational level is taking a big shot in the dark because it's difficult to know and keep up to date with what is sort of the supply of that set of expertise. We don't know how many people are going to apply, how many qualified candidates we'll receive for this job posting. And we really just cross our fingers and do what we call post and pray because it's really impossible today to understand what the supply of that expertise is. And lastly, there is a grossly fragmented data landscape and also a grossly fragmented content landscape. And so many different professional associations have their own annual reporting that is conducted but these are all silos and that's within the U.S. alone. If we think about this on a global scale that just multiplies exponentially. And on the content side, a lot of the training that takes place by folks that in organizations like the logos you see here including CNI, all of those efforts are also being done in silos. And there are hundreds of these training providers that manage hundreds of their own websites and repositories of training and they aren't connected in any systematic way today. Faced with these challenges, we started asking ourselves some questions. Could we layer a technological solution on top of the organizational structures or groupings that already exist within the library ecosystem? Take the consortium as a hub linking multiple organizations together. As such, knowledge of its member organizations available skills or like thereof allows this consortium to serve as a skills broker of sorts enabling resource sharing across its membership in ways that have traditionally been near impossible. Traditionally, if an organization needed someone with a particular skill to temporarily contribute to an initiative, they might take the route of costly and time consuming search or try hard to find someone internally willing to learn this new skill. With this model, however, an organization can instead leverage their consortium memberships to surface someone within their own network who previously would have been unknown to them. This approach also empowers consortia to leverage their unique position to provide a new level of service to their members and foster increased collaboration and resource sharing. Let's dive into a quick demo of this capability. I'm going to log into skill type and immediately what you're gonna see is a learner profile. As a user of the platform, I have a couple of different roles. I have the role of a learner which is by default when I log into my dashboard you're seeing that I'm getting some recommendations for learning I can engage on this week and what I was recommended last week. But we're not gonna spend too much time on the learner aspect of things for the time being. The second role that I have is that of an organization owner and that of a consortium owner. So to demo the consortial experience, I'm going to select the artificial consortium here. The default page or rather the profile page for a consortium would be no different than that of a member organization, right? It has a strategic directions, it has key skills and key products just like any other organization that are a member of this consortium. The, in the same way there is a directory that lists also all the members into my test account here. The, what makes this interesting however, is that in the under the members section I get to see all the members that make up this consortium. So for example, I have several organizations here. I'm going to pick the Dallas Public Library which is a consortium member. Once I select this, I get to see this organization's its own strategic directions, key skills and key products. The, and those, the members that are a part of that organization, their skills can then start to surface up through this consortium relationship that artificial consortium has with Dallas Public Library so that when I navigate to the insights for this consortium, the, I'm seeing sort of a rollup of all of the skills spread across all of the organizations that are linked to this consortium. So this is the beauty of this relationship that is established between a consortium and consortium members because that we can start to surface these skills and then now the consortium is able to sort of be that broker of sorts that we talked about previously whereby they know which organizations have the people with the particular skills in mind. So if I wanted to navigate to find those with the Alma, as a skill, I could do a search here and pull up the members of my consortium or this consortium here and which organization they come from. I can see that I have one individual that exists within this organization but also I have one within a member organization in this case, Grinnell College. So the, again, all of that data is bubbling up to the consortial level allowing the consortium then to then be able to sort of establish your relationship between these different member organizations for that resource sharing capability. There's plenty more to go over that we don't have a ton of time for but again, please, we invite you to our regular monthly town halls where we can dive a bit deeper into the power and the capability that this linking together about this data can provide. So we've been able to make some incredible progress towards this, what we would consider a global problem, looking at the library industry considering that there's over two and a half million full-time professionals at over a million libraries. This is certainly a long-term view towards upgrading the talent infrastructure for our organizations but also for our professionals. But we're not starting from scratch. The past two years have been incredibly productive. We've built a global community of libraries, training providers and information professionals across three continents and that is growing each month. We've also been able to make a large amount of headway on standardizing a set of APIs that allow us to start using the same terms when we're describing various objects in this platform. So for example, as Johnny illustrated, people using skill type are using the same terms when they describe their skills and interests as organizations are when the organization described their needs and same for training providers describing their webinars. We're now all using the control vocabulary that has been packaged up into modern standardized APIs. And the content aggregation and description effort is well underway. We now are proud to say that we have the largest training database for library professional development. There's over 8,000 of these resources that go through our metadata enhancement. We're adding about a hundred of these per week. Most of these are open access resources that are publicly available on the web but we're helping people and organizations surface the needle in the haystack. And lastly, in the most difficult part that we've achieved thus far is standardizing an onboarding process for libraries across library type and across geographic regions. This has been the most gratifying part as well. And I'll walk you through what this onboarding is like in the next slide. So first libraries conduct what we call a needs assessment. So this is an automated process where a library's leadership team can come together and create a single source of truth on what expertise is needed. And this will vary from library type, whether it's an academic library or a public library. We even have state libraries and medical health sciences libraries in the skill type community. So regardless of the type, this gives the library a way to say, hey, here are the skills that we need in an ideal world. Phase two, we call the talent audit, which is where we invite all of our employees. They take their own personal skills assessments and we see what people are interested in learning and what they're capable of doing. And we're able to layer those data sets on top of one another to do an overlap analysis which surfaces the skill gaps within that organization. And then once we can see what skills we have, which ones we're missing, we're then able to do a content survey, which is to look at that 8,000 resource database and say, here are the skills that you're able to reskill people for based on the available content and training versus here are the ones you'll have to go outside of your organization and recruit for. And if you belong to a consortium, we can surface the expertise that that consortium has if you're missing it. So this is a process that we're already seeing libraries can sort of put some effort in upfront about a month's worth of time to set it up. And then afterwards, each of your employees are off to the races, managing their own training and development, taking ownership over their growth. So current challenges that we've identified that we're working on each week, I'd say the first is there is an organizational learning curve for this idea of data-driven talent management. Most of the work I'm personally involved in and others on our team that aren't on the engineering team is really just explaining and onboarding organizations to this new way of thinking about talent. We usually don't associate our personnel and talent with data. It's usually a pretty qualitative environment, but we're bringing data to this conversation and we're finding ourselves in really interesting conversations, positioning the library at the university level to say, hey, we have data to contribute to the broader institutional priority of assessment. And so now the library has a stronger voice to play by taking a more data-driven approach to talent management and human resources. There's also a significant personal learning curve around training automation. We're building this platform during a time where there is a very high degree of skepticism to technology and software. There is a very real surveillance state at play with big technology. And so we out of the gate have embraced policies like GDPR out of the EU and others to hold ourselves to a very high standard to make people comfortable with this idea of automating their career development, automating their training and development because once this is sort of done correctly, there is a vast amount of benefit for people busy professionals who don't have time to keep up with the amount of resources that are out there. People don't have time to monitor the email list serves all day. And so there's a lot of missed opportunities for finding that right opportunity and skill development, whether it's a webinar or a conference. And so there's massive benefit but there is a personal learning curve around a modern privacy policy that makes everyone comfortable with the amount of data that's being used for personalization here. And lastly, as we've alluded to before, out of the gate skill type is already a global community but that also implies that there are languages, policies and other localized traits that skill type has to evolve and grow in order for this truly to be a global experience. But we're surrounding ourselves with the right partners and the right thinkers in this area and we believe we're well on our way to addressing each of these challenges. No one thing I'll add here is that there are patterns from a technology standpoint. So usually when we come up with these challenges, Tony understands the business aspects of these challenges and it is my job to come up with a technological solution for them. And thankfully for a lot of these there are existing technological solutions to address these things such as the privacy concerns such as the globalization of data, there are parts of the world that have localization requirements, data cannot travel across borders and things like that. So we have the technological capabilities and expertise to provide this level of flexibility for organizations that so require it. It is something that basically we have as part of the sort of foundational aspects of the platform so that this is not something we have to retrofit and after the fact, which can be quite costly. So this is something that we factor into the platform on day one. And in terms of what's next, we as I mentioned have a pretty active community of people ranging from library workers to administrators and from all different types of libraries. Each month we hold town hall meetings that are publicly available. And it's one of the first places I've seen where you have public libraries intermingling with academic libraries, state medical health science, special libraries all centered on the conversation of how can we use technology to better support the profession with our growth and development. And so we'll continue to experiment with these emerging technologies and approaches. Each of these are validated and vetted by our community before we put these into development. I think another thing to look forward to next has to do with the way that we collect feedback. Part of the reason we are excited to be at CNI is that this is a community that ideas can come in their early form and a constructive dialogue can take place with some of the greatest minds in our community. And so we do look forward to the feedback we receive from this fall CNI meeting because we're certain that some of the challenges you're dealing with in your institutions can play a role in the priorities we set for the roadmap. And lastly, but certainly not least, achieving that critical mass. We still don't know what that specific number of institutions is or the specific number of learners is. But we are very optimistic that the potential of skilled type will be unlocked once we achieve that critical mass. And so our call to action to you today, aside from just giving us that feedback is to get involved. And so any of you can create a free account for skilled type right now just by visiting our website. And if your organization is in the process of rethinking the way people are managed as we wrestle with this new post pandemic environment, contact us, we're able to set up a trial for your organization to take a look at this more data-driven approach. And so thanks so much for your time and we look forward to getting your feedback.