all right thank you catherine and welcome everyone to our final session of the event my name is melissa harris and i'm a senior researcher at gov cio medium research i'll be moderating our closing panel which is our cio roundtable with our wonderful guests here today joining us today are the national institutes of arthritis and musculoskeletals and skin diseases cio latonya burden national institute of allergy and infectious diseases cio mike tartkowski and servicenow federal cto and principal digital strategist jonathan album thank you all for joining us for the panel um so i wanted to circle back to the top of the program real fast we heard from dr susan gregerick about the greater data strategy that nia nih is implementing to enhance its mission so would you each like to go into how your strategy strategizing your own data infrastructure in modernization from your institute cio level amid these broader efforts and what technologies or infrastructural approaches such as you know cloud or different automated capabilities are helping you but tanya do you want to get us started sure good morning uh at miami's as you heard from susan we are a large entity and 27 institutes and centers and you can imagine with all of that everybody uh does not do it the same way necessarily but for us at niams i create a five-year infrastructure modernization strategy and that that strategy lines up with my um my life cycle of our on-premises hardware we revise it yearly based on any new key technology mandates or lessons learned from any of our projects along with that we collaboration with our intramural scientists there's a lot of constant communication and collaboration on their specific scientific data storage needs uh niams has set up a partnership with strides team to accelerate use of our cloud services and in that we this year are have have done our first i'll say real stride initiative with backing up so we're replicating to aws to support our dr requirements in terms of looking at uh you know cloud things we are we're partnering with aws and azure to identify fedramp moderate compliance solutions and services and we're currently looking at doing our vmware dr solution moving that potentially to azure site recovery to see how we can do things better in terms of the things that susan spoke about the and the odss office again that's a relatively uh new office and has been extremely beneficial to us as we move forward they offer educational sessions and funding opportunities that we have found helpful as we learn to move forward so that entity is really extremely uh helpful for us as we learn to to move forward in our next next talk charter very we know too thank you mike would you like to add to that yeah uh latanya addressed quite a few important things here related to the infrastructure and transition to the cloud so i will talk a little bit more uh about um data science strategy and enabling data sets one of the trends that uh i noticed that everybody wants to build additional repository to build you know the data science solution based on that in nid we opted to somewhat different solutions we do not want to build a new repositories rather than that in order to comply with the fair principles that was defined by susan's office findable accessible interoperable and reproducible that's what we concentrate so think about the uh the best analogy i can come up with is like kayak.com kayak.com doesn't sell tickets but it's an integration engine that goes around findable websites of the airlines or other you know they added hotels and other uh consumer uh areas there so we're trying to use this similar approach towards the data science there are a lot of different repositories uh which have the data that being funded by the nih in general and id in particular trying to discover this data and once the data is discovered trying to come up with a common environment for the researchers to be able to manipulate that data in the cloud that includes storage resources that includes the provisioning of the high performance uh compute and so on so that's the strategy that we're implementing for the data science for enabling your data science uh to add to the additional pressure uh here we are now watching you know the another phase of explosion if you want in this scientific data so a few years ago we all were watching you know what the genomic sequencing was uh how it was impacting uh the our approaches to data storage uh data analysis we see the even bigger trend right now for the electronic microscopy okay that's a new phase of science that putting a lot of pressure on our infrastructure and in our data storage thank you for that and um jonathan even though you're not part of the nih i'm sure you have some great insights so would you like to answer the question sure you know be thank you um before i join into servicenow i worked as a cio in the federal government for many years so while while i wasn't in a uh in an agency just like nih i was at the department of agriculture there's a lot of scientific activity at the at the usda and a lot of similar kinds of requirements for managing and understanding the data but you know my role now is i work with um federal agencies cios across the government i think there's a lot of very consistent themes that i that i heard in our opening remarks you know that that dovetail very nicely with with what my experience of servicenow has been i'm trying to find the data and understand what you have so you can manage it uh the right way and in the case of science scientific organizations it might be creating you know placing it somewhere where it's easily accessible and people can interact with it at other times it might be understanding what data you have so you can secure it properly and make sure that it's protected it it you know it it's really based on the mission but understanding what and where your data is is a i think a fundamental requirement for or for cios that plus understanding how that data is ultimately used and how it flows through the organization to either to drive an outcome or to be made available for for research it requires some thoughtfulness about what what the data is where it is how it uses how it flows you have to take some time to understand all of that if you want to be able to do the bigger things that we all want to do with our data excellent um so now that we've talked about um you know these sort of greater goals and initiatives i want to talk about how um you know your mission is being integrated with the it modernization and data strategy that you have going on so um you know how are you know from the nih perspective how are researchers across your institute leveraging the technologies and strategy plans that you're introducing to enhance their biomedical science and maybe jonathan with your experience working with different cios across the space can you provide your own examples sure yeah if you'd like to get started so i i'm happy to kick it off i see you know routinely agencies attempting to to modernize and digitize services that they that they offer and again as i said before understanding how the data flows through the organization how the you know and that's a representation of what the work of that agency is understanding those workflows you know become very important because you know oftentimes and i think we saw this off a lot during covet you know we had processes that had just you know evolved over time and they depended in some cases on people being in an office and being able to interact and we had to adjust very quickly and all the agencies that i that i work with were able to do that so we made adjustments to these processes so we can still continue to uh do our mission whether we're sharing data or doing research or fighting forest fires like the at the usda but what we had what we have to do now is i think return to those processes that we adjusted and ask ourselves are these the right processes the right workflows right data flows for digital government and for digital services for digital transformation and making sure that we take the time to rethink and redesign those processes gives us a chance to modernize in a way forward that supports what work looks like and what the what the uh hybrid environments are going to be and how we're going to work in this in this new environment that we're all emerging into great i'm going to work in reverse order here so if mike you want to answer the question that'd be great or you know if latonya you want to jump in there were multiple questions you know and there are very loaded questions here so let's address the integration okay the the first one so um you know um i see all this uh being treated you know and looked at as enabler and supporter of the main mission of the organization what i am seeing these days uh and trying to position my organization that i see also become an instrument in advancing the scientific way well in our case scientific mission of the organization uh in case of the other industries advancing uh what the their mission uh is for many many years i this was you know in any presentation that i was giving in any uh talk uh that there are no non-computational disciplines uh left in science everything is complication so and leveraging uh that ability is well relatively easy now these days okay what technology provides i can give you one example you know what we are doing recently with one of the systems that we uh enable we build uh an operating for uh our instance genomic research information systems which uh allows the precision medicine for our patients in the clinical center okay we sequence uh do the full genomic sequence of every patient who is admitted to the uh clinical center provide genetic counseling everything is enabled and managed by our system that we built our bioinformaticians working together with the genetic counselors are providing you know advice to and uh explaining the outcomes of the uh analysis of the sequences of those patients which creates a new um the way for design new treatments basically better treat those patients and the way to design the uh new treatments we're creating uh new analytical tools that allow to join the clinical informatics uh data uh for uh from our patients again from the clinical center and so on so i think there is a big synergist now more than ever you can see synergies between the science and technology and that's very encouraging yeah i'll definitely get to that soon following question but i want to give latonya the chance to answer as well sure uh taking off with mike says a lot of a lot of what we're doing so at nih we have two parts so so when i'm the cio i'm the cio of our actual researchers that are doing doing clinical research and things like that right at the nih and then i have another group which which is responsible for um doing grants and giving out grant money to the rest of the world the us so those those two um entities have very different uh needs and part of that is really coming to understand them um we you know it really behooves us to do a lot of communication with each side to really understand what their needs are one of the things we started did an undertaking of again of a modernization we up just finished our a three-year legacy um of our applications and what we found in that is that roughly about 40 of the old applications were the functions were still being used because things had changed so drastically so really you know giving them what they need sitting down with them talking to them really dialoguing with them feeling like again we were a partner what we do at niam's my scientific director is really big on not calling me not calling him a customer he really gets upset with me on that i am a partner and in order to be a partner you really have to understand your business and really again do a lot of talking so that we're helping them so an example simple example we had many instances of a personal uh github applications right and so nih has has just uh put out a enterprise github application for all of nih and so that's a small thing of being able to to leverage what nih is doing helping our our scientists take advantage of those things and making it a little bit easier for them to do shareable data across across platforms we also again as mike talked about high performance computing again high performance computing is very big at nih and allowing the the scientists to be able to use the tools biowulf helix those applications to be able to do what they need to do but at the end of that they need to pull that data back to us and we have to be able to store it and allow them to use the tools that they need to that they need to do to do their analysis so it's a really kind of um when you talk about the the interaction between it and uh and and mission it's it's constantly doing a lot of talking and um making sure we're we're meeting their needs melissa if i could just jump in for one second what i really appreciate so much about those two responses is you know i t is there not for the sake of i.t i.t is there because it's driving the mission um latonya might both describe these use cases that are relying on the technologies they provide and you know as a former cio someone who's you know seen a lot of technology be purchased a lot of technology used it's it's not always um it's not always very explicitly stated how it's going to drive the mission and i think they both did that so i i really um give them some credit for thinking about the mission first definitely um you know uh lots of the modernization you're doing even though you're trying to be like a partner rather than a customer owner relationship um you know sometimes it's hard for lots of stakeholders to see that you're trying to develop for them and with them rather than um you know just being an inconvenience so um have you faced any challenges with change management and just generally trying to encourage a culture that embraces these new capabilities that you're bringing in um are there any challenges you face and how are you handling it like oh jonathan you want to start well i would just you know change management is something that people often overlook and uh there's always a a rush to get things done which i think we all understand and you know it felt in our different are different roles but sometimes you know if you go too fast you can create some blind spots in your in your approach and that can really impact your success so change management's one of those things that can sometimes be overlooked i i would just love to hear latonya and mike's experiences but mine was you have to plan for it and be explicit about the need for it if you want the technology you're rolling out to be adopted and successfully and for the people who you support to really see that value because if they don't see value in the work that you're um that you're doing um if you can't tell uh explain why um it's you know better and if they don't see why it's better to help track the mission it's very hard to get funding and support to do that whatever that next project is now you're absolutely right jonathan it's about the value you know the business seeing why this change is being made okay and continue to the topic you know to the previous topic it's about the partnership right it's about the partnership between the ac organization and business the old phrase is that there's no such thing as an ac project they're only business projects right we do not exist to do projects for ourselves our job is to help business to do their job more better faster more efficient right that's what uh we we supposed to do so partner equity business because it goes much easier and much faster when you have a stakeholders fully vested into that particular change so that way you change management process going much faster much smoother that's my experience with this definitely agree with that and an attempt to really help with that change management i meet with my scientific director and clinical director every other month and that's really again to make sure that we are on the same page they're allowed to give me some insights into where they're going and i give them an idea of of you know what i t is coming down the pike and of course we we we always talk about money at some point in the conversation but the the other part that's really kind of helpful when we talk about dr driving change management if i'm putting out something to to the organization um my scientific director is generally my first tester so he'll take he'll take it he's he'll learn it he'll do whatever and then really it makes it very hard for my scientists to say oh no we can't do that when your scientific director takes the lead but also i'd like to say in terms of our change management you know again i t driving the research is really research driving i.t and a lot of times we find that our scientists are driving much much faster than we can move so new tools to do analysis with upgrading instruments that create you know 10 times the the data of the last version so when we talk about change management again it's across the board that we have to sit down and kind of really have a lot of conversations about that when you asked about the the biggest challenges so for us our biggest two biggest challenges i'd say are out of control data growth and a culture that wants to save everything and then certainly again our i.t staff being able to keep up with the pace of technology at their pace that they want us to be at that's a great point um and you know going back to that whole aspect of how you know you know you could say it is driving research but research is driving the i.t um how are you generally acquiring and managing these it portfolios to meet those needs and the drive that science is you know pushing toward your um i.t organizations um i know latonya you mentioned strides before but how you top it um also uh tapping some of these common resources that nih is providing um to sort of uh you know meet those needs as well again the beauty of here the beauty of nih is is in our sharing of stuff so we are a big complex of you know the cios are intimately involved with each other we talk a lot um so strides again is new for us again i'm a small to medium institute so strides is a great opportunity for us to learn how to go to the cloud without um without having all the pains of that so we definitely have tapped into odss's the things that they have provided they uh just to give you a few examples of some of the things that we have taken advantage of they do something called for summer interns through a program called the civil digital program we've had two of two years of outstanding college graduates or college students in helping us move further in our data management quest there's a data scholar initiative that susan talked about earlier that uh suzanne dr susanna stein has has tapped into and then they had this year another thing of they offered funding um for the use of strides initiative on high value data sets so again it's a it's a complex thing you you do what you can do within your budget you look at without what's out there at the nih um the other part is that again when i talk about the the institutes again mike and i talk i learned from him the other big institutes their wealth of knowledge of sharing we spent a lot of time with the cancer institute as we started to really develop our data management initiative heart lung and blood again a large institute they as they started to do their modernization of uh hardware they they started doing something called flex on demand we spent a lot of time with them they they're about six to seven eight months ahead of us on on our next purchase but we're tapping into them in terms of uh changing our our i guess a funding stream really from uh from uh opex to a capex to an opex um and using that technology but again we're tapping into them and learning from them fantastic till latonya addressed that question atlanta i will be brief on this uh so uh what we're trying to implement uh with uh you know some successes and not necessarily all these successes is to have some kind of common operating environment strides is one of the examples of the common operating environment for the nih that nih is buying into uh there are a few others like uh we recently started uh actually expanded the initiative that started at many years ago electronic content management it's now expanded to the entire nih so we're trying to achieve efficiencies at least on the technology level uh to provide uh support for both scientists and administrators of science because keep in mind that over 80 percent of the nih are grants and contracts to the outside organizations it's important uh part of our business so uh that's what that's where we stand we in the very delicate phase i would say where the demand for the technology exceeds our budget and our ability to provide uh those services so uh governance is important uh very important for us as well as trying to standardize where possible as donnie was saying you know before our technology stacked to achieve efficiencies there so building on mike said um i i hear very similar kinds of uh challenges at agencies i work with across government and you know one of the one of the ways they solve for these common environments uh are finding some platforms that they can standardize on and you know i don't think that a large complicated organization like an nih or or nyad or you know these institutes there's necessarily one platform i think there's a few that was my experience at usda but you know once there's a few platforms it becomes very important to make good choices about which platform you use for the requirements that you have so really understanding what a platform is good at what is that where a natural fit is and having the governance that mike was describing help direct uh requirements into the right platform it that's a that's a way to reduce your technical debt lower costs over time and create more standardization which is what i i think i hear him i hear him saying but the idea that you know and there are platforms at nih's platforms at every agency but sometimes they're purchased non-strategically and you know i'm very much an advocate for really thinking through um uh having you know a platform strategy like to say you your platform as a strategy and um having a very clear understanding about why we're using servicenow why we're using microsoft so on and so forth so we we have less complexity in the environment overall and when you can share data across institutes or you can share um across research institutions you get a lot of value for that um that investment and those investments can be really you know managed uh pretty tightly when agencies are buying um comprehensively when they buy with an enterprise view of mine instead of 27 entities all purchasing the same tool individually we have to think enterprise even if the requirements are a little bit different that requires the governance everything that mike was describing the platforms are absolutely a way to achieve some of these long-term cost reduction and uh compatibility uh issues that exist everywhere but especially in an environment like mike's talking about ah great points um i want to zone out a little bit or zoom out i guess is what i'm the term i'm trying to find um so there have been a lot of administrative directives around security and equity and customer experience um just in the past year even so how do you see these um directives coming from uh up down impacting your approach to work um this could be you know within uh you know representation across health research or you know how you're creating a user-friendly environment for clinical trials how do you see these things um sort of uh manifesting in the way you approach work um i know mike you work a lot with clinical trials do you want to start we do work a lot with clinical trials okay and uh well what uh your question uh probably is uh if you're asking how we create more user-friendly environments for the our participants in the clinical trials uh there are some trials that we're running where we have what called uh patients reported outcomes okay so for those one yes it's absolutely critical to have not only the good interfaces but they secure interfaces that providing um you know a reliable way you know for the participants and protect participants uh who from this clinical trials can protect their data from uh instant accidental uh data release if a challenge is a challenge um we trying to utilize uh platforms uh for this we have a stand standardized architecture for uh all of this but uh i i will stop here and i'm not gonna go into greater details you know on how we ensuring security here uh because that's quite a complicated field no worries um i i think that the these directives you mentioned the cyber security executive order the customer experience executive order the diversity equity inclusion accessibility order i think these are being taken very seriously across government having been in government you get a lot of eos you get a lot of requirements and always it comes down to prioritization and how these things impact the organization because you can't do everything the budgets are always very limited so i think it's so important that you know from it and has a seat at the table and can talk about prioritization and resources if you can do that you can make a lot of progress across all these very important topics all right latonya did you want to add something real fast or you you set okay you're set um i know we're almost out of time but before we end lightning round from the cio perspective what are one or two lessons learned or best practices that you think other health it leadership would find really helpful or insightful so one of the things you know the biggest lessons learned you know in the last couple of years if you want uh we need to establish a solid digital foundation for all of our initiatives that's probably the biggest lesson we learned that uh once we moved uh people to the maximum seller okay we have to make sure that our business process were automated that people have access to this and to uh to the tools to do their jobs uh even remotely so uh i think that's the biggest lesson okay solid digital foundation need to be built uh so we can expand as new the other one that i would be that i would like also to mention we're talking a lot about the data analytics especially data analytics in the clinical uh world okay and there was a couple of talks before cup panel before us talking about all of this um we need to make sure that before we even talking about the analytics we do the proper data collection at the point of care okay because transforming that data and preparing for the data analysis one of is one of the biggest challenges that we had during this pandemic okay data is being collected to the different standards so standardization of the uh data collection the point of care is absolutely critical for us okay and i would have to say for for me the stakeholder involvement is critical to the success of any endeavor while technology rolls out and adoption is moving faster and faster than ever stakeholders and it teams are not always ready to move at the same time so really again that that that dialogues about what's coming down the pipe on each side so that we can help each other move to that and then certainly again as a this whole thing of data management big data again we we're learning so much about it and really again that governance that planning time that that thinking time of what is it going to take for us to be successful as an organization to to empower our missions and those lessons learned a line very uh you know very well with what i learned in my cio career you know you have to understand the data how it flows through the environment what what's the work of the environment how does it flow and then again like i think i stated earlier take the time to rethink in the redesign the processes that we have to the extent that we need to do so to be a really digital organization to have that strong digital foundation that mike was describing i think you have to do both things and then from a stakeholder involvement perspective latonya was suggesting if you can't tell um a a story about value that the technology is providing to your stakeholders to the mission uh you know research drives the uh the mission research drives the technology if you can't explain how you're playing a very important part in mission delivery as a cio it's hard again it's very hard to be successful it's very hard to have the trust and respect of your of your peers especially in a scientific or healthcare community and so it's so important to know what your baselines are what your improvements are and be able to get out there and and very uh proudly tell that story just like michael latonya have been able to do today fantastic um so i know we're a little bit over but i just wanted to take a second here to thank um all three of you for sharing a great amount of knowledge and a little bit about your work so um now as we close out i'd like to pass the program back to amy to give some closing remarks