Leadership’s Role in Driving Digitization in a Remote Era

[Jess Bozzo] Hello. I’m Jess Bozzo of Proformative. I’d like to welcome everyone to today’s webinar “Leaderships Role in Driving Digitization in a Remote Area”. I would like to think our sponsor Trovata. Trovata helps businesses automate the work it takes to gather and normalize all of its financial data provider like finance and treasury teams, access, build, manage and control their own trove of financial data from banks, businesses and accounting systems, an external markets connecting to these sources can minutes in terms of the learning objectives for today’s, webinar, we will explore why cfos and controllers are in a unique position to drive innovation for their organizations including digital transformation, how to fully involved leadership, the form and yeah your digital strategy, practical first steps for getting started including how to ensure that digital goals align with corporate strategy. And finally how automation can streamline processes like Bank reconciliation and increase efficiency. Before I introduced to these featured speaker, we have just a few housekeeping items to cover. Provider has made a case study available to you today, the case study feature square and can be found under the related content tab. Please take advantage of the case studies. We will send you links via email to the presentation and the recording within 24 hours. For those attendees on the line, we’re seeking CP, he credit today must answer all pulling questions and remain on the line for the duration of the webinar. Afterwards. If you are eligible to receive credit, you’ll be able to click on an icon to download certificate located in the certification section. You have any questions, you can email cpe at performative. Dotcom. We encourage you to submit any and all questions that come up during today’s. Webinar to the queue and a section of the interface. We set aside some time to address your questions following today’s session. And finally, please take the short survey at the end of today’s. Webinar. Nowadays, my distinct pleasure to introduce you to today’s. Featured speaker on the line today. We’re super excited to have Joseph who’s the chief technology officer with Trovata working with key fortune level brands including capital one, marriott international, Microsoft, Harley Davidson, and all state insurance, Joseph is help brands and navigate the digital landscape by creating and executing innovative digital strategies, as well as enterprise product integrations that incorporate cloud architecture, analytical insights, industry leading UI, you X and technical recommendations designed to bring measurable ROI before I turn things over to chose us to start things off. What we’re gonna do is start today’s. Webinar with our first point question of the day, this one will help us a baseline for today’s session on the screen in front of you, you’ll see our first pull. This one says our CFO and controller drive innovation across our organization including digital transformation. The answer options on your screen here are agree, disagree. Our finance team is generally not involved or I don’t know. We’ll give you a few seconds here to go ahead and select your answer. Again for those attorneys she can credit for today, to answer all three point questions. This is our first one, believe this question up for just a few more seconds here to give everyone a chance to answer. And then once we close this question down, we’ll share the results and have Joseph think a few comments before we dive into his content for today. So please go ahead and make your final solution here. Again, answer options or agree, disagree, or I don’t know, alright, without further, do let’s go ahead here and take a look at the results. I think this is pretty encouraging Joseph, but we’d like to get your thoughts here. It looks like about 80 percent of our attendees agreed that their finance team drive innovation across the organization. Do you have any thoughts here based on how our attendees have loaded?

[Joseph Drambarean] Absolutely. And I actually think this is an exciting question to kick things off because it’s segways perfectly into some of the talking points. And what we have seen here at Trovata is that there is a wave of finance transformation that is taking place on the heels of cloud kind of taking over as the dominant infrastructure posture. And add those conversations have been taking place which are forcing mechanisms for doing an inventory of different technology solutions within your corporate enterprise, whether it’s within finance or operations sales. All the different core ecosystems have been under review as cloud architecture is coming to… to kind of transform the way that… that enterprises do business. And with that, what we have found is that the CFO is really uniquely positioned to give direction and insights when it comes to the future of, or operations within the finance organization and how they set up their forward looking infrastructure for storing processing and utilizing the data that comes from the different sources, whether it’s from banks, ERP systems, whatever it might be kind of part of that… that ecosystem that they currently have. And sitting in that posture of being able to look from a forward looking lens as cloud. And as data transformation conversations are top of mind for it, it’s creating a unique opportunity to plan and to prepare for a world where all of your infrastructure is built for real time. It’s built for centralization and built for global scale. And I think that’s… that’s a perfect segue because it, you know, I’m actually happy that the… the result of the pool played out the way that it did. It would have been funny if it did it because I would strongly disagree, but it’s… it’s good to see that… that we have alignment.

[Jess Bozzo] Excellent. No. Thanks so much for your comments there, I agree. It’s a great way to kick off our webinar. And without further, do I’m, just if I can turn it over to you to get us started?

[Joseph Drambarean] Yeah, absolutely. I… I kind of mentioned a couple of the… the key insights that we’ve been seeing. And really it comes around this notion that the financial data that is used to drive reporting to drive predictive analytics, whether it’s the forecasting or RFP and bake rooms, or even add an operational level for the accounting teams that are responsible for reconciliation. All of those depend on data and data centralization and that data being formatted setup for accuracy and resilience overall. And what… what we have seen is that there’s really a director of solutions out in the market that provide a long-term strategy that is focused on the needs of the finance community when it comes to data transformation. And while there are, you know, plenty of conversations happening with regards to cloud architect, right? How cloud will impact, you know, finance transformation and how that could lead to a world that is, you know, driven by machine learning, driven by data resiliency and things of that nature. What often gets missed is the… the notion of how you get that data in the first place, which in the… the… the current kinds of way of doing things is fairly antiquated. It’s based on standards that were built in the eighties. And in some cases in the nineties their file base. They’re… they’re not flexible from a data perspective, and they are right for transformation. And really that comes on the heels of what’s been happening in the banking world as well as banks have been forced to adapt more open platforms with regards to financial reporting, which of course began to the… the consumer landscape, but has tripled now to wholesale corporate. It’s driven more open an accessible data reporting format that is driven by API and API, is our… our simply pipes that give us access in a more secure in real time way too and resources, whether it’s taking data, whether it’s ERP data, it could be data from different formats. But the… the… the key differentiator here is that instead of being flat file based which is not valuable, it’s… it’s kind of pre formatted. You can’t do much with it unless you, we take that data API provide a pipe that is significantly more valuable in terms of the data format. It gives you the opportunity to set up a world where performance and resilience and opportunity is kind have extended because of the… the data itself. And that’s kind of where we’ve been seeing a lot of the conversation with regards to financial data transformation. It starts with the data and you get advantage of the transformation that banks have been pushing through these new standards. And once you build on that foundation and you have data that for example, gives you advance remittance data, giving you payment details, or gives you real time information, for example across your balances, whether that means you know, intraday transactions as well in some cases with some banks that… that can be extended, of course. But the idea that being able to have access to better data much more real time pace is creating opportunity, whether it’s from an app development perspective, creating unique apps that performed things like forecasting in real time or providing multi variant forecasting or doing analysis on a real time basis, and providing triggers that give you alerts. When there are opportunities that could be had because of movements and market or movements, volumes within your business. These are accomplished because of… of kind of the base platform that… that comes from a data centralization strategy, at a strategy that is built on the foundation of clean data and data that is normalized. And that ultimately it unlocks opportunity at a time frankly for… for the organization type that may have been spent used on collecting data from different banking portals, collecting data from different resources, cleansing that data by hand to make sure that it is accurate first and foremost, and then to make sure that it works in, plays well with different reporting that you’re trying to build into it in the past that’s been a fairly, you know, excel dominance task that is driven by humans that is driven by folks that need to do it on a daily weekly, you know, monthly basis depending on the reporting intervals and with an appropriate strategy and a data platform to kind of create the foundation for it, you really unlock all the time that would have been spent in that manual process, which of course, that manual process is also right with… with errors and opportunities to… to introduce airs which of course, can be disastrous in time crunches can be disastrous if those results aren’t… aren’t accurate. And then there’s also the opportunity for data corruption, right? So when you have a lot of cooks in the kitchen, especially as, you know, we’re all getting used to this new environment with… with COVID and working remote and having folks kinds of work asynchronous lead distributed throughout the nation and throughout the world and working, you know, through cloud trying to work with it files and collaborate and everybody getting used to that you normal, it’s only kind of increasing the opportunity for… for errors that data mutation and things to go wrong that weren’t anticipated before. And of course, the security, it is also concerned that’s at this data is downloaded, you know, to computers. And… and what have you? So all of this to say that ultimately we have seen that, that’s a trolley of data is really where the conversation begins with regards to transformation within finance and what… what we have seen. As… as… as we’ve kind of brought to life the business, we were founded in 2016, you know, we had the opportunity to work with… with some key partners right out of the gate square, being one of them and helping understand a highly complex reporting environment that was global by nature with, across many different banks, you know, millions of transactions with regards to that volume and having the opportunity to work on a problem space that was a big data in nature and that needed the latest technology to solve at that… that scale. Really created an opportunity for us to build a business that was kind of built on the foundation of big data architecture and bringing to life technology solution that is kind have innovating within a highly under served community… community within finance that is used to workflows that are excel documents that are manual by nature and that really required a tremendous amount of manpower to create the results that… that… that they were driving. And so, Trovata at its core kind have innovated within that space. We’ve since, you know, raised our series day, we’re integrated with some of the… the… the biggest global banks whether it’s the JP Morgan the cities that HSBC, deutsche Bank, Silicon Valley Bank, and because those integrations exists directly within Trovata from an API perspective, we’ve had an opportunity to innovate within the data itself and provide standards and… and normalization around data reporting that really drives a tremendous amount of value. And the way that we’ve set up Trovata from a platform perspective, is kind have a three layer cake. As I… as I mentioned, we… we of course, begin with the data, make sure that we have the best data quality from the banks and of course, data that is real time by nature. But of course, we take that data and we prepare it from all the different formats that come from different banks. We prepared for a perform it’s a kind of mindset where it’s distributed with regards to it’s reporting capabilities. There’s no penalty for… for doing various different types of analytics or machine learning on that data. And then we set it up for the ability to… to plug and play with… with different systems, whether it needs our application that we’ve built focusing on forecasting, focusing on… on data analytics, or any other system provider, you know, plugging into the oracles, the Netsuite, the stage and tax the black points using that data set travesty to drive value throughout the rest of your ecosystem. And we’ve seen a tremendous amount of value in this conversation because of course, we are built on the foundation of the modern cloud. The concept of zero it required is one that’s pretty forward within this space. If there’s a lot of excitement when we are able to kick off a solution that gives you value within the first hour of onboarding, whether that be see your data live within the platform or be able to use it across different API that we expose. Trovata is setup for performance and for data accuracy at scale. So, I know that that’s a lot about… about us and a lot of bunch of audits. So I wanted to pause and give us an opportunity to transition to the next full question.

[Jess Bozzo] Excellent. Thanks so much for doing a really nice job of setting the stage Joseph. I think this is important context for the discussion that we’re about to have, but you’re absolutely, right. Let’s pause briefly and go ahead and launch our second pull question of the day. This one directly relates to the conversation that will have coming up in… in just a minute here. So we’d love to hear from you again. This question says our organization has developed a digital strategy to ensure we are investing in the right technology. You’ll see the answer options for this one are agree, disagree, or we are in the process of developing our digital strategy right now. Please take a few moments to select your answer, friendly reminder for those attendees who are interested in CP credit for today, you’ll need to answer three questions. This is our second one will use this question up to just a few more seconds to give everyone a chance to answer. And once we close this question down, we’ll share the results and have Joseph make a few comments before we transition to our fireside chat. Again. Friendly reminder. We’ll leave some time for audience queue. And towards the end of today’s session. So if you have any top quick questions for Joseph, please submit those in the queue and a section of the interface, and we’ll address as many as we can towards the end of today’s. Session. Alright, please go ahead and make your final selection here. Again. Answer options are agree, disagree, or we are in the process of developing our digital strategy right now. Give me just another second here and let’s go ahead and take a look at the results. It looks like the most popular answer with 47 percent is agree. So a little less than half we’ve got 12 percent disagree and a large majority are in the process of developing the strategy right now, which I know Joseph, we’ll talk about in just a few minutes. But any initial thoughts about how our attendees have voted for the second pull?

[Joseph Drambarean] Yeah, this… this sounds right in line. And the reason for that is because of course, as a cloud has been a big forcing mechanism. As I mentioned, not every organization is fully through that transition. And digital strategy at… at a transformation level is one that has the beach holistic. And I have, you know, heard quite a few different stories around where folks are in that process, whether it needs hey, you know, we… we have a vision for what we want to accomplish. You know, from a reporting perspective, from an organization perspective, how we want to set up our infrastructure, but we don’t know what we need to do next, right? What tools we need, how things should be set up, what kind of… of pitfalls we need to plan for. And then on the other side of the spectrum, it may be we did plan our digital strategy. And some of the things that we didn’t anticipate were how important extensibility would be, you know, in our… in our digital ecosystem, being able to connect some of the investments that we’ve made across different pieces of infrastructure, to be able to play nicely with other investments maybe that were making in other parts of the organization. And I… I feel like the… the dichotomy between those two is only going to continue as we get deeper into, you know, as… as a WS and Google cloud. It. And then Microsoft azure continue to dominate in the landscape of it. These will only continue to… to… to drive the conversation. So it’s… it’s very interesting. I think that’s right in line with my expectation.

[Jess Bozzo] Excellent. Thanks so much for commenting there. And now, I’m super excited to get into our… our interactive fireside chat here. I’ve got a number of questions I’m gonna close out to… to Joseph that relate to pretty much everything we’ve… we’ve chatted about so far. And again, after our… our fireside chat, we’ll save some time for Q&A.

[Jess Bozzo] So submit your questions, and we’ll get you as many as we can towards the end. So just to kick things off, you know, the… the overall theme for today is leaderships role and driving digitization in a remote era due to the pandemic, maybe a good place to start is by having you reflect on what you’ve seen from companies and how they’ve navigated through the… the crisis over the past year.

[Joseph Drambarean] Yeah, it’s I think that there’s quite a… a bit of variety in terms of things that we’ve seen. The first is the… the shock, right? The… the… the culture shock of having to work environment, we’re collaboration and sharing of information is no longer as simple as your colleague is sitting next to you and your, you know, sitting together looking at a monitor and… and working through a problem. Now everything has to be done securely through a means that is purely digital. And whether that means you’re sharing on screen, share or… or interacting with… with data in a way that is invaluable and can… can be done, you know, by a group or, you know, a handful team members that’s been an interesting transition because of course, not every a staff within… within finance is used to idea of having to work purely digital and remotely and do it in a way that is secure the, in a way that is conducive to… to collaboration. And as a result, there’s been tons of duplication of effort, tons of duplication of data and inaccuracy is that have been introduced. And it’s been interesting to hear that side of the story because it’s one that’s probably often missed just the… the… the culture shock of that transition. But of course, as… as we’ve all gotten used to it and, you know, we’re over a year into it now, it’s… it’s gotten to the point where because of the tools coming to light in… in the forcing mechanisms of it having to source different vendors, having to source different technologies, there’s there is quite a bit of… of you a capability that’s been introduced. So it’s… it’s kind of too much all at a, in a short period of time, I’d say which is driving the fragmentation of solutions, whether it needs doing a little bit of work in excel to prepare some of your insights. And then maybe transitioning to a database that is plug into a Tableau interface that maybe helps you drive dashboarding or… or drive executive stakeholder reporting, and then having to publish that in a way that is secure and centralized. What we’ve seen is that there’s a tremendous amount of fragmentation at the tooling as well. And as we’ve been approaching this conversation, you know, from… from… from Trovata and our perspective, it’s been interesting to get feedback around how important data centralization but also app centralization is to the workflow of… of… of finance groups and having harmony between the security resilience that is trying to drive as we are getting, you know, more and more remote in… in our culture and more… and more remote in our workflows. But then at the same time having the same level of collaboration and the same expectations. The stakeholder perspective as we’re trying to get you solve that. It’s been interesting to see that the academy because, you know, Trovata has always had a fully integrated philosophy, you know, top to bottom whether you’re looking at a data integration perspective with the banks or an end reporting solution through our software that can be delivered, stakeholders, we’ve had the mindset of creating a solution that… that covers all of the gaps in that value chain. And what do you don’t have that? It… it kinda introduces a friction in places where maybe it might have been on natural in the past because we didn’t have to deal with fully remote.

[Jess Bozzo] Yeah. I think… I think you’ve covered a lot of the key themes that we’re going to be exploring and a bit more detail coming up. But I think that’s really… really great insight and it sets the stage really well for our next question which, you know, in your opinion Joseph what is leaderships role? But, you know, primarily finance audience today. So cfos, controllers, VPS of finance, but what’s their role in… in driving digitization or… or maybe leadership at the highest level and a company not even specific to finance? And, you know, what’s that role driving digitization? And I guess I’d be curious if… if you’ve seen that rule should… should all now that you know, everyone’s remote like we were chatting about with our… our first question there.

[Joseph Drambarean] Absolutely. I think that there’s… there’s been a tremendous shift and I think the most significant one has been forcing leaders to sit into a visionary posture, were reacting to some of the new realities of the landscape, whether it means… the fluctuation of the markets and being the lack of predictability within the… the economic environment that… that we’re living through. That is one major culture shock that I think has been driving the need to… to sit in the visionary posture, looking at the reality of the… the… the organization as it stands today and playing out over the next three, two, five years. If, you know, if this continues, if… if we continue to March towards the path where some of the uncertainties that we’ve seen continue, how do we nimbly react? How are we set up for success? So that, whether it means from a, an understanding of… of core fundamentals and marketplace and our business, how can we get the right information in real time to be able to react appropriately? And then of course, the flip side of that being, can we predict, can we prepare for a future that is uncertain? It is there variability in the planning that… that we can accomplish, whether that means using technology or machine learning to help augment some of that in and applies statistics and insights that maybe couldn’t be accomplished by a workforce that had access to the same data. Some of these challenges have been top of mind, but of course, it’s not just about being a visionary and, you know, you can be a visionary and you can’t put together a great strategy. But then it’s all about the execution of that. And I think that finance leaders especially within the CFO role have been forced to enter the… the conversations around vendor management and around retooling, looking at data transformation in partnership with… with it stakeholders, and with folks that are responsible for technology overall within their workforce. And it’s… it’s been an interesting development to see that, you know, the CFO role is… is moving from being, you know, just focused on… the… the… the fundamentals of the business and… and driving value, you know, from a finance leadership perspective to also then mutating to include leadership with regards to productivity, you know, productivity across their… their finance teams, but also through the wider ecosystem, whether it needs planning for a future where data is… is not only highly available but also distributed to different vendors that are mission critical, you know, for… for different tasks or whether it’s month end close or, you know, analytics or… or… or payments.

All of these really require both a visionary long-term outlook, but also then an execution layer that is driven by pursuit to… to innovation and the transformation is you set up your future for a one of uncertainty. So, I think that, that’s those. Two has been very interesting to observe it. It’s of course, the time compression is also an element here that is unprecedented where these decisions need to be made in a quick fashion. Whether it means, you know, vendor management and selection that implementation and how long that takes. Because of course, what’s the value of setting up a long-term vision and execution. If then you have to wait a year or… or… or longer to… to onboard at, to implement, you do lose out on… on all of that value. And so having an ecosystem of vendors that are set up for modern computing, modern workflows that have minimal footprint. So, with regards to it, I’ve also been key to that discussion and… and finding value as quickly as possible to enable some of this nimble decision making.

[Jess Bozzo] Yeah, I think that’s spot on and I think you’ve touched on. It just says around why cfos and controllers and their teams are uniquely positioned to drive some of this information. And is that because, you know, you alluded too, it, they’re… they’re now having to step up and enter vendor management responsibilities. They… they see so much data across the organization. So that data transformation that you were talking about, you know, why do you think finance can be uniquely positioned to help drive this across the organization?

[Joseph Drambarean] Well, I think that the… the most easy answer to this is because of the sun travesty of their role in… in driving the outlook of the business. And if, you know, what do you think about it at its most basic level, if finance doesn’t have the right tools, the right data and the information available to them to be able to make the right decisions that impacts everyone, impacts operations that impact, you know, even it… it impacts sales, they affect every… every chain of the business. And so, I think the central the of their role from a strategy perspective helps drive the need for some of this… this transformation. And the buy in is… is usually as… as far as we’ve seen pretty wide because it’s not a question of should we do this? It’s a question of how, you know, if nobody disagrees with the reality of, hey, we need data that is accurate. We need data that is, you know, in real as close to new near real time as possible because we need to those decisions quickly. There’s not going to be much the bait about that both from a board and from an internal kinds of stakeholder perspective. The… the… the base will happen around the house. You know, when should we do it? How systemic of a shock are we ready to take on who will manage this process? And what’s the process is kicked off? Can we, depends on this technology? How much of the future do we have to plan on from a mitigation perspective? Where maybe we are, you know, straddling between the old way of doing things of the new way of doing things for, you know, a few months to a few quarters to maybe even a year as… as we go through this process, all of those questions are fairly new to the finance organization. What, but focusing on, you know, the specifics of vendor management and implementation and all of that. I think that that’s driving an evolution in some of the… the… the roles that we’re seeing within finance. And of course, and evolution at the leadership level.

[Jess Bozzo] Absolutely. And I wanna take us back to our… our second pull for question. For the… the next question. I’m about to ask excuse mean, and we know that a strong digital strategy, as you mentioned, it’s crucial now more than ever for I just want to pull those… those results back up quickly. You know, we have a majority of the group who is developing their digital strategy right now. Do you have any best practices for forming that digital strategy and then implementing it? And I guess in an ad on question would be who should be involved internally in… in developing that and building that out?

[Joseph Drambarean] Yeah, that’s a great question. And I think the first thing that comes to mind from a strategy perspective is of course, that there is, there’s the maturity curve with regards to that strategy. And it, we have talked a lot about the strategy of data and how important that is. And there’s no disputing that. But as you start to put the fundamentals in place of how you want your foundation to be set up, the next, an obvious question is value it, how can we leverage modern technology? Whether it’s within artificial intelligence or whether it’s within the real time and dynamic alerting, real time and dynamic decision making? How can we take advantage of these tools that were built for a future that is highly automated where roles that may have in the past been responsible for making a decision can potentially be deprecated, favor of strategy where you can depend on a system to make a majority of the decisions that you would be making based solely on preferences and in some cases, based on the analysis that is performed by an artificial intelligence… intelligence module. And so, asking questions around how that type of technology might fit within the vision that you’re crafting from, you know, three or five year tenure outlook are really important because it sets the stage before adapting that kinds of technology to your workflows and also preparing staff for a world where that client of technology is working hand in hand with the day to day operations. And I think that… that has also been an interesting segue with regards to the future at some of these roles. As you get into a more strategic posture and more… and more of your time is spent analyzing data that has already been curated, data that has been dissected and… and analyzed in a way that surfaces the key insights, how does that change your approach? And what does that mean from the process design perspective? And another area that has been interesting to see conversations kind of bubbling up is once we have technology, once we plan for a technology solution, how do we then redefined some of the process workflows that we have to date? And that’s kind of one of the areas where we’ve seen tremendous amount of friction because as you adapt to realities of real time realities of… of the sheet driven analysis, the old ways of… of reporting and the old ways of setting up stakeholder management, it that’s where the… the friction kind of takes place. And I think that… that has to be built into the conversation especially when… when trying to plan for the future.

[Jess Bozzo] Absolutely. Yeah, I couldn’t agree more. And we just, we’re… we’re talking about it’s… it’s. Been kind have a thread we’ve… we’ve touched on throughout our discussion, but we hear so much about machine learning about AI. You know, are there any specific we use that you’re seeing finance teams, whether it’s… it’s customers, or even internally, how they’re trying to leverage some of these technologies? And I’d be curious as part of that. Are there certain processes that they’re trying to automate specifically? I know in the beginning we… we talked about Bank reconciliation. So what would love to hear your thoughts there, Joseph?

[Joseph Drambarean] Yeah, absolutely. I think that there are three key areas that we’ve seen and of course, this will continue to evolve aggressively as… as finance stakeholders have access these tools. But the three that we’ve seen that have been fascinating have been around the forecasting of financial data, the coalition and analysis of historical financial data, and then ultimately the identification of anomalous behavior within historical financial data. Those three have been very interesting areas of the development that squarely use the power of machine learning to attributes as well as you know, AI driven insights that are fully unsupervised. And what’s fascinating. I, at least within the forecasting realm is not necessarily the you of anything that is, I’d say dramatically game changing from a statistics perspective. A lot of the techniques that are used in… in forecasting from an overall perspective are rooted in H old, you know, mathematical techniques. The only difference of course being that the access to tremendously higher volumes of data and compute capacity that enable to work through that data with very little penalty, allows for the operator to explore nuances around forecasting. It, even some cases, competitive models that allow for them to navigate essentially different views and vantage points of outlooks from a forecasting perspective that if you were to sit down and kind of having a team or… or an individual try to work through on… on a similar dataset would be very good goals. You know, possibly it’s possible that it would be impossible and that kind have advantage, you know, from machine or machine perspective drives simple. This is having a no penalty approach, the forecasting where it gives the past, the penalty of course would be in the preparation of the data and having to rerun your… your data segmentation, and the modeling that you have in place, whether it’s within a specific database within excel or, you know, even in… in a more modern approach with, in… in a database in the cloud, both require kind of Huber, duration of… of that data. But what you’re working within an environment where there’s no penalty that data is already setup for high performance compute, you could take advantage of a more with some approach to forecasting where you can explore maybe eight goals, many of versions of a forecast to see and understand where the gaps might like. Where the exposure is my client, where you might want to have a more aggressive versus a more conservative approach that’s a key area. I think where machine learning has driven a tremendous amount of value within analysis and kinds of segmentation of data. I think that’s another fascinating area… area of machine learning and artificial intelligence. Because of course, machines are built to identify patterns at a scale and add a speed that you would could never do. And of course, when you’re working with a huge volumes of… of transactions where you know, thinking from an eCommerce perspective, for example, where my new developments in… in… in patterns that are taking place from an operations perspective, from a payment perspective, from a vendor management person, all of those could be best, you know, in a traditional finance opt where… where an analysis is… is undertaking. And of course, those traditional workflows can’t do it all the time. You know, you have to plan in advance for that kind of… of effort and you may be reporting on a weekly or maybe even a monthly basis and that… that insight may already be inaccurate and stale at that point. And so, one of the big, one of the biggest advantages I’d say have a headless and fully unsupervised machine learning approach to insights is that you will find insights that are driven by statistical analysis that you might never find if you did it through… through manual workflows and that is a huge advantage especially when looking at, you know, the third rail of what I mentioned which is an anomaly detection understanding from understanding cases where unplanned flows are existing within your… your… your operations, fraud detection and anomaly detection is an area of key interest at Trovata, one where we are applying a tremendous amount of… of machine learning talent to identify a cases where Trovata can have your back and give you the peace of mind that if there are areas of your flow volume that maybe you would not have discovered before we will, and we will alert you and that’s a very modern posture I’d say with regards to… to management of data where instead of having to be a proactive around managing your data, you could be passive. You can expect that your data is not only pulling accurately and at scale but it’s also being monitored for cases that you may not even understood.

[Jess Bozzo] Absolutely. Yeah. The… the benefits that you mentioned, I think are… are probably some especially the access to insights and at speed. So faster than… than previously was available. Our… our major advantages especially now that… that businesses most likely want to take advantage of. So I appreciate you outlining those and then sharing the processes as well. I think that’s… that’s hugely helpful… helpful. Excuse me, to our audience. We… we talked about it, you know, a little bit earlier a bit, but, you know, I’m imagining we have attendees on the line that this sounds really good. They’re… they’re ready to start if they haven’t already digitizing some of these other processes internally, have you observed? And, you know, with your customers and you just hit falls that team should watch out for when it comes to digitization.

[Joseph Drambarean] Yeah, I think a major one that comes to mind. And of course, the angle of… of this talk being specifically on… on data transformation, but the data that… that you have access to make and breaks the entire reporting pipeline. You know, it’s… it’s one thing to talk about machine learning and the benefits of it. But machine learning works only as well as the quality of data that you’re putting into the machine. And one of the fascinating areas of discussion that… that we’ve seen is kind of the full stack assessment of the finance operation going all the way to bake and working with the bankers on, hey, if… if we’re embarking on this digital transformation journey, what can you do to help you know, what kinds of capabilities do you have available to help supplement some of the work that we’re doing to setup infrastructure that will take advantage of a centralized strategy? Because of course, if… if you’re working with data that is built for, you know, the legacy reporting posture that you’re not going to people to take advantage of some of these more modern techniques, whether it’s you know, it’s site analysis, or anomaly detection, if you don’t have enough met a data and your financial data to drive some of those insights.

And so areas where we’ve seen a tremendous amount of opportunity to innovate and kind of have discussions are… are at the banking level and working directly with your banking partners to accomplish some of these goals. And then as you layer on top of that, the next step of course is to… to plan for… for the… the data environment that will drive some of these reporting capabilities. And what needs to be kept top of mind is… is not just the availability of the data to the organization, but some of these long-term objectives, right? If there’s a vision that a CFO might have out taking advantage of some of these more advanced capabilities, whether it’s within the machine learning landscape or within the… the payments landscapes, it really matters if… if… if you don’t bring it up kind of at the beginning of that discussion because the wrong architecture, the route, the wrong cloud architecture can actually be put in place from the beginning, preventing some of those capabilities. And what we’ve seen is partnering early with stakeholders within business systems within it will really drive value. Especially if you have a vision in place. I think the final thing to consider is how do you design your… your operation as you can make some of these fundamentals. I touched on that a little bit and how roles are evolving and adapting and changing as a result of some of this technology, I don’t think that… that can be overlooked especially when we’re looking at… at operational efficiencies when taking advantage these tools because the worst thing that could happen, it is you invested a ton in… in some of these tools but folks have not redesigned the processes and that the outputs and recording needs to accommodate some of these new tools that you’re kind of sitting where you were after having spent a ton on investing in those tools. So having a training regiment, having a, an onboarding sequence for… for new hires, having a plan for operationalizing some of these tools and driving proficiency. Of course, we’re talking about proficiency in excel added database and sequel that has been, you know, in place for the last 15, 20 years. It’s not easy to rip the band aid off and converts to a more modern approach, right? And so planning actively and… and well in advance and working with vendors to high kind of on board and… and create planning modules that will drive efficiency in… in the workforce is really important as well.

[Jess Bozzo] Absolutely. I think that’s a really crucial point. I’m investing in… in the right tools for your organization, but perhaps more importantly investing in your people to… to backup the technology and… and make sure it works for your business. So you can really, you know, reap the benefits that… that we were discussing earlier. I think that’s key. So, so thanks for pointing that out. I have just a few more questions here before we leave a couple of minutes for Q&A. So again, for our attendees, if you have any questions for Joseph, chat those in and we’ll save some time towards the end. As we’ve been highlighting Joseph access to information, it’s happening in real time. It’s fine. How can finance teams be equipped? So they’re prepared for what’s next? So they can be less reactive and more proactive. Do you have any insights there?

[Joseph Drambarean] Yeah. I… I think that I’ve mentioned this point that I can… I can maybe elaborate on that a little bit further that the posture of… of nimbly reacting is one that is readily available with today’s technology, right?

You know, there’s… there’s no innovation required in order to take advantage of current rails that are driving real time reporting. I think that where the… the innovation lies and where some of the more on natural pastors will take place are in the idea of having a proactive notifications and proactive alerts to drive decision making when you’re not in front of your workstation, when you’re not focusing on the data and that’s… that’s an area that we’ve been focusing on quite a bit. You know, to what extent does real time monitoring play into real time data reporting? Because you can be, you know, extremely nimble, and maybe you’re… you’re the type of… of operator that will be in front of your computer and be monitoring some of these statistics and insights over the course of the day multiple times a day. But if you’re… if you’re like me and, you know, you’re… you’re in back to back meetings pretty much every single day, you’re focusing on strategic decision making and maybe you have an opportunity to do some of that research once a week or maybe once a day, then it’s possible that you’ll miss out on quite a bit of that insight. And so setting up for questions around hey, what kinds of monitoring capabilities are available? What can I take advantage of with regards to monitoring? Allows for me to set up a web of preferences that keeps me up to date without me having to do any work. I think that’s where the future lives.

Because ultimately, you’re only as good as the latest data, right? In terms of reporting perspective, you can do storable analysis and see the trends. But if something is happening in real time and you’re not aware of it, you can’t react and that’s where some of the concepts that are more familiar and the consumer landscape, the… the, you know, the… the notion of being made aware in real time when something is happening that’s something that you would expect from a consumer technology. But we are seeing the need to transition the enterprise to those… those same concepts and drive that kind of behavior change that will ultimately drive more nimble a decision making.

[Jess Bozzo] Absolutely. No. Thanks so much for… for sharing there. And I’m just keeping an eye on the time here, Joseph and we’ve got a couple of minutes left, I think before we transition over to audience queue and I just like to round out all of our fireside chats. You know, we chatted about so many different topics. And… and before we… we go ahead to our last pulled some queue. And is there anything else you’d like to leave our attendees with anything maybe that? No, I didn’t get the opportunity to ask you or anything else really hammer home some of these… these topics to… to our attendees on the line.

[Joseph Drambarean] Yeah, I… I actually do have one. And this one usually isn’t top of mind, which is why I wanted to bring it up. Some of the most fascinating discussion that we’ve been having with our customers are in an area that I truly think it’s nascent in data transformation, which is that many corporates and organizations that are starting to invest more and more data transformation have availability from an engineering perspective in house. And as result, it’s driving custom application development. So outside of even sourcing capabilities from a vendor or from a specific tool, because of the availability of engineering resources in house, it’s driving an appetite to build custom solutions that are built by internal engineering. But that’s still have the same basic needs from a vendor perspective, right? So that data in that data out. And so what we’ve seen as a fascinating development is the rise of Trovata, his own API, being exposed to internal engineering programs to drive custom app development, whether it’s for reconciliation purposes, whether it’s for a data collection purposes, whether it’s for even, you know, nominal tasks like it’s feeding the data lake internally. These are starting to be conversations that maybe didn’t exist three years ago. But now we’re very much top of mind as data transformation is running its course. And as… as you resources that are… are being hired within the enterprise, I would keep an eye on that because it’s… it’s an area of fast development and it’s also frankly an area of tremendous innovation where we will see a diversion between different industries if they’re in house application developers that are driving value that a lot of the posturing becomes, what kinds of platform do they have available to them to drive some of that value? What kinds of API does that platform provide, kind of resilience? Does that platform deliver? And all of that kind of becomes a completely different angle to the conversation, right? We’re driving a developer community internally is really not something that a CFO would have at the top of my topic, but it could very well be calm and interesting twist to the conversation as resources are made available within their… their tool sweet.

[Jess Bozzo] Excellent. I think you’re right? I think that’s probably not something we would initially consider. So I think that’s an excellent point to… to kind of leave us on there. So, thanks so much Joseph. I… I thoroughly enjoy having the opportunity to chat with you today. I’m sure our attendees have as well. So thank you again. I really appreciate it. I am starting to see some questions come in so we’ll save some time for those. It’s great. We’ve got a couple of minutes left. I think before we get to those will go ahead and pull you a final time or third and final pull right here on your screen. I’m just like to hear from you a final time on how your finance department, but it’s current level of automation. Are you fully… automated largely… automated, largely automated with plans to upgrade partially automated or not automated at all? We’ll give you a few moments here to go ahead and select final answer. And just like our other two poles, we’ll have Joseph make a couple of comments and then we’ll… we’ll go ahead and take some attendee questions. So give you a couple of minutes here. Excuse me seconds. And then go ahead and take a look at the results. Again, friendly reminder will get to Q and a and just a second. If you have any additional questions those in and we’ll get to them in… in just a moment here. All right. We’ll give you just another second or two. And now we’ll go ahead and take a look at the results. I’m just scrolling here. It looks like the… the most popular answer. I think perhaps not surprisingly, especially after our discussion today is personally automated with plans to upgrade, Joseph. Is… is this in line with what you guys are seeing? We’d love to hear your thoughts.

[Joseph Drambarean] I love that the responses are as fragmented as they are because it… it is very common place.

And I think the reason for the partially automated with clients to upgrade being as high as it is because it’s really tricky to get it right on the first try, what also working through and it transformation, right? Because having the rights, a plan and the right data capabilities in mind from… from stage one as so many things are getting blown up from an infrastructure perspective is… is just really tricky. And what we’ve seen is that having the ability to be in those moments where maybe you got it wrong from a plumbing perspective, but you didn’t get it wrong from a data storage perspective and a data centralization perspective, then you are setup for being nimble and reacting to a new tools that you might introduce or new capabilities that you might introduce. And so, I think that’s why storage and normalization are so key in these discussions because the… the… the foundation that you build on ends up being the thing that you… you leverage when you are, you know, dissatisfied with… with an existing integration. So yeah, this… this is very in line with what we’re seeing.

[Jess Bozzo] Excellent. Thanks so much. And I think we have time maybe for a question here. I just saw one come in that would love to have you try me on this… on this attendee, right? What the data that’s being reference is all in real time? What is the capability to have data timestamped in quote, unquote locked, for example, month and closing cycles and reporting their capability to have more of a live version and historical version?

[Joseph Drambarean] That is a great question. And I… I actually think that it’s one that we missed during our… our fireside chat because that is an important element of the data ecosystem. It’s the concept of it beautiful data and beautiful data, right? Data that you want timestamped because, you know, in this case, the… the month end close being an important process. But there are other cases where maybe in forecast analysis, you want to make sure that when charging a variance, you’re looking at data that was, you know, as of the type when the forecast was made, you can apply a true variance analysis to it. And that is definitely something that we look at very critically from a Trovata data infrastructure perspective. As I said, that… that dichotomy between beautiful and immutable data is one that is really important to Trovata data stack. It, beautiful data, of course, is… is… is data that is data that cannot be changed, right? So data that comes from a Baker, ample of that transaction records Bank balances things of that nature. But then also Cuba generated data preferences that were set with the mindset of saving this report. It’s current version for future purposes, forecast the data for future purposes, analytical and reconciliation data for future analysis or… or for auditing purposes. That is, it’s… it’s really important to have a mindset of a kind have it, but it’s snapshot, if you will be able to save that data in a way that I scaleable. And that takes advantage of a web of users, right? Because that snapshot capability, it shouldn’t be at just the top level. It should be at an individual user level where activities that… that take place within the platform. And from a data perspective, can be stored by user, by entitlements and by purpose. And I think that that’s… that’s actually a great question. It’s… it’s an important aspect to any data strategy.

[Jess Bozzo] Absolutely. And I think, you know, just to… to close out, and since we’re you know, we’re lucky enough that you’re a cto and you have that unique lens. Speaking to what is primarily today a finance audience. I was just wondering just if… if you have any advice on how our… our finance executive can better work with their cto or their CEO when it comes to digitization, do you have any unique insight there? Any lessons learned over the course of your career that… that you’d share on that topic?

[Joseph Drambarean] Yeah. I think that the… the best less than that I have learned is that when communicating goals and objectives, they go away from solutions and instead focusing on intent is key. And I’ve seen many cases where even in my career where in driving to quickly to a solution might cause a recommendation that is missing on the, you know, the forest for the trees, right? And focusing on intent really drives value from an engineering perspective because when appropriate incentives understood especially if it’s visionary, if it’s hey, I want to live in a world where I can nimbly react to market and… and internal data that is flowing through my workstation as well as through my old mobile app. If that’s… if that’s the tenth, if that’s something that you want to accomplish that in engineering, executive could sit there and it says, hey, is that even possible right now be, if it isn’t possible, what do I need to change? What do I need to do to accomplish that intent? And then see if there is strategic risk to doing that… that… that transformation, then you can engage in dialogue with your stakeholders, your partner and say, look, I agree with your intent. I think your intent is awesome but you have to understand what it will be from a transformation of your organization perspective, what it means for us from a digital transformation perspective, how long it might take the… the value benefit chain. Those types of conversations are best setup when intent is the… the… the driver.

[Jess Bozzo] I think that’s really great advice and I think that’s a really nice way to… to wrap up today’s webinar. So thanks again Joseph for again taking an hour out of your data, share some of your insights and expertise… expertise with us. It was great discussion and a hugely enjoyed being a part of it. We’re going to go ahead and wrap up since we’re at the top of the hour today. So again, big, thank you to Joseph and Trovata for a really great session today. Please do remember to take advantage of the square case study that can be found under the related content tab. Welcome to join us at performative dotcom to continue the conversation with your peers in the community. And if you’d like an introduction to Joseph or just Trovata in general, please do tell us in the survey once again, we want to sink provider for making today’s webinar possible. If you’re interested in learning more, please visit their website which can be found on the slide here. Thank you again to everyone. And we hope that you enjoy the rest of your day.