Host Dave Sobel welcomes Sri Ganesan, co-founder and CEO of RocketLane, to discuss the evolving landscape of professional services automation (PSA). The conversation delves into the challenges faced by IT service providers in managing client-facing projects and the need to transition from a hero-driven approach to a more systematic, governance-focused model. Sree emphasizes the importance of standardizing project delivery to enhance consistency and efficiency, which is at the core of RocketLane's mission.
Sri elaborates on the integration of artificial intelligence (AI) within RocketLane's platform, distinguishing between automation and AI. He provides examples of how their software utilizes machine learning to optimize project staffing by suggesting the best-fit team based on various criteria, such as availability and skill sets. Additionally, he discusses the innovative use of AI in automating post-sale documentation and communication, allowing project managers to streamline their workflows and focus on high-impact tasks.
The episode also highlights the significance of data quality and governance in effective project management. Sri shares insights on how to improve data collection by making it low friction for teams to input information. He explains that by automating data entry and providing integrations, such as calendar syncing for time tracking, organizations can enhance the accuracy and reliability of their data, ultimately leading to better decision-making and project outcomes.
Finally, Sri addresses the balance between automation and human oversight in project management. He discusses how automation can serve as a proactive tool for project governance, alerting leaders to potential issues before they escalate. By combining automated insights with human intervention, organizations can foster a more responsive and efficient project management environment. Looking ahead, Sri envisions a future where AI continues to play a pivotal role in enhancing service delivery, making it more predictable and standardized across various projects.
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(upbeat music) - Professional Services Automation is an area that IT service providers talk about a lot, but what can we learn from those in the project-based professional services automation space? Sree, God of Sunnet is the co-founder and CEO of Rocket Lane, who joins me today on this bonus episode of the Business of Tech. Well, Sree, thanks for joining me today. - Dave, thanks for having me on. - So I'm super excited to talk to you because you've been leaning into professional services automation tool focused on project and focused on infusing AI into the product. Give me a little bit of a sense of what problem you're focused on solving. - Yeah, I think the core of what we are trying to do here is there's a lot of client-facing projects that various services teams run, and you wanna move away from being hero-driven, in how you deliver on these client-facing projects to making things more system-driven, bringing in tighter governance. And today, I think the way all of this happens is best effort, not driven by tools. You're always relying on someone doing a great job. That's where we started our journey. How do we standardize and make project delivery consistent? That's the crux of where we started building our company. - Now, everybody fuses the phrase AI to make it hip and cool, and I get that. Give me what your definition of the artificial intelligence component of the product is. - Yeah, the way we see it, there's automation and there's artificial intelligence. Sometimes people conflict the two. We've employed both in how we have thought about creating our product, right? So there's an angle of automation that helps people do their projects more efficiently, but there's also intelligence that we've brought in. I'll give you a couple of examples. One is when you think about staffing a new project, that's common. You need to match various conditions. You need to know who is available when, you need to know what their skillsets are. You need to also look at what is their cost and do you want to optimize for profitability on this project? Or do you want to balance the load on your team? Basis, which options you select, our software will automatically suggest the right team for you to staff on your project. You can still add further filters, variances. This is more of like a machine learning model that you're talking about, which suggests, hey, this is the best fit team that we have for you. And then in one click, you can go and staff that project. The one click part is, of course, automation. The rest of it is machine learning model. So that's one example. Another great example is, I think, in the sales world, a lot of us are familiar with tools like GONG and ABOMA, et cetera, which do call recording and then automation for same themes to do their work better, fill in the CRM automatically, et cetera. In the post-sale delivery world, there is nothing that is built to integrate and work well with your project delivery tools, right? And that's an area where we've been awaited to say, hey, if there is a project delivery team that's going on calls with customers, what can be gleaned from those calls which can help automate filling a document that you need to put together? What can be automated pulling from those calls to fill in an email that you need to compose after the call? And you can define your own prompts for what you want to get as placeholders that go into email templates that we have or document templates that we have. Great example is, hey, I want to document all the decisions made on this call along with the key dates that are mentioned and who made those decisions. Now that can be a placeholder. We call it an AI fill which you can templateize and say, this AI fill needs to go in this part of my email template. And then when a project manager needs to send out communication, they pull a template. The template has one or more AI fills. You can substitute those with the actual content just by selecting a gong recording or a zoom recording saying, hey, here's the recording I want to pull from. And then the rest is magic, right? So it sort of gives you a head start in all of the communication and documentation and the mundane part of note taking that needs to be translated into something that's delivered in a customer-facing manner. - Yeah, I would think with this approach, you've learned a lot about what is necessary to make data usable, to be very effective in this kind of. What are some of the lessons you've learned about data and data governance that make the product really effective? - Yeah, I think the more you automate collecting data or you make it no friction for teams to enter data, these are the two things that are gonna help you get better quality data. There's a reason why very often, you know, when you look at tools in the CRM space or customer success space, for example, you will find that, you know, the intelligence that you build on it is not very effective. You don't trust, for example, there's this world of customer success where people don't trust the health scores that are predicted or the risk scores that are predicted from systems because when the underlying data is wrong, you can't get the predictions, right? Our approach to this has been, how do you simplify inputting data into a system? A great example is, you know, the chore that we all hate to do, time tracking, right? End of week, teams need to track their time. You know, they're gonna put in their time based on maybe referencing something from a calendar or like they have some logs, notes somewhere that they're looking at. What we've done is provided them with a beautiful calendar integration where you can say, hey, I wanna pull in, I can see all these meetings on my calendar. I wanna pull those indirectly into my time sheet. So select those meetings. It also automatically categorizes things based on, you know, patterns it's seen before. Hey, this meeting last week was, you know, it's a recurring meeting. So I already know that this was last week, counted as a customer facing meeting. So I wanna say this is a customer meeting. It's by default there. If I wanna override it, I can, but how much ever you can pre-fill for a team member, how much ever you can like automate their work, the quality of data is gonna become better. I would say that's our biggest learning, make it low friction, provide the right nudges for people to, you know, build data if they need to do it manually, you know, not just nudges, but also I would say, wherever you can take the action to where they are. For example, there's a Slack integration from which in Slack you can update the state of support task. Then it's more likely than that the team member will select and update that status right there versus having to come to a different system to do it. Those are the small things that we've learned and optimized for over the last few years. - And that makes a ton of sense. And I think the other area that I really like to get your expertise in is, is you've managed to balance both automation with human oversight. Tell me a little bit about how you've achieved the balance there and why it's important and how you've achieved that and implement. - Right. The way we look at this, intelligence and automation can be more about signals and call to actions for team members, right? A great example is from a project governance standpoint, the way people govern projects in the old world was, let me look at a dashboard for something. Let me, you know, go to this dashboard every Monday. Look at what projects are in the red. Let me ask some questions to my team members about it or have them fill out a different spreadsheet somewhere else, et cetera. When you bring in automation, this can be more proactive. This can be about, hey, we've detected that this project had a slippage of schedule on a critical milestone two times now. So VP of, you know, this delivery team, do you want to reach out to the customer about this? Do you want to ask your team about this? Do you want to intervene, right? So it's gonna push a prompt to a leader so that it's not about a project manager raising their hand and saying, hey, I need help, which often doesn't happen on time. It happens too late for you to recover. But if there's an early warning about a signal, it could be schedule help, it could be scope help, it could be budget help, it could be customer sentiment, which is all things we're detecting from the system itself, right? Here's what we're seeing in the system. Based on that can be, you know, send this early warning signal to a leader and it can be an escalation matrix plus it goes to a manager then it goes to a director, then it goes to a VP depending on what's happening. Then it turns your delivery world around into being more proactive, into leaders engaging faster when they can still save situations with customers. And overall leads to, I would say better rigor and more on time delivery, more, you know, projects that don't have to go into an escalation, right? So that's sort of how we look to balance what is automated versus where, you know, the automation is helping the right folks get engaged at the right point in time in the journey. Likewise, you know, depending on the size of a customer, size of a project, maybe in some cases, it's okay to automate certain like weekly status updates that are going out, where you make it about, okay, here are the updates that we wanna push out and it's gonna, you know, go out every Friday, you set expectations with the customer that this is automated and it goes out on time. At the same time, there may be, you know, larger enterprise projects where you don't want something to just go out automated, you want the team member to take their effort to do it. And in those cases, again, you may still have automation do bulk of the work in putting together the initial version of or the draft of what you have to send out, but then a team member still overrides it, adds their additional context that they have and then pushes it out to the customer, right? So you're able to balance where you do more automation, where you do assistance from technology with human oversight. - Now, I would feel like that there would be areas where you've encountered significant barriers in adopting this style of project management, particularly for those that are career project managers or have been trained in classic project management style. How do you see companies addressing those? - Yeah, I think we've seen in our earlier, you know, years when we started Rocket Lane and launched it, we had some pushback from project managers who were used to working a certain way. And I would say our first lesson was project management is a very personal experience in the way people have their ways of doing it that they wanna stick to. You know, someone is used to operating off mists, they want to do that. Someone is used to keeping things very simple in a Kanban board, they wanna do that. Someone else wants like the perfect Gantt chart with, you know, all kinds of dependencies and, you know, lags built into it and whatnot. And to service this market well, you need to do all of it. You don't have like a escape from that. At the same time, if you're able to showcase, here's how we are improving your world. Here's how we are enabling you to provide better visibility to customers out of the box through a beautiful branded customer portal. Here's how we are helping you automate sending out those weekly updates. So once we give them those power tools, which help them hold customers accountable more easily, help them, you know, reduce the amount of grunt work they have to do, help them focus on like the high impact work that they do. I think that it actually resonates with them. The other part is they actually appreciate the fact that you can systematize how project management happens. You can productize governance in a way because they know that they have colleagues, you know, PMP holding project managers who are, you know, very, I would say, you know, very strong at their, their, you know, field, they want to bring that same rigor in projects that their colleagues are doing who may not come from the same background who are almost part-timing as project managers along with serving as consultants in a project for smaller projects, et cetera. And they appreciate the fact that the rigor that they want can be imposed on everyone or like that compliance is now possible with, with software in place. - So I'm going to ask you to get out your crystal ball a little bit. Tell me where you see professional services automation going in the next two to three years. - Yeah, my sense is we've already entering the next gen of PSA in the sense that what used to be more of like glorified time tracking and, you know, some amount of financial tracking, budget tracking has turned into a full-fledged, you know, all-in-one delivery tool for, you know, services team, which does both the backend operational side of, you know, staffing, managing the effort and budget, understanding the profit and utilization, et cetera, as well as the front end of the collaboration with the customer, the delivery, the experience you're delivering in the customer, like digitizing all of that. Where it's going towards, I feel is, there's going to be more influence of AI for sure, where AI is not just helping you with productivity and automation, but also, you know, providing insights proactively, telling you, hey, this stakeholder from the customer side hasn't joined three meetings in a row. So maybe something is wrong here, take a look at that. Or it's giving you insights on, here's what we've learned across all the, you know, projects that you're running, here's where things are going wrong for you. Or even guiding and coaching a project team member, hey, you know, in your kickoff calls, there are the five things that need to happen. And by the way, you do these three things well, but you're always missing out on these two other items. So being able to, you know, see, you know, what's happening in sales from a coaching, from a intelligence account intelligence standpoint, et cetera, that's going to happen in the post-sale world as well. And I feel that will help service delivery teams level up in new ways, sort of become more productized in how they deliver the service. And I think we talked about productization of services usually in the context of like the offering is productized, the offering is, you know, standardized. But I feel the delivery of it can also be standardized and be made more predictable with more AI and automation coming in. - Well, Sri Ganesan is the co-founder and CEO of Rocket Lane. SaaS started specializing in AI-driven project-based professional services automation with a strong background in customer experience, artificial intelligence and SaaS he previously co-founded, Conatora, a mobile first user engagement platform acquired by Freshworks in 2015. Sri, I've learned a lot today. Thanks for joining me. - Thank you so much for the opportunity to be happy to check. - Are you ready to get your brand in front of the tech leaders shaping the future of managed services? 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