96
Redefining Efficiency: Moovila’s RMM for Projects
View this email in your browser
The weekly newsletter of the Business of Tech, giving you new insights into the world of IT service delivery.
Looking for stories from the podcast stories? Check out the pod itself on Apple Podcasts, Spotify, or daily in your inbox. Stories are available to everyone for five days,and Patreon supporters forever.
Was this forwarded to you? Join the list!
Redefining Efficiency: Moovila’s RMM for Projects
It’s not often that I’m confused – at least when it comes to tech news. So when I received a pitch about Autonomous Project Monitoring and Management, I was surprised to admit that I couldn’t quite grasp what it was.
What better way to unpack its meaning than by chatting with the company’s CEO? I welcomed Mike Psenka onto a bonus episode of the Business of Tech to share more about the technology behind Moovila, a leading provider of APMM.
If this mysterious new term also caught your eye, keep reading for a rundown of the tool, Moovila’s approach to AI, and the value proposition for MSPs.
Defining APMM
I began our convo by asking Psenka to explain his definition of APMM and how Moovila came to be.
When developing their tool, Psenka explained, he and his team knew that the world didn’t need another project management platform. But the more they dug into their competition, the more they noticed that ‘contaminated project data’ was a frequent problem – one that automation could solve:
“Most projects and most organizations struggle with projects and have contaminated project data because it’s just not possible for human beings to keep up with the dynamic nature of projects and project portfolios. So APMM is an automation of the data in the project, supervised by humans, but it automates a lot of the minutiae and data that just drives PMs and organizations crazy.”
The goal is to elevate the experience level of project managers, empowering even inexperienced or accidental PMs to enhance their skills.
For MSPs specifically, Psenka says to think of APMM as an RMM for your projects.
Remember the days before RMM when work was full of unpleasant surprises?
“When RMM came out and allowed a much broader span of control for engineers, they could manage and observe networks deployed across the country or across the globe. And it identified problems early, and helped you resolve those problems early. APMM does the same thing. It autonomously monitors your projects and portfolio and identifies risks early, allowing people to have a much larger span of control over those projects,” he said.
I asked how Moovila is different from Microsoft Projects or Excel, and he said that you can load in and build your projects on the platform just as you would with these more popular tools. It’s apparently quite fast and resembles a spreadsheet.
But the difference, Psenka explained, is that Moovila looks at project phases, orders, tasks, and subtasks kind of like a programming language. It even debugs project plans:
“Just like a programming debugger, we allow the PM to go in, identify where those bugs in their plan occur, remediate those bugs, and then they can have confidence that their forecast, their scores, and their schedules are accurate,” he said.
Moovila even generates scores through a Robotic Project Assessment Index, which rates projects on a scale of 1-1000 by structure, timing, delays, resource problems, capacity conflicts, etc.
The last piece, of course, is everyone’s favorite buzzword: the AI agent.
Moovila’s AI Agent
“For massive, complex projects, you can have nearly an infinite number of defects in a project plan based on a combination of issues. But to remediate it, you have to remediate it in a very specific order,” explained Psenka.
Enter Carmen, Moovila’s AI agent trained to guide PMs through project remediation at a high capability level.
We all know that AI is slapped onto nearly everything these days, so I asked Psenka to tell me more about his particular AI model. He explained that compared to the ‘black box’ AIs out there that hide how they come up with answers, Carmen is an interpretable ‘white box’ AI, meaning you can see why it makes the decisions it makes.
“We do have a black box AI component coming where we have a chatbot assistant, where we’re vectorizing data in that process, as many organizations are for their tasks and their data in their process. But the majority of the value when we talk about predictive dates and process, the remediation of the projects and looking and analyzing that data, that’s all white box AI,” he said.
Using this white box model, Moovila’s AI approach helps users debug projects by:
Tracking the data
Forecasting outcomes
Statistical and probabilistic modeling for dates
I asked if Carmen learns over time, or tracks engineer performance. He said that although they’ve rolled that type of feature out in the past, they didn’t want to go too far down the big brother path. But now that they’re working with more MSPs who really care about that type of data, they’re going to start reintroducing it on an engineer-by-engineer basis.
APMM in the Wild
Psenka is newer to the MSP space, so I asked what other industries Moovila is used in. He mentioned that Komatsu, the world’s second-largest heavy equipment manufacturer, uses Moovila for autonomous construction management. They also have clients in retail, manufacturing, and finance.
I found this part particularly interesting: he said that Moovila is most successful in segments that are actually open to digital transformation and major technological shifts. MSPs, according to Psenka, fit the bill.
Within those segments, companies that like Moovila the most usually handle either really big projects or a lot of smaller projects with similar structures. As you might expect, Psenka caveated that small projects with small teams wouldn’t need an APMM.
The Ethical Question
I always like to check in with AI leaders about the ethical applications of their tools and any frameworks they utilize for responsible usage.
I ran this by Psenka, and he made it clear that they have no intentions of helping companies replace employees:
“We’re looking at supporting the human interaction in a supervised way, we’re not looking to replace.”
He pointed out that with their white box AI model, results are interpretable and configurable by operators and owners. It doesn’t make its own decisions, so there’s less of an open response or interpreted response than a lot of the generic black-box AI products have.
“Our thesis and our process is always enabling and supporting the human, kind of giving them an Ironman suit as opposed to replacing the role,” said Psenka.
That’s it for this week’s newsletter! If you want to learn more about Moovila and APMM, head to www.Moovila.com.
As always, my inbox is open to connect.
More from MSP Radio
Missed Things?
How about our latest videos to catch you up?
The Daily Podcast available as videos
Insights into Product Management and Revenue Growth with Jessica Nelson Kohel
Exploring the Role of Transformational Leadership and Small Bets in Tech with Jen Swanson
Friday AI: The World’s First AI-Driven MSP? with TJ Karwal
The Importance of Churn and Retention: Lessons from the SaaS Market with Luke Diaz
Lessons in Communication: An End Customer’s Perspective on Working with an MSP with Tom Cahue
Want the Daily News?
All the stories from the daily Business of Tech Podcast are available in the daily digest, and stories are available to everyone for the first five days, and Patreon supporters forever. Catch the audio of the show anytime on Apple Podcasts, Spotify, YouTube, or wherever you find podcasts. Links at businessof.tech
Copyright © 2024 MSP Radio, All rights reserved.
Want to change how you receive these emails?
You can update your preferences or unsubscribe from this list.