Dana Bullister isn’t the giddy type. Dressed in head-to-toe gray, she tosses down her black backpack and takes a seat, leaning forward with her elbows on her knees and an intent look on her face. She’s at ChannelCon, CompTIA’s annual conference, and she doesn’t want to miss a thing.

Dana might be a no-nonsense woman, but when she talks about data and the channel, a small smile slips through and her eyes light up. She runs the Strategic Data Initiatives program at LogicNow, and she developed a feature of the company’s MAX RM remote management platform called LOGICcards. LOGICcards use advanced analytics to add an additional layer of intelligence over and above what users get from a typical dashboard.

Luckily for us, Dana’s very good at sensing when she needs to spell things out like she’s talking to a fifth grader.

“The stuff you usually get from a dashboard can be called descriptive analytics: it describes what’s going on right now. Moving forward, predictive analytics describes what’s going to happen,” she explains patiently. “The next frontier is prescriptive analytics, which not a lot of platforms have. It isn’t just descriptive or predictive; it’s actually telling you what to do. It’s saying, ‘I prescribe this solution to this descriptive or predictive intelligence that I’ve gathered.’”

If it sounds a little like artificial intelligence, it’s because that’s what it is. Basically, the technology uses machine learning to mine all the data MSPs collect and then tell them how to solve business problems. Instead of just throwing data at partners, it makes specific recommendations. For example, it can tell providers when a lack of disk space on specific machines is creating a potential issue, give an estimate on when that issue will surface and tell them what to do to remedy the problem.

That’s pretty cool, but even cooler is that the cards don’t just use that one customer’s data. They aggregate data from every MSP that uses the cards so it can not only prescribe more accurate solutions, it can tell customers where they rank among LogicNow’s more than 10,000 MAXfocus customers worldwide for things like time-to-patch, service and help desk tickets and the quality of devices they have under management. It then alerts the user with customized push notifications.

Similar to other push notifications, the customer has different options: click to expand for more details, snooze or just dismiss them completely. The LOGICcards take all of this information and the underlying algorithm actually learns from the way the MSP interacts. It begins to figure out which types of notifications are more important to each customer. Over time, the user’s feed becomes more and more customized toward the types of things that are of most use.

This is one of the big first steps LogicNow is taking toward integrating machine learning into as many of the products as possible. Dana says the ultimate vision is to create an actual “intelligent dashboard” for channel partners.

“There’s so much that, right now, is left on the table just because people aren’t fully taking advantage of the massive data sets that they have in front of them,” she says. “There’s so much potential there in terms of figuring out which things cross sell more, which customers are most profitable, which actions I should take to optimize the way that I grow or the way that I execute processes in my business.”

So why aren’t SMBs in the channel taking more advantage of data? Dana says it isn’t because of a lack of desire. They know the data is there, and they want to leverage it. It just comes down to a lack of awareness and resources. The channel lags behind certain other sectors in terms of analytics simply because of a lack of historical knowledge.

“Some of the earliest adopters of data analytics were in the financial industry. Why? Because all they do every day is quantify how much value they’re bringing to themselves. That’s all they do! So it was plain as day to them how much value that running these types of analytics would have,” she exclaims. “Secondly, they simply had the financial resources to commit to it.”

Part of the reason Dana loves her job is because she works for a company that’s large enough to have the resources to hire a data science team. The other, bigger reason is that she legitimately loves the channel. When she talks about where she envisions this space in the next five years, she can’t help it. She gets a little giddy.

“It’ll be really, really exciting. I can’t wait. I think that automation will play a huge role, and the type of automation that happens will be much more advanced. The people at MSPs will be the sorts of people that almost never work on the same problem twice.”

As for the data science skills gap everyone is panicking about, she doesn’t seem too worried. She compares it to the advent of computer science and the internet a few decades ago, which caused a similar amount of hand wringing.

“You don’t have to be a programmer to appreciate, at a very high level, what’s happening when you click on an email,” she says. “I feel as though a similar thing will happen with data science.” Not every person is going to be an amazingly skilled data scientist, but Dana thinks people will have a general, broad understanding of what’s going on in the background, to the extent that they can actually benefit from it.

When she’s asked about what she loves about the channel, she breaks into a grin.

“I think we have the coolest customers in the world. People just don’t appreciate this fact. They’re foundational to how the world works right now,” she says with complete sincerity. “We survive off technology. If people truly understood what an IT person was capable of doing right now—the cool, cool information they can see and ways they can make people’s lives easier—I think everyone would be in complete and total awe.”

As much as she might want to stay and talk about how great the channel is, she’s heard there’s a Rise of the Robots presentation about to start, and there’s no way she’s missing that.