Omri Kohl, CEO of Pyramid Analytics, says the next wave of BI will be driven by generative AI and making data accessible across organizations. The real blocker isn't technology: it's building a data-driven culture where leadership and individual contributors both trust and use data to make decisions.
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There are actually a lot of really great BI solutions out there. Like a lot of the platforms just kind of work. So what's left to innovate in the BI space?
So first of all, I'm not a future teller, so it's hard for me to tell you what's going to be. But I think when you look at the evolution of data and analytics is a big part of that, I think that we're definitely at the maybe beginning of, or the middle of the beginning of the next generation of analytics tools, which refers to AI. So I think a lots of things to innovate in around access to insights and creating insights. That's one side. I think the other side is getting to the data assets. You know, data became the next, whatever golden era of data is today and people refer to it as, you know, the next maybe oil. So draining into the data or harvesting data or collecting data is definitely another area where loads of innovation will have to happen in order for those two big tectonic changes to happen. On the one hand, getting people to build insights from what they collect in their companies and the second part is how do you actually, you know, manufacture that data to be, to make it usable?
Okay, yeah, that's really interesting. And I like the idea that the next sort of evolution is just about making data more accessible so everyone in your company can get, can get those insights. And it's also interesting that it's like a, it's a kind of multi stage process. You need that kind of the data processing up front and then you have the sort of BI layer at the end and then that's how you're going to get the insights. So it's like it's a whole flow. So you also mentioned AI. We're definitely going to spend plenty of time talking about AI and particularly generative AI.
How can you not?
I know it's just invading everything, but yeah. Are there any other trends you think that aren't related to AI that you think are particularly notable?
So I think that one thing that is not even related to technology, when you talk about data driven culture, it's actually internal behavior. How can you transform people that are very much driven by intuition, they're driven by their experience, they're driven by sometimes conversations with their peers and colleagues to ignore that noise and look at the data and drive their business from that lens exclusively. And this is one extreme, obviously. The other extreme is completely ignore data. So how do you augment the two behaviors together? On the one hand, build top down and bottoms up data Culture. So management will only discuss, I don't know, sales performance once they have the data. We're not going to talk about your aspiration, we're not going to talk about your expectations. We actually want to look at the data and then we can discuss what's the additional layer on top of that. So that's top down and bottoms up. How can I in my organization make sure that the next decision I'm going to make, and people make sometimes hundreds of decisions a day in their line of business. How can I make the next decision using data? Is it accessible? Is it accurate? Can I trust it? Is it available for me? What do I need to do to get access to that data? I think that embracing that culture first is without that there's no point in implementing any analytics tool.
Yeah. So process is always like the hard part. And working with people like generally much harder than working with technology. I think a lot of the time.
You know, data literature is probably the most important, difficult first step to even starting to appreciate the importance of becoming a data driven organization.
Absolutely. And so you mentioned the idea that sometimes you have people who are completely driven by intuition, they don't look at the data. The other extreme is like, well, not even going to talk about what we think until we've seen the data. Is there like a happy medium and how might you go about implementing it?
Yeah, I mean, first of all, I think that happy medium is proportional. My happy medium might be very different to your happy medium and to someone else's. I think we need to have a very critical experience. You need to start using data and start making decisions and then look back and say, okay, that decision about that data for that line of business was successful to that degree. How can I improve it? How can I fix it? So I think constant feedback and constant feedback into the data and into my decision making is the first step to building a much more successful analytics implementation. We're talking about BI and we're talking about AI and those are amazing tools. But eventually if you don't use those tools properly and you don't utilize the insights that you will receive from those tools, they're useless. It's just a tool. We eventually will control the outcome and the narrative that we will be creating using those systems.
Okay, I like that. And just thinking about my own experience, when things are going wrong in some area of business, that's when tend to notice my intuition is probably wrong. That's when I tend to start pushing for, well, I need to bring more data into this. So do you have a sense of, like, what the point is, we go, okay, we need more data here.
I'll take it to the macro level when, you know, companies are investing the most in their data assets in times of crisis. So, you know, macroeconomic crisis is maybe the first step for people to say, okay, I need to understand what's going on in my business. Where am I bleeding? Where am I successful? I want to double down on the areas that I do well. I want to shut down, you know, line of business that don't perform. And in, you know, the kind of, when you're cruising along, you couldn't care. This, it's fine, everybody's happy. But in a disastrous moment, in a critical moment in downturns, that's when you actually want to have super visibility to your business. And I think that it's really interesting to hear you say, kind of reflecting about your own experience. But think about it from a global perspective. When you look at companies holding off on technology spend, it's true, they will stop spending on all kinds of tech stuff, but they will increase their spend on data and analytics. Why? Because eventually there is a very clear ROI to implementing and using properly data and data analytics. So I think that those moments are definitely defining moments for our space.
