Tim and Juan were joined on the Catalog & Cocktails podcast by special guest Kelly Wright, president and COO at Gong and former VP at Tableau, for a discussion on data and analytics past, present, and future.  Below are a few questions excerpted and lightly edited from the show.

Tim Gasper: Honest, no BS, when we talk about having a data-driven enterprise, why does it still sound like a pipe dream?

Kelly Wright:

I think actually some people don't think it's a pipe dream. They actually think that their company's data-driven, but there's a difference between our companies being data-driven by just collecting and storing the data, or do they really have a data-driven culture and a data-driven enterprise. There's been this huge evolution in the whole data ecosystem, and just because there's so much data out there and your company is collecting it, doesn't mean that you're tapping into your data asset as much as you could. 

Tim Gasper: What do you think are the big keys to success for moving from data-collection mode to self-service? 

Kelly:

Self-service takes a couple things. In order to enable people to ask and answer their own questions, they have to have access to the data. And there's some organizations that lock down the data so much. You can't give all data to everyone, especially for those of us that are in public companies or affiliated with companies that are soon to be public.

But some companies take that to too much of an extreme and then lock down so much of their data, and if we're going to empower people to have a data-democratized environment or culture, then they need access to the data. Once they have access, then are we giving them the tools to be able to interact with that data themselves and to be self-sufficient to have a conversation with that data? And that requires companies to think about tools, systems, processes to enable the everyday user who might not be so technical to be able to have that interactive conversation with their data.

Juan Sequeda: Can you give us some examples that you've seen in your experience of how people are actually maximizing their value once they have all this data really well connected?

Kelly:

Yeah. Well, I can give some examples to just what we're doing at Gong. The way we talk about it, like “unlocking reality.” If you think about it, oftentimes, reality is very locked. It's like there's data somewhere, people don't know what to do with it. So what do we mean by this tangibly? I'm a salesperson so I'll give sales examples. There's a whole slew of sales people and sales reps, and they're going and having a whole bunch of conversations. Now, I can look in my CRM and I can see what’s happening in different stages.

I can see what's in the system, like what is the reason that the rep wrote in, or the reason that the deal came out. I can hear what they're saying, what happened with the conversation with the customer, etc. I can maybe even go listen to a customer conversation. But, if I want to see pattern matching of what is actually happening, it's hard for me to understand. If I want to unlock reality, now think about a system where I have all of those calls, all of those emails, all of the Slack, all of the text, all of the Zoom video calls, all the WebEx, and taking all of those customer conversations, pulling it into a system where now it actually tells me everything that's happening in all of my customer conversations.

I want to understand what’s happening for those deals, where they're winning versus those deals that they're losing. I can look at what's happening with the certain competitive track. What's happening with the pricing? Is the rep actually talking about our playbook? So rather than just going with the hunch, it's actually pure data, which you wouldn't be able to do if you didn't wrap AI on top of it.

The other thing that people often aren't thinking about when considering the importance of data-driven culture, one, we've talked about tapping into the asset. We've talked about empowering people to be more self-sufficient and productive in their work so that they cannot only have that interactive conversation with the data, but they can actually tap into the data to serve up the right information at the right time to make them more productive and efficient.

Juan: What are do’s and don'ts that you've seen over your career when it comes to establishing data cultures?

Kelly:

The first is being thoughtful about access and how can you actually empower people to have enough access to data to be able to do their job? I think that's the first piece. The second is, oftentimes, people think that, if people aren't technical, that they aren't interested in interacting with their data. And it's just not true. Everyone's interested in interacting with their data. 

Even if you're not in business, think about even someone that is like a little league coach for their kids, they want to look at the data and all the stats. So I think it is a mental shift to believe that everyone actually is a data user. Everyone is a knowledge worker and everyone should care about data and information. And how are you empowering those people that have questions to do their work? How are you empowering them to get that work done without having to depend and rely on someone that's highly specialized in a different group? That's the second piece.

I think the third piece is, how are we continuing to use our data to help people be more effective and more productive so that they can work faster? I think about onboarding. People are onboarded. They go through two weeks of training. Are they actually benefiting from that training? How are managers helping them to ramp faster? Well, what if you had a system that now every manager could go in and hear what people are saying, see what they're doing, and then you can be faster? It's just making everyone be much more productive.

The fourth piece, which some people don't even think about, is when people are empowered to answer their own questions and to work faster and more effectively, not only are they more productive, they like their job better. They enjoy what they're doing. They're more passionate about being able to get their job done. This empowerment of data, allowing people to get their lives back and to spend more time with their families. That’s very inspiring.

Key Takeaways:

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