June 7, 2024
861: Business INTELLIGENCE and how data is EVERYWHERE in your business w/ Nathan Westfall
Prepare to have your perspective on data transformed as we bring you an extraordinary story of transition and business intelligence with our guest, Nathan Westfall. Nathan's leap from air traffic control to wine tech wizardry exemplifies how a fervent passion, when intertwined with data, can revolutionize industries. His insights will illuminate how the seemingly mundane details of customer behavior can become the cornerstone of a robust business strategy, empowering local wineries to thrive in a post-pandemic world.
We delve deep into the essence of business intelligence and how it transcends size and sector boundaries, with Nathan's journey as a living proof that it's not just for the big players. He'll share the secret sauce of blending qualitative feedback with hard numbers, allowing entrepreneurs to elevate their offerings and sharpen their market edge. Get ready to change the way you view every transaction, survey response, and inventory count as a vital piece of your business puzzle.
As we wrap up, you'll learn the importance of distinguishing between leading and lagging indicators and how to leverage them for forecasting and growth, especially when historical data might be scant. We'll also explore the fusion of technology and strategy, from the simplest spreadsheet to the most intricate AI systems, and how these tools can tailor solutions to unique industry challenges. Nathan's narrative is a masterclass in adaptability and innovation, offering a wealth of knowledge for those who seek to harness the power of data in any entrepreneurial venture.
ABOUT NATHAN
Nathan Westfall is an entrepreneur in the wine-tech space and founder of an analytics and strategy firm called Vine Valley Analytics & Strategy. He didn't always work in and around the wine industry though; in fact, he started his working career doing a job that's very similar to air traffic control for the United States Air Force for almost ten years, controlling some of the busiest airspace on the planet. Upon leaving the Air Force, he moved to Sonoma County and fell in love with the natural beauty here. He has always been a photographer, so he leveraged that skill into a small business creating marketing and promotional content for local wineries. It was during that time he was first shown the wealth of data each and every winery was sitting on, and as they all started to reemerge from the pandemic, pivoted into the world of data analytics and business intelligence. The rest, as they say, is history!
LINKS & RESOURCES
00:00 - Leveraging Data in Wine Industry
08:53 - Harnessing Data for Business Success
15:02 - Decisions in Data-Driven Business Strategies
20:51 - Leveraging Data for Business Growth
23:49 - Leveraging Technology for Business Growth
35:32 - Thanks to Our Amazing Guests
WEBVTT
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Hey, what is up?
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Welcome to this episode of the Wantrepreneur to Entrepreneur podcast.
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As always, I'm your host, brian Lofermento, and I'll tell you what.
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We always hear certain buzzwords in the world of business and in the world of entrepreneurship, and some of those are data and analytics, and that's why today, we are bringing on a brilliant guest to walk us through that ground and, more importantly, to share some light on us on how we can use data and analytics to actually make a positive impact in our businesses.
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So let me tell you about today's guest.
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His name is Nathan Westfall.
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He's an entrepreneur in the wine tech space that's a cool industry we're going to talk about the wine tech space, for sure and the founder of an analytics and strategy firm called Vine Valley Analytics and Strategy.
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He didn't always work in and around the wine industry, though.
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In fact, he started his working career.
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This is such a cool story doing a job that's very similar to air traffic control for the United States Air Force for almost 10 years controlling some of the busiest airspace on the planet.
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Now, a side note, I'm going to geek out when we talk to Nathan here today, because I've heard that air traffic control is one of the most demanding jobs in the world when it comes to intelligence, and so this is someone who's able to piece together a lot of variables and literal moving parts to make sense of it all.
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Upon leaving the Air Force, he moved to Sonoma County and fell in love with the natural beauty there.
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He's always been a photographer, so he leveraged that skill into a small business creating marketing and promotional content for local wineries.
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It was during that time that he was first shown the wealth of data each and every winery was sitting on, and as they all started to re-emerge from the pandemic, he pivoted into the world of data analytics and business intelligence.
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There's a lot of good stuff that I'm super excited to jump into, so I'm not going to say anything else.
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Let's dive straight into my interview with Nathan Westfall.
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All right, nathan, we've got so much we're going to dive into, but first things first, welcome to the show.
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Hey, thanks, brian.
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Happy to be here.
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Heck, yeah, super excited.
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Honestly, I'm excited on so many different levels.
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Obviously, I tooted your horn quite a bit in the intro here today, but take us beyond the bio.
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Who the heck is Nathan?
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How did you start doing all these very cool things that you're up to?
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You know, it's always just been pursuing passions.
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I was just chasing the thing that I really enjoy doing at the moment and finding the end to it.
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So everything that I've done has always been, you know, just directed at what I'm passionate at.
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Yeah, I love that overview, especially because passion is the name of the game for so many of us in the world of entrepreneurship.
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But I'm going to give you extra credit here, Nathan, because you didn't just you weren't aware of your passions, you actually followed and pursued those passions.
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So give us the origin story going from the Air Force and an air traffic control similar type of position to now you're an entrepreneur Like.
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That's an incredible transition.
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I want to hear more about that.
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Yeah, absolutely.
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It's not what I expected.
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And then when I initially started my career as an air traffic controller in the Air Force but joined when I was quite young and fell into this amazing opportunity to do one of the most interesting and diverse jobs I've ever done in my life, you just kind of follow things from one to the next to the next and before you know it I end up controlling some of the busiest airspace on the planet.
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Pivoting from that.
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You never think you can find anything that's going to be nearly as engaging or fun as something that's constantly changing 100% of the time.
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But moving back to California, trying to take things a little bit slower, and I fell into this world of data analytics and business intelligence and it's been equally interesting and engaging ever since.
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It's just a completely untapped resource in the industry that I'm in and it's been something that's really fun to leverage because you're kind of paving the way, you're making all the inroads, making the paths and meeting people and really causing a disruption in the wine tech space.
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Enough to where people are willing to listen and really excited to listen.
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Yeah, really well said, nathan.
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Your passion does shine through even in the way that you talk about these things, so I'm really excited to get some of your brilliance and strategies here today.
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But I guess we've got to start.
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It's a big term that's thrown around so frequently of business intelligence, so we're going to start by.
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It's a big term that's thrown around so frequently of business intelligence, so we're going to start by going deeper there.
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What the heck is business intelligence, nathan?
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Oh, you know, it's just the program that people use.
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You know Microsoft, Microsoft Power BI, that's it right?
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No, it's a whole different subset of.
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I like to explain it to folks as kind of like it's directed strategy.
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It's taking your business and strategizing based on the data that you're collecting and the data that your business provides, on how you're going to move forward, how you're going to most effectively capitalize on what you're good at and how you can trim off what you're bad at, to be 100% functional all the time.
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Yeah, I love the fact that you call out, because you probably get all of these things from people all the time of oh, is it just that one tool that I use that?
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But what's interesting to me and I love the fact that we're wrapping today's conversation around the wine industry is because a lot of people may think, you know, business intelligence must be large, fortune 500 level enterprises, whereas this really does apply to all of our different industries.
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So I guess I'm going to give you so many of the challenging parts of today's session here, nathan, but one talk to us within your industry how you've seen it apply and how you've seen it really complement the successes of these businesses in the wine industry, but even beyond that, on a irrespective of size level of industry.
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Talk to us about how business intelligence touches all the different businesses out there, especially for listeners who might be thinking well, does this apply to me?
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We're talking wine here today, but extrapolate that.
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Oh, it applies to everybody.
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There is no industry out there that could not do with a little bit of business intelligence and data analytics in their life.
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I mean everything from.
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I've worked at very, very large wineries and worked for very, very large wineries that are internationally distributed, that have their wine all over the world and being able to leverage data and show them.
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Oh, you know, we have a serious off the shelf.
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So let's kind of change our inventory plan and shift our inventory more to the east so we can really supply those folks that are ordering online direct to consumer.
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Or maybe you know our route is really here deep in Sonoma County, where I am, and we want to make sure we have a large amount of inventory here and that we're really investing in the local community to kind of bring up our local, how folks see us, our local perception.
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You know all the way down to I've worked for really small wineries and other small businesses.
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We have a pizza place right across the street from us.
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That is a perfect example.
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They're super small, very local, hyper local place, but seeing you know you can take all of their data.
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We're looking at all of their data combined.
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I'm like okay, your pepperoni slice.
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How often do you offer that on the menu.
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Okay, that's on the menu three times a week and it seems like those three days that the pepperoni slices on the menu, those are when you get the most business and everybody seems to be going for the pepperoni slice.
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Maybe we put the pepperoni slice on the menu for four or five days to really leverage that.
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It's the one everybody loves and we can, you know, come up with a plan to draw more people in, give them a little bit more of a taste and a flavor.
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They come in for pepperoni, but maybe we offer them, you know, a little margarita pizza over here, because they're here.
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We already lured them in with pepperoni.
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So business intelligence is taking that data, all the data that we have, all the data that we're collecting, everything from our sales to our marketing engagement, everything and amalgamating it into one narrow scope strategy that shows us okay, this is where we're succeeding, this is where we may not be succeeding as much, and this is how we can leverage what we're doing to succeed even more.
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Nathan, coming armed with real life examples.
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Listeners absolutely love this.
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I love those tangible examples of managing inventory, of looking at sales data.
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You even mentioned market perception.
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These are data points that we may not always think about, which is why I wanna segue naturally right into this next line of questioning, which is when we say that word data, way too many business owners, way too many entrepreneurs they may think to themselves, well, I don't have data and it may not be organized data.
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It probably is not organized data, but, Nathan, it seems to me, like you see data everywhere.
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What are some of those data points that people may not even realize?
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That one they have and two they can leverage?
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Oh, absolutely.
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I've got actually a fascinating story, which this is what led me into the world of data analytics and business intelligence.
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I was, as you had mentioned previously, I was doing my content creation business.
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I was taking photos, I was doing videos, drone shots, what have you?
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And I was working with the winery and they had their point of sale and you know customer CRM system up and was looking in there with them.
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You know, kind of helping them.
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Okay, you know, these are our customers, this is what we're trying to leverage, this is who we're trying to attract.
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I was you guys realize you're sitting on an ocean of data, right, and, like, what are you talking about?
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This is just.
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You know this.
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This is the customers that we have.
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This is our sales.
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Yeah, every single one of those points is a data point.
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You know this customer.
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They've purchased three times in the last year.
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They purchased in December, they purchased in June, they purchased in February.
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What does that tell you?
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Like, okay, how do we put those things together?
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What happens in February, valentine's Day?
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They probably purchased a bottle for Valentine's Day.
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What was their purchase date?
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The 14th?
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Oh, beautiful, we know, yep, they purchased on Valentine's Day and then, oh, they purchased in June.
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That has to be for the summer.
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What kind of wine are they purchasing?
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Probably rosé.
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It's hot out, people want to drink rosé, so it's tying things together.
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Everything is a data point.
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Everything, if you look at it in the right light, is going to be a data point, and if you're able to tie those things together into a cohesive strategy, then you're just ready to go.
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You are light years ahead of everybody else.
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Yeah, I love that you call it out as you're going to be light years ahead of everybody else, because we see it as consumers, nathan, like none of this stuff is rocket science, because we all shop on Amazon.
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We all know that when we check out from Amazon, it says, hey, you may be interested in these other things.
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That's not magic.
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That is obviously data driven recommendations from an enterprise company yes, like Amazon.
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But what you're alluding to and what you're really talking about here today is data that we can all get our hands on.
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I mean, I'm even just having this conversation with you today.
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I'm thinking where can I export data from?
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Obviously, my payment processor is one looking at seasonal trends, looking at customer by customer trends, volume trends, all of those, as well as my different services and offerings, which ones are selling, taking an intentional look at that.
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So obviously, that's one example from my own businesses that we can leverage data on.
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Where can we find these sources of data?
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So if payment processors is one place for a potential data collection that we don't realize, what are some of those other real life practical data sources that you've seen?
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Payment processors is always where I start people.
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If you can see what you're selling, then you can see how well you're doing.
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You can see what works and what doesn't work.
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That's the easy, that's the low-hanging fruit, because it's always there.
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It's easily exportable.
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You can throw it into a spreadsheet and tease out exactly what you want.
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But when you want to get a little bit more advanced, just beyond the payment processor, I'm a huge fan of just even surveys talking to your customers, talk to people as they walk through the door hey, how are you doing?
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What brought you in?
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Today?
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If you have a patent, you know a pen and you can sit there and write down.
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You know what brought you in.
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How did we attract our folks?
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How did people come in?
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You can be your own data collection machine right there.
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You can just collect things, write them all down and then map your trends.
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If you know, 10 people came in because they had seen an ad that you put out in the local paper.
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Then boom, there's a trend.
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Yes, those ads in the paper are working.
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We can tie those two things together so you can get data.
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You can harvest data from yourself.
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You can harvest data from payment processors.
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From your online.
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You can harvest data from your inventory.
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You know where is my inventory moving.
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Where you can harvest data from your inventory.
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You know where is my inventory moving, where you know.
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Am I putting out more of this or more of that?
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Everywhere is a data source.
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There are no holds barred.
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You can collect data from any different source, as long as you find value in it.
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That's all that matters.
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Yes, nathan Gosh, you rattle those questions off effortlessly, obviously because you live in this space, but you brought up an important point.
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Is that a lot of times, when we tune into these types of conversations about data, we talk so frequently about quantitative data, but you just introduce us to the wonderful world of qualitative data.
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But I would argue that the reason why you can rattle those questions off so succinctly is because you have the end in mind.
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You already know what data is actionable, because you've done this for a living.
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So talk to us about how to make that qualitative data collection actually have a purpose, because, as a consumer, I'll bring it back to that.
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I've been on email lists where companies send out like how likely are you to recommend us to a friend?
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And I'm just like you don't even know why, though, like you don't know the things of your business that I really appreciate.
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So how can we be more intentional and strategic with that qualitative data?
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I think it's taking every single piece of data you get, piece by piece, and being able to not only map it into a trend but also take it at face value.
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You know, take it, see who gave you that piece of data, kind of associate the two and, you know, really move forward and like, okay, this, this is this person's specific perspective.
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And once we can start putting things in little boxes, that's when we can start taking qualitative data and turning it into something a little bit more quantitative.
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We can see, you know, okay, what are the demographics of this person that told me this specific thing?
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This is a, you know, older person coming into my shop that is looking for this specific item.
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Let's talk to some more folks.
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Oh, it seems like there's a trend.
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We see people on the older end of the spectrum that are all kind of shopping for this specific item or this specific subset of items.
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Okay, now we have a trend, now we can start mapping that, now we can start really targeting the questions that we ask these folks as they come in the door.
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So instead of hey, what brought you in today?
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Be like hi, nice to see you, nice to meet you, are you perhaps interested in this particular item boom.
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Right there.
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You've already gauged their interest.
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You know, based on your match trends, that this is kind of what this subset of person is possibly looking for, and it makes them feel like they're very well heard and that they know that you know what they're looking for.
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So it really it ups your game that way.
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Yeah, nathan, I guess we're about to get into the geeky part of today's conversation because, as a former econometrics geek it was in college, I majored in economics and finance I quickly learned the value of understanding causation versus correlation, and I remember that one of my econometrics professors had us do the correlation between the number of sheep in Scotland and the number of ice cream cones sold in New York in a given summer.
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And so, with those things in mind, obviously there is a dangerous side to not understanding how to use the data.
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I'm thinking of confirmation bias and all the other natural human biases that come into it.
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Without geeking out too much but still bringing it to practical terms for our listeners.
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What are some of those dangers?
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Because obviously you're an expert in this, but your everyday entrepreneur or business owner may not understand what to do with it all when they collect it.
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What are some of those things to watch out for?
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No, you really hit on it.
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Correlation does not mean causation and I feel like that is the biggest sinkhole that everybody falls into.
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They see two or three things that correlate and they don't wait long enough to really vet what they're doing and vet what the data it is that they're collecting and how we can be actionable with it.
00:15:18.677 --> 00:15:39.385
So, by not leaving that extra amount of time to collect enough data to really take it from just a correlated thing to a this is an actual, you know, actionable thing that we can execute on, not taking that time can lead to some, you know, snap decisions that really don't benefit you in the long run.
00:15:39.385 --> 00:15:45.687
You know who knows they might, but then how does that work for your data collection and for moving forward after that?
00:15:46.195 --> 00:15:46.937
It's not great.
00:15:46.937 --> 00:15:51.187
I mean, you made a snap decision and, yes, it worked out, but why did it work out?
00:15:51.187 --> 00:15:54.325
You don't know, you can't map it, you can't come back, you can't rely on it.
00:15:54.325 --> 00:16:02.996
So, allowing time for things to play out, realizing that none of this is instant, that you can't get, there's no cure.
00:16:02.996 --> 00:16:22.620
All with data, it doesn't automatically solve anything for you, it takes time, it takes patience and I think really what folks should be focusing on is broad collection of data, patience in collecting their data and then taking the time after to really sift through it and create actionable trends, as opposed to just knee-jerk reactions.
00:16:23.322 --> 00:16:26.017
Yeah, I love the way you give us that overview, nathan.
00:16:26.017 --> 00:16:26.499
It is.
00:16:26.499 --> 00:16:36.219
I think it's an essential part of what we have to talk about within the world of data, and you really brought it to where I knew we'd end up here today, which is that key word that you said a few times there decisions.
00:16:36.219 --> 00:16:49.664
Obviously, all of this data and business intelligence and analytical work is so that we can make better decisions as business owners Cross that bridge for us, because I think it's such a cool part of what your business does is that you don't just do the data side of it.
00:16:49.664 --> 00:16:58.261
You sit down with your clients and say, hey, here's how we can make it actionable, here's how we can make strategic and intentional business decisions.
00:16:58.261 --> 00:17:03.081
What does that look like, especially considering, I would imagine, especially, I mean, in the wine industry?
00:17:03.081 --> 00:17:04.826
Not everyone is a data geek.
00:17:04.826 --> 00:17:07.768
Not everyone understands causation versus correlation.
00:17:07.768 --> 00:17:10.880
What does it look like bringing it to business decisions?
00:17:12.163 --> 00:17:15.335
Honestly, it's quite the opposite for everybody in the wine industry.
00:17:15.335 --> 00:17:18.623
The wine industry is traditionally quite tech averse.
00:17:18.623 --> 00:17:20.988
They're very much rooted in tradition.
00:17:20.988 --> 00:17:26.240
I've been doing the same thing for however many years at this point and it's worked so far.
00:17:26.240 --> 00:17:27.781
Why should we bring on a whole new strategy?
00:17:27.781 --> 00:17:40.602
Why should we bring data into the equation, so trying to shift that perception and get into the room with people where you could walk into the room thinking that you're the smartest person in the room?
00:17:40.602 --> 00:17:53.825
But it's never going to pay off in an industry like wine, because everybody has so much more time in the industry and kind of realizes and maps those trends in their own head that they're not going to trust you right off the bat.
00:17:53.825 --> 00:18:00.961
So it's a trust building exercise sitting in the room, turning it from you know, actual collected data to actionable trends.
00:18:00.961 --> 00:18:07.237
But I think there's that, that concept of you know relating to people meeting them where they are.
00:18:07.237 --> 00:18:08.740
You can sit down in the room.
00:18:08.740 --> 00:18:10.525
Don't try to talk over them.
00:18:10.525 --> 00:18:11.694
Don't try to you know.
00:18:11.694 --> 00:18:16.596
Hit them with a bunch of fancy terms, hit them with a bunch of you know lingo that they don't understand.
00:18:16.596 --> 00:18:22.416
Hit them exactly where they understand things, where they know things are working.
00:18:22.457 --> 00:18:27.117
Take it back to like oh, it looks like back in 1996, we can see that you had a really fantastic year.
00:18:27.117 --> 00:18:29.384
What made that year so fantastic for you?
00:18:29.384 --> 00:18:33.161
Well, you know that was the year we were selling our 94 vintage.
00:18:33.161 --> 00:18:34.703
The 94 vintage was amazing.
00:18:34.703 --> 00:18:42.438
That, you know, had wonderful, you know, beautiful late, wet spring, and you know we made really really good wine from all of our great crops.
00:18:42.438 --> 00:18:46.346
So, yeah, when we released the 94s and 96, things went really well.
00:18:46.346 --> 00:18:48.019
And what was the weather like in 96?
00:18:48.019 --> 00:18:49.362
Oh, you know, it was beautiful.
00:18:49.362 --> 00:18:50.184
That 96 too.
00:18:50.184 --> 00:18:51.695
We had a great, great summer.
00:18:51.695 --> 00:18:53.117
It was warm but not too hot.
00:18:53.117 --> 00:18:55.281
People were coming out in force.
00:18:55.281 --> 00:18:55.982
It was amazing.
00:18:55.982 --> 00:18:56.383
We.
00:18:56.383 --> 00:18:57.625
That was the best year we ever had.
00:18:58.066 --> 00:19:01.778
Like, okay, well, if we look at today, it's 2024.
00:19:01.778 --> 00:19:05.151
Now, how are your 2022 vintages like, oh well, 22 was pretty good.
00:19:05.151 --> 00:19:07.903
You know we had that same trend that we had in, you know, 94.
00:19:07.903 --> 00:19:09.771
So we're going to see some really good wine coming out.
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