"Utilizing Data-Driven Decisions for Raising Capital in the Cannabis Industry" Lara Fordis, founder of Fortis Consulting, joins Dan Humiston to discuss how cannabis companies can utilize data-driven decisions to raise capital successfully. She emphasizes the importance of vetting data sources and avoiding skewed data to avoid misrepresentation. For investors, Laura recommends seeking a second set of eyes to validate data presented in pitch decks to ensure reliability and credibility. Produced by PodConx
"Utilizing Data-Driven Decisions for Raising Capital in the Cannabis Industry"
Lara Fordis, founder of Fortis Consulting, joins Dan Humiston to discuss how cannabis companies can utilize data-driven decisions to raise capital successfully. She emphasizes the importance of vetting data sources and avoiding skewed data to avoid misrepresentation. For investors, Laura recommends seeking a second set of eyes to validate data presented in pitch decks to ensure reliability and credibility.
MJBulls - https://podconx.com/podcasts/raising-cannabis-capital
Dan Humiston - https://podconx.com/guests/dan-humiston
Lara Fordis - https://www.linkedin.com/in/larafordis/
Fordis Consulting - https://fordisconsulting.com/
Recorded on Squadcast - https://squadcast.fm/
[00:00:00]
today on the MJ Bulls Raising Cannabis Capital Podcast, we are joined by Laura Fortis, the founder of Fortis Consulting. Laura, welcome to the show.
Thank you.
Well, I really appreciate you doing this , with me today because with so many companies in the cannabis industry, Needing to raise capital and with such little capital available, cannabis companies need to use every possible tool in their toolbox to attract capital.
And as a market research expert, I thought you'd be the perfect person to talk about. How cannabis companies can use cannabis like onsite data-driven de data to make these decisions to help them raise capital and how that can enhance their chances of raising capital. I also thought that investors may need to know some of this, some of this information too for some of our investor listeners who are listening, what data they should be looking at or how data can help.
Them make the decisions as to [00:01:00] what businesses to invest in. So I thought maybe to get started, we would just talk in general about how you access this data and provide companies with this data to help them better make decisions.
Well, sure. There, there are different types of, of data and they kind of fall into a couple buckets. One is called. Quantitative data. So you see charts and tables and online surveys in numbers which for investors and for pitch decks tends to be what you predominantly see. And then there's also qualitative data, which comes from focus groups and in-depth interviews.
There's also secondary data, which is what you see in point of sale data, retail data, and primary data, which is when someone does a, a survey or a focus group. So there's lots of different kinds of data. What in the cannabis industry is, I, I sense is disproportionately used as is point of sale data, p o s data, retail data.
And that's a [00:02:00] major source on which people rely and, and in, in of itself sounds really good. I would caution people to really look closely at their data and, and scrutinize it because what's even worse than going on hunches and gut feelings is going in with data that. You think gives you a sense of things, but is is open to misinterpretation or is out of context.
So, what, what I encourage people to do is, is to round out their data, just like you wouldn't have a stock portfolio. With all your investments in one thing, it's good not to put all your market research in one basket and to have a more well-rounded approach to market research so you're not overly reliant on one source, especially if if you haven't vetted that source as being the right.
Perspective for you. I'm trying, trying to be very diplomatic, [00:03:00] but I am known for having some issues with retail data because it. Underrepresents how many people actually consume cannabis. And it over represents , how much those people who are represented are consuming cannabis. So it does a disservice on both sides of things.
We talked about this before we came on, if. Yeah, you were only relying on the grocery store data to say that my only customer is a female because , most men are not grocery shoppers. Then you'd be like, man, these women are eating a lot of food and no men are eating anything.
You wouldn't do that.
Yeah, no, you wouldn't. I mean, you wouldn't presume that there are a bunch of, moms in the suburbs eating copious amounts of Captain Crunch. It's probably not happening. But in other consumer packaged goods industries, there's an awareness that in certain categories the. [00:04:00] Consumer, the end consumer, whether it's a child or a family member or whatever, is not necessarily the shopper.
And cannabis is complicated because legally you're not. You're, it's supposed to be a one-to-one correlation that what the purchaser is the consumer. But we're all adults here. We know that just because something's the law doesn't mean that that's what's actually happening.
And in the case of cannabis legal, retail, dispensaries, I'm seeing a, a lot of volume that's attributable to people shopping for other people. And that's coming in on the retail data side as. Under the demographics of someone who's not really the end consumer. I mean, there are obviously, like if it's a product for, menstrual cramps and it's bought by a, so a man or a man someone who identifies as a man, you know there's tip offs.
It's pretty obvious [00:05:00] areas in which, you can tell that the person purchasing is not the end consumer, but for the most part, it just washes away under the radar. You have no way of. Of proving or disproving except for that I can look at how, at at custom data on who's, what are people purchasing, who are they purchasing for, what percentage of their monthly spend is for themselves versus others,
Yeah.
that kind of thing.
And it becomes very clear that a lot of purchasing is for other
So, so that's a really good point that I think everyone , should really pay attention to, especially within your pitch deck, is that the data that you have in that pitch deck , has been vetted and is sound, because the last thing you wanna do is make it all the way to a, to an interview with an investor and have them ask you a question That you get tripped up on, and that would be one place where you could be vulnerable.
Let's talk about that pitch deck and some of the data that you put on. You talked about charts and you talked [00:06:00] about some other things that you could utilize data to support your position or to, support the value of your company. Is that, is that what you've seen in the past?
Some companies have done.
Yeah, I mean for the most part when it comes to a pitch deck, you're gonna be looking at mostly quantitative research. A and I think disproportionately you're gonna be looking at what's secondary research, research that exists out in the universe, and you buy it or acquire it somehow and incorporate it into a pitch deck.
Sometimes people will commission something if it's a new product. So I do work. For venture capital firms where they're considering launching a new product. And in that case, I mean, I'm making up a product, wasabi flavored cannabis infused lip balm, doesn't exist. But if someone decided that, that it was an unmet need that they perceived, and don't even get me started on unmet needs.
'cause I don't believe personally that I. The key is to fill an unmet [00:07:00] needs because you can have an unmet need. If it's not an unmet want that people are willing to pay money for, it doesn't really matter that it's an unmet need, from a, from a bottom line point of view. So I've seen that happen as well, that people think they're filling a need.
And no one's willing to pay to have that need filled 'cause they don't really want it. And you see that happen categories all the time. . It's very hard to say what people will pay money for.
You can ask them, but that tends to be in inaccurate. People will In some degrees inflate what they'll pay for other degrees, deflate what they say, they'll pay for something. So I'm not a big proponent of that being a a, a good guide for knowing what, what the market will bear per se. But like.
You can't, if you're gonna launch something new in a, in a category that doesn't exist, which for a lot of cannabis businesses in innovation, it doesn't exist. So [00:08:00] what are you gonna do? You need to do some custom research. But instead, sometimes people go on hunches of gut feelings, or they'll do a survey with their Facebook or Instagram group, which is called a self-selected sample, which again, produces data.
But it's skewed data, so it's even more dangerous because you think you have data and you're, you're playing with fire in that case because you've got data that's going to Give you a, a false sense of success usually because when you ask people who are first, second, third degrees of separation, it usually ends up being a little bit more self-serving and reinforcing than if you extrapolated it to a larger objective population.
makes a lot of sense, Emma. That's a lot of sense. Well, before I let you go, , I'll give you two scenarios that you can maybe just touch on briefly. , if a company , was in the early stages of raising capital and wanted to validate [00:09:00] their data and , needed somebody to help them with.
That may maybe explain that process, but then I'm gonna give you one other one, which would probably be pre pretty similar if an investor was about ready to invest into an organization but wanted to just. Have a second set of eyes looking at the data, how would you help those two companies?
Mm-hmm. Well from the latter perspective, I do do work for Investors that get a great pitch decks sometimes the, the people are charming. They're very convincing, but they wanna see the bottom line. No, I'm not. I'm not trained as a, as an accountant in terms of being able to assess that.
I, I look at more market research data. But you do wanna make sure that what. That basically the, the deck that, or what you've been presented with isn't self-serving and a very common way in which data's manipulated is [00:10:00] suggesting a causal relationship between data when it's really correlated.
So for instance 98% of men in prison are bread users. Well, that doesn't. I mean that the bread using caused them to be in prison. It just happens to be that about 98% of men eat bread and. So that's reflective of that population. And obviously that's, that's absurd when you hear about it. But when you start seeing it in pitch decks, you see data points that suggest one thing leads to another, when in reality they're just correlated, but they're not causal.
So investors and people seeking investments may get really stars in their eyes. Like, can you believe such and such percent of this, look at this market potential, but potential is that it's potential. So, it could be zero to a [00:11:00] hundred, like as much as 80% of people might buy this product.
Well, that's. Zero to 80%. If you talk to, to a sort of, data nerd or, or cynical person, or a cynical data nerd, you're, you're gonna quickly see that that information is subject to interpretation. So, I guess what I would recommend for investors and people seeking to really button up what they present is to make sure that they have an outsider.
Take a look at it, spend, spend the time and say like, does this seem sound, are there any issues or red flags that you think I need to return to? Because there's nothing worse than having a potential investor say this data is not reliable. Hence, even though it's 1% of your pitch deck, it casts doubt on the rest of what you have to present, because that's how quantitative data cuts.
If there's one [00:12:00] mistake, then how do you know that the rest of it isn't a mistake? And it, it really undermines your confidence. And that's the last thing
No, that's a, that's some really good advice and I, I think people that are listening right now, . Could benefit from working with you and I'll have all of Laura's. Information, the show notes , linked to her website. And I'm sure if anybody has any follow up questions, she's the right person to speak to about this because like you said, if there's one thing in the pitch deck that they, they get thousands of pitch decks and they just need to move on.
So they're not gonna spend a lot of time if there's any questions. But, well, Laura, I wish we had more time. 'cause this is really good stuff and I know people are gonna benefit from listening to it and, following up with you in the future. I, I really appreciate you being on the show for today.
Thanks for doing this.
you. Thanks for having me. I appreciate it and I love talking to people about data so anyone can reach out to me anytime and have nerdy conversation and hopefully learn something they didn't know [00:13:00] about Market research.