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Intro: I’m Paul Higgins, an ex-corporate executive turned business owner who, for five years, struggled to grow a cloud Consulting business whilst battling a chronic disease. With the help of mentors and experts, I got the business model right, built a sales and marketing engine, and developed a high-performing team that ended in a successful exit. I received a kidney transplant from a mate, and now on my second life, I dedicate my time to helping other Cloud Consultants go quickly with less effort to enjoy life. Detecting an accent, I'm an Aussie working globally from Melbourne, Australia. I interview successful Cloud Consultants sharing their scaling story to give you inspiration and practical tips. I have dedicated experts for Cloud Consultants on the show to save you time and money by working with the right people. If you want to scale quickly with less effort to enjoy life, you're in the right place. Let's get started.

Speaker 1 (0:55): I’m Paul Higgins and welcome to the cloud consultants show episode number 475. Today's topic is maximizing the potential of in the cloud: insights for cloud consultants. And you're gonna learn three key things. One is what data piece stakeholders are looking for and how they're using it. How you as a cloud consultant can partner with someone like our guest today to provide that data. And thirdly, how AI and machine learning can be leveraged having the right data, i.e. wrong data, you can't really fully leverage those services. If it's your first time welcome, and if you love it, you're here. Please subscribe, it's for you as a cloud consultant, consulting and deploying a SaaS platform. And if you're a regular, thanks for being a regular, but why don't you let me know you're a regular because it's hard to know otherwise. Send me an email at [email protected] and also tell me what topics you'd love me to cover. Summary will be in the show notes and the platform you're listening to and you can get the full transcript at PaulHigginsMentoring.com/podcasts.

Speaker 1 (1:56): Before we go into the interview with Aaron O'Lite to thank our sponsors, the first is the cloud consultants collective. The world's only revenue focused collective for cloud consultants. It's peers answering business questions for other peers. It's faster than Google and YouTube. Why don't you try it out for yourself? Go to the cloudconsultantscollective.com to join free today. And the next is workflow academy. Are your top performers feeling overwhelmed by their workload? Do you worry about their performance and will it suffer? Or even worse, they're going to leave your company? We have an innovative solution that we can help you. We've partnered with a company called Workflow Academy to provide you with highly trained junior talent who can support your top performers and ensure your team stays on track. To learn more about this game-changing solution, just go to PaulHigginsMentoring.com/WFA today. Let us help you support your top talent and achieve your business goal.

Speaker 1 (2:53): So our guest today is Aaron Clymer. And he's the founder and CEO of Data Clymer, a data generation and analytics consulting firm that empowers every client's success by unlocking the value of data. The Data Clymer team implements modern cloud data solutions that drive positive results through data accessibility and actionable insights. Aaron previously established and built a product intelligence team at Salesforce for seven years, which he covers in here and also he supported over 400 product managers. He also then went on to look at pop sugar where his team democratized data and supported their little legal data science across the company. Aaron has grown Data Clymer over the last six years in a nationwide team of deeply experienced cloud data professionals. So now what I'll do is hand you over to Aaron Clymer from dataclymer.com. Great to have you here Aaron.

Speaker 2 (3:52): Hey, Paul, great to be here. Thanks for taking the time to talk.

Speaker 1 (3:55): Yeah, yeah. Really looking forward to this because, you know, we have a lot of people on that help cloud consultants and a lot of them are sort of focusing on their core business. And I'm not saying that this isn't them, but I do think this is a great revenue stream of what you do and people. You know, data is, you know, is like water these days. It's, you know, it's the most important thing within a business. And sometimes it's very hard to organize and very hard to find at the right time. So I think it's, you know, perfect to have you on. But why don't we kick off with who your ideal clients are and what problems you love to solve for?

Speaker 2 (4:28): Yeah, you already kind of explained the problems, actually. So the problem we're solving is that rapid ability to do rapid analytics to answer your business questions in a quick manner to the speed of business, right? So you can always be on top of your strategy, be optimizing anything from cost to revenue, anything in your company, actually. And so being able to do that with data quickly is the goal. We do that by helping clients implement cloud, modern cloud data warehousing systems. Modern cloud data systems. So what that means is fully cloud, of course, but it's a central analytical system where you have a 360 degree view of your company with all the data that comes in from all the various systems you use to run your company. And it ends up being the only place where you actually get the full view of everything that's going on.

Speaker 1 (5:16): Yeah, yeah, great. And I know that you spent a little bit of time at Salesforce. And I mentioned that sort of in the introduction, but tell us a little bit of what you did when you were at Salesforce.

Speaker 2 (5:25): Yeah, that’s right. I joined Salesforce back in 2008 or so. And back then they were the largest cloud company in the world. They're still definitely rivaling the largest cloud company in the world. And I knew that they were sitting on every piece of usage data from the platform, right? And they had every click. They knew what everybody was doing. And my goal was to maximize the value of that data for Salesforce. So, I came in, there really wasn't a data team when I came in there. There was a small data warehousing team, but nothing was very organized and especially the product people, but also marketing sales, customer success, nobody was really using the data. So I built a data team and built up an entire data set of all of that usage data so that everybody in the company could really leverage that and use it for great success. An example would be like the customer success team. We built a customer early warning system that would notify them of customers that needed some help, that weren't using the product well, having some struggles. So let's get ahead of that, let's reduce attrition, let's make sure people are successful with Salesforce. When I left eight years later, I was servicing about 150 product managers with all of their usage data about how they can improve their product, whatever piece of the Salesforce solution and ecosystem they owned. So it was a wonderful place to be. I loved the journey, I loved building a team, I loved building a methodology around data. The idea was to really democratize data across the organization and show people how they could actually use it, right? So we had actionable metrics with actionable data at the end of the day.

Speaker 1 (6:58): Yeah, yeah. And did you get to spend any time I'll call it in the field, like with Salesforce partners themselves?

Speaker 2 (7:05): So actually, no, I did not as much because I was mostly working on internal data sets. And so just very little of that. I mean, definitely, definitely was paying attention to a lot of the partners at the time, but my role was really more internal facing. So I didn't have that opportunity.

Speaker 1 (7:20): Yeah. Great. Well, now you've jumped ship. So you know, you've left the safety of, you know, one of the best companies in the world, Salesforce. And I know you've had a couple of other roles, but now you're running your own business. You know, let's quickly touch on that. Like what's it like to, you know, leave the parachute behind and run your own business?

Speaker 2 (7:39): Yeah, it was definitely anxiety provoking at first, but I'm very glad I made that decision and I love what I'm doing today. I really wanted to become a true expert at the modern data stack and data warehousing and data solutions specifically. After about a decade doing that at Salesforce and other places I realized I'd only seen a handful of data sets essentially, a handful of business challenges with data and I wanted to see 50 or 100 of these and I can only do that as a consultant. So I started a consulting firm with the goal of again helping companies organize their data and be able to action on it quickly in a self-service way. So what that means in practicality is that I hire a lot of data engineers and we're a full stack data engineering group that mostly does solution architecture helps with strategy at first but a lot of the work is implementation, best practices around data modeling and data warehousing if you will that's still a lot of an art. It really depends case by case with clients about what data they're interested in and what are the big use cases they're trying to solve for and focusing on that and making sure that they get the value out of that.

Speaker 1 (8:45): Yeah, and look, before we sort of kicked off, you were talking about some of the verticals that you're in from an incline point of view. You just want to give us a quick snapshot of those?

Speaker 2 (8:54): Yeah, we're in quite a variety. And it's really a struggle for us in terms of coming up with verticals, we really go deep on because, you know, what we do below the covers is quite a transferable industry to industry. You know, we're bringing in data from a lot of different sources. That's a lot of data engineering work that is very similar across the board, modeling data. Again, that's somewhat similar. You know, usually there's a customer 360 kind of model data model, again, regardless of industry. I mean, whether you're in banking or you're in professional sports, same pattern under the covers, right? But we do focus on those two. So that was two of them. We're in professional sports, a lot of national major league sports teams in the US - NFL, MLB, NHL. This is football hockey. Baseball, all sorts of teams like that. We're working with the leagues themselves. We work with some collegial teams with college teams and leagues like that. The big 10 is one of them. It's a big conference of college sports. So we do a lot of that. At the same time, a lot of FinTech, HealthTech and e-commerce as well. So lots of different areas that we specialize in.

Speaker 1 (10:03): Yeah, brilliant. And suppose you as a partner, you might be a Salesforce partner or you might be another partner across another platform. But I suppose the reason that I got Aron on is to talk about maybe an opportunity to grow more revenue and by having data services. And a lot of this you can't do by yourself, right? So yes, some of you will build in-house practice, and I get that. But the majority of you are at a size where you'll need to bring in an expert to help you. And that's why we put Aron on. To sort of talk about that because you know if you think about it you often will own the customer relationship you'll know the client better than anybody and then Aron can come in and support you in that way and just I don't know if you've got any examples Aaron where you worked with a partner to you know to make that happen to bring that to reality.

Speaker 2 (10:50): I could talk about that absolutely and maybe we could focus just on Salesforce as an example. Well Salesforce is the number 1 CRM that we and we are helping our clients with in terms of their data, and also a lot of the times what some of the analytics and what we would call reverse ETL are getting data back from a data warehouse back into a system like Salesforce. So we do a lot of Salesforce two-way integrations between a data warehouse and Salesforce and so that's absolutely a use case that will come up and I almost guarantee any of your clients you know that you're working with if you're working with them on a Salesforce implementation. And the reason is just to be very clear and succinct about that is that Salesforce, like any other tool a company is working with, is almost never going to have the full customer 360 or product 360 or all the data around whatever it is you're interested in at your company in that one tool. It's gonna have a lot of it perhaps. Salesforce will obviously have a lot with your prospects and your customers. But even if you go back to my job when I was at Salesforce, Core Salesforce was using our own instance of Salesforce with our customers, but the product usage data was not in Salesforce, right? I was in a data warehouse and we would surface that back up through Salesforce, but a lot of the data was in, you know, elsewhere. The other thing you can do with a tool like Salesforce is you can embed analytical UIs in there. So your BI tool or whatever you're using as a central analytical tool, you could embed that in Salesforce. So, you know, sales reps can just stay in Salesforce, but under the covers, you have two or three systems, right? And a data warehouse is really the central place that you're surfacing all this data from. So anyway, yes, the nutshell is that any company of any reasonable size, even small companies of 20, 30, 50 people require a data warehouse. And so you're going to end up needing to, they're going to end up needing data and analytics and business intelligence in a central source of truth like that.

Speaker 1 (12:44): Yeah, and then how does it typically work? Is it a Salesforce partner basically bringing you as an equal partner? Like, you know, talk us through you know, typically how it works.

Speaker 2 (12:53): Yeah, thanks for reminding me of that. It's a variety of ways. We work with a lot of partners in a lot of different ways, but usually you have to start out with, you know, it's more just a partnership where we both will just service the client. So, you know, if you're a Salesforce consultancy, you're doing all the Salesforce work, we're working side by side with you. They often will just refer us through the client, you know, refer the client to us. We'll sign our own contract. We work side by side. If that goes well for many, many clients, you know, then there's all sorts of possibilities of either white labeling us with, you know, your service or vice versa. We figured that out. So we've worked in a variety of different manners there.

Speaker 1 (13:35): Yeah. And like if, you know, you Salesforce partner at the moment, listen, Aron, you're thinking like, Aron, what am I looking for? Like, I know it seems nearly too obvious because the problems sometimes are, you know, right in your face. But, you know, what are the signs when a CIO or someone like that is ready to make a decision to move versus, you know, he's got a problem that, you know, the problems, you know, is not in his top three.

Speaker 2 (13:59): It goes back to the problem we were talking about the beginning when the CIO is frustrated because they can't get the data they need to make a decision on a daily or weekly basis. Right. They've got some critical, strategic decision to make about anything, sales strategy, marketing strategy or customer health, whatever it is. And they're just frustrated because they feel like they can't make a data driven decision. And why is that? It's because not all their data is in Salesforce. And so they have a piece of the puzzle there, but they're not able to quickly just get it all together without having somebody on their team spend a week in Excel to actually gather the data and do the analysis, right? So we need, they want to be able to do that in a day or two, or maybe even an hour and not a week or two. It's too long. When it's that long, you end up only answering a few of your top questions. There's a lot of questions you never even answered because you don't have time.

Speaker 1 (14:47): Yeah, yeah. And what's the buying cycle typically? You know, is these short cycles to sell, solve a solution into that problem? They long cycles, you know, give us a bit of a perspective on that.

Speaker 2 (14:57): Yeah, and that's kind of the beauty. If we're going in with a partner who's already on top of like a Salesforce implementation, already understands tet data already understands a lot of the use cases, they can actually help really quickly put together what the needed solution is, especially the business case that we're looking to solve. And so those can go pretty quick, even under a month, sort of sale cycle time, our sales cycle times are usually one to two months anyway. But if we have a partner coming in and helping quickly identifying the problem, we can come in and develop a solution very rapidly and work together to implement the full solution for the client.

Speaker 1 (15:34): And what are some of the biggest objections that you normally see?

Speaker 2 (15:38): The biggest objections might be just not understanding. Maybe what it is is sometimes the cost, because these systems, although they're so much cheaper than they were 10 years ago, I mean like 10 times cheaper kind of thing, and they require so much fewer people to maintain and manage and develop off of. But if the cost is, if you're thinking about the cost is one specific use case, then yeah, it feels like it doesn't make sense. But what we have to educate clients on is that this is not a single use case solution. The system that we're providing is going to be able to be applicable to any business case you have across the board enterprise wide. And so it's a wonderful framework and baseline to start with to then build off all sorts of other projects on top of.

Speaker 1 (16:23): And is there any particular function? If I go back to my old school, you know, 18 years ago with Coca Cola, you're generally aligned by functions more than anything. Is there any particular functions that you're seeing that, you know, have a greater need than others at the moment?

Speaker 2 (16:39): Boy, I think no, I mean, all functions have such a great need, but we end up having a lot of we're seeing a lot of great results in marketing, sales, and then product as well. But marketing and sales is a big piece of a lot of what we do for our clients, whether it's a major league sports team for them. We're often helping them with fan activation in a marketing context. We're building a customer 360 with a D-dooped sort of golden record of a fan, which is the same thing as saying a golden record of your customer, you know, whoever whatever organization you are. So you have a clean view of your customer, you can imagine the effectiveness of your marketing and sales goes way up. So that's, that's a big use case right there.

Speaker 1 (17:19): Yeah, great. And, and if you got any examples, say in a FinTech where you work with a salesforce partner. What was the quick synopsis of what was the problem that we're looking to solve and, you know, what did you do and what was the result?

Speaker 2 (17:31): Yeah, you know, a lot of compliance use cases there actually. So just being able to get all, all their transactional data. So not necessarily, you know, marrying it with salesforce, but the main data sets are often a lot of the transactions and long history of transactions, which are very high volume. That's what data warehouses are great for. They scan billions of rows quickly and give you an answer. So there's a lot of compliance use cases actually where they need to be able to quickly answer auditors, questions, and make sure they're in compliance in all zillion different ways because it's such a managed industry. So that's one of the primary use cases we've seen there.

Speaker 1 (18:06): Yeah, great. And where does machine learning sort of fall across this field? Like, you know, we're all using, well, I'm assuming you were using chat GPT at the moment. I know I certainly am for, you know, everything I write, I sort of get it to improve. But, you know, from a scale perspective, where does machine learning cut across, you know, the data warehouse and the role that you play?

Speaker 2 (18:30): You know, it's actually been true for over a decade, maybe two. And it's still true today is that you, you know, as a company, you can't really take advantage of a lot of that technology. You can't do it for your own services, your own products, your own customers, until you have a clean trusted data set on which to build these models and have AI learn about your business. So it always starts with a data warehouse with a clean data model. And that's still today like the fundamental. That's step one in a data journey. You can't just dive into AI or data science directly. So there's, it's never just the switch and it works. We use it a little bit. I mean, I don't think that AI is going to be going deep into the data warehousing world in terms of what we do in the engineering piece of it. Yes, they can generate code, but it's not generating anywhere near the kind of code that you need to actually do the data warehouse piece of it really well. We use it to help us with some codes and tax and things like that, it's great. But it's not designing a data model for you. It's that we're still a long way off from that kind of thing.

Speaker 1 (19:31): Yeah, yeah, great. And as far as, like you said, the cost has significantly come down. Like, if you fast forward five years, like is it gonna continue to be on a, is it a linear curve or do you think that it'll substantially change in the next five to 10 years?

Speaker 2 (19:48): Yeah, that's a really good question. I mean, I think it's become more linear. It was very much, I mean, if you go back to even my Salesforce days, we had it, it would take 10 people including data engineers and some DBAs, database administrators to manage a data warehouse. Whereas today that same data warehouse probably take two people to manage. So you're coming down in terms of personnel cost by almost 5x, maybe even 10x. The technology costs have come down about the same. It's amazing. It's about 5x, call more cost effective in general for the tech. And the beautiful thing is for that much reduced cost, you have this huge increase in innovation and features and functionality and they've gotten rid of all the headache, that sort of technical headaches we used to have in terms of maintaining a system in the cloud. Everything scales indefinitely. You know, all the technical headaches have kind of gone away and you can really focus on just on your business logic and your business problems. That's what I love about it. So, I talk a lot about how companies can, or anybody in a company can become a data hero. And what I mean by that is that the technology has come so far that you actually don't even need to be very technical at all to be a data hero to a company because the tools sort of solve the technical aspect for you. You know, I can show you a tool. You can know nothing about databases, about SQL, which is the language of databases and data warehouses. I can give you a tool that allow you to look at all your data, explore it adhoc and find unlimited insights, you know, and really drive home the value of data and then spread that across your whole company, because the tooling is so amazing now and again, cost effective, right. It's really easy to democratize all that data.

Speaker 1 (21:28): Yeah. If I remember back to my sort of Cocoal days like, there was the standard reporting then, there was people that really knew how to customize it, right? And we all had data analysts or business, you know, BI's attached to the key stakeholders. So that was great. And is that still the case? Or now is the key person should have the competency or the capability to actually do some of the data mining themselves? How does that sort of sit within corporate today? 

Speaker 2 (21:57): Yeah, it's absolutely the latter now. Anybody in your company should be able to explore data adhoc and just see the raw data too. And when I say raw, I shouldn't say raw data, that's not the right term. Low grain detailed data, because raw data is never good to look at. That's why what we do is so important. We come in and take raw data and make it business friendly and business ready. There's a very big difference. But it's still very detailed data. You know, every transaction, you know, details about every interaction with your prospect or your client, it's not rolled up, it's not aggregated. And the beauty of that is not only is it rich in information, but yeah, you can answer any question that you could possibly answer with data because it's all there. You don't lose information as you aggregate up and roll up data into summaries, because you don't have to do that anymore. We used to have to summarize data to get the system to perform, because the data was too large in its low-grain state. But now, with the power of these modern data warehouses, you can keep the low-grain data and then you keep all the information. You can slice on a zillion different dimensions and look at it all day long.

Speaker 1 (22:59): Yeah, yeah, that’s brilliant. And just on the cost of energy, right? So the cost of energy is sky-rocketting at the moment. We're in 2023. The war with Ukraine and Russia, unfortunately, continues. Is that putting cost impost on warehousing all this data? Like, you're seeing it flow down that far? Like you said, some of the other synergies and other benefits sort of outweighing that?

Speaker 2 (23:24): Yeah, that's a good question. I haven't really seen that much in terms of the overall cost of these systems. But what I have really seen over the past even five years is the total cost of ownership has dramatically plunged. And that's not necessarily the tech cost as much as, again, the overall cost of maintaining and operating and running and building a system like this. And then the fact that the value you get from 100 people looking at data versus the three analysts that you have, the value there is huge. So the total cost of ownership has come to way down and then the value has really gone quite a bit higher. So the ROI is absolutely there.

Speaker 1 (23:59): Yeah, great. And so if you're a salesforce partner, you're listening to Aron and you're thinking, this sounds great, but I'm not quite sure where to start. So for you, Aron, when people, salesforce partners first approach you, how do they typically do that? And how does it normally work?

Speaker 2 (24:14): Yeah, I think it's just a short conversation about, you know, again, what are the business challenges that we're trying to solve for here? And working with us, we have solution architects, you know, we have a lot of folks who will can quickly understand both the technical and the business side, so, you know, can quickly work through what the customer needs. And then it's just a, you know, again, a full solution, integrating everything that you're doing with your platforms and then everything we would do to augment that and putting that together as a bigger plan.

Speaker 1 (24:44): Yeah, and just your scope. So is it, you know, more the way housing or do you also cover some of the reporting aspects or do you use other partners that cover more of the reporting aspects?

Speaker 2 (24:55): Yeah, we're full stack business intelligence and data and analytics, if you will. So we do, we can absolutely work with a cloud business intelligence tool, what we're usually working with at a client. And this is something that they're going to centralize the whole company on. So again, I, the way I would say it is that especially for a larger company. You do want one tool that every single person in the company only has to learn kind of one tool. No matter whether you're in sales or PR or, engineering or product, you know, you're all in the same tool. So it's a lot easier to share data and under and learn from each other on how to explore data. If you're in sales and you're in Salesforce, again, you might embed that, that BI tool in Salesforce., but they're still looking at the same user interface essentially as other people that other people are looking at to answer their sales specific questions. So yeah, we can do all of that and we can work with a partner to help figure out how to both, how to basically integrate whatever data needs to be integrated back into the system, like Salesforce. Cause there's a lot of ways to do it. There's embedding, which I was just, was referring to where you embed a BI tool. But you also might want to pipe data directly into salesforce right through their API. And so we can help do that. And often our partners are defining, again, I'll use Salesforce for an example. Our partners are defining the custom objects, the custom fields, all of that stuff, the whole object model in Salesforce, and again, the business process, and on and on and on. What is the solution in Salesforce? What is all the data that solution needs from the warehouse? And giving us those requirements, right? Here are the 50 different fields we need on these different objects. We want it updated every 15 minutes. And so we'll take that and we'll build the, we'll call it reverse ETL in this case. We'll build the data pipeline that pushes the data from the warehouse back into there with quality checks, making sure it's trusted, all of that. That's a good example of how we work with the partner directly. We're doing the warehousing and the business and the reporting and dashboarding side as well.

Speaker 1 (26:48): Right, and I know we've spoken predominantly about Salesforce, but there are other platforms, SaaS platforms that you support. I know you've mentioned HubSpot, are there others that you're working with at the moment?

Speaker 2 (26:57): Oh, yeah, HubSpot, Marketo. I mean, there's a list of about 50 different platforms we worked in across the board, absolutely. And we often will build these integrations both ways between these products. So there's a long list. Yeah, almost every popular platform we've definitely touched.

Speaker 1 (27:14): Yeah, fantastic. So no matter who you're supporting, as you listen, there will be an opportunity to bring Aron in and just reminding that we're listening to Aron Clymer and its C-L-Y-M-E-R, and it's episode 475 of the Cloud Consultants show. So what we're gonna do now, Aron, is just go into the rapid fire at the end. So are you ready for that?

Speaker 2 (27:35): Yeah. 

Speaker 1 (27:35): Let's do it. So the first thing is what are some daily habits are you do to help scale your business, Data Clymer?

Speaker 2 (27:41): Yeah, good question. My role now, we're almost a 50 person organization and my role has really become the longer term strategy. You know, working on the business instead of in the business. So I'm really focused on long-term strategy, getting customer feedback on our services and our products, doing thought leadership and market research. So I really have to just calendar my day. I make sure I put that on my calendar. I've got five or six priorities this week. I wanna make sure I get a good, whatever that is, 10, 15 hours on my calendar blocked off. I need a good hour or two to focus, which is really hard when you're trying to run a company, you find those chunks of time. So I literally think just calendaring it, is one of the biggest tips that I have for just getting it done and making a daily habit of it.

Speaker 1 (28:29): Yeah, great. And where do you go to find more information about scaling your business?

Speaker 2 (28:33): Yeah, so that's interesting. I've, up until recently, I was just kind of pulling its straws for that. I was just learning as I go. I was getting feedback from some peers that I'd found, or advisors, and even of course, a lot of the the folks I had hired. But more recently, I found a mastermind group that I've really come to look at as a guiding hand in what I'm doing. It's called the Collective 54. It's for professional services companies that are boutique. So that's defined as 10 to 215 employees. So I'm right in that sweet spot. And they help companies grow scale and exit. And we're in the scale phase where we're scaling out. So I'm learning a lot from my peers in that organization. But I think that whatever your company is in, whatever stage you're at, I think finding peers is the best way to go. That's where you're going to get the best information. Because they're all going through this very similar experience.

Speaker 1 (29:27): Yeah, spot on spot on. That's why we have the cloud consultants collective for that very reason. The next one is grant you a wish. What's one wish that we could grant for Data Clymer?

Speaker 2 (29:37): One wish. Well, that's an interesting one. Two ways that answer that. One is just the wish that data could even be easier. Data is still hard despite all of the technology and all the solutions we've talked about. And it's still difficult. Data is difficult. And I think one of the biggest reasons that is, is it's hard in an organization to have true data governance and find ownership. Who really owns data and who owns data quality? And that's why I kind of mentioned that raw data is something you don't want to look at because raw data is really difficult to use, often because it could be low quality. It's hard to interpret. There's mistakes in there. There's issues. So I guess I would wish that more companies would think of data as a first class citizen, as a valuable asset, an asset that needs to be curated and invested in.

Speaker 1 (30:31): Yeah, yeah. Well, certainly from my color background, like even now my team, sometimes I then get frustrated because I'm like, no, this information in our sales CRM has to be accurate, right? Because it's just drained into me. Yeah. You know, crazy things like, you know, just even the way that you call a street name and all like there's so many instances like at an entry level, it seems like it does make a big difference, but when you aggregate the data as you know, it can make a significant difference. So totally agree. The last last question is what do you know now about running Data Clymer that you wish you had known earlier?

Speaker 2 (31:05): Yeah, I think Knowing more about how to build and grow a sales and marketing team. Actually I mean we've done that and I'm really happy we've done that. I wish we had done that even earlier on in our growth because it's something that you want to take a lot of time and effort and you know and curate over the years and learn from as you go, so maybe that would be it but I am I am glad that I'm not in a position I know a lot of my peers are in positions where they have not really built out maybe a leadership team. And so they're doing it all themselves and they're the bottleneck and they're stuck. And that's, that is something that I'm glad I have not been a big bottleneck at our growth.

Speaker 1 (31:44): Yeah, brilliant. Well done, well, like it's been fantastic having you on Aron. If you’re a Salesforce or one of the 50 partners that Aron mentioned, then you see the opportunity where, you know, you might know that you've got certain data in the implementation that you're doing. But it's not the universe. As Aron said and you want to help make it easy for your clients to make those fact-based decisions. Well, reach out to Aron. We'll have all the links in the show notes. Aron, but Aron, thanks a lot for coming on today.

Speaker 2 (32:14): Oh yeah, thank you. It's been a pleasure.

Speaker 1 (32:16): That was a great interview with Aron. It was really just to highlight to you the importance of data which you probably know anyway, but more importantly, put a resource in front of you that you can get help with so that you can solve that end client opportunity. And if you really enjoyed what Aron had to say, please share it. Take a photo of the show notes or take a photo of the podcast and share it with him, telling what you'd like to about the interview. Also, if you've got one or 10 peers, you think we'll get huge value out of this. If you know that they're looking for an opportunity like this, just share it with them. They'll think you're an absolute rock star. Don't forget to check out our solo shows. And if you're scaling your cloud consulting business and want to know a blueprint, right? To find out if you've got all the right elements in place to scale, just go to Paulhigginsmentoring.com/blueprint, I should say to get your free copy today. Please take action to scale quickly with less of it to enjoy life more.

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