The B2B Revenue Executive Experience
The B2B Revenue Executive Experience

Episode · 1 year ago

How to Craft a Truly Data-Driven Culture w/ Nick Amabile


You’ve recently purchased some fancy technology that promises to capture all of the data you need to make better business decisions. The problem is, only the IT guys know how to use it — and, frankly, they don’t know anything compared to your sales team about revenue. So, now that technology is just money thrown down the drain, right? Well, what if you could get both teams working together in a truly data-driven culture?

 That’s exactly what my latest guest is here to help you do. Nick Amabile , CEO at DAS42, is an expert on the correct way to integrate data into your organization. 

In this episode, we discuss: 

  • The role data should play in your organization 
  • What it means to have a data-driven culture 
  • The technology that helps you get there 

Now that you understand the role data should play in your organization, are you ready to learn why sales enablement 3.0 matters or finally figure out how to bring up challenges at work? Check out the full list of episodes: The B2B Revenue Executive Experience. 

You're listening to the BDB revenue executive experience, a podcast dedicated to helping executives train their sales and marketing teams to optimize growth. Whether you're looking for techniques and strategies or tools and resources, you've come to the right place. Let's accelerate your growth in three, two, one. Welcome everyone to the BB revenue executive experience. I'm your host, Chad Sanderson. Today we're talking about data strategy, modern data governance and what a data driven culture is. Everybody's talking about data today, a lot of people don't know what to do with it. To help us, we have with US Nick Ammabile, CEO of DOS forty two. Nick, thank you so much for taking time and welcome to the show. Age Chad. Great to be here. Thanks for having me on. Really excited. I appreciate you taking the time. My friend, we always like to start with kind of an oddball question, just the audience gets to know you a little better. Yeah, sure, and I'm always curious to know something you're passionate about that those that only know you through work might be surprised to learn. It's good question. I mean, I don't know if the team that I work with would be surprised to hear this, but I'm a big music nerd. So collect vinyl records, I like wow equipment. You know, I used to play the drums, you know, haven't been a long time, but I love music and that's it's a big passion of mine on the side. So favorite genre? Well, so, you know, I actually collect the kind of funk rb soul record is from like the S and s. But I love all kinds of music, jazz, you know, Rock, everything. So I'm just kind of applied glad when it comes to a kind of comes to music. Awesome, awesome, man. All right, so let's talk data. So we've all heard about the importance of data. It's every ever. You can almost open an article about something talking about data, government or it is tragic, data analytics. But I feel like many people don't really connect the dots on how data strategy enables business decisions. So can you help the audience better understand it the role that they should play in an organization? Yeah, well, maybe what I'll do first is kind of just start start by where I see a lot ...

...of our customers and clients at US forty two, where we see them coming to us with different challenges, and so I joke with a lot of folks that the job that we do at US forty two is really about getting people off of spreadsheets. And you know, there's nothing wrong with spreadsheets. But you know, a lot of folks, even in big companies, traditional enterprises, they're so using a lot of manual processes and this is taking up a lot of a lot of time from high value analysis. It's also prone to error and there's just, you know, a pretty big issue of you know, if your spreadsheets says one thing, in my spreadsheets says another thing. You know, we're arguing about who has the right numbers, right and as opposed to talking about insights with data and what should we do about the numbers? Like, you know, okay, what we're orders yesterday, if I asked ten different people in a company that question, I'm going to get ten different answers a lot of times. And so it really the challenge is not from a technological standpoint. There's really great software out there. There's really great analytics of technology out there. If I've seen kind of state of the industry reports and stuff like that, there's literally like a thousand logos on this kind of you know, industry map that you you've kind of seen this right, and so our customers that we work with that best way too. They're coming to us with these challenges, but they don't necessarily know where to start. They know there's great technology out there, but nine times out of ten these are really organizational challenges that we help our customers with rather than technology problems. Certainly, technology is a big enabler and a huge component of any sort of data driven culture, but you know, again, really it's these organizational processes that we help our customers with. And when, when customers are doing it right, which take time. Yeah, what kind of impact should they expect to see in terms of the way that organization operates, with the returns it generates, sort of the Dese yeah that they make? Yeah, really great questions. So, you know, as I kind of alluded to a second ago, those discussions and arguments around whose data is right, whose numbers are correct, those type of things just kind of fall to the side and now, instead of talking about issues with data, data quality, you know, is this the right definition, or orders or customers or whatever it is that you're talking about, those arguments follow the wayside. And now we're talking about what do we actually do about these things? What are the drivers behind these...

...changes in the numbers? What do we do to try to address market opportunities and threats and things like that? But it's also about getting data to individuals across the organization. And you know clearly you have in a lot of companies you have it and other engineering type folks that are very technical. They have the skills and capabilities to access data themselves. But it's the people on the front lines of the business, the marketing team, the sales team, the finance team, those kind of folks often don't have the skills to work with data in a very technical sense. So it's really about enabling those folks who are domain experts. Right the marketing team knows the most about marketing and sales team knows the most about the sales team or sales in a company. So it's really about how do we enable those folks to ask can answer their own questions without being limited by it bandwidth and things like that. And so if a company, you know at the companies probably have more data than they're even aware of. quickly, frankly, Veri all of the systems that they're running. If, if all of a sudden they just said, okay, I really want to make it a focus to create a data driven strategy, where do they start? Yeah, it's good question. I mean, like I kind of said at the top of the show here, a lot of people are already working with data and numbers within their within the organization, and often times what we see is that there's these data silos. So, especially in the days of software of service applications, every business is being run by ten, fifteen different applications. Could be sales for us, could be Google ads, whatever it is. So what we see a lot of times as folks literally logging in these platforms, downloading disparate data sets, combining them and excel those type of things. So really what it's about is centralizing your data, first and foremost in an automated fashion, so that kind of manual prep work and that manual information retrieval goes away and then the data is fresh, right, in other words, you know, we're not looking at data from two weeks ago or three weeks ago or last month. We're looking at data for like yesterday or today or now right, so decisions are able to be made in a much more informed fashion, based on fresh data, automated data, now we're not doing manual retrieval. And then also the other pieces, having a standardized set up definitions, so that when you're talking about revenue and I'm...

...talking about revenue, we know what we're talking about, right. So it should revenue include tax or should it include shipping? Right? How do we deal with refunds? And this is all stuff again that's not really a technological issue. It's basically like you and I having to agree on what we're talking about. And so that's the the the day the governance peace comes in, and that's really what we help our customers do is roll out these data governance programs, define their metrics and definitions for dimensions and other things like that, standardize those definitions in a way that's automated and sort of trusted, and then getting the data to everyone in the company. So, like I lose it to a second ago, getting the data to the frontline folks on the business so that they can ask and answer their own questions. And so when a company has that in place and they have near real time, you know, twenty four hours and right near real time data to make those types types of decisions. It has to impact culture in some regard and so, you know, you mentioned in our prep you know, data driven culture. Help US unpacked that a little bit. Yeah, it's really good question. I mean so, so here's an example that we actually talked to a customer of ours recently, and this is relevant to the sales folks were listening. But a lot of times, you know, Salesperson's calling out a customer. They may be looking for a renewal or cross cell or you know upsell type situation. And you know, we've heard of sales folks calling on customers and then getting blindsided that the customer isn't happy. Maybe they have like ten, fifteen different support tickets that are open right. So you know, if I'm the salesperson, I called the customer, I'm like Hey, you know, are you interested in Xyz, up cell, cross so whatever it is. The customers like no, I'm not. I'm really upset right because I have these support tickets that are open and then of course the salesperson is just surprised and blindsided by that and that's not a great experience for the customers, not a great experience for the sales team. So for example, what we've been able to do with a lot of our customers is create what we call Customer Health Dash Boards. It brings up all the information that's relevant to a customer on one screen. So it's like support tickets, contract renewal dates, usage of a product, if it's like maybe a SASS company that we've worked with, show all their product usage data, when the last time they've logged in, all...

...these types of different things that you know are relevant to the to the salesperson when they're calling on this account, and you know that. Basically then saves that customer or that salesperson from getting blindsided by these different issues that maybe are there, and so they're able to be proactive and we're able to set up like automated alerts, for example, that say, Hey, this person has ten open support tickets, you should call on them and make sure that they're getting their concerns addressed. Or Hey, this contract is coming up for renewal on ten days and they haven't logged in and they're, you know, ninety days or something like that. So having that proactive information really starts to drive that behavior and really just it leads to better business outcomes because, like, for example, what the salesperson has that information at their fingertips, they're going to be able to more effectively, you know, sell or make sure that the customer is successful with the product that they're selling. Absolutely, and so we think about data analytics, there's a lot of agreement on what you know, the data set is, how it's compiled, that to have stuff. A lot of people don't spend time thinking about that stuff, but they endually access to it. They need access to the result. You're talking about, that customer health profile or read out. Does that enable self service analytics? So if I'm somebody who doesn't have the data strategy mindset but I knee of the numbers, I can go someplace and just get the information I need to make the decisions and not bother it. Help, help kind of guess that out little bit. Yeah, that that's that's really the goal right. And I mean, you know, there's there's great technology out there. Were partners with looker, which is a selfserve bi tool, but there's plenty of other bi tools out there that really enable folks to kind of slice and dice their numbers, drill down, generate their own reports, their own dashboards. So it's a true self service model. But with the selfservice model comes like you're kind of talking about it. I needed an understand what I'm looking at. I need to understand what these numbers mean and kind of what, you know, what they're telling me, and so that's kind of around data literacy that we work with our customers on. There are things like data catalogs that sort of pair some of the technical information around data with the business definition and so like. That's really the key thing that we like to do with our customers... set up these kind of programs that, you know, cover data quality, they cover data catalogs, that cover data ligit literacy. We also do a ton of training and enablement with our with our customers. So, in other words, we'll need to sit down with the sales team and walk them through that Customer Health Dashboard and we need to make sure that all these things that that they would expect to see, we need to work with them to understand what that is and also make sure that we're talking about the right labels for things. And, you know, we need to really understand their business process first and foremost before we can go just creating an it solution. A Lot a lot of times we've come into places with failed data analytics projects, it's typically because it's been driven from it and not from the business. So that's the number one that's the number one rules that I will still to say for success for these kind of projects is start with those business use cases first and then work backwards from there. If you're if you're doing it from a technology standpoint, oftentimes it gets up delivering less value to the business than you might think absolute and so there's also an interesting challenge around, not necessarily from an internal standpoint, although I guess you could argue it is, but data privacy for your customers. And then the changing regulatory environment. You know Google's decision to change where they handle cookies and things like that, enabling CDP platforms and things. So how do you when you look out across the horizon, what is it? What's the future of data analytics look like? Is it going to be another industry where there it is just in a constant state of change and there there has to be somebody focused on ensuring an organizations and compliance in terms of how they're collecting, analyzing or applying their data, or is there something on the horizon that will help stabilize it a little bit. Yeah, it's good question. I mean certainly we've always had to consider even before the recent regulations of come into effect, we've always had to consider data access and privacy. I mean we work with very large public companies, for example, and there's obviously lots of non public financial information that folks have access to, and so we always have to consider who should get access to what, what level of access they should have, and so that's something that we always work with our customers around. In terms of some of the more recent impacts,... you mentioned the Google cookie policy changing and things like that, I mean that's that's very difficult. I mean there's obviously no one can predict kind of the regulatory environment going forward and you know, by no means are we sort of lawyers or legal folks. So you know, we mostly take our customers the sort of regulatory posture into consideration, but they have to drive that for us and you know, we're able to implement it on a technical standpoint. But, like I said, we always have to consider it access data privacy. We do a lot of work to you know, anonymized data for our customers so that they're able to have, for example, very detailed level of data, but it's an appropriate level that doesn't necessarily reveal personally identifiable information, for example, and they're able to do the analysis that they want to do but, you know, sort of still maintain an appropriate sort of security and privacy posture. In terms of kind of the future, I think of the industry. I mean, certainly there's a lot of change and there will be, but I think we you know, at the end of the day, the strategy that we employ is kind of technology exhaust agnostic. Really it's about, you know, centralizing your data, standardizing it with a kind of semantic layer, as we call it in the business, and then also getting data to every everyone in the company. So that strategy, I think, is tried and true and we'll continue to work going forward. What we start to see a little bit more mature customers ask us for is you okay, let's say we got our data and a data warehouse and we got a Bi tool that lets the sales team have that customer health view that I talked about, for example, and now customers are asking us, okay, what else can we do with our data? And now it's talking about we start to talk about activating on data, so getting data to your email service providers who can create customized, personalized emails and getting it to push notifications, other types of activation that you can do, even putting things like creating applications with data that allows folks within a company to have a very curated, specific experience to what they're trying to do and inserting data into their everyday workflows. I think, you know, machine learning, AI, that stuff still a little bit further out on the time horizon. I think most of the customers that we're working with and a lot of things that we see in the industry are still...

...just getting the basics down. So I think there's still, you know, three to five years of companies still adopting a lot of these technologies and really creating a mature kind of, you know, data analytics program at the first level, and then from they're starting to build out applications on top of data, activating on the data, and then eventually we'll get to machine learning. Eventually, and I love it when people you know, how there's artificial intelligence in there. Uh Huh, let's have a conversation about what that room. Yeah, I'm a naturally skeptical persons. I'm always a little bit scuptical of that, but you know, you see it on you know, I watch a lot of golf and you know they have a lot of you know, enterprise type AI things out there on advertisements when you're watching golf. But you know, I think the truth is a lot of people are still just had square one and there's a lot of work to still do to get to get folks to the point where they're able to embrace those type of new technologies. And from a consulting perspective, that's really what we help our customers do is understand the art of the possible right and say, okay, what's possible, where is the cost of benefit and impact your business makes sense to actually do some of these initiatives. You know, it's not just AI's one one thing and or machine learning is one thing. It's going to be many things and a lot of folks are still going to have to figure out what is the right sort of mix of software versus you know, services forces internal resources to go capture these initiatives and where do we actually apply data sort to the business to actually get outcomes? So that that's something that I think folks will continue to need help with. All right, love it. So now we've gotten a good sense, I think, of what Josh Forty two does help us understand how you arrived, how you arrived there as the CEO? Yeah, it's good question. I mean, like I've been in the industry for a long time. So I was most recently the head of business intelligence at jatcom before they sold to Walmart, and held senior analytics rolls at that sea. So I've been on the other side of the table, not as just as consultant but as a practitioner. And I mean, believe me, I have learned lessons the hard way and Bang my head against the wall, like a lot of our customers have. But I think we've been able to I've been able to kind of, you know, be a little bit of an early adopter on some of these technologies and methodologies. I've learned a ton over my... and really just wanted to share those lessons with other folks and try to save them a lout of the headache that I experienced. So started the company back in two thousand and sixteen and you have grown it since then. But really my passion has always been you know, in analytics and data and helping customers solve problems with data and technology, and so I feel lucky to be able to do that on a day to day basis now. So, and as you lead the team and, you know, focus on the business, what's your strategic business subjective for DOS forty two? Yeah, so, I mean I think there's a really great opportunity. I mean, you know, like I said before, are a lot of people out there are struggling with these kind of things and, like I said, my passion is to help folks solve those problems and I think there's a great opportunity to go do it. I mean, we're exclusively focused on modern cloud technologies when it comes to data and analytics. So I think that's a little bit of a differentiator for us relative some of the bigger consulting firms out there. So I think we have a great opportunity to continue to grow the business. We just received some private equity investment earlier this year or partners with snowflake, and that ecosystem is growing really, really fast. So, you know, our our goal is just to keep doing what we're doing and, you know, hopefully in the next few years will be able to grow the company to somewhere around two hundred and fifty people and I think Philip gap in the market place because you have the big consulting firms that aren't necessarily focused on the newer technologies. They have sort of a different service model than we do. So I think we're able to be agile and, you know, really expert and the technologies that we support. So we're going to continue to grow the business and just kind of double down on what's working. So we're really excited to go do that. Awesome. So let's Change Direction here a little bit. We ask all of our guests to standard questions towards the end of each interview. The first is simply, as a CEO, that makes you a prospect for a lot of people out there and I'm always curious to know when somebody doesn't have a trusted referral or reference into what works for you in order to capture your attention and earn the right to time on your calendar. Yeah, that's really good question. I mean, you know, cheer point. I do get it up a lot by different services in vendors and things like that. You know, a part of me I was kind of thinking about this and you know, before the interview here, and I think it has to really, you know,...

...solve a problem that I have. I mean, I know that's obviously it sounds sort of intuitive, but like the other day I was thinking of all, man, we really have this issue with, you know, whatever it is, I can't even remember, but I had this problem they were wrestling with internally and then I got I got an email message from some service and I was like actually, this might this is relevant to what the problem I was trying to solve. So I think, you know, the thing like that I've noticed is that a lot of folks are trying to understand where we are as a company and what problems we might have. You know, I think a lot of services providers out there, our vendors, they have kind of a customer journey map and things like that. So catching us at the right time with the right sort of solution really does work well. But timing is everything right. So understanding, hey, we just raise private equity investment, for example. We might be growing, so we need recruiting services like that's that's a good you know, a good bet, right, and certainly we are trying to grow. So we do need recruiting services, for example. So it's just finding the right message at the right time and solving an actual problem and also provide a little bit more differentiation. I mean, obviously there's like a million recruiting services out there, for example, so why is your service different or those type of things. It's got to be some sort of Hook that's going to be like okay, maybe that is something that I'll check out. It's a little vague, but you know. Anyway, no, no, it's a great it's a great point. It's a great point and well stated, I think so. Last question. We call it our acceleration insight. One piece of advice, only one, that you could give to marketing, sales, professional services people, anybody that you believe would help them hit their hit work seed their targets. What would it be? M Why? Well, of course, coming from a data person, it's creating a holistic view of your company and your customer. That's super critical. I think that Customer Health Board that I talked about before, something like that is super critical, and you know that is I think that the simplicity of that concept of the customer health to Health Dashboard is belied by a lot of complexity underneath that. So you know, that's really the key. And getting all your data sources together one place, merging them, creating a holistic view of your customer, holistic few of your company, tying marketing, for example, marketing spend to outcomes and customer success and other things like that. You really can only do that with a, you know, a pretty robust day... solution. So I'm a little biased there, but certain that's that's what that's what I would say. Awesome. I love it. All right, nick, of listeners interested in talking more about these topics. We're reaching out to you to learn more about doss forty too. Where do you wantus to sign them? What's the best place? Dos Forty tocom certainly is a good place to start. My emails also just nick at DOS forty tocom. So feel free to hit me up directly. All right, man, I appreciate it. Thank you so much for taking time today. My pleasure chat. Thanks for Hav me on. Really enjoyed it. Talk to you soon. All right. All right, everybody, you know the drill does it for this episode. Here' US UP AT B Tob read exactcom share with friends, family, Co workers, leave us a review if you like what you're here and until next time, we value selling associates, with you all nothing but the greatest success. You've been listening to the BB revenue executive experience. To ensure that you never miss an episode, subscribe to the show and Itunes or your favorite podcast player. Thank you so much for listening. Until next time.

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