Bridging the Organizational Data Gap to Build Better Decision-Making ToolsBridging the Organizational Data Gap to Build Better Decision-Making Tools

Bridging the Organizational Data Gap to Build Better Decision-Making Tools Transcript:

Announcer: You’re listening to The Kula Ring, a podcast made for manufacturing marketers. Here are Carman Pirie and Jeff White. 

Jeff White: Welcome to The Kula Ring, a podcast for manufacturing marketers brought to you by Kula Partners. My name is Jeff White and joining me today is Carman Pirie. Carman, how you doing, sir? 

Carman Pirie: I’m doing well, and you know, Jeff, I’ve been looking forward to today’s show. 

Jeff White: I am too. 

Carman Pirie: Because I just feel like marketers these days feel, and maybe just manufacturing organizations overall, not just in the marketing department, are awash with data. 

Jeff White: Yeah. Lousy with it. 

Carman Pirie: Indeed. And they’re getting more and more of it every day. I’ve likened this I think in the past to the classic I Love Lucy scene where she can’t eat fast enough and the candy, bon-bons or whatever, keep coming. 

Jeff White: Keep coming? Yeah. 

Carman Pirie: So, it’s like they’re collecting more and more data every day and they’re buried under it, and they have a sneaking suspicion that there’s gold in those hills. 

Jeff White: But they’re not entirely sure what to do with it. 

Carman Pirie: Yeah. 

Jeff White: Or they just have so much and we’re not data scientists. 

Carman Pirie: Or just where to start or what have you. So, that’s why I’m excited for today’s show. I think it’s gonna be an interesting kind of exploration of data in the manufacturing enterprise and really how to begin to wrap your arms around the potential. 

Jeff White: Yeah. And I like that you used the I Love Lucy reference, because I’ve also heard of it as the elevator scene from The Shining, and that’s a very different thing. 

Carman Pirie: Yeah. 

Jeff White: Yep. Bon-bons. And we’re also really glad to be welcoming back a previous guest of The Kula Ring. Ryan Knox is the co-founder of Bridge Digital and we’re glad to have you here today, Ryan. Thanks for joining us. 

Ryan Knox: Yeah. Thanks for having me, guys. I appreciate it. 

Carman Pirie: Ryan, why don’t you introduce our listeners to Bridge Digital? I know that it’s a fairly new venture for you, so let’s kind of get that elevator pitch, if you could. 

Ryan Knox: It’s kind of cool to, like you guys said, go full circle, because you guys welcomed me on when I was still at Flexfab, and we were talking about how we were trying to use data, and machine learning, and things like that to improve efficiency at Flexfab, and now I guess we’re a couple years later and I’ve started Bridge Digital. It’s a separate company but it was from all those learnings. And I bet if we went back and we listened to that recording, you could kind of see the foundation of Bridge Digital in our conversation. 

But the whole idea is exactly what you guys were talking about. How can we utilize our data and utilize technologies like artificial intelligence and machine learning to help improve operational efficiency? And so, that’s the idea. 

Carman Pirie: Now, when we speak about operational efficiency, that doesn’t always whet the appetite of marketers, you know? But I guess how is that coming to life on the revenue side of the house? Are we using data to better understand customers? Are we just making better marketing decisions through the visualization of the data that we have? Gleaning insights from it? I guess talk to me about that. 

Ryan Knox: Yeah, so I think a couple different things. Number one, marketers typically aren’t data scientists, but if you’re a good marketer typically you have potentially more experience than some of the other areas of your business at trying to improve efficiency, trying to utilize data. We should be doing things like digital marketing and some of these things effectively to improve the efficiency of our campaigns, for example. And so, in some cases it’s what you were talking about how can we be better marketers internally in just doing our day-to-day job? And that’s absolutely something we focus on at Bridge Digital. 

But it’s also, in part, I think a good marketer, it’s not only the external customer. It’s the internal customer, as well. And I had somebody tell me a few months back that marketers are one of the best people for helping with data science projects because in theory we should be pretty decent at communicating things effectively, especially through data, and so if we can not only help ourselves with our day-to-day job, but if we can also go out into whether it be the HR department… You know, there’s a lot of HR departments right now that are collecting a huge amount of new data. They’re trying to figure out why people are leaving. They’re trying to figure out why people won’t come on board. And marketers should have a good skillset to be able to help them with items like that, so I think it’s the internal marketing and the external marketing are very critical for being an effective marketer. 

Jeff White: I think it’s interesting because you mentioned two core departments that exist in manufacturing organizations there. You’ve got HR, you’ve got marketing, and we’re talking about data, and I noticed that you left one out, and it’s the one that is often most responsible for collecting data, and that’s IT. How come they’re not in there? 

Ryan Knox: Well, IT is facing really difficult challenges right now, so marketers have been pretty good at being one of the sources of the problem of siloed data, and so marketers are probably one of the least checked departments in most manufacturing for where are we capturing all this data, what are we using, what type of technologies are we using. We do a lot more than, for example, HR, or production, or quality. Those people typically are staying within their own systems. So, we’re just kind of by nature kind off by ourselves, and a lot of times IT allows us to kind of… “Hey, that’s just the creative people over there. That’s just the marketing team. Just let’s let them be.” Our ERP system isn’t built for helping them, so let’s just let them do whatever they want type of thing. 

And so, I think IT is being put into a difficult position right now because over the years individual departments, their needs have gotten larger than what the existing systems most IT departments know well, like an ERP system. And so, what happens is ERP system providers are trying to build out more and more complexity into their tools and typically what’s happening is the ERP system tools are getting very kind of shallow in the capabilities of some of these features. 

And then what’s happening is IT is just saying, “Well, we’d love to help, but the tool that we know about doesn’t meet your needs, and so just go do whatever you want.” And so, what’s happening is across the board more and more departments, including marketing, are realizing that the internal systems and software that IT is comfortable with just don’t meet their needs. And so, what’s happening is we’re starting to collect more and more data in more and more systems. I have a customer that they did an internal audit and I think they had like 68 different systems that they either were using, collecting data, or had at one point collected data in. 

And so, think about that as an IT person. They’re typically not data scientists. They’re typically not machine learning engineers. Sometimes, they’re not even software engineers and here they are, and they have a mess on their hands with way too much data, way too many systems, and now we’re asking them to create simple dashboards, so that’s the challenge IT is facing today. 

Carman Pirie: It’s interesting. It was at one point in the enterprise basically if it involved a computer, you needed to deal with IT. Now, of course, everything is technical. Technology is everywhere and IT is, to your point, they’re not data scientists. Why should they be assigned this task? In some ways they’ve been asked to do a lot of things that are kind of outside of that core skillset. 

Jeff White: Yeah. And I mean you’ve mentioned dashboards there. A dashboard shouldn’t just communicate the data. It should provide some insight into it. And generally speaking, you’re not going to get that insight, the BI intelligence, from IT. 

Ryan Knox: And that’s the challenge. We’re seeing the same story with all the companies, including the company I worked for, and all the companies I’m working with. Basically, all of them have the same story. What we just said, where all these systems, all these data have been created. They don’t talk to one another and now all of a sudden leadership team is coming to IT and they’re saying, “Hey, how can we make all these systems talk to one another? How can you give me a one-pager that tells me all about our entire business?”  And what does IT say? “Okay, let me go talk to the vendors I’ve always worked with.” So, who do they go to? They go to their ERP supplier, and they go to Microsoft. 

The ERP supplier, they’re like, “Yeah, we could definitely help you. It would be really expensive.” And then Microsoft goes, “Actually, you know how you migrated over to Office 365 recently? Yeah, I know. Oh, actually you’re already paying for Power BI. It’s this really awesome tool that’s almost free to you guys. It’s like $8 and you guys just totally have access to it.” They’re like, “You’re kidding me! It’s not gonna cost us anything and I’m gonna be able to do everything my CEO asked me to do?” “Yeah, that’s what’s gonna happen.” “Awesome!” 

And so, then everyone comes together and they’re like, “Okay, I got a solution, CEO. It’s not gonna cost us anything and we’re gonna give you everything.” And then what do they do? They come together and they realize all their data is siloed. They don’t have any clue how to get it to Power BI. They start uploading .CSV files. They start trying to create random API connections. They get uncomfortable connecting their ERP system data to it. They try to ask the data guy in the corner of IT, “You know, you could probably do this, right?” And for a little bit he or she thinks, “Yeah, I could probably do this.” 

They create a dashboard and then after a week it breaks. Why? Because they’re not scientists. They don’t know dimensional modeling. They don’t know how to organize these systems in a way where they work together. And so, what we found over and over and over again is that same story where you have these awesome tools available to us, but nobody knows how to use them, and IT is being put in a really, really difficult position. 

Carman Pirie: You know, people should really be mindful of the fact that if something sounds too good to be true, we can get everything we want and it’s gonna cost us nothing, that’s probably…

Jeff White: Five years ago, they said it was Dynamics, five years before that they said they could probably do it with SharePoint. 

Carman Pirie: Exactly right. 

Jeff White: The fact of the matter is they may all be there, but they’re not easy to use and they’re probably not gonna give you what you want. 

Ryan Knox: Power BI really is really cool. I mean, I picked on Power BI just because it’s the popular one and almost everyone has access to it for next to nothing, but it’s just an example of where companies have to start leaning on people, like at my company, there was even a point in time where the marketing team was working on these things instead of IT because the companies are searching for people that are data focused, and they’re like, “Hey, you can probably create a dashboard, right?” 

And so, that was part of the reason why we created Bridge Digital, because we knew there was this huge need. We kept hearing the same story over and over and very few people have the resources to build out three or four full-time employee teams of data scientists, software engineers, and machine learning engineers to be able to build the tools that the leadership team really wants. That’s kind of the background to why we ended up deciding to start Bridge Digital. 

Carman Pirie: Ryan, I don’t know if this is a foolish question or not, so I’m gonna ask it anyway. I’m just kind of wondering like in the ecosystem of a manufacturing world that you interact with, when they’re looking for help in this area, to what extent are they looking for quick wins, insights to power immediate decision making, versus to what extent are they thinking about it through the lens of a long-term system to support their business and to support better decision making? What’s the balance there in the motivations?

Ryan Knox: That’s a really good question. I think it’s an important question because in a perfect world you want to say, “Oh yeah, most leadership teams are really realistic about new things evolving into more data, more AI, more machine learning. It’s going to take time.” And I’m sure there are leadership teams that do feel that way. What we’ve found is that what’s more important is not necessarily the leadership’s willingness to have patience, but what’s been more important from our perspective is the internal team and getting that quick win. Because if you think about it, guys, if you go and you talk to a manufacturing company and you go in and you say, “Hey, we’re going to have some type of major software evolution that’s going to change the way you do your job,” what is the first thing people think about and the experience they have related to that? 

Jeff White: I’m getting laid off. 

Ryan Knox: Well, maybe. But I think most people probably think about ERP. ERP, some type of ERP-

Carman Pirie: Implementation gone wrong, like they got the-

Ryan Knox: Yeah, migration. We use these types of language. And there’s not one single person, and I’ll tell you, my stepmom, she’s retired now but six or nine months ago she was planning her retirement and her boss came to her and said, “Hey, we’re planning a new system implementation, migration,” whatever the right terms were for it, and she said, “If you guys are gonna do that, I want to be a good team player, but we literally just finished this other system where I just learned it. If you guys are gonna do that, I’m just gonna retire early because I just can’t possibly take learning another system.” And that’s how people feel. 

When you come and you say, “Hey, here’s this new software,” it’s this… It has this really negative connotation. It almost never is, “Oh, you’re gonna be able to help me do my job better?” So, regardless of if you’re a marketer, and I think marketers are a little bit more open minded to this with marketing automation tools that are out there, but when you look outside of marketing, that’s the connotation that comes with a software implementation. And so, when you talk about quick wins, I think it’s absolutely essential, and if you go back to… You know, Kotter has his 8 steps for change and whatnot. How can you create a sense of urgency? How can you enlist this volunteer army? Acceleration, short-term wins, how can you do this? The reason for that is because if you can get all the people doing the work using the systems on board, excited, and start showing them results that actually help them do their job better, that’s how you’re gonna win. 

And so, I would just say to answer your question, does the leadership team matter? Yes. It’s very important that your leadership team is aligned that hey, we’re not gonna maybe figure this out on the first go, but we gotta start moving in this direction because this is an essential part of our future and remaining competitive. But at the end of the day, on the implementation, I think it’s absolutely critical to get people on board and help make it as easy of a process as possible. 

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Jeff White: I mean, in that way it’s a lot like a forced CRM implementation with the sales team, you know? If you don’t have internal champions for that, if you don’t have people excited about it, if they’re not seeing the potential benefits, they’re never gonna get on board and you’re just going to have a very expensive piece of software and a lot of people who are still doing things in their head or Excel. 

Ryan Knox: What a great example. I should have thought about that instead of the ERP. Yeah, I mean that’s probably worse, right? For most people trying to adopt Salesforce, it’s probably worse for some teams. I’ve tried to implement Salesforce at two different companies, and I ended up implementing other CRM tools that are a little more simple, but it’s… Man, when you’re going out and you’re asking people to change what you’re doing… Man, you better have a good reason for it and you better have them on board, and how do you get them on board? If you make their life better in some way. 

And so, I think that’s a critical thing that we don’t think about enough, is forget about leadership team. You need their support to get the funding, but once you get past that stuff, how can we make sure this implementation goes right by getting as many early adopters as possible? 

Jeff White: Yeah. It doesn’t help, either… You know, you talked a bit about this a moment ago, but you know, you just want to create a simple dashboard that gives the right kind of data. It doesn’t help that so many of these pieces of software are incredibly complicated to use, are incredibly horrendous user interfaces. I’m talking about you, Salesforce. 

Ryan Knox: Hopefully they’re not a sponsor. 

Jeff White: Mark, if you want to call us, we’re happy to help. We’ll make it better. But you know, it really does kind of make things even more complex for people to adopt something when they don’t necessarily understand how to use it. It’s not intuitive. 

Carman Pirie: Yeah. I’ve rarely encountered a sales organization at a manufacturer that has Salesforce that has universal adoption of it within their sales team and actually has compliance that the sales organization is using it. I mean, it never happens. 

Jeff White: Well, and you’ll hear of sales managers who love it because of the reports they can run and the things they can do with it. 

Carman Pirie: Oh, sure. 

Jeff White: But you never really hear about salespeople just going, “I love Salesforce.” 

Carman Pirie: Exactly right. 

Ryan Knox: Exactly. 

Carman Pirie: Well, let’s not beat them up too much, because that’s not part of the show, but it is fun. I’m just curious. You know, you’ve mentioned this a number of times through the words after data, insight, et cetera, are AI, machine learning, kind of the promise of that, and you know, that is one area that I think manufacturers have, especially on the operations side, have taken advantage of that in terms of machine health, understanding in the factory, et cetera, although that’s not widespread. 

Sometimes it can seem I think to marketers that especially operating in these very kind of B2B manufacturing niche categories that there’s maybe the promise of AI is more hype than real. 

Jeff White: More artificial than intelligence? 

Carman Pirie: Indeed. 

Jeff White: Yeah.

Carman Pirie: But Ryan, set me straight. Do I have that wrong? 

Ryan Knox: Well, I think people put the term AI just on so much stuff. You know, for example, we’ll take something which is like marketing automation technology, and we’ll call it AI, and realistically, how much AI is being built into automating… I don’t know, emails or something like that, is pretty minimal. But there’s actually some pretty cool stuff out there, like for example this year I adopted some natural language processing technology that helps write my marketing content. I use a tool. I don’t get anything from this. This isn’t a plug, I guess. Copy.ai is what I’ve used, and you can use that to write marketing copy, but that’s interesting to me. Areas where you’re actually getting some type of benefit from it, like for example with that Copy.ai stuff, you can actually get much more keyword enriched content. You can drive additional insights that you just aren’t gonna think about and you can automate it with that process. 

I also like the idea of using AI machine learning. The place where I don’t think most marketers are using it is taking their campaign information and using machine learning in a way where we can try to drive insights about, for example, when I’m trying to get this type of conversion, in this region, what is the most efficient use of my advertising dollars? We’re doing that for an HR recruiting firm right now, where their whole thing is their demand is way outpacing the available supply in the market. They’re doing something where they’re… It’s called RPO and in RPO you’re hiring high volume for retail, manufacturing, places like this. 

And so, it’s a very, very competitive field right now, so they have a lot of great data that they’ve captured in their… let’s call it a CRM over the years. They also have a lot of great data in places like, for example, Indeed. Well, most marketers were not taking all of this data. What does Indeed say here? We’re looking at things like costs per click. We’re looking at things like cost per application in this situation and we’re driving entire campaigns based on some of these insights. Conversion rates, click rates, so on and so forth. 

Well, we can go significantly deeper with machine learning where we can drive insights about what’s the most likely result if I use my dollars this way or that way? And so, what we can do is we can become significantly more efficient. When a marketing team… Some of the marketers that are listening are very well connected with the sales team. They might even be managing the CRM tool. If you can go into your CRM tool and understand the sales funnel better, you might be able to go in right now and I would imagine there’s a lot of people listening that they couldn’t do something simple, like try to figure out where the friction points are in their sales funnel, okay? 

So, first you need to be able to do that. What’s taking too long? What needs to be improved? Those types of things, that’s easy. But when you want to get into an actual insight, like, “Hey, if we improve this part of the sales funnel process by X%, it increases our likelihood of conversion by Y%.” And when you get to that level of insight, now as a marketer you can focus in on things that matter. So, let’s say for example maybe we’re finding that maybe when you dig into the data you find that a specific region is responding poorly to the way a specific proposal is being presented, for example. But you can see in other regions it’s being responded to differently. 

Well, maybe that has to do with the way the person is handling it. Maybe that has to do with that region and how… just kind of culture differences. And how can I take that information and maybe… It could be as, “Hey, if we attached a $25 gift card,” I’m just making something up. “If we attached a $25 gift card to this region when people get to this stage of the funnel, it’s going to increase not only the success of that part of the funnel, but it’s also going to increase the conversion rate significantly. So, that kind of stuff… I think marketers have a high level statistical understanding. You know, good marketers have a high level statistical understanding of their spend, of their sales efficiency, things like this, but diving in deeper in a way when you have a lot of data in a way that only machine learning can do, that’s where we’re missing it in sales and marketing. 

Carman Pirie: Thank you for that and proving me wrong on… No, it’s true. I think that was fantastic insight and I think it gets people kind of… gets the cogs turning, you know? Well, I’m curious, because of course as you come into an organization and begin to help them attack these challenges, I’m pretty sure given a bit of the knowledge differential that you would have coming in that there’s some stuff that you can pretty much kind of know that you’re gonna find, like almost before you start looking you know you’re gonna find it. I’m curious, what have been the biggest surprises in your work thus far? What have you encountered where you’re like, “I just didn’t see that coming?” 

Ryan Knox: So, from the highest level, obviously I can’t say any specific names-

Carman Pirie: Understood. 

Ryan Knox: … but from the highest level, you guys remember growing up, you watched these hero movies and you watched what… I don’t know, whatever the government was doing, or what these special ops, or these heroes are doing. You’re like, “Oh my gosh.” Or you look at these businesses and you’re like, “Oh my gosh, they’re amazing. I can’t even fathom how advanced and just amazing they are.” And then you get into the real world, and you start noodling around a little bit and you realize everyone is really behind almost across the board when it comes to just adopting pretty simple technologies. 

You know, I always like to go back to the example of one of my friends started a really cool tech company that he took to Google and Google was an early investor in, and when he sat down and he talked with the folks at Google, they said, “Man, we really need this because we are doing a crap job of utilizing our data.” You know, at Google. Google is doing a crap job, you know? 

Jeff White: Oh, no. 

Ryan Knox: And I have another example in the automotive industry. A large automotive OEM where sat down with them and, “Hey, we’re using 30 people here where really machine learning could basically automate all of that.” And so, I have examples of sitting down with large companies and they don’t have any visibility right now into their supply chain. That’s probably been… If you want a very specific example, unfortunately it’s outside of sales and marketing, I would say that’s… You know, because realistically, marketers for the most part are pretty data driven, at least you should be if you’re not. It’s almost impossible to be a digital marketer and not be data driven. And so, my biggest surprise has not been in the marketing area. It’s been in everywhere else operationally, just the lack of visibility and understanding of what’s going on, when our materials are gonna arrive, how much it costs to make things, insights into that stuff. It’s lacking almost across the board at every company I meet with. 

Carman Pirie: There’s something a bit liberating for the listeners to at least… Well, when you say everybody thinks they’re behind, or everybody’s behind, well, everybody can’t be behind. Or maybe just the definition of what is ahead maybe needs to be a bit recalibrated and folks maybe ought to feel not as intimidated about getting started, because frankly nobody has it cracked. Yeah. 

Ryan Knox: Well, what I’ve learned is that if you can simplify things, people hide in complexity, and so if you can simplify things down at your company and once again, I know we’re focused on marketing here in this podcast, but I’m just going off my own experience. I like to go outside of marketing when I was in that role and I like to try to help other areas, because at the end of the day marketing is trying to grow and improve the business, and so you should be trying to help your internal customers just as much as your external in my opinion. 

But when you go and you sit down with people and you want to try to understand what’s going on and how you can help, try to bring things back. If I could make any recommendation of what’s helped me, try to bring things back to the lowest common denominator and just something as simple as, “Hey, do we know how much that actually costs to make that thing right there? Could we tell? Could you tell me how much that costs?” You know, that’s a good place to start. Or “Hey, those materials, do we have visibility into… We’re relying on those materials being here. Do we know how much material we have available and when it’s going to arrive? What are we counting on?” 

Think about your business. What are you counting on? And try to kind of work from the lowest common denominator up. And what you’ll probably find is if the person allows you to have a good conversation and not get too deep into the weeds, because the weeds is where they’ll lose you, you’ll end up learning and finding opportunities to improve the business. 

Jeff White: I think that’s really cool. 

Carman Pirie: Yeah. It’s a fantastic way to cap off this episode, I think. Ryan, thank you so much for joining us today. It’s been great to have you on the show again. 

Jeff White: Yeah. And all the best with Bridge Digital, too.  Hope it goes really well. 

Ryan Knox: Thank you, guys. Yeah. It was great talking to you. 

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