Using Data for Sales Teams Success

Welcome to the Oil and Gas Sales and Marketing podcast, where every week your hosts, Mark LaCour and Matt Bertram share proven strategies and real-world tactics to help you connect with customers and close more deals. Let's do this. All right, welcome back, everybody.

Matt and I, this is what three guests in a row that we've done episodes with. Yeah, yeah. The guests are very, very popular. Welcome to the Oil and Gas Sales and Marketing podcast, Sarah. Thank you for having me.

Delighted to be here, Mark. Yeah, Sarah and I have a funny story. 2019, she was actually doing Oil and Gas Sales of it in Aberdeen and we were going to attend. And all of a sudden, we started hearing these rumors about this virus thing.

And this was at the very beginning of 2020. And we had to make the hard decision to not attend, even though I had bought plane tickets. And I was really disappointed because it's like, this is just like the flu. People are making too big a deal out of this COVID thing.

And I was obviously wrong. That's how Sarah and I first met was right before the COVID pandemic happened. That's right. And we had you on the big screen, Mark, because we were allowed to go ahead with the event.

It was on the 5th of March, 2020. And because you couldn't join us in person, I remember blowing your face up on the big screen in the end and having you talk to the audience. So thanks for doing that. Yeah, yeah, crazy times.

I never want to go back there. Next time, we're going to do it in person, like we're supposed to. So Sarah, real quick, introduce yourself, your real quick, your background, the name of your company,

and let's talk sales and data today. Sure. Okay. Thank you for having me again. So my name's Sarah Downs. I am the Co-Founding Director and CRO of Dukare.

We are a sales enablement consultancy based in Aberdeen, Scotland, mostly serving the energy and tech sectors. My background, I'm a bit weird. So I own a sales consultancy today, but I started life as a nurse,

a trauma nurse to be specific. And when I left the nursing world and came into the big bad business world, I had no idea where I was going to fit in. And if you had told me back then, I was ever going to be involved with sales,

I would have been in the A&E department myself. So yeah, it's been quite a journey and I'm sure we'll cover lots of it during the podcast mark, but yeah, in sales, but certainly wasn't where I thought I was going to be. Well, Sarah, you may not remember this,

but my degree is actually in wildlife management. So I'm having an equally weird story in that I started off managing wildlife and now I run a podcast network in the oil and gas industry to figure that one out. Sales, data.

The old way of doing stuff doesn't work, even though there's still some people out there that think it does. This industry for the longest time, sales was built on relationships. That is not always the best thing for the buyers,

is having everything built on relationships. And now it's about solving problems, in my opinion, what sales is actually about. But in order to do that, you have to understand what's going on. In order to understand what's going on,

you have to have data. Absolutely. Absolutely. Yeah, so you want to talk a little bit about your experience in helping, using data and helping companies

with their sales efforts. Sure, I'm a nurse and my business partner is a petroleum engineer, okay? So we like data and we like to understand why we're doing things. We look at sales a little bit differently

from people that I guess have grown up in sales and have done sales for decades and have gone from junior sales right up to sales leadership and beyond. And I guess that's what makes us niche in the marketplace. But I think let's talk about, I guess, data first.

When I use some medical analogies here, so bear with me. But when I first came into business, I felt that everyone was checking in on what the symptoms were and they were jumping into surgery.

That's how it felt. And in sales, it was the same. Sales person would go into a buyer, have a conversation, and we'll get to relationships in a while. But they would act on symptoms alone

and then they would create this great plan to sell product service or the Met Value Proposition. As a nurse, I think about it when someone used to come into the trauma unit. So if you come into the trauma unit and it looks like your leg's broken in three places,

even the world's best orthopedic surgeon is not going to diagnose you yet. They're gonna go back, they're gonna do the MRI, the x-ray, anything that they need to do to be absolutely clear on what's going on.

So I think in business and in sales, we need to go back and do the MRI more often. And that's something that Dukaru does a lot of. But then even once you have a diagnosis and you understand what the problem is or as we call it in the industry a lot of the time,

the root cause, like what's really going on in an organization, you can start having a think about what the strategy or in nursing the treatment plan might be. Yeah, you might need surgery, you might need to go on certain medication.

But for anyone that's ever been in hospital before, what you'll remember is they actually do a lot of other tests first to check your general health. So they do the blood work, they take your temperature, they take your blood pressure and they're checking that you're actually

going to be ready for that treatment plan. That's not happening enough in business either. We diagnose if we've got really great salespeople that can go back and do the MRI. We set the treatment plan and we jump in. We don't actually check the impact,

the implication of what selling that product or service is gonna do to the rest of that organization and whether that company's actually ready for what you're about to sell. What's that knock on impact into operations, into finance,

all the other functions of a business. So I'm really passionate about going back and really understanding what's going on. And when we work with sales teams, again, a lot of people will jump to surgery and that jumping to surgery will be,

we need to new sales process, we need a new CRM. We need some really cool technology in the business. We need to put everyone on sales training. And if I hear that, I'm like, whoa, whoa, whoa, whoa, stop, we don't know that yet. Let's go back and do the MRI.

And we do that by competency assessing the people, really understanding what's getting in their way, doing pipeline analysis, really looking at everything that surrounds that sales function. And by doing that, we can have a much clearer understanding of the ROI of whatever treatment plan

is they're going to follow. So for example, you embed a new process in a CRM and you follow some off the shelf methodology and there's thousands out there to choose from in sales. But then we do the competency assessments and we see actually everybody in the team

or like 70% or 80% are really struggling in this key area. That's the bit we need to hone in on. That's the bit we need to enable through training, through process, through everything. And our data set now is over 2.3 million. It's not our opinion.

There's no bias getting in the way here. We're benchmarking the people in that team against millions of other sales professionals. That's not 2.3 million general public or students of a university. That's 2.3 million sales professionals.

You know what I love about this story? So if I'm a sales leader, instead of me throwing money at a problem and hoping that I fix it, you're going to allow me to pinpoint exactly what that problem is in my team.

And just listen to your talk and maybe think back to my past sales career at times that I led sales organizations. And you're right. You can have a team of 12 sellers and each one of them has a different constraint.

The one that I see a lot with salespeople is they don't want to discuss finance. They don't have good financial acronym. But even that, you have some salespeople that are really good at that, but they're horrible at presentations.

And you have some that are great at presentations, but are horrible in closing the deal. And then another one with salespeople is the ability to say no. You don't have to close every deal. It may not be good for your company or for you.

So I love the fact that you're coming in and evaluating. Now, do y'all evaluate more than just the sales team? Do you actually pull back a little bit and look at the whole organization? We don't look at the entire organization as in we're not about to competency assess

their engineers and their financial experts and things. But what we will do is look at anyone that's supporting the sales function. Sometimes job titles are all over the place. It depends on the region you're working in, the sector you're working in,

the size and type of business you're working in. Like if I go into most oil and gas companies and speak about SDRs, they look at me like I have three heads. Where I go into tech industry, everyone knows what an SDR is.

So which is a sales development representative, sorry for the listeners. And it's really top of the funnel kind of lead gen world. We're looking at anyone that's supporting the sales function. And we talk about things like sellers, sales management, sales leadership,

but the sales leader could be the CEO. It's whoever has that P&L responsibility and is managing the sales managers. Sales managers have to be managing the sales people. It doesn't matter if you're called a sales director and you're a team of one,

we're not gonna give you a sales leadership assessment because you're not leading anyone. You're a sales person. So we don't let job titles get in the way. And for example, we're working with a, they're a software company in the drilling space

at the moment where we're taking a team of technical experts in the drilling space. So they're all, you know, petroleum engineers, petro physicists. And we're actually moving them towards becoming sales people. That's really interesting.

And we track the data when they start and we're not expecting to see anything great in their sales competency. But what it does help us to get an understanding of is some of the belief systems that may get in the way. So things like their comfort level and discussing money,

their ability to handle rejection, their need for approval, their commitment, what motivates them, are they intrinsic, extrinsic? All of these things help as we start to move people from technical roles more into commercial roles. I love what you said there Mark about you look back

and you think about this team of 12 and they all have different strengths. Sometimes a sales leader thinks they have a two year plan of training and development ahead. And it's actually as simple as we do the MRI and we realize all you need to do is restructure the team.

You have great people, they're just all in the wrong roles. You have amazing hunters sitting in a management and all that kind of thing. And sometimes they're gobsmacked like, wow, that's all I had to do. And I've just raised revenue by 20% in six months.

Yes, sometimes it is that simple. We're not here to make it more difficult than it needs to be. We're there to provide data-driven insight that helps the leadership make the decisions they need to make to get growth, to get more predictability in revenue,

not just growth, but we want predictability, want sustainable revenue. That's what it helps us to do. So Sarah, the whole audience perked its ears up when you said, oh, we're taking some engineers and we're moving them into a sales role.

That is a very hard thing to do a lot of times. But y'all are able to do it because you have the experience and the data to show the steps you need to do to make that successful. We've also done it ourselves, you know, nurse, petroleum engineer.

We've been there. That's true, I didn't think about that. If an engineer sits in front of Yicami and says, I'm an engineer, I can never be a salesperson. Wrong person to say that to, right? She's ex, total, slumberj, large register.

And she's worked with the sales guys and then the technical sales guys. And we get the difference. We understand that the mindset shift first before you start looking at the tactics and the skills and the tactical competencies come second.

It's that foundation and the principles of sales. The mindset on that needs to be shifted first. This is something probably right up Matt's alley. Thinking about everything you just said, I could also take that and turn it completely around and use what you're doing to help me hire the right people.

Oh yeah. Right? Because you can identify where the gaps are in the organization. Yeah. If we set the algorithm to really understand the role,

that role, so we take, I'm just gonna use Coca-Cola. I'm not gonna use any oil and gas company names, just in case anyone gets upset. But they use Coca-Cola and they say we want to hire five business development managers, okay? Every single one of those roles will be different.

Same job title, same salary maybe, but every role will be different because they're selling to different markets, different regions, different level of sales cycle, velocity of sales cycle. They'll have different buyers,

some might be selling to end users, some might be selling to C-suite, all that kind of stuff. So we set our algorithm to really understand the role and then we assess all candidates which removes all the bias because you're not looking at loads of CVs,

loads of application forms and making assumptions based on somebody's industry experience, number of years of experience, which you often see in job advertisements. Someone can drive for 50 years, it doesn't make them a competent driver

and it's no different in sales. We remove all the barriers to entry, everyone assesses and then we can give 92% predictive validation on the performance within the first six months. Sarah, I want to back up, I guess,

on how you're doing this. So you have big data, you have large data set, you're training the data. Can you go into that a little bit more? I don't know what's proprietary or not, but like how are you taking that data set

and then customizing it for a Coca-Cola or something like that? How are you training that data or how are you feeding in new data from a new client? I'm trying to wrap my head around that data component so it's not as black box for everybody.

Yeah, you and I should gotten a call one day and I can show you, but we're not gonna have time to go into every bit of detail, but just for the audience to get their head around it a bit more.

Once you have that level of data set and you are validating data, so for example, when it first started, there wouldn't have been a promise of 92% predictive validation. That'd be crazy and that comes with a guarantee.

So we really would have been crazy and commercially not viable. Everything needs to be validated over time. So if we do, we call it our effectiveness and improvement analysis with a team. We're gonna do that again another six months,

12 months later, so that we can understand the pattern, the trends, the changes that are going on. The same if someone is hired using the data, we're checking in regularly to see validating that is coming true, that that person is performing

and what's getting in their way and is that's what's showing up in the data. So there's a lot of validation has needed to be done and by setting the algorithm. So I said we set the algorithm on the individual role for recruitment,

but if you're doing an existing team, we go through what we call our selling profile, which is essentially telling the algorithm much more about that organization. So there is no one-size-fits-all with this stuff. You have a lot of inputs.

Yeah, you have to input first for it to understand where the business is right now, where that business needs to be and then we're understanding that gap in the middle to provide the insight and the recommendations that businesses really need in the boardroom

to help them move forward. But if anyone wants to see it, happy to show them, so get in touch. In the audience, we'll have a link in the show notes both to Sarah's LinkedIn profile and actually to her company

if you want to go check out what she's talking about. Just for everybody that's listening, let me try to translate some of what she's saying if you don't fully grasp it. Basically, she has a huge data set. From what I understand, Sarah, correct me if I'm wrong.

You have a huge data set and then you've trained the algorithm. You have all kinds of case studies or whatever that you've trained of the data. You put that client's specific inputs based on certain criteria

and then there's some validation that happens. But what's cool about this is it's not anybody's opinion. It's what the data based on the immensity has shown over time consistently based on a bell curve, it's applicable. And that's the thing with marketing too

that the transition from traditional marketing to digital marketing is, oh, I think that you should do this. I think that this is a great idea based on my experience. And that's how it used to be and how you run the ad and, okay, we can't do anything about it.

What we're saying is, or what you're saying is, we're taking and we're inputting as much data as we possibly can for your organization or your specific salespeople. We're looking at what that looks like against the overall data set

and we have some algorithms that we built that work for different kind of things. And then the algorithm's spitting out the data and that's telling us what to do and then we're just helping you interpret that. There's no bias in it because it's just big data.

Exactly, and we don't sit and interview people. Some of the larger consultancies out there to get even close to this level of insight, they would live in your organization for years and there's a lot bias getting in the way because it's someone's opinion,

because somebody's in there interviewing your team and all their own experience and their own preferences and assumptions are all getting in the way. This removes that and that's really important. It's also important that we move quickly

and to give an example, if you have like a team of 50 salespeople all around the world, different regions, different divisions, from deciding to go ahead with this, to having the answers in your hands

is a matter of like three to four weeks. And obviously everyone has to cooperate and it takes a lot of coordination and we can do it on a team of three to a team of 3,000, it doesn't really matter. It's the way we break it down.

And if it's a big company, you obviously need to break it down almost into like smaller chunks of analysis based on division, based on business function, based on region, whatever the structure of the organization looks like,

rather than throwing everyone into one pot. So yeah, the speed to getting the answers is also really important, I think when you're in the boardroom and you're under pressure, you know exactly what you need to achieve,

what your business objectives are, but you often don't know is how do we get there? And sales has not been professionalized in the way that other disciplines have been. And I'd say even less so in oil and gas actually, because we've worked in quite a lot of other sectors

and there's a lack of professionalism. And that's not from the sales people, that's just the way people perceive and look at it. It's quite unknown, like they don't seem to have their secret recipe, like they would in planning and quality and safety

and all this stuff. I attended a conference on process safety a few weeks ago and I was sitting there and I was just like, again, mapping it to the sales process, to the nursing process. It's no different, it's just not being professionalized and regulated

in the way that other functions have been yet. I hope it comes. You know what I love about this? Everybody has seen this, I've seen this myself. You're hiring a sales professional, you find a top performer,

has an unbelievable track record of just killing it. She or he's personality fits in with the team, so you know you're making the best hire you've ever made. You bring them on board and they fail. And they fail for a variety of reasons, but usually it's because they're not a good fit,

you just didn't catch it. And you got wowed by their past record of success and you weren't able to make sure they were a good fit for the position. And Sarah, you've turned what I just said into a science, like literally a mathematical equation

to make sure they are a good fit or that you identify that they're not a good fit. And we see it a lot with potching from competitors and we can pick up on it. If we're using the data and recruitment, it's things of the EPC contractors.

They're always potching and it's the same clients, the same industry, the same products and services. And they cannot figure out why someone can fly in two organizations and then come to their organization and plummet. And there's so many reasons why,

but we can pick up on that before it happens, thankfully. Sarah, I'm just curious based on my background, like what has been your experience of working with like recruitment firms? Because I think that what I've seen at least from like UK, Scotland, when they come over to the US,

that term of professionalized from the recruiting standpoint, they've got it kind of figured out to a lot of degree. Now, I haven't seen them use machine learning and like data sets to do some of this, but it's very process driven on how they do it. They know actually from a recruitment standpoint,

when they hire somebody, what their potential to make is within probably like a 15% Delta, maybe even less. I've really just seen that come out of UK, Scotland area. I'm just curious, has there been any crossover with recruitment companies with what you're doing?

Yeah, there has and not just here, we've worked with more headhunters than generalist recruitment over in Texas as well. Yes, of course. Yeah, that's what I'm meaning like executive placement. Yeah, because our clients are all over the world

and a lot of them are multinationals. So they're recruiting everywhere. It's really interesting. A lot of recruiters don't like having to work with us. Once the client knows what they can do, they won't let it go.

And therefore they make it happen. But we've had so many conversations about collaborating because most recruiters you speak to hate recruiting sales professionals. It's one of the most unpredictable parts for them and we can make it more predictable.

So we thought, oh, they're all gonna want to work with us, but that's not the case. And the reason for that, it's taken a number of years for me to figure this out. I think the main reason for it is they don't want to change their process

because they're getting paid for reviewing hundreds of CVs, application forms, screening interviews, and we've removed that. The in-house recruitment teams love us. They love working with us.

But the external agencies, headhunting kind of outfits, they don't like it so much because we're removing a lot of the work that they get paid to do. And the ones that are open-minded, they've actually ended up making more money

because when we take this value proposition to gather to a client and say, look, we're gonna shift the process, you're gonna get more value, we're gonna spend less time, but you're not paying us for time,

you're paying us for the impact, the outcome. We've done quite a few collaborations with more headhunting than general recruitment again, where we'll go to the client, it'll be their client, and we've hired 15 salespeople across the last two years and 80% of it's failed.

We know it's difficult. So we've now found something that if we can take kind of Sarah, you know, the Dukari way of doing it, and then where their expertise comes into it is managing and coordinating the candidates,

which we don't want to be doing, but also making that business attractive because it's a candidate's market a lot of the time and they're great at doing that, selling the role to the candidates, and then all the interviewing stuff at the other end.

So what we do is we work with them until we have what we call a set of recommended candidates, the candidates that come with the 92% predictive validation, and then we'll sit with the recruiter and the hiring manager and translate the data into something really useful for them

to then move into interview process with, and we can work together. I think it's a great bolt-on like value add to a headhunting agency or corporate recruitment agency because really, yeah, is this person gonna work long-term?

And a lot of these contracts, it depends, but you don't get paid for a couple months potentially and that person's gotta work out. And if your date is confirming this person's gonna work out, you can sleep much better at night.

And I think that that's very attractive too if you're approaching employers, right? If you're a headhunting agency saying, hey, this is how we're doing it and we're gonna combine big data science with what we're doing. I think that is a very attractive type of problem.

We're selling the recruitment thing on its own just because we don't want to be confused with it as a recruitment company, because we're not, that's not our accident. No, no, no, I'm just thinking as like recruitment firms, I've worked with a number of recruitment firms

and they might be interested, I would be if I was them in your technology or data, yeah. I tell you what else, imagine being a candidate. I think those are ways because when we assess a team, we identify the gaps that they need to recruit into. Often we're looking for great recruiters, headhunters

to help our clients fill those gaps, but it has to be people willing to work to our process because the client is already all in on the data by this point and they're not gonna shift away from that process. And it's amazed me how many of them have actually walked away

from that opportunity. They assume they'll have to make less money, but that is not the case. It sounds like they'll make equal amount of money for less work. I would love to have that problem to deal with.

Matt and Sarah, the other thing is, listen to y'all to talk. If I was a candidate, do you know how much more positive I would feel about accepting a job offer if the data says that I'm a 96% fit there? That would just give me another layer of confidence

that I'm making the right choice to accept this offer, where there's a data set saying this is a good fit. If you're moving from one organization to another and you've been at one organization for eight, 10 years, to move somebody is very difficult. If you're saying, hey, I know that this is gonna be a change,

but look, the data's telling me you're gonna do amazing. I think that, yeah, Mark, there's some great value there. Candidates can, because obviously, when people are really on the market, they'll often apply for a number of jobs in a row that our clients are using our data for.

So what happens is they'll be recommended for some and not for others and they can get quite confused and a bit upset about that. If that was the job they really wanted and it's saying not recommended, but they're being offered something over here.

I've spent lots of time with candidates over the years explaining that and explaining that it's actually not just about how competent they are, it is also about the fit with the organization. So for example, if somebody has a high,

we call it figure out factor. So if they have a really high figure out factor, you don't want them in a sales office, in a sales team, they'll be completely disruptive, they'll be fed up, they'll be demotivated, not their outfit for them.

Equally, if someone has a low figure out factor, they need to go into a business with a really strong sales manager for them to thrive. And a lot of businesses don't have a sales manager, let alone a really good one. Once you explain that to the candidates

and understand that it's not just about them and how competent they are, it actually is about the fit with the organization as well, that then gives them a lot more confidence in the decisions that are being made. Well guys, unfortunately we are at time,

we need to wind this thing down. Sign up for our two newsletters, the links are in the show notes, all in gas events newsletter, and then also our new Sunday update, which people just love to death.

Sarah, my marketing team grew that from zero subscribers to 26,000 subscribers in seven weeks. Isn't that crazy? Amazing, that's awesome. Yeah, also Matt and I are social channel links are in the show notes as well.

We're hard at work on the insiders groups, stay tuned for that. Now it's time for our LinkedIn fail or tip of the week. Do you have one Sarah? Sure, I'll go for the tip of the week, because if I go for the fail,

I might just come across very ranty, but the tip of the week is LinkedIn headlines. Okay, so it's that little bit that comes up after your name, so it's your profile photo, your name, and then your headline. And most LinkedIn users have job title and company name.

It's an absolute waste of very valuable space on LinkedIn, because that headline is your stalker. Everything you do on LinkedIn, it follows you around, whether you're cop posting, commenting, liking, connecting, DMing, whatever you're doing is there.

You have a lot of characters to use, please make the most of it, get your value proposition in there, say something interesting, say something that's gonna help build those connections, those relationships.

Please don't just have job title and company name, it's just such a waste of space. There you go. What a great tip. I know it's a great tip. I'm reading yours right now, Sarah, on LinkedIn.

That's what I was doing. I'm kind of cheating. We do LinkedIn training, and we speak to LinkedIn all the time to stay on top of the algorithm, so I'm kind of cheating that I know the importance

of that feature, so please do use it, everyone. Great, great tip. All right, we need to get out here, so remember everybody, make a difference and not a sale. Thank you. Check us out next week for another enriching

and cheeky episode of Oil and Gas Sales and Marketing Podcast, a production of the Oil and Gas Global Network. Learn more at oggn.com.