The Sales Engagement Podcast
The Sales Engagement Podcast

Episode · 1 year ago

A Guide To Using Data in the Boardroom


If you’re looking for the latest trends in the market but don’t want to be late to the game, your best option? Look at the data outliers.

Data has become integral to the future success of a business. If your organization hasn’t made a place for it in the boardroom, today is a good day to start.

We speak with Sameer Rahman, Director of Insight at The Royal Mint. He’s here to talk us through data’s importance and where it’s headed next.

We talk all about:

- The modernization of data over time

- What data in the boardroom looks like & its impact on future success

- The best tools to leverage data

For more engaging sales conversations, subscribe to The Sales Engagement Podcast on Apple Podcasts, on Spotify, or on our website.

Listening on a desktop & can’t see the links? Just search for Sales Engagement

in your favorite podcast player.

Welcome to the sales engagement podcast. This podcast is brought to you by outreach, the leading sales engagement platform, and they just launched outreach on outreach, the place to learn how outreach well does outreach? Learn how the team follows up with every lead in record time after virtual events and turns them into revenue. You can also see how outreach runs account based plays, manages reps and so much more using their own sales engagement platform. Everything is backed by data pulled from outreach processes and customer base. When you're done, you'll be able to do it as good as they do. Head to outreach that Iola on outreach to see what they have going on. Now let's get into today's episode. Good morning everyone, welcome to the sales engagement podcast. You have your host Citelin Kelly here, senior manager of sales development at outreach for the Amia region, as well as cofounder of STRs anonymous. For today's episode we have some Mere Ramin from Royal Mint, who is director of insights. Today we're going to be focusing on data in the board room and the importance behind leveragine data. Today's environment. Sa Mere. I'm going to toss it over to you tell us a little bit about what you do over at Royal Mint. Good. First of all, thanks a lot, Caitlin. Quite looking forward to this podcast on. Very much enthused about sharing mindsights. So yeah, the Royal Mint role is is quite a three part tight roll, because the Royal Mint has got three different business models within it. One is a manufacturing part, which people know the Royal Mint for. My role within that is to look at efficiency gained, productivity gains through through the use of clever use of data and technology, things like predictive maintenance so that a machine doesn't go down and we don't run out of money in our pockets and and things like that. So it's and and forecasting is also a big part of that. The other part is the ECOMMERCE or or the retail model, which essentially is...

...selling historic coins and commemorative coins, coins that we design on the website. So the royal mint tax as a typical retailer and our job is really the usual marketing job, which is really who should we target, how should we target? What should be the messaging? What should be the pricing? Whole Suite of predictive models, right from prospect modeling to retention modeling, to churn modeling, to reactivate modeling. So it's a usually commerce retail kind of environment with lots of predictive models, segmentation, targeting and and possessioning in of the right product with the right audience. Then the third part, which is quite upcoming and quite quite a profitable one, driven by market dynamics, is really the precious metals division, which is goal trading and selling a goal bars and coins which is very reflective of what the goal price is on that day. So I job is really dynamic forecasting, dynamic fixing of prices, looking at the market and basically responding to the market within seconds, if not Milli seconds, to change the pricing and everything. So yeah, I might team plays a key role in driving all those business forward and at a strategic level we are also very much aligned with the business strategy and drive the business strategy in so most of those strategies are really very much driven by insight bottom up, and the recommendation, initial recommendation to the business goes from our team. So it's quite a pivotal role it. It's a role it's from the team's perspective. It goes through the breadth and depth of the roilment. Oh, I fantastic. I love how that's kind of structurally at three different avenues. there. You guys are leveraging the data to really drive those strategies forward, which is huge, especially in today's environment. You know, Simiar, you were voted one of the top one hundred data leaders by data IQ in the past year. So how have you really seen the modernization of data evolve over time? Yeah, so it's a good question. I think the modernization, obviously...

...we all know about the technology that is driving it. The technology has becoming has become faster, quicker more effective. Similarly, the amount of data that we are generating is bigger, better. They always talk about the veracity, velocity, volume and and the vs. from my perspective, my different spin on this is the mindset and the way that data should be treated, is treated is has changed, and that is what I call data modernization, rather than the technology itself. I mean the analogy is clearly during covid times, the whole country strategy is led by data, is led by insights. I mean, when was the last time when a prime minister of a country and the chief chief medical officer comes and gives press conference, which is all about data and decisions are all about what the data is telling us, what the protecting modeling tells us when to lock down a country. So that is typical modernization, saying, okay, you looking, you're looking at the data and you're driving the whole country strategy based on data. It doesn't obviously the people read data and make decisions which which always they don't get everything right, but that is what I call modernization. It's a modernization of mindset. It's the modernization of culture, it's the modernization of how data is driving out, how data literacy is driving decision making is the highest possible level, which really is impacting every individual within the country. That is a that's a really good point. They're saying that. You know, it did start with the prime minister and a leverage in the data there to wead the country in the strategies. How have you seen a teams kind of adopt this methodology to use this at to use their data and you know, how the information they have their fingertips as their commercial driver? Have you seen this interning? Very much. So I'm so. I mean, for me, I think there's two arms. I mean, you can you can cut it in various ways. I call it offensive and defensive. The defensive one really is how I got the data...

...structure right, how I got the data management right. The defensive one is really the data being the enabler and the utility for the organization. Okay, so that's that's what data engineers used to do. The more exciting bit not saying the defensive one is not exciting because you have you have to lay the foundation. The more exciting bit and the modernization and which which might team. I'm trying to instill. That is the confidence of being proactive and of what I call offensive so go away and recommend new products, go away and recommend new business ideas, go away and recommend innovation, disruption. Look at the data and the out what I always call the outliers, of today will form the norm of tomorrow. In the past, the analytical team would read an outliers. Okay, this is an outlier, remove it from the modelaying I will concentrate on the norm, but it's the outliers that dictate the as I said, the norm and the fashion and the regularity for tomorrow. So the offensive thing for me and the modernization and the and the confidence that every leader needs to instill in the team is really how to be confident in taking that outlier and studying the market around that, figuring out which one is a fake outline, which one is a real trend going forwards, and then basically pushing the business forward saying look, this is a trend. I really believe, through the evidence that I've got, that this will become a normal very soon, or either we follow others and watch what the norm is or we start to disrupt the market. And there's lots of examples within the Royal Mint and within other organizations I've worked whether we have picked up one or two norms which has really opened up a new revenue streams, which has developed new markets in different territories for for four companies. So the data analyst and the data scientists or today should be well, should get it to the defensive, but it should also be confident enough to drive the business strategy through their offensive approach.

I really love the you just mentioned there about talking about, you know, look at what the outlier data is showing, see if that is a trend, seeve that there's like a it could be an untapped strategy and untapped market it could be something that you could double down on if you drive the results. Just from like my experience, when I'm thinking like from like a sales there's always going to be a you know, the maverick in sales that and that's kind of that the outlier person. But there could be breakthroughs living there that then you could replicate across all teams or drive strategies for it as well. That's such a great call out. Yeah, the beauty of being a college data Maverag in your terms it in. The beauty of that is that this datum maverick is led by more evidence. He is not taken the outlawyer just per se. He has investigated that outlawyer, looked at market data, competitor look at every bit of data and then they will be probably one outlier out of ten or something like that, which will be a real trend changer. The beauty is identifying that, getting more data to support or negate that and then presenting that data as a very credible next generation disruption to the market. Yes, that brings me on to my next question. Here. Some mireor so previously, we talked about, you know, the importance of using data to really drive the conversations, especially in you know, when you're looking like driver outcomes and you want to have data in the boardroom. Can you kind of elaborate what that really looks like when you're talking about having data in the boardroom? For me, that having data in the boardroom is again going back to its more mindset. At other than lots of companies have gone down the route of having a cdeo or a CEO or a CDA or the chief information officer, which is good, which is which is good stepping stone. That means the company's thinking about the importance of that, that function, functionality within the business. But really one person cannot like, I mean the whole concept of marketing. Who owns the consumer? Everybody owns the consumer. Everybody...

...needs to impact and work towards improving customer experience. Data is very much data in the boardroom is very much the same. Every executive in the boardroom should understand the importance of data and should understand what it brings to the table in their own areas and across the organization. For example, for the HR person, for the C HR or HR director, in the boardroom, it's all about how many employees are churning. Do you know why they're channing? How do you stop them? The productive modeling around HR analytics and the churn analysis. That's how the data can help them and their own work streams. Finance forecasting is always a big thing. That's how time we can the data signs, can apply time series and other sophisticated methods rather than spreadsheet forecasting. So it's a case of for me, the data in the boardroom is every skill that a data person and every bit of data that they have how they can impact their own teams at a both a and operation and at a strategic level, and it's understanding of that and the CDA or the cdeo makes them understand that. But then from then on it's a mindset change in the new ways of working that they have to adopt, and obviously the cheer leader within the boardroom has to be the CEO and the CDO who's leading that mindset change. So data in the boardroom is equally about personalities and who is present in the boardroom. It's about what they do to change the mindset and make people realize how important data is to all of their teams and obviously to drive the business strategy forwards. That's all true itself. From the top down, it's going to be everyone's going to be on board day it's how are you really implementing it? How are you talking about it and using it? On the outside of that, would you say that if companies were not making this shift already, this could prevent them from scaling defficiently? I think yeah, I mean every company is different. It's quite contextual, isn't it? But I think if they're not looking at their business from what I call a data Lens,...

...then they are missing out on something. So I mean typical example is, for example, even big companies of today, let's say Google and facebook. Google had no credible commercial platform. It is big brand, we all know, we all use it day in a day in a day out, but up until ten, fifteen years ago it did not have a credible commercial model until it introduced the paper click at words campaign. And what is that? People giving the data and Google building on data that we give them. If that data did not exist, no commercial, credible model for Google would have existed. Same with facebook. FACEBOOK makes more most of its money through through what data we give them, what we tell facebook about us, and then it bids on that shows us contextual targeting and things like that. So again it's that data Lens. If you don't use that Lens, you're missing out either on a big commercial driver for the organization or you might be missing off completely to make your business commercial. And Curias, you know, semere. I'm what are some keyed tools that you're using to ensure that your team's over at where meant, are leveraging the dartity drive their desired outcomes. Yeah, I think the tools at every level is we're not using any earth shattering tools, I think, Caitlin. I think the tools are as said, the tools are tools of a reporting. For example, we are on the Microsoft suite. We use the whole of the Microsoft suite. We use as your as UML and all those platforms, obviously for reporting, an EMI and automation. We use power Bi and things like that. For predictive modeling we use Python. So I don't think we differentiate ourselves in the tools that we use. I think again, the differentiation comes with how good your data is, how how are you extracting it and how much time you're spending in actually looking at the outcomes, because tip typically it's a case of analyst would be use a tool, do a job, move on to the next job. I think one of the things we have quite imboved within the team is once you finish a job, you give yourself at least a day or two to think...

...about what you've done, to look at the outputs, to give tangible recommendations to the business and also the next steps, saying, okay, this is something of a trend, we need to investigate further, for example. So it's the thinking time. I think that's the main I would say that's the main differentiation. But, as I said, the tools are important to get the work done. It's just the experience and the thinking time after you've used those tools trick to extract the right insights. Thank you so much, mere, for sharing your insights here on the importance of data making sure that not only are you playing it back to the data and insights that you you have, but how are you driving that culture and conversation forward as well? Lastly, some mere I would love to know if there's one book that you would recommend toory listeners that's had an impact on your career development. What would that book be? Yeah, it's typical to choose one if I choose, if I can choose too, because both of them have been a kind of career defining moment for me. So one of them was when I was doing my masters in business and I was working on a dissertation on Customer Loyalty and Club Guard and stuff like that, and and I read a book called scoring points by Clive Humbay and Terry Hunt. They were the ones who set up the whole concept of using customer data to target back and the whole concept around the TESCO club guard and the loyalties game. The penny drop of this is back in two thousand and four when I read that book and that was really their career defining moment for me, saying, okay, I've done my engineering and I'm now doing my business. At that point I wasn't right shore as. So what's the overlap between the two? When I read that book I said, okay, now data has become such an important entity and the analysis and the outcomes of data that it can change business operating models and if it can change it for behmoth like Testco, it can change it for anybody. So that really became my saying I want to develop my career in this analytical field and my engineering degree and my business degree both can collide together and give me that give me that strong platform. So that was one thing. Then the...

...other bit. I've always been interested in sports and use of data within sport. So again, they everybody might have seen the movie or the Book Money Ball. I first read the book. It was more around how Oakland, Oakland Team, uses quite intelligently uses data without having proper funding. They end up winning the tournament and beating the big, big guys. So that really was my my initial sort of for ay into. I want to become a non executive director or a director within sporting organizations, I mean non executive rector to sporting organizations currently and using data and guiding them to use data for player strategies, match strategies, play recruitment and things like that. So those two books are really really key and defining moments for my team. Everybody's got their different choices, but for me genuinely those two have made me do something different in my career. Amazing. I'm that I've seen the movie money ball. I've not read the books. Are To add in there, but I'm curious to mere what is your goal to sports team. Well, I'm very much into cricket. So yeah, I mean it's yeah, I mean there's no up to us. I there's no go to sports team. For me. It's it's my passion is I need to use data to raise awareness of the sports that I like and to get more people, more people driving, and for teams to get more successful. So any team who really uses data in the most fascinating way will be will be quite interesting for me to watch. Oh, I love that. That's fantastic. So, sire, if any of our listeners wanted to reach out to you after today's episode, where would be the best area for them to connect with you? You can always connect on Linkedin, some a raman and by email. I run my own side data consultantcy which is monetizing data. So you can always reach me on submit at Data Monet Code Ort UK, and I will be very happy to share insights and learn from each other. All right, fantastic. Will you heard... here first had a leverage data in the boardroom. Samiar, thank you so much for joining us today and have a fantastic after it. Thanks careclar this was another episode of the sales engagement podcast. To help this get in front of more eyes and ears, please leave us a shining five star review. Join US at sales engagementcom for new episodes. Resources in the book on sales engagement to get the most out of your sales engagement strategy. Make sure to check out outreach that ioh, the leading sales engagement platform. See you on the next episode.

In-Stream Audio Search


Search across all episodes within this podcast

Episodes (334)