INBOUND 2015 HTT: Steve McKenzie "How to Run Your Sales Team Like a Data Scientist"

Thanks, guys. And thanks for taking the time to listen to me drone on for 40 minutes today. Hopefully it's valuable to you. This feels very weird, so I'm going to stand over here. Please tell me if it's awkward for you if I stand down here. I'm going to give up my crib notes over there and try and wing it. So let's see how we go. Is this okay if I stand down here? Yep. Cool. Okay, just quick question. Who here is a sales leader of some sort? Cool. Marketing leaders, Individual sales contributors. Okay, cool. So, bit of a spectrum. So I want to talk a little bit about how to run your team like a data scientist. Let's just get straight into it. One of the reasons why I think this is important is we have to have context, right? We have to think about why is this relevant. And I'm not going to quote the quote, but the statistics are all over that if you are more data driven within the sales organization, you are just more successful. So I think this is just an indisputable fact. I think that what we're seeing, you can Google it anywhere and you'll get a, a whole bunch of data coming back that proves out the point. And I just took out a credible publication, Harvard Business Review, that talks to this. What's interesting here is if you look at the thing that talks about your bottom performing reps, you really want to improve those guys because the guys that are your eagles, the people that are over 100%, you're not really too focused on worrying about improving them because they're doing a great job. What we really want to focus on is those reps that are perhaps struggling a little bit and using data to try and drive behaviors definitely does work. And hopefully I'll prove that out during the course of today's session. Another reason why it's important is because most of us work for CEOs and Bob Brennan, who's a well known CEO in the Boston area, was the CEO of Iron Mountain. Now the CEO of Veracode came up with this quote, which I think is great. Every company and more particularly every CEO has two kinds of problems. The first one is not, not enough revenue, and then everything else, right? So CEOs are absolutely focused on revenue. And most of us here are probably in companies that are looking to grow. I don't know too many people that are very happy with staying stagnant. And as a result of that, we're continually thinking about how do we grow, how do we get more, how do we do better, Right? So if you have a boss, you want to make sure you can speak his language. It is advisable. So let's get into what a data scientist is. So I'm kind of going to read this a little bit. This is a definition of a data scientist as per IBM. So these are people with a background in computer science, applications modeling, statistics, analytics and math. Strong business acumen, with an ability to communicate findings to business. And it. I'm not going to read it all. You can kind of read it for yourself. But this is kind of a data scientist, right? So as the world is moving, I think that in the sales profession we are lagging. Our colleagues in the marketing world, our colleagues in the marketing world have been more data driven earlier on than we are and we are now paying catch up the sales professionals. But I guess you're also thinking as a sales leader, that is certainly not me. It's certainly not me. Although I come from a finance undergrad background, I spent the early part of my career in investment banking. But I'm certainly not a data scientist and I do not aspire to become one. But I want to see if I can cheat my way to becoming a data scientist. So most sales leaders probably in the room are thinking, I don't have those five characteristics that you just listed up there. So the good news is you don't have to. A lot of salespeople think like this. A lot of sales leaders think like this. Listen, I don't need all this data crap. I'm an artist, right? I'm good with people. People like me, I take them to board games, steak dinners, like it's all relationship. I don't need this data stuff. It's not going to make me any better. Just leave me alone, back off. I'll go and get the deals done. Well, if that's the case, buddy, I think you're coming very close to the end of the road. Right? People with that attitude are dinosaurs in our industry. And it's not okay just to focus on the artistic element of sales. We have to combine it with the science and the data that exists out there to make us better. Because there is empirical data out there that just proves that we can be a lot better. But I do want to go back to the art and the science because I think that for those of you that have ever done a deal, for those of you that have ever led sales teams, you will know that the artistic side is still absolutely relevant. So if we read the common marketing theory that exists out there, we know that about 55 to 75 to 65 depending on which report you read of the sales cycle is completed by the time a human being engages. Right. But that means a human being still has a massive impact. So I don't want to take the artistry side and push it and say that all salespeople can be robots because I fundamentally do not believe that to be true. So there's a whole nother session that I can do about the artistic side of things because actually naturally that's the way I lean in terms of the way I came up through the sales ranks. But I'm increasingly realizing the benefit of the left side over here. So I want to make sure that what we don't do is swing the pendulum too far. It's all in vogue, right? As is evidenced by all of you sitting in the session. It's in vogue to talk about data driven sales organizations and the like. And I think it's fundamentally important that we adopt this and we help improve. But let's make sure that we don't swing the pendulum too far because we still want to focus on our sales reps development, our sales methodology, how we approach deals with an artistic side. But today we're going to talk about the science. Okay, so let's get into it. When you look at how a data scientist operates on a day to day basis, this is kind of what they do. They're figuring out how to ask questions of their business using data and then bringing that data back and presenting it in a human readable format such that we can make decisions. That's really what they do. And the important thing is to never stop questioning. So I have to, as a result of my quotas going up every single quarter, every single year, and we're trying to achieve ridiculous growth rates. I have to obsess over how do I get more, how do I get better? And I'm pretty sure it's the same for all of you in this room, right? So we cannot stay stagnant, we cannot think about just doing the same things. Because if we do the same things, we'll just get the same results. And that's the definition of insanity. Right? So what we want to do is continue to be questioning how do I do more, how do I get better? And that's really what a data scientist does on a day to day basis. Always thinking about what they can do to help improve performance within the business. And I like this, this is a customer of ours that we did a big deal with the other day. And we were the final hurdle. This person had just joined, he runs a very big sales organization. He had just joined the organization and he came up with this quote and I really liked it. He was like, steve, I'm a believer. I absolutely am a believer. This is exactly what I want within my business. We have to be more data driven. Because ultimately you cannot improve what you cannot measure. Because how would you know, right? If you cannot measure, how would you know if you've actually improved? So it's kind of an obvious statement, but I quite like the simplicity thereof. So big data, like I started getting involved in high growth sales businesses back in early 2008 when the word cloud was not a word. You know, there were still those things in the sky, but cloud computing wasn't a word that was talked about. And then suddenly cloud computing became all in vogue and everyone cloudified their business. There was a lot of, but there was a lot of guys who were putting cloud in front of what was already like a managed services type thing. So cloud became invoked. And what we've seen is the same thing with big data. People are talking about big data. This, it's the panacea, it's the answer to everything. Big data will solve all your problems. I kind of want to unpack that a little bit because I think that's too much of a broad topic. We like to talk about big data versus small data. For us, the definition of big data is like the Internet of things. Everything is a sensor, it's machine generated data. This is like lots and lots and lots and lots and lots of data. But for us who are running sales organizations, trying to coach, mentor and develop sales individuals to be better, we're really focused on the small data and that is human generated data. Data being generated by our people and the systems that our people use. More specifically CRM data. And that's what I'm going to focus on a little bit here today. So I spoke about this earlier. The good news is that all those qualities that a data scientist needs to have, you don't need to worry about it. You don't have to suddenly retrain your brain. The tasks that a data scientist performs is something that you should be thinking about adopting into your daily jobs that you do. But you don't have to change who you are. You can cheat your way to becoming a data scientist. And the beauty is it's actually quite easy. You just got to do it. I do want to caveat this, right? What you find is so just a quick little background, finance undergrad, spent a couple of years, five years in investment Banking, Moved into big honking enterprise sales in the city of London. Who thinks I'm English? Oh, I might knock you out. Well done. Cool. Please don't call me English. We're about to play them in the World cup in rugby. And anyway, so one of the things that. Sorry. So going back, spent time in London selling big conking enterprise solutions, then went back to South Africa, business school, started my own business, sold it, moved back to London with three young children, joined a SaaS startup where we had to make things up as we went. It was like a really early stage company and we built it to something quite nice. And then I've kind of gone back in inside squared for the last 12 months. So I've built a few sales teams and let me tell you now, it is not easy, but if anyone thinks this is an easy job, then maybe you're in the wrong place. There are certainly no silver bullets and sometimes those of an engineering orientation might say it's simple, you just do this, this and this and then you achieve this, this and this and then we're golden. Right? But there are so many dynamics to successful sales. So I don't want to stand up here and profess to be a complete know it all and have all the answers. Hopefully I can impart some of the experiences that I've had as to things that have served me quite well. But I do want to caveat. There are no silver bullets. Right. One of the things I like to talk about is this. So we live in a results obsessed world. There's two things for us that are carrying quotas that are driving growth within our businesses that we obsess over and are forced to obsess over. And that is the results. What's our forecast and how did we do against our forecast? Right. And that can be quite paralyzing. So I would encourage you to think about, not that and think about performance. And the definition of performance is doing the things you need to do to get the results that you want. So results is merely a byproduct of performance. And if we can maintain the discipline of saying, guys, I'm not going to obsess over what are we going to do this week, what are we going to do this month? I'm going to obsess over the things that are going to allow me to be successful. So I'll just say it again because I think it's quite a powerful statement. The definition of performance is doing the things you need to do to get the results that you want. And results is merely a Byproduct, it's like if you think of Usain Bolt, I'm pretty sure when Usain Bolt is at the start blocks for the 100 meter sprint, he's not thinking about winning the 100 meter medal. What he's thinking about is how long, how many strides do I keep my head down for how high do I raise my knees? When do I take my first breath? How many breaths do I take in the hundred meters that I'm going to be running? How do I perform optimally? And if I perform optimally, the result will be I'll win the race and I'll win the gold medal. But if he obsesses over the gold medal, he will not focus on his performance and therefore he will probably falter. Well, he's a bit special, so maybe I'll just win anyway. But. So that kind of gives you an example of like obsess over performance and the results kind of take care of themselves. So some of the performance questions that I think that we should be asking ourselves on a day to day basis is, how am I doing? I always want to know, how am I doing? How is my team doing? How are my guys doing? Do we have an ability to answer those questions? Did I have a good day, week or month? How would I know? You know, if you ask someone any of your reps, how was your day today? I guarantee you that they'll say, yeah, it was a great day. And you go, how do you know? I don't know, it felt good, I had a couple of good calls or whatever it is. But you really want to use data to support the answer to the question. So you really want to be thinking about what does a good day look like? And can they answer that? How did my day compare to yesterday or last week or last month? How was my performance today or the period in question versus the previous period? And how do I know? How do I compare against my colleagues? Is it an emotive thing? Do I feel a certain way or do I have data to back up my performance? Did the changes I made have an impact? And we always want to be thinking this. Remember our obsession with more and better. So a good thing to do is look at AB testing. If you've got a particular value proposition that you want to test, a pitch or an approach, split your team into do do the traditional way. Take the second part of the group and let them go out to market and test a message or a picture and approach. See how it works. And if you get a better result, just port everyone over to the new way of doing things. Or if it doesn't work, then you retire it and go back to the old way of doing and hypothesize about a new way of getting better. And again, a B, test it within your sales organization. And you want to be able to test and how do you know? So we have to use data to support whether the changes you made were effective or not. You cannot just be rhetoric, cannot just be, yeah, it felt good, felt a little bit better. We really want data to support those. How am I going to do against my goals based on my performance? So if we know that our goals are the results, what we want to do is focus on performance, track our performance, see how we're doing so that we can predict the future. We know we live in a, in a forecast obsessed world as well. A lot of our success will be determined not only by hitting our goals, but our ability to predict whether or not we're going to hit the goals. And even if we're not going to hit the goals, we should be able to predict a number that we're going to hit. And I guarantee you now that most of you will be judged on your ability to accurately predict. Because sometimes the goals that are set are perhaps a little bit too stretchy. And so it's almost more important to understand your business. And we all know that when you get into the, the public markets, your share price gets absolutely hammered if you do not do what you said you were going to do. So everyone who's aspiring to get into the public markets should start to look at this as a discipline now, from a grassroots level, saying we have to be able to predict our business. Because very soon it's not the head of sales or the CEO or the board who's going to want to know. It's the public markets. And our share price gets crucified if we get it wrong. So everyone wants to know, are you controlling your business? And then how did I do against the goals that I set? And indeed are the goals right? When you set goals, you actually don't know if they're right. So what you want to do is set the goals, execute a plan against those goals, and then see, how did we do? Did we achieve what we thought we were going to do? Other goals, right. Maybe we need to pivot. Were they too high? Were they too low? But we need to have data to help inform the answers to these questions. So what I'm gonna do is I'm gonna take it down a notch and kind of give you Some insights as to how I see the world. And I am not a data scientist, therefore my IQ is not through the roof and I'm a dumb sales guy. So I like to keep things very simple. So I'm gonna give you some insights as to how we like to see things. I like to talk about this notion of a customer journey from awareness to loyalty. And if you think about it, the awareness component starts with marketing through the sales journey from when they sign up, become a customer, hopefully they renew, you have an ability to upsell, and then they tell their friends and you get referrals out of them. So that's the loyalty component and the awareness component. It starts with marketing and goes through the sales journey. And I'm going to stop at the end of the sales journey through the eyes of a sales leader. I think most of us will probably appreciate the analogy. We always think of things in the, in the form of final a lot here and a little down at the bottom. And there's a series of steps that we want to go through. There are many, many things to analyze. Again, I'm just going to give you a snapshot of a few that I think are the absolute basics that we should be thinking about on a day to day basis. But there is also the notion of analysis paralysis. We all know that. So I would encourage you to think very long and hard about the sort of things that you want to measure. Measure them with a very strict cadence. Have that measurement across the entire organization so that everybody speaks the same language. What sometimes happens is every day someone's asking a new question and what it does, it takes you off piste, it confuses you and it stops you from executing on your plan. So start simple and then slowly but surely add more questions that you want to ask. But if you start with a gazillion questions, the answers to those questions will really confuse you. So try and keep it simple. So if we look at the top of the funnel here, what we're seeing is a graph that denotes the gray line sort of starting bottom left up to the top right is something that talks about the marketing goals. So what we want to do is we want to make sure that sales and marketing are lockstep, that we understand the goals. We've mutually agreed on what those goals are in terms of leads or MQLs or however you score marketing success. The different colors are denoting different types of campaigns. Very useful to see which campaigns are producing the best types of leads. So in this example, what you've seen is the marketing crew have absolutely blown the doors off it. But that's not the full picture. What we want to make sure there is alignment between marketing and sales and the marketing organization responsible for this dummy set of data are not walking around high fiving one another saying awesome, we're so good. Look how we've blown our goals out of the water. It's good to have blown your goals out of the water. But. But that's not the finished, that's not the end result. We need to take it down a step. The next thing you might do for those of you that run the classic inside sales model where we have marketing producing MQLs, passing those MQLs over to an SDR or BDR team, this is kind of assessing what the BDRs are doing. So in terms of the SLA, the contract between marketing and the BDR group and BDRs by the way can sometimes sit in marketing, sometimes in sales. I've run both. There's merits in both. There's no right answer. But what we want to do is marketing want to know and the leadership of the BDR group want to make sure that they're saying marketing, great job. We're accountable now to taking that ball and catching it and doing things that we said we were going to do. So we'll have an SLA around number of calls we will make, the number of touches we will put into a lead. Like what is our SLA before we say we either convert it to an opportunity or we say no. So you want to highlight what those SLAs are and then you want to monitor and measure those things with a daily cadence. You want to set goals around these things, but you also want to check in to see whether those goals you set were right. Who has a BDR group under their watch? Whose KPI for them? A BDR business development rep, those people who set appointments or SDR sales development reps whose KPI for those guys is measured other than the result, which is meetings opportunities, who has a strict KPI run number of dials? Whose dials is more than 80 whose dials is less than 50. Cool. So you can already see people have different versions of what works for them. So there is no single point of truth here. There is no right answer. To be fair, no one's ever going to get hold of me on the phone, ever. I don't answer my phone, especially if it has no caller id. You're going to get hold of me via email or via LinkedIn message. So you know, if I tell my guys who are trying to sell to guys like me to make 120 dials a day. Well then I'm probably wasting their time. I need to think about blending their activities that is appropriate for them to achieve the results they want. Right. So we want to start thinking and firstly what we do is hypothesize as to what those KPIs should be execute on those and see what the results are and then maybe look at tweaking the dials to see what is the right blend of doing that. So what we're looking at here is a simple graph. Again it's. It's good metrics to track whether it's and you can set whatever metrics you want. But calls, what's your call to connect ratio? What's your connect ratio to meeting scheduled ratio? What is your up sourced from meeting scheduled? So it helps you look at their funnel the BDRs accepting leads and then doing things to convert this into an opportunity. And we want to know if we set them the right KPIs are we driving the right behaviors and are we yielding the results that we hypothesized that we would yield? Similarly, this is very important when it comes to capacity planning. We usually start off with our corporate goals. Don't start off with what is possible. They start off with how much money did we raise. Awesome. So we've got to do like 150% growth this year. Cool. Here's the number. Let's re engineer and architect a plan that gets us there. How many leads do we need? What is our lead accepted? How many calls need to be made on the leads that were given to connect? How many connects conversations do you have to schedule a meeting? How many meetings do we need to have to convert into an opportunity? So I would encourage you to start thinking of top down bottom up. Right. You take the top down corporate number that's being given to you and you re engineer how you're going to get there. And then you've got to look at your human being capacity and your marketing capacity whether they can flow enough leads into the funnel to ultimately get you there and you reconcile in the middle. Now what we often then do is going so if we look at this graph we go like look at that. Awesome. I've done tons of calls. I've spoken to 10 people. Each person's spoken to 10 people a day. They've each booked two meetings a day. We're golden. We're now high fiving one another. So marketing have high fived themselves here and BDRs have high fived themselves here. But what we want to make sure is the yielding pipeline as a result of those efforts is the right kind of pipeline. The blue line here, the kind of light blue line at the top talks about in the red. Sorry, the kind of the bars, the red bars below the line denote out. So what we want to make sure is they're not throwing shit against the wall over the wall. Right. So we want to make sure that we are having a high level of quality control. Because those two previous slides, you might have two departments that are going on spiffs at the end of the month that are celebrating their successes. But when it goes over to the guys carrying a quota, they're realizing the pipeline that these guys are producing for me is just not of a quality that we can do anything with. So you want to look at the net inflow, outflow, not just what's going in keeping the other parts of the organization that kind of trifecta between marketing, BDR and sales, that everybody is holding themselves accountable and keeping themselves honest. This is my favorite. So the next two slides are my favorite. If there was only two metrics that I would ever look at, it would be these. This one and the following one. And that is the sales conversion funnel. I hate the notion of applying a weighting to opportunities based on sales stages. So some people will set up their salesforce instance where they will say if it's a stage one, give it a 10% weighting, if it's a stage two, give it a 15, et cetera, et cetera. That's complete bullshit. It's just completely made up. You should be using empirical data to inform that. And this is what you're seeing here is conversion ratios through the different stages in the funnel. This cannot be a human being made up decision because you will just make bad decisions. If that is the case, you want to look at saying how much do I need at the top? So that I can hit the numbers that I need at the bottom based on actual conversion rates. But this is only one component. Sorry. The other thing that I think is hugely important here is this is so powerful as a coaching tool for individual reps. So powerful. Because what you want to do is say, okay, this is my aggregate across my organization, a 22% conversion rate from stage one all the way through. How does this compare within separate sales groups, perhaps selling different products? So there might be some nuances, so organizationally interesting, but when we want to drive improved performance, we need to take it down a level. So how does different Products align to our sales funnel. How do different teams align to their sales funnel? And then how does an individual rep compare to another individual rep within the same team? And if we see wildly differing conversion ratios, it's an absolute trigger for coaching. So very quickly you can realize if someone is losing most of their opportunities from stage one to two, therefore you worried because they're burning through pipeline. But you might say, well, either the pipeline they're getting is crap, so we need to look at that. But similarly, maybe their ability to tell stories and convince people to come and engage with us through an evaluation phase is where we need development on them. So let's do some sales training, some coaching and mentoring. So very, very informative. Just wondering if you could read the stages. Sure, sure. So they could be anything. But this is qualifying, evaluation, buying process, fulfillment, and deal. These sales stages actually are aligned. Sure. I'll tell you the logic behind the stages and then I'll read them again. What we do here is we talk about a buyer experience, not a selling experience. So we try and map our sales stages to the journey that a buyer is going on. So they're qualifying us to see whether or not they want to keep talking to us. Stage one, stage two. We actually have another stage in our actual. This is kind of dummy data. We have a stage two that's called discovery, which is we're discovering whether or not we can do business together. They're discovering whether or not we're an organization that they could potentially buy from and is this technology that they want to evaluate. So we're evangelizing at this stage the art of the possible. You know, this is what we do. This is our value proposition. They then make a decision to go into an evaluation phase where they start evaluating us. They start evaluating whether or not they actually want to buy, whether or not this is technology or services or products, whatever it is that they want to endorse and put into their business. Once you pass that, you've got someone saying, I'm in, this is my project, or I'm the sponsor. I now need to go through a buying process internally, which is I need T's and C's to be looked at. I need to make sure that commercially we're in good shape, etc. Etc. So I, as your sponsor, have made a decision that I'm in and I want to do this. I'm now trying to get a quorum internally. The next phase would be fulfillment, which is, guys, we're good. T's and C's are agreed, commercials are done. You should receive the order in the next two or three days. So just kind of fairly standard sort of sales stages that you might want to think about. So very, very, very valuable information here. Very, very valuable information to help inform capacity planning, coaching, how many leads you need. But you have to overlay it with this, which is how long does it take? So it depends how you decide to do it. Everyone's different. I like the idea of having a lead, which is usually data. Then I like the idea of something happening, some interaction with your content perhaps, which causes a slight hand raise, which would be a marketing qualified lead. So in other words, marketing have done something to create this. The marketing qualified lead then goes over to perhaps BDR where they have that human interaction. They try and book the meeting. If the meeting is accepted by the salesperson, I would call that then a sales accepted lead. In other words, looks good, I'll take it, thank you very much. I'm going to accept it. And then I do the first meeting and I have the conversation and I'm going to say, you know what, that's now a sales qualified lead. I've had the first conversation, I've qualified it. I'm going to take ownership. It's now my responsibility to try and take them down the journey to turn them into a customer. That makes sense. Yep. So overlaying the conversion rates with sales cycle helps you figure out how much stuff you need at what point in time so you can forecast more accurately. Because our conversion rates might be, I don't know, 90%. That's great. But you might have four sales stages and your sales cycle time might be 12 months. So you're not gonna hit your number this month because, you know, 12 months hence. So what we want to do is overlay time with conversion rates. Very, very important for us to understand. Where are we? Are we in a position? So how much pipeline. Sorry, how much pipeline do I need and where does it need to be for me to hit my number at the right time? So looking at those conversion rates and sales cycle, two very, very important pieces of data. The other thing that we want to start thinking about is are we wasting time on time wasters? All of our guys hate saying checking out of a deal. They hate checking out of a deal. So they are like, I think I'm in. And most salespeople have happy ears. The reason for that is because we get rejected all the time. It's a terrible job. People say no more than they say yes. So they get so depressed for themselves. And when someone says kind of they go, yeah, baby, I'm in. Deal review. So how's that deal looking? Amazing. Absolutely amazing. They said kinda, I'm forecasting it. Oh really? That's awesome. Well, they didn't tell me to get. So this is good news, right? Well, hold on. Let's look at the makeup of that deal. Let's look at the information that you have. Let's do a full inspection of that deal and where we are on that deal to figure out is this the right type of account we should be chasing. Just because somebody who might perhaps not be the type of Persona you want to sell to is maybe helping you educate them, is saying kinda you want to make sure that you're not wasting time on time wasters. Let me give you an example. The best way to quantify the cost of a salesperson, back of an envelope type math. If you have a million dollar quota, you divide that by 12 months, you divide that by four and a half weeks, you divide that by five days, you divide that by eight hours, you get to something like $462 per hour. That's the cost of a salesperson's time per hour. I just did that in my head. I'm joking. I did it five minutes before I came in. So that is about the cost of someone coming at a million dollar target, right? So if it's half a million dollars, it's half of that. And so what you can start thinking about is the value of a salesperson's time. And therefore we want to make sure that they're not wasting time on time wasters. So not only is the quality of the pipeline needs to be inspected, but the quality of the individual deal, their engagement and the human beings that they're engaging with, what the next steps are. So you can help assess and be that critical eye on their business as to whether or not they should really be spending time on those opportunities. And what you're seeing from this, sorry, you probably can't see that what you're saying is at stage one, the deals that are won is the green bar. So the green bars here are the deals that you're successful with. You can see that you sitting in this example data at stage one for less than 10 days and then you shift straight through the final. But the deals that you lose, you spend about 22 and a half days at that time. And the blue line is saying that those are still open opportunities that you're engaging. So arguably the blue and the green line is full of deals that are crap. And your guys should be Going hard for a no to try and qualify them up. Otherwise they're spending so much time on those opportunities when they could be hunting and in richer pools of fish. So again, another overlay piece of data to help make sure that you guys are spending time in the right areas. Another thing that you might want to consider is what are the deals at risk? And you can come up with your own risk metrics. But the way we like to look at it, is this a deal bigger than what you would normally see? So if I'm seeing a deal that is bigger than my average, I'm going, hang on, is this our type of customer? Can we win this type of deal? If the answer is let's do a deal inspection, but I want to know, I want these things to bubble up to me, to the surface. Do a deal inspection and say, guys, let's not waste our time. We're never going to win this deal. This is not our market or we have a real shot at this thing. Let's bring in the cavalry, let's bring in the executive team and let's over invest to win. But let's make sure that we're surfacing that information. Other areas of risk might be, when was the last time you touched them or spoke to them? So if it's camping with no activities logged against a particular opportunity, then you want to be going, hold on a second. Sounds like they're just not that into you. I have this thing within our sales process called, used to be called action and I've called it manner, which is mutually agreed next action. And if the action, the next action is not mutually agreed upon, it's probably not going to happen. So most people don't want to be horrible. So when you say, hey, can I catch up with you next week to see how you're going? They go, sure, give me a call. Hey, does three o' clock on the 15th sound good for you? Sure. Three o' clock on the 15th comes along. You know what, they just went dark on me. It's really weird. Don't know what happened. Well, the action wasn't mutually agreed upon. There was no benefit to the other party for actually saying yes to that. And a clear objective was not communicated and stated. Therefore they're not going to, you know, time is the most important asset we have. And salespeople, their job is to keep asking for more time. And if they cannot demonstrate the value of the time that they're going to ask for, then the person on the other end of the phone is going to say or in the meeting is going to say, no, I'm good, thanks. So what we want to figure out is when was the last touch that we had and how long has it been sitting at a particular stage. So again, if we look at that, what we want to figure out is how do we bubble up those opportunities that have perhaps been sitting at a stage where longer than is the average? And there might be a perfectly plausible reason, therefore, but we want to at least have that information at our fingertips so we can go and inspect it to say, why is this taking longer than normal? And if there's a good reason, fine, carry on. But maybe your sales rep is a little bit stuck or they're just not that into you. Other thing we want to check out is why are we losing? This is really, really good information for sales and marketing to talk about because we can start to maybe engineer marketing campaigns and collateral that talks to the reasons why you're losing. So here we've got timing that sounds like apathy to me. Lost momentum that also sounds like apathy to me. Authority that also sounds like apathy to me. Which means how do we drive momentum, how do we drive urgency so that we don't have those as our loss reasons? How do we get people to start thinking this is stuff we got to do and we got to do it today or tomorrow. So loss analysis, win loss analysis, very, very critical to do as well. And then what we can do is if we take all of that and we use the data science approach and we have tools that allow us to do this, we have an ability to forecast more accurately and with more confidence. We have an ability to start thinking about going into your board meeting or your executive meeting or your Monday morning forecasting call to say, say guys, this is the number I think I'm comfortable delivering based on all the stuff that we've just gone through. Because I had very quick and easy access to the data, to my pipeline, to my win loss ratios, reasons why we've lost the shape of the pipeline, my sales funnel, my sales cycle time. I think I'm good at predicting where we're going to end up. And the results merely take care of themselves. Our job becomes easy. So if we focus on the performance, the results take care of themselves. And we don't live in a results obsessed world and get paralyzed by the obsession over results. So remember, we spoke a little bit about this. This is a day in the life of a data scientist. They're extracting data, they're running it through analytics platforms, creating visualizations. It shouldn't be this hard. I've just showed you a very easy way to do it. By clicking buttons and seeing data at the edge of your fingertips, you really can cheat your way to become a good data scientist. I'm speeding up, so I think I've got one minute left. Five STEP guide Get support. You cannot do this in a silo. If you choose to become more data driven, you want to get support from the rest of your peers within the organization. Going it alone means you will fail. So you want to really talk to the benefits from your peers within the organization and don't just tell them, sell to them. The benefits to individual sales reps are unbelievable. If you give this information to individual sales reps about their business, they become much more sophisticated about what they choose to do and not to do. Set your smart goals, specific, measurable, achievable, realistic and time bound such that you can lock them in, execute against them, and then assess how you achieved. What were the results that yielded from those very specific and time bound goals that you set yourselves? Create a culture of transparency and celebrate it. You know, the amount of people I've spoken to are like, no, no, no, I don't want people knowing about that. I don't want my CEO to know what I'm doing. I don't want other parts of the business to have visibility into the sales part of the business. I mean that is just ludicrous because people are there to help, right? We're all on the same team. And then let's make sure that our one to one reviews with individual reps that all the conversations about driving the business forward are using data to inform those conversations, not just opinion. I mean, it's obvious, right? Data shows data driven teams will perform better. It's not that hard if you know how. You just need the tool to be able to do so if you want to improve. I always swear, but this room is too big for me to get away with it, so I'm not going to. You should just do it. Do it, measure it, assess it, look to improve it and then repeat cycle, that's it.