The 4 key roles of a High Performing Analytics Team ( Webinar Post )

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How to Build a High Performing Analytics Team

Nick Reddin

Published November 27, 2019

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Link to webinar: How to Build A High Performing Analytics Team Webinar

Assembling a new team or department within your organization can be cumbersome and tricky. From reporting to management to roles to talent, all the parts must fit together cohesively and function properly for optimal performance. It can be even more of a challenge when dealing with a complicated business structure, as analytics. Nick Reddin, Vice President at ATC and Jenny Schmidt, Analytics and Human Resources Consultant, break down the steps to ensuring you set your analytics team up for success.

Are you interested in being a speaker on our webinar? Let's chat!


Kelsey Meyer: Hello everybody. Welcome to our webinar on How to Build a High Performing Analytics Team. I have Jenny Schmidt here with us from J Schmidt Consulting. Thank you for joining us and I also have Nick Reddin in here. Can everyone hear me okay? If you cannot hear me, send me a chat. Otherwise, we will go ahead and get started. So I'm going to start the screen share here. All right. We do have a slide deck for everyone today.

So, How to Build a High Performing Analytics Team. Let me tell you a little bit about who we have here. Nick Reddin is our Vice President at ATC here. He has over 25 years of experience in the employment and technology services industries. He has worked with Fortune 500 companies in achieving their workflow and technology goals. He specializes in innovation and disrupting businesses. 

All right. And we have Jenny Schmidt here as our guest, owner of J Schmidt Consulting. She is an HR expert. What she does with her company is she partners with analytics and HR departments to develop analytics talent on individual, team, and organizational levels. She also provides leadership coaching team building for these analytics teams and organizational design consulting, which is something that we're going to start off with today. So glad to have you here. So real fast before we get started, a shameless plug for ATC. So, we are a technology company that works to help our clients bridge the gap in technology and process to help accelerate their growth and allow their companies to scale. So that's really what we do here. Since we are a business solutions company, we are kind of all over the board, which is why this analytics team webinar seemed to be really what our viewers are interested in hearing about. So that's a little shameless plug for us and now I will hand it over to Nick Reddin here to get us going in the webinar. 

Nick Reddin: Great. Thanks Kelsey. So Jenny, I'm really excited to have you here today. We've talked before and it's always been really engaging and really interesting. So I'm excited for this conversation to be shared with our listeners today and others that join later. I think it's a really fascinating topic, and as we discussed even before we started today, this is something that companies are really interested in. It's something that companies are really trying to figure out, and there's not a lot of strategy around it. And so that's why I think I find your niche so fascinating is because I think you're the only person on the planet that has put a strategy around this to help companies really understand how to put together a team that is not only going to make sense for them, but also move them forward in building the right team and then in harnessing their data, if you will. So welcome and with that, I'll let you kind of kick it off with your agenda and start walking us through. 

Jenny Schmidt: Great. Thanks Nick. And thanks to ATC for having me here on the webinar. Yeah, I'm going to cover a couple of different topics today. The first one is just talking about analytics roles and really getting that structure in place. Just kind of from the beginning and then also as the analytics team matures, how does that structure come into play in building that team? And then we'll also go through just some skills and behaviors that analytics leaders or just corporation leaders should focus on as they're building out the analytics talent. And then, specifically, how do we develop talent in this area of analytics, either for specific analytics professionals or just anyone in the organization that has some of this aptitude and wants to provide more service in the area of analytics? 

Nick Reddin: Perfect. 

How do you Retain Analytics Talent?

Jenny Schmidt: So let's start with this topic of career development. Everything that I'm going to talk about really ties back to that. Studies continue to show that career development is the number one attribute that's tied to retaining talent. Employees continually want to know what's next, where can I go, not just what's that first position and what am I doing now. I actually got to participate in a research brief with the International Institute for Analytics earlier this year. And it was about attracting and retaining talent. 

And in our study we found that communication and career development were the top two ways that a company could overcome any deficiencies they might have. So maybe they don't have a company in New York City or in San Francisco, maybe their company doesn't already have an analytics team of a hundred people. What can they do to still attract the talent that they need? And it's all about communicating and being honest about what you do have and what you can offer. And also being able to show that perspective employee that they do have the opportunity to have a career with you, so that's really important. 

Company Culture is Critical to Your Analytics Team

Nick Reddin: So when it comes to hiring, in some ways it's kind of like dating, where looks attract and personality keeps so with companies it's usually salary attracts and culture keeps. Are companies willing to institute the right culture to keep employees? 

Jenny Schmidt: Some are, some aren't, right? Hopefully most are headed down that path because it is about the culture. Employees are looking for that company that can help do good to all of humanity and where they can see themselves in the future. But it ultimately comes down to relationships. How well they get along with their boss and their team, and the leaders have the opportunity to create a culture that will really keep those employees and attract the right talent. 

Nick Reddin: So is it even possible to have, what I would say is a cross cultural dynamic? You've got people nowadays that especially when it comes to retention, if you're going to retain them, right? You have to meet a lot of their, what we would call, felt needs. But some people don't want a cubicle. They are like, I'm never working in a cubicle. There's people that just want to work from home, and then you still have people that want to work in a cubicle. How do companies, and are they willing to address that, especially as it relates to these types of roles, which are so critical for companies nowadays? 

Jenny Schmidt: Yeah. Again, I'm big into strategy, right? It depends on where you're at with your analytics maturity. So if you are starting kind of from the ground up, I would recommend a bias towards having people in the office being able to create that team bonding, if you're farther down on that maturity path and being more open to flexible working, hiring an employee that's at another part of the country and bringing them as a part of your team. And so really aligning it with your strategy as it relates to what you want to get out of that team, how you're going to retain talent, and also where you're at in your maturity of building out that team. 

Nick Reddin: Sure. Well, it makes sense to me, but then again, I'm a Gen X-er so. 

Jenny Schmidt: Yeah. So let's dive in a little bit to that first topic of developing the structure and really identifying those analytics roles. So I'm going to talk a bit about the reporting hierarchy. Where should you put this analytics department, holistically within your company? Talk a little bit about the roles within that team, and then address this issue of career development from a technical career ladder standpoint.

The Reporting Hierarchy: Centralized vs. Decentralized

Jenny Schmidt: So from a reporting standpoint, if I really break it down from a simplistic perspective, one option is to create a centralized analytics team. So, we traditionally have our standard departments that have been around for decades, whether it's accounting, finance, marketing, sales, customer service. Being able to create a truly new department that's not embedded underneath anything else, but reports directly to the CEO, to the leader, and creating that centralized analytics team. This can be really helpful for organizations that are sending the message of how important analytics is to their future. It can also really strengthen the budgetary and visibility that that team starts to have when they're producing output for the rest of the organization. So that centralized model can really work for some organizations in order to jumpstart it. 

Nick Reddin: Is there a preference? I think the bigger the companies go, the more that they probably want that centralized model, but that may not be the case, right? I mean, I guess it depends on the personality of the folks. And is there a preference dynamically one way or the other? 

Jenny Schmidt: Some experts would say that centralized is the way to go, that you're not fully mature in your analytics development unless you have a centralized team. I would beg to differ a little bit. There's also benefits to the next structure that we'll go to which is decentralized. But I do believe that centralized can be very beneficial depending on where you're at. So again, if you need to add visibility to it, if you need to gain some traction, and if you have a need to have cross functional projects. So we tend to get siloed in our organizations. And so as that analytics capability matures, there's often a need for someone to look at it from an enterprise level to say, "How do we actually develop projects that benefit us as an entire company?" And not just in marketing, not just in customer service, not just in operations, but combining all that together. And that centralized team can play that role as well. 

Nick Reddin: Sure. No, that makes sense. 

Jenny Schmidt: So the other structure that is an option is to be more decentralized. Or another term that's often used is federated. And so this would be having an analytics teams embedded in departments that already exist. So within your marketing department, within your IT department, you have an analytics team. So that means there are multiple teams throughout the organization. The federated part comes from an operating structure separate from the org structure or reporting hierarchy that says we as analytics leaders are all going to get together in some type of format, whether it's forming an enterprise leadership council or some type of connection for our recruiting efforts. But that although we report separately, we operate as an analytics function holistically. This method or structure can also include a centralized analytics team that's smaller, but the bulk of the analytics talent is reporting up through the operations, through the respective functions. 

Nick Reddin: So this, in my mind, would be for a pretty large organization and if they're going to break down their teams to this level, unless the teams are pretty small, but typically, I know you'll discuss this as we go, you have to have a certain amount of people for sure to have a true team put together. 

Jenny Schmidt: Yeah. So one way that this structure could be modified over time is you could start with a decentralized structure with having one analytics team underneath one function and the team is three to five people. So that's how you get started down this path. And then as you get going, you might add another team under another function and another team under another function. So it doesn't have to start with a hundred people. It could start with two people and you call it our analytics team that happens to report up to IT or happens to report up to marketing. And then as your analytics capability continues to grow, you just continue to add to the existing teams or add more teams in different functions across the company. So those are two models for how to organize your analytics team. 

Jenny Schmidt: Let's just talk a little bit about that decentralized model and if you have the hub of your analytics reporting to different leaders, how it impacts the focus that they'll have. So if an organization says we are going to have a centralized analytics team, but we want them to report up to the IT space, to our Chief Information Officer, our Chief Technology Officer. My bias perhaps is just to note that the analytics team may lean more towards the data and the tools that it takes in order to make analytics happen because that's kind of the expertise that that department typically brings to the organization. So they're also going to apply that to analytics, making sure that the business intelligence tools that are being used, the data science tools that are being used, and the data structure is ready for analytics and really top notch. If I contrast that, if you will, some organizations choose to have their analytics team report up to the CFO, the accounting finance function. Oftentimes what I see is those analytics leaders are very much focused on the ROI.

Jenny Schmidt: So there's a lot more scrutiny on the projects that they're working on because the projects have to have a defined ROI. What are you getting from the investment of all these people we have doing analytics.? Another option that a lot of organizations choose is to have their analytics report up to their Chief Operating Officer, more of their operations group. Those analytics teams oftentimes focus on productivity, reducing costs, localizing the analytics, self service analytics happens sooner. So the flavor and the strategy of the analytics team just changes depending on where they report to. 

A couple other examples of this analytics reporting to a Chief Marketing Officer is going to focus more on how do we use analytics to gain more customers, gain more sales? This is oftentimes a place that organizations start with when they're building out their analytics team for the first time because there's almost always opportunity to analyze more when it comes to customers and sales. And then from that HR and analytics standpoint, an analytics team reporting up to a Chief HR Officer would focus on engagement and that talent analytics. And then the Chief Analytics Officer is really focused on strategy if they're really reporting up to that CEO. 

How to Blend Personalities for a Cohesive Analytics Team

Nick Reddin: So all of these people, and I've worked for very large organizations, and I've sat in some of these roles in large organizations, and the one thing I know is you've got leaders that are used to making decisions and having things the way that they want it. And you're talking about a lot of different personalities. How do you get them all on the same page? Because what everybody's asking for is all your bubbles lay out very clearly and accurately, is everybody's looking for something different. When I meet with the CFO, you're absolutely correct. They love technology, they love what we're going to do for them. But if we can't help them understand where the ROI is going to come from, we're never going to get anywhere. And we know that, and they know that. But everybody's got a different opinion. How do you get, or are you able to even get, everybody on the same page so that they're all moving forward in the same direction? 

Jenny Schmidt: Yeah. And that's where these operating models come into place. So the reporting structure may stay the same, but it's being able to come together over an overall mission. So it really needs to tie with the overall business strategy of where are we at, where are we focusing over the next three to five years? What is our company trying to achieve? So if you're entering into a new market, if you're increasing market share, if you're focused on increasing your profitability, really giving everybody around how we can support that overall enterprise goal and everybody has a different piece of it, while, at the same time, supporting their individual department goals. 

Nick Reddin: Yeah, because my assumption and what I know is that when you're building an analytics team for any of these folks, these are not inexpensive people to bring together. And these are talented individuals as well. And they've got their own demands, they've got their own ideas for things. And so you've got a lot of personalities and a lot of demands on both sides of the house, seemingly, that have to be met. 

Jenny Schmidt: Yes, for sure. And it's a matter of understanding everybody's different objectives and being able to come together in synergy over the overall mission of the company. How we can work together. So that hopefully gives a little bit of just a baseline when it comes to that structure or where to place your analytics organization holistically. 

The Four Key Roles of an Analytics Team

Jenny Schmidt: If we dig to the next level of who makes up this analytics team, here are four different roles that I commonly see on analytics teams as they continue to mature and grow. So to the point earlier, if you have a team of three people, I wouldn't expect to see all these roles. But if you have about 50 analytics people in your organization, you might start to see the development of some of these. So we'll take a minute and just at a high level, go through what these different analytics roles are. 

The first one is a data scientist and there's a lot of debate on when somebody can be called the data scientist or not. What I work with clients to define really shapes around the box of obviously using data to draw insights, but specifically using statistics. So, for me, if you're not using statistics, maybe not technically a data scientist and also being able to do some programming. So it's really that combination that would do that outline framework of saying that's a data scientist position. Business intelligence really works on descriptive analytics. So it's also using data, also being able to draw insights, but it's really focused on using that technology to tell a story. And being able to help many people across the organization to be able to understand the data that they have, that's in a useful and relevant way to the questions that they're trying to get answered. So that business intelligence department or individual can really help bring that to the table. 

An analytics translator is oftentimes not a dedicated role until you're pretty far in your maturity and have a fairly large analytics team. And that position, I equate it to a business analyst in it. So their job is to implement analytics projects in order to solve those business problems. So they translate the needs of a particular business unit and say, "I think analytics can solve that for you. Let me go back to my analytics team, work on some initiatives, and some potential projects that can help solve that problem." They have to have a strong amount or a large amount of business acumen and really understand the business problems, but also understand data and what's possible with it and really connect those two things together. And the last one there is the data wrangler. People oftentimes chuckle at that title. You do see it if you go out to right now and type in data wrangler and you'll see some positions posted for that. It's a term that's really specialized within the data field, a position that is specific to organizing data for the use of analytics. There are a lot of different ways that data needs to get organized and managed. This particular position is a part of the analytics team and is specific to getting the data ready for that analytics professional. 

Nick Reddin: So if I'm a small company, if I'm a mid-sized company, and every company has data no matter what size they are, they've all got data of some sort that they're trying to make sense of, and I can't afford these four people. Is there a role or is there a particular position that I should start off with to say, "Hey, I'm assuming there's not a one size fits all person, but where should I start? And with that one person that's going to help get me on my journey?" 

Jenny Schmidt: Yeah. Business intelligence seems to be a great starting point with the understanding that that position is also going to be doing some analytics, translating work, and some data wrangling work, and perhaps some data science work. But that's a great place to start for organizations that just don't have the ability to have large teams is hiring that business intelligence professional who will work closely with it, assuming that the IT department is continuing to do all they can to get that data clean and ready. 

Nick Reddin: And then I'm assuming, and of course it's based on your slide, that the hierarchy is, the data scientist is kind of like the architect and control, or is that not how it works? 

Jenny Schmidt: I wouldn't quite say it that way. They're just different specialties. So the data scientist has that statistics background and is going to work a little bit more in the predictive space. But that business intelligence professional, that's great with creating visualizations and telling stories, that can be just as valuable to an organization. So I wouldn't necessarily put one above the other. There are some pay differences as far as salary, but both can be extremely important to the company. 

So as you're building out this team, regardless of how big it is, keeping in mind again that importance of career development, this topic of technical career ladder often comes into play and technical professionals like data scientists or business intelligence, they want to know what is my next step. And there oftentimes is two options. They can continue down the technical path or they can go into management. 

The management one is one that is always around. You can become some type of supervisor or leader in the organization. The difficulty can be finding the individual that wants to go down that path. And so as an analytics leader, it's important to work with that employee that you see has potential and really allow them to see themselves in the possibility of being a manager someday. Oftentimes they have the skills and they just don't realize it. Also, there's a fear if they go down the management path, they won't get to do the fun stuff anymore, and they won't actually get to continue to build models and dashboards. But oftentimes analytics leaders are still doing technical work. So it's not like you're going completely away from it. 

Nick Reddin: Sure. How good are companies that you're working with at creating career paths? I've dealt with a lot of companies. I've heard, I can't tell you how many companies talk about career pathing and then when you really press them on it, none of them really do it well. Is it really something that companies are wanting to do? I know you obviously think it's important and most people in the working world would absolutely agree with you 1 million percent as I do. But are companies really putting it into practice? 

Jenny Schmidt: Well, like most things, I think it varies. Again, the studies show that career development is still a number one attribute to retaining employees. And so it's just a matter of leaders prioritizing that. I think, oftentimes, the reason why it's not done is because it's hard. It takes time. And what analytics leader wants to spend their time doing a job description and figuring it all out. But yeah, my bias would be that it's important to prioritize it. It's not something you're going to do continuously for years. 

Take a short amount of time and really figure out that structure of how your jobs line up and providing that technical path, which allows someone, they don't want to become a manager, to still advance in their career at your organization and really being able to show them what their career options are and have clear expectations. Not everyone is going to become a principal data scientist. 

You're probably not going to have 10 principal data scientists at your organization. Maybe you'll only have one, so not everyone can get there. But being able to show those different options. Oftentimes it's leading analytics, going to work for a business unit, gaining that business acumen, doing some very analytical work within a business unit, and then coming back to that analytics team. In particular, millennials, that younger generation, they're more open to those latter on roles. They want to learn, they want to get experiences, and being able to show someone how they can have that technical path even outside of your particular analytics department can really help retain that employee and let them know that you value the skills that they bring. 

Nick Reddin: Sure. Now millennials also take a hit on wanting to move up the chain pretty quick. Are companies prepared for that, or is that a reality, or is that more of just a generalization of that generation? 

Jenny Schmidt: Yeah, my personal opinion is it's always going to be that you can put a millennial mark on that. But when I was out of college, they said the same thing, right? Most people in their twenties are excited to take on the world, and so it's just managing those expectations of what is possible, because you never know what somebody can do, but also being realistic if you're probably not going to get promoted three times in the next three years. That's just not the way we work at our companies. So being able to balance both of those. 

Nick Reddin: Now, my generation did skip that. Initially they said Gen X-ers were slackers and then they realized and relabeled us by realizing we just want to do things our own way and not the old way.

Jenny Schmidt: Yeah. Again, kind of an attribute of youth is I don't want to listen to the people before me. I want to figure it out and there's got to be a better way. So that's a little bit of information just about structuring your organization for success.

Four Skill Roles to Fulfill When Building Your Team

Jenny Schmidt: Now let's dig into the people side of things if you will. You've got your talent. You've got your team assembled. Now how do we focus on building their skills and knowledge, and also what behaviors we want to reinforce and then really creating a cohesive team. So from a skills and knowledge perspective, here's a framework I use when I work with clients. It's really outlining four different skill areas to focus on building up within your team. At the top there you can see business knowledge. Ideally you're going to hire people that have five years of experience within your industry or within your company. 

It's hard to do that all the time. And so anytime you have an individual or a team that's lacking that. Really coming up with ways that they can continue to learn about your company, learn about your industry, and really increase that business knowledge, it is key to being able to develop high value analytics products. 

The visualization leans more towards that business intelligence side of really being able to use those tools like Tableau, like Power BI, like ClickView, and use that tool to the point where you're actually providing value in telling that story and answering the questions that business needs answered. 

The statistics and modeling is where that data science position comes into play, and understanding what you are requiring of your entire analytics team when it comes to the math part of it and the modeling part of it. And also again, tying that with what tools they should use, whether it's Python or R Shiny or SPSS. And then, of course, data is the root of it all, so constantly providing opportunities for your team to increase their knowledge of data, their skill sets, and working with data and programming if that's a part of their role. 

Nick Reddin: So when it comes to the skills and knowledge, this is of course the critical piece and it relates back to the human that's going to take the job. How patient should companies be as they're trying to build their team and finding that right mix of your recommendation or their culture fit? It seems like everyone knows there's not enough talent out there, so people are going from slot A at Company A to slot A at Company B. How does that fit into the picture with them? Are they willing to be patient or what's the gist of or feeling that they're going through with all this? 

Jenny Schmidt: Sure. I am not a professional recruiter, but when I talk with my colleagues that are professional recruiters, they almost always say they wished managers were more patient and more open. It's really hard to find that unicorn candidate that has everything. And so really being willing to say, what can I teach? What can I develop and be a little bit more flexible with taking that individual that doesn't have everything. However, it is worth it sometimes to be patient to find the right person. Because if you have a whole team of folks that don't have the skill set, then you're in trouble. You do need someone that can mentor them and that can lead the way. One example of that is just regarding this topic of tools. So I meet analytics leaders that say I have learned to be more open about the experience someone has in a particular tool that we use. 

In other words being more tool agnostic because I know I can teach them the tool. I can send them to the classes, I can have them learn that pretty easily. So I'm going to be more open if they don't particularly have that background. Or the same with the business acumen if they haven't worked in my industry before. But I know they've got great skills. I can teach them the industry, I can teach them the acronyms, it will take some time. But being open to what particular area you feel comfortable being more flexible on and teaching what's to get on board. 

Nick Reddin: Gotcha. And folks, just to take a pause here, if you have any questions, you can submit those questions at any time to us and then we'll look at them at the end of the presentation. 

What Behaviors Should Your Company Seek in Analytics Employees?

Jenny Schmidt: So we've got that kind of framework for the skills and knowledge we needed from the team. I am a strong supporter of it's not just the technical skills, but it's also the behaviors and that really to me is the differentiator. If you will, table stakes is being able to have the technical chops. It's how you interact with your colleagues that makes all the difference. 

And so here are five different areas that I recommend analytics leaders look at as there is taking initiative, curiosity, applicability, being an influencer and being adaptable. The nature of an analytics team is that it is constantly changing, oftentimes they are charting new territory if it's not figured out already. And so hiring people and really encouraging that adaptability and flexibility and also that curiosity. Where else can we go? How else can we do this? And even curiosity of the data. Why is it that way? Where was this? Why did this exception happen? 

And then oftentimes analytics leaders find folks that are good in a couple of those areas, but struggle with the applicability. You can build the best dashboard or the best model. If the person that you're building it for doesn't actually start using it, then the value isn't there. And so instilling in your organization the importance of what we build is going to be applied, that we're user friendly, we're customer focused, and that we're actually solving the business problem that we're being asked to, people use what we develop and it's applicable to that business case. 

Nick Reddin: Well, it seems like in my head, I think of these folks and I think straight linear thinkers, they're not creative thinkers, but in these attributes that you have here in these behaviors, it looks like, honestly, they need to be both. So can they just be a linear thinker or can they just be a creative thinker? I mean, it is rare to usually find somebody, especially in the technology field, that is both equally well, or even 70/30. 

Jenny Schmidt: Yeah, I see what you're saying and how they can be against each other. You're one or the other. I actually believe everyone has a sense of curiosity. It's just a matter of what they're curious about. Oftentimes they're curious about why the data is structured that way. How can we make it better? What is that exception? So it's channeling what they're naturally curious about into the business goals and the alignment for what we need there. So I do think it's possible to have that linear thinker and that curiosity is finding what they're naturally curious about, connecting that up with their work. 

Nick Reddin: So if you look at these boxes and you look again at these attributes that are there and can you pick two out of those and have a good hire or do you have to have three out of those? Or is there a fall off point or a point of diminishing returns if they don't check enough of these boxes? 

Jenny Schmidt: Yeah, I think it depends on where you're at with your team. You're not going to find someone that's strong in all five of these areas, but if you already have someone that's really good at innovating and thinking of the next new thing and how else can you break this or what else can we do? Then it's balancing that maybe with someone that's really good in the applicability and had that stronger business acumen. So for me it's all about the team and having a team that ultimately has all of these strengths. And then, we'll talk about here in a few minutes, and then with each individual, helping them to build on those strengths and also fill in any gaps that they might have, an area that they're not as good at. 

Nick Reddin: Perfect. 

Jenny Schmidt: So we've talked about the skills, behaviors, and I just was talking about the team and so it's also important to really focus on how do we as a team continue to gel.

What is Insights Discovery?

Jenny Schmidt: I happen to teach classes using a tool called Insights Discovery and it uses a simple four color model that helps people really understand themselves and then others. It's all about why do I act the way I do and why do they act the way they do? And we can sometimes have a bias to say all analytics professionals are, if you will, linear, analytical, very much in that box and this particular model, it would be considered a cool move type of persona. 

In reality, what I have found is that any team, including an analytics team, works best with their balance. When people have the ability to bring out other parts of their personality, whether it's the creative, curiosity piece in this model that's represented by the color of sunshine yellow, or it's that sense of urgency in completing tasks to get it done on time that is the fiery red or the green, really focusing on the customer and the user and what matters to them and how we can make it better for them. So being able to, even though it's an analytics team and they are very detailed and linear, having that balanced persona within the team. 

Nick Reddin: So when I look at this and I think, okay, so to have a perfectly balanced team, I need one person to be red, one person to be blue, one person to be green, one person to be yellow. Because if I have too much red, that's going to be too hard to manage. So, I know that's probably not accurate, but is that kind of how people look at this when you're explaining it to the hiring managers or to companies? 

Jenny Schmidt: Yeah, that's the flavor. So once you've got your team on board, just being able to really understand who's bringing what to the table, oftentimes we're not just one persona. We're very complicated people and we can tap into different parts of our personality. So maybe it's a mix of that person that has that analytical ability, but also has a drive to get things done and really being clear on what strengths they bring to the team and allowing them to do that. So it's a challenge to get all four colors, evening the representative, but it's important to understand where your team actually lies and how you're compensating for any gaps they may have. 

Jenny Schmidt: Just the last section that we're going to cover today is actually developing that talent so that individual person on your team, and it starts with really creating the culture overall and then providing those opportunities, and ultimately customizing it using an individual development plan. 

How to Develop Analytics Talent

Jenny Schmidt: So if we start with that learning culture, analytic professionals love to learn and as a leader like we talked about earlier, the importance of training and culture that will retain that talent is trying different strategies, having multiple tactics to be able to allow them to learn. Depending on the size of your organization, it could be creating an internal community of practice. It could be really focusing on virtual communication and how we connect to people across the organization, allowing people to go to conferences or attend the online training. There is so much material out there for people to do self learning. 

Again, back to that tool agnostic, a topic we were talking about earlier. People can learn on their own online very easily. It's just a matter of a budget and giving them the opportunity to do that. And say we're going to allow you guys some time to just innovate and bring out that curiosity. Or we're going to partner with our local university and allow you time to do some research and really dig into some trending topics. 

Nick Reddin: So if you show this to a company, and I look at this and I'm a part of the head of the company here and I look at that and I go that's a lot of pressure to have to be able to arrange all these things or make all these things available to people when at the end of the day we have a job we need them to do. Is that a common thread or do companies get it and go, this is something we're trying to do anyway, so it fits right in? 

Jenny Schmidt: I hope it fits right in. It's not intended to be overwhelming. And this is just a list, right? It's picking what does your organization need? What does your team need at this point in time? And oftentimes it is making the decision to say, "I'm going to invest in my people. People really are the biggest asset of my company, and I'm going to carve off some budget dollars to allow them to go to a conference." There might be some kind of rules tied with that when you come back and you present to the team what you've learned, to really be able to enhance the ROI. But setting aside time and setting aside budget and really believing and putting your actions with that belief that says, "My people are my greatest asset." That hopefully isn't overwhelming. I believe that's where all managers and leaders should be.

Nick Reddin: Yeah, I don't disagree.

Jenny Schmidt: So we've got that overall culture. Now it's a matter of how do we actually get to provide opportunities for each member of our team. So again, here's a list of ideas I am a strong proponent of. It's the combination of technical skills and people skills that they should be focusing on as you're developing that talent. It could be identifying a mentor for them, either in your organization or if your analytics team isn't large yet, finding a mentor in the community. 

Someone else that maybe is that principal data scientist or has been in business intelligence for years that can mentor one employee or your small team. I am a coach. I work one on one with analytics professionals to help on that, but the people side of the equation and so that can be a really big benefit either for a first time supervisor, for someone that you really want to retain, or just an individual on your team that's got the technical chops but is still needing to work a little bit more on the relationship and communication part of the job. 

Then not just connecting them up with the right person, but once they've gotten to that conference or once they've done that online training, give them that opportunity to present their findings. Just show their expertise and you're giving them projects to apply what they learned. People get really excited about the opportunity to learn. Then they're like, I want some data to actually apply it to. And the best way to learn is to teach. And so perhaps for some of them, give them an opportunity to mentor others. Maybe that's an intern or a new college graduate. Being able to partner up and really grow each other. 

Nick Reddin: Yeah, I think this is a great slide and agree with everything you've got on it. I think mentors are incredibly important. The best managers I've had were mentors and what made them good, and not all of them were good, what made them really good is when they really believe in you. And even if they're being hard on you, it's coming from a place where they're trying to challenge you and grow you beyond your current comfort level, whatever that may be. And that can be hard to find. 

I mean, even when you ask people about what teacher made a difference in your life going to school, most people can only name one teacher. And I'm one of those. I can remember one teacher that ever really made a difference in my school curriculum years back in the day. And it was an English teacher and her name was Mrs. Yate, and I still remember it to this day because she made such an impact on me at that time. But it's a rarity to find good mentors. Are companies working more towards trying to help their people understand what it even means to be a mentor and what that looks like? 

Jenny Schmidt: It varies. Obviously going back to that learning culture, that development culture. Again, I hope so, but it is more rare and oftentimes, especially in this new field called analytics, you say I don't know who would be a mentor for my new analytics team or my professional because they're charting new waters. You don't have anybody that's been there before. And oftentimes a mentor can be the person that has the business acumen, really understands the industry or maybe someone in that it space that has the data. And I'm a big proponent of trying out mentors. If we can people up and say try this for a couple of months and if it doesn't work, no hard feelings, we'll walk away and try again and find another mentor. 

Because it is a little tricky to find that right match. And so believing that you can do it on the first go probably isn't realistic. You got to give it a shot. And again, being willing to hook them up with the right person and you keep trying until you find that right person. 

As we just kind of wrap up the slide portion of today's presentation, it's really about being serious about the development of that and putting it down on paper, putting together an individualized development plan that lists here are the particular development opportunities for you. 

I'm a big proponent of going beyond your just going to go to a conference in 2020, and we'll call that a development opportunity. But really getting serious about those skills, that knowledge or the behaviors that you want to see changed over the next 12 months. And really working through what are some ways that we can give you opportunities, whether projects or presentations or connecting you up with the right people to develop that particular focus area over the next year. 

And also that development plan can talk about what are some potential career paths. You know, I want you to work on this skill because I see you have potential to be a manager someday or I think you have potential to becoming a senior in our organization, and yet this is a skill gap that still exists. Really be honest about the potential you see, but also understanding their aspirations. Again, not everybody wants to go climb ladders. Some people want to really move around and experience a few areas of the company and just want to provide value. And my biggest guidance to leaders on this topic is don't make any promises because things constantly change. So being able to balance that ability to show promise, to see what potential you see and that individual, but not promise that they're going to get a particular promotion or raise or next step within a certain period of time. 

Nick Reddin: I can see where that piece in particular can be difficult because if you've got a development plan that says if I do X, Y, Z, I get a corner office and a raise. And so I check all those boxes and now you're telling me now's not the time. It can be pretty deflating among other things, right? 

Jenny Schmidt: Yes. It's a delicate balance and oftentimes in order to get to that next level, it's not just one, two or three things that are easy. There are hard skills and knowledge that you need to develop to get to that next level. And so just continually having it be a focus of where learning and growing and not making any promises, this is not an actual checkbox. If you do one, two and three, you will get it. It will set you up for being a more likely best candidate when it comes time to interview for that job. 

Nick Reddin: And I like having plans. I think plans are incredibly important. I remember reading in the Harvard Business Review that people who write things down and then refer back to them frequently are 85% more likely to hit their goals as opposed to people that just write them down. January 1st, I'm going to lose 10 pounds and then never looked back at it again as I'm going to the buffet. So I think writing things down, staying on track, referring back to them and then making it a part of your internal culture. I think that's really important. 

But back to your other points was not everybody wants to go into management, and I think it's really rare, in some senses, when you find people that kind of know where they fit. I think it was in the 70s, there was a book called "The Peter "Principle," where people kept getting promoted based on their competencies and their success in the different roles. But then they got to a point where they were no longer effective and efficient and ended up getting fired, so they were promoted past their capabilities because they didn't realize where they really fit. Do you think people are self aware enough to kind of know like, hey, this is really where I fit, this is what I want to do, or does everybody just want to be that manager and have a different idea in their head? 

Jenny Schmidt: I think in the analytics space there's a lot more people that don't want to be the manager. They love the technical part. They want to continue to learn the technical chops and to be able to be on the cutting edge of what's happening in that space. It's actually harder to find people that want to go manage the people so that self awareness is really high. I would say most of us are still exploring how we fit, so yes, I know I don't want to be a manager, but then what? What is the expertise path that I can don't go down without dragging myself into a corner or into a pigeon hole where I only have one set of expertise? 

And an example of that would be in the space of business intelligence visualization. So someone that has become a Tableau expert and really spent years developing their expertise in that tool. That's great. It's really helpful. But it can limit them if the company decides to switch to a different tool or if they're looking at going to another company to continue their development. They have only learned one tool. So just as an example of kind of that balance between building your expertise but also looking if your specialty is telling stories and doing digitalization, how do you continue to maybe even on your own, continue to play around with some other tools and continue your running beyond just that one niche? 

Nick Reddin: Sure, that makes complete sense. So we're at the end here and we're going to go and move over to the Q&A section. We've got a few questions coming in. If you do have a question, feel free to submit it over. And then Kelsey is going to read those to us. So Kelsey, we're going to hand it back to you for the Q&A section. 

Kelsey Meyer: Okay. So we do have a Q&A here sent in by an anonymous attendee. Thank you.

Is There a Future Analytics Career Path?

Kelsey Meyer: Machine learning, AI are growing exponentially. At the same time, most business platforms offer extensive analytic tools that are constantly improving.  As the analytics become more and more available to individual business users is there really a career, a future career path for analytics? 

Nick Reddin: So that's a great question. This is a hot topic with a lot of folks because you've got platforms out there like H2O, you've got DataRobot, and you've got Skymind. And a lot of people are wondering, can this be a profession that will ultimately be automated? I'll let Jenny tie into this, but in my mind it's not and for a lot of reasons. One of the reasons being what Jenny talked about is being creative. I don't think computers are ever going to get to a point where they can bring that creative part into it. 

Jenny Schmidt: Yeah, I would completely agree. You know, if you think about an ERP system or in the HR world an HRIS system, the standard system is great, but man, you always want to customize it to your particular needs in your particular business. And the same is true in analytics. There are some amazing technological advances that can really help your organization where you don't have to create a whole team yourself. You can utilize that technology and yet that's not enough. Having that expertise within your organization that really understands your customers, your operations, and can identify how can we leverage this field of analytics to set us up for our future, to be able to be the company we're going to need to be in 5 to 10 years from now. You need the boots on the ground. You need the person that can actually understand how do we utilize the tools that are to best benefit us. 

Nick Reddin: Yeah. I've noticed with a lot of those platforms that I named, they have a lot of amazing automations built into them and they've got a lot of casual experts that have helped build these from the ground up. They still need people to run them. They still need people to make sense of it because as I've seen them, and I've seen companies implement them, they're still having us come in on one side and help still make sense of it for them. So while the data is there, the algorithms are there, the AI is there, if you will, they still need help making sense of it. And I don't know that that's really going to change either anytime soon. At least I think it'd be years and years before any of that would even get to the point of being cognitive. But even then, it's not creative. 

Jenny Schmidt: Yeah. It's this constant evolution of I've taken this data and I've gotten an insight from it. After six months of looking at that dashboard or report, you're like, okay, but now I have five more questions and it always leads to the next thing. 

Nick Reddin: Exactly. And what is valuable to me today to your point, on my report and on my dashboard and on my data today is going to change tomorrow if we acquire a company, if we get acquired, if we take on two new lines of business, if things are just constantly in flux. 

Jenny Schmidt: Yup. And then you need that specialist there to help guide the organization as to how to take advantage of that.

Nick Reddin: A lot of these are even based on historical data, but a lot of historical data is bad. That's one of the biggest problems. I mean, if you're using historical data for predictive analytics, you're basically going to be repeating the past forever, which is not always a good thing. 

Jenny Schmidt: Yeah. And again, that's where that curiosity comes into play. What other external data can we acquire? Whether purchase or towards, there's a lot of public data out there. It's a combination of the data sources. What you have and what's available that can really unleash the potential. 

Nick Reddin: Yeah, absolutely. Great question. 

Kelsey Meyer: Yeah, that was a good question. So there's another question that's somewhat related. So which soft skill is most important if you have limited team members or just one particular employee? So, Nick did ask the question earlier about technical skills and not one individual. So what is the soft skill that would really make the difference? I have a feeling it would be the curious, curiosity... 

Jenny Schmidt: Yeah, actually again, you know, the standard HR answer, it depends on again, what that employee has for strengths already and what you're looking for in that analytics department. Applicability is pretty huge, but if that's already established in your culture and the expectations, it might be, I want you to have initiative. I want you to be able to figure things out without me telling you. Hey, go look at this data to find this. Go look at this data and see what you can find. So a mix of that curiosity and an initiative can be really important if you've only got a small number of people on board. And that's where you are at with your maturity is finding that kind of go getter might be more important than how applicable it is because it just generates ideas and get some excitement going. So it depends on where you're at. But focusing in on one can be really helpful if we're going to really work on developing this skill over the next couple months because that's what we need right now in our evolution in our company.

Are There Other Careers That Transition Easily Into Analytics?

Kelsey Meyer: Great. So are there other positions that transition into a position for this type of team? So we know that the environment is there's a very low unemployment rate and it's hard to find great candidates, so do you find that it's like, for example, in marketing, sales people tend to transition into marketing really easily. Have you found any trends of people who transition into these types of roles easily from another industry or expertise? 

Jenny Schmidt: Sure. So from a generic standpoint, anyone that has curiosity with data and analysis. So I have an accounting background. So I would say your accountants already are analyzing data. They've been analyzing data for decades. There are a lot of positions, pricing analysts and marketing analysts, you probably already have analysts somewhere in your organization. Same thing with the IT area. There's some really strong data skill sets. A few people that come up through that IT career. I was just counseling with a client recently and they were asking the same question like, "How do we develop our talent strategy as far as finding the talent?" 

I said I would be willing to bet if you have at least 50 employees, somebody has already heard of analytics and outside of their full-time job, they're already thinking about going to get a Master's degree or certificate. They're already doing online training. So it's asking the question, hey, we're getting ready to launch our new analytics team. Ask your employees, does anybody have any interest in this area? Because if somebody has an interest in it, they're going to do whatever it takes to learn what they need to learn. So that's a little bit more of a generic response, but it really is just asking people, hey if you have interest in transitioning to this area that can be a great places to start. 

Kelsey Meyer: Great. So, the last question here, I am just curious here, this is mine. How do people get started working with you? So we looked at it from the candidate perspective, we looked at it from a management perspective, and now from a business perspective, how would people find you, what specific challenges would they have and in which case you are the answer or the answer to their prayers? 

Jenny Schmidt: I appreciate that question Kelsey. My information is there up on the screen. You're welcome to email me or check out my website. I am located here in Des Moines, Iowa. So I run a local networking group. it's the Des Moines Data and Analytics Meetup. You can find me there in person as well if you want to check me out first before reaching out. 

I really help that analytics' leader to think through a strategy and develop a plan for how to develop their talent, either from that organization design standpoint, where should the department report to, how should the makeup be or even the tactical stuff that Nick mentioned. Who actually puts together the plan or does the career path, I can help with that. You're overloaded with work. I can come in and write that job description, partner with you to do the heavy lifting on that or to be able to come up with that individualized development plan for that individual. 

Now for those that wanted it into the analytics space, or maybe you are the analytics person at your company and you're like, I wish I had a mentor. I do coaching one-on-one and really helping either from a career path or just a personal development. How do I actually work on that skill of getting my voice heard, of making sure people know that I exist and what I can bring to the table? So people are welcome to reach out to me and just inquire about the coaching services I have as well if they're interested in getting into this space or being able to develop their skills. 

Nick Reddin: So you just breezed by your meetup, and your meetup is probably the most prolific I've ever seen. You've got an unbelievable amount of members and you probably get the highest attendance of any meetup I've ever seen, which is impressive. And what that tells me is content is good, leadership is good, organization is good, and that all comes back to you. So it's pretty impressive. So well done there. 

Jenny Schmidt: Thank you Nick. Yeah, we're not stopping here. We've got a board meeting coming up here in December and we're going to look at 2020 and beyond. And it's really about the Des Moines community. There is a talent shortage and so how can we come together to provide opportunities to our companies and to those that are in this space to put someone on the map. We're doing some great things here. And how do we continue to show that analytics is one of them? 

Nick Reddin: Yeah, no, that's great. And then on our side of the house, for any companies, if you're looking to stand up a business intelligence unit and get your reporting under control, we would love to help you with that and a lot of other technical aspects that we bring to the table as well. Jenny, I want to thank you for being a guest with us today. It was really good. I thought the conversation was great. I appreciate your knowledge and your helping us here today. 

Next Steps?

Analytics is such a complex and fascinating topic, we just touched on a small part of it. During future webinars we will cover other aspects in greater detail now that you know how to build up your analytics team.

If you have any questions or would like to start a conversation with us, reach out to Nick Reddin and ATC directly here, or you can tune in to our upcoming webinars.

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