September 23, 2022
Ryan Buick
Ryan Buick

Defining the role of Biz Ops and its future in data with Yazan El-Baba at Emergence Capital

Welcome to the Canvas podcast, where we bring on business and data leaders to talk about how to make data easier for everyone. Today, I am super excited to have Yaz El Baba from Emergence Capital on the show.

Tell us about yourself!

Yeah. Thanks so much, Ryan, for having me on. Quick background on me. So I’ve been at Emergence for three years now.  And before that, I was over at LinkedIn where I held two roles. The first was in Biz Ops.  And I worked across all types of teams there. So I worked on the GTM side as well as the Product side and actually transitioned during my time there over to the Corporate Development group.

So doing all things, mergers and acquisitions and strategic venture investing. And before that, I was at the greatest public university in the world called the University of Michigan (Go Blue!).   But a lot of people ask me, “How’d you end up in a Biz Ops role right out of school?”

Honestly, I just stumbled into it. I didn't know anything about consulting or banking. I went to business school, but I didn't really want to do an investment banking job or a consulting job. My time at Michigan was mainly spent boxing on the team there and that's all I really cared about. And then when I found out I wasn't good enough to be Floyd Mayweather, I decided to get a real job.  I ended up stumbling into tech. I fell in love with the cloud and cloud software, which sounds silly, but I really was just enamored by it and studied it quite a bit.

I spent a summer at Microsoft, so I listened to everything Satya Nadella said about the cloud-first, mobile-first world and got hooked and ended up moving out to Silicon valley.

Tell us a little bit about the work that you're doing now at Emergence. What do you specialize in? What do you look for?

So Emergence is, I would say, different from most early-stage venture capital firms.
So the quick history of us as we've been around for 20 years. Our very first investment was in a small company at the time called Salesforce.  And we've since stayed really laser-focused on the space in which Salesforce really trailblazed being enterprise software. And so we've continued to stay solely focused on B2B software as a category.

And we tend to be thematic in a bunch of different areas within B2B software. And obviously, the landscape has evolved quite a bit in the last 20 years across different business models and across different types of products, but that's where we tend to stay focused. And the other way in which we are focused is despite the successes we've had as a firm, being the largest investors in companies like Zoom, Doximity, and Veva, we've decided to keep the fund size small.

So we're a team of 10 on the investment team today. And we make six investments per year with six partners. So on average, each partner makes one investment per partner per year. So it's a very highly concentrated conviction style of investing. We like to say that we make commitments, not bets.

So it's really in the trenches rolling up our sleeves, helping with organizational planning, hiring, and some strategic thinking when it comes to the work we do.

What drew you to VC in the first place?

Yeah. It wasn't being at Michigan. I'll tell you that much.  There wasn't much of an early stage of the venture scene. It wasn't until I moved to Silicon Valley that I really got exposed to this world and, and understood what's happening within the startup ecosystem.

I'd say the awakening moment for me when I realized that this was just in my opinion, the coolest job in the world was that  I found that I was being more proactive as an early stage thinker than reactive as a later stage thinker. And what I mean by that is when I was on the corporate development side, doing things like M&A and corporate strategic venture investing, you were reacting to what was interesting and exciting at the moment.

So I remember while I was on  LinkedIn's corporate development team, we were strategic investors in companies like Salesloft, Gong, and G2 Crowd. And these were in their larger growth stage rounds further along in their journey.

And I remember looking at the early-stage investors that took a stance on this space years prior. And one of which was Emergence, who played in either. Each of those companies is at least a competitor in the categories that they played in. And there was published content around why we think the world is moving in this direction five years prior to all the growth stage investors coming in.

And so when I thought about what excites me, it was more about how can I be proactive about what's going to matter in the future. And now I have to scramble to make a play, which is the name of the game. It's these high-risk appetite founders build in a category once they've crossed the chasm between what is pre-product market fit to product market fit, they prove out a new category.

Then it's time for a larger company, like LinkedIn to make a play. And while that is interesting work, I was more interested in predicting what was going to matter. This is going to be the way people work in the future.

Yeah, I think it's definitely a lot more interesting to play on this side in trying to. You know, you said it's not the best of its commitments, but there is a huge element of being creative and trying to think about, you know, where the market's going and, and how that informs your investment strategy.

But in reality, I found out that I learned more from my losses than anything else. And so in a space where you're constantly challenging yourself and taking a stance on something and trying to support it and being comfortable with the fact that you could be wrong, but so long as you, you dared to try something new and think in any way.

So we got connected through your post on Biz Ops. Can you explain what Biz Ops is and talk about your time in that role at LinkedIn?

Biz Ops is such an ominous topic. So many people aren't familiar with what an actual Biz Ops role is, which is why it could be misinterpreted by those hiring for the position and those that have to work with people within that position.

And so, because of all the ambiguity and the wide spectrum of things that you see, people don't really know how to wrap their heads around the role. So I think it's a great question. The way I think about Biz Ops is, “How do you bring someone into an organization that is data-first and can roll up for sleeves, executes when need be, and have an unbiased opinion on what's taking place within the organization?"

Oftentimes as you move earlier within an org, they become the connective tissue between parts of the organization that may not speak with one another or may be incentivized in different ways. So Biz Ops really is the trusted thought partner to make unbiased decisions based on data and analytics.

What are the different types of Biz Ops roles that you see?

Yeah, I really think there are three core buckets and obviously, there are some that sit somewhat between them.

So it's not very clean buckets and there could be a spectrum along them. But the three main categories that I think of are. First off the embedded Bizos model, which I was very familiar with. And I'll touch on that a little more in a second here. Then there are the incubation Biz Ops teams - think of these as a function before a function like Sales even exists at an org.

The thinking is, “Let's hire someone that's a little more on the generalist side, but can pick up the function and start doing sales.”

And then on the very opposite end of the spectrum, there are the internal consulting Biz Ops teams. Think about Google, when you get to such a massive scale, you have people that you'd otherwise hire at like a consulting firm, like a McKinsey or Accenture or so forth that end up in-house and are full-time employees that aren't necessarily nestled within an organization, nor are they picking up the phone, like an incubation Biz Ops team, but they offer like strategic recommendations similar to how a consulting firm would operate.

So those are the three core buckets.  As far as LinkedIn goes, the model that I'm most familiar with is what's called the embedded Biz Ops team. And what I mean by that is most organizations are aligned by functional group and by business line. So when you get to a certain scale of a company, you're going to have multiple business lines and you're gonna have your Sales, Marketing, and Product leadership.

Obviously, there are more, but those are three core groups in the org. And so for me, in particular, when I worked on a Biz Ops team for an extended period of time, I would be aligned to both the functional group on one axis, as well as the business line.

So at LinkedIn, our largest business line was LinkedIn Talent Solutions, which was our recruiter tool, the jobs marketplace, and so on and so forth.  And I was aligned with Sales. So my business partner, the person that I embedded myself within his organization, was the Head of LinkedIn Talent Solutions Sales for the region that I was focused on.

And so the types of projects I worked on were very pertinent to what he was working on.  As the leader of that group. And so you could see every different permutation for each different business line, as well as being someone supporting the product organization. And so I, in my time at LinkedIn actually spent time between sales and marketing, as well as products being embedded within those teams.

The types of work actually varied quite a bit. You can imagine being on the GTM side for an enterprise business, you're thinking through like SFDC objects. Thinking through things like Salesforce records, account information, and organization records.

But on the product side, you're dealing with multiple billions of worth of data points on how people are interacting and engaging with the product and informing very different types of decisions for the product organization. So that's how the embedded type of team works. That's how it worked at LinkedIn.

What are the prerequisites or conditions that should trigger the need to hire Biz Ops?

So the incubation Biz Ops team tends to be the most popular for startup leaders. Sometimes it has different names than Biz Ops with slightly different flavors of the work that that person is doing. I often find that the Bizos person and an incubation style often do a lot of things like a Chief of Staff does.

But the things that need to be in place for an incubation Biz Ops seem to be successful is really like first and foremost, that you have access to data. First and foremost, do you actually have a product?

If you don't have a product to sell and you don't really have a sales motion in place, what's this person actually going to do? And so you're not gonna hire this person to go and just figure that out.

You have data, but you’re just aimlessly running towards it. So you hire someone within an incubation Biz Ops role when you have a product in place that is in a market that is selling and is going through a growth period. And the second piece is that you actually at least have the base layer of a data stack in place such that that person can actually go and access and utilize that.

I tell some of our founders that are like, yeah, “I wanna hire a Biz Ops person to help our data-driven decision making.”

But you have to give them things that will give them insight to some of the analytics that you do. Those are, there are two very important things like, “Where are you as a business?” And some people are at this stage as a seed stage company. Some aren't even here until they're a Series B company.

So it's not about what round of funding you have. It's not about employee headcount. Do you have a product that's in the market? That's selling with people actively engaging in a product. Do you have data to leverage and do you have a place in which you can actually start working with that data and it doesn't have to be perfect?

It doesn’t have to be like you have the most comprehensive data stack. I actually think this second iteration of what a Biz Ops person looks like. They can have quite a bit of impact on how to actually staff up your Data team. They might not be the ones that actually go and build the data pipelines, but are and input into the things that actually matter and help set up that infrastructure for what should be tracked within an org. But those are the two main things that I think are really critical for these teams to be successful.

What conditions make it right to start thinking about having the second type of Biz Ops teams you mentioned - incubation teams?

Incubation Biz Ops teams are the best when you don't have a strong Head or VP or within a functional area in place.

Because again, like the name suggests you're incubating like the early workings of these things and these types of Biz Ops people. You have to have a higher bar for these types of people. And they have exposure to some of these things. Like you're not going to just hire some person two years out of consulting to go be an incubation Biz Ops person when you don't have some of these leaders in place.

So the bar for an incubation Biz Ops person is higher just in terms of relevant domain knowledge necessary to get these things off the ground, despite them not being the full-time person to lead Sales or to lead Marketing. So, that's the number one thing. And then when you transition to the embedded Biz Ops team, it's when you have those people in place.

You really need to anchor towards people that understand and appreciate the value of data and having a thought partner that can make use of that data.

Because then you have this controversy where you have someone that doesn't really value the insights that this person is bringing, and it ends up being more of a contentious relationship between the two people where you have some Head of Sales or Head of Marketing that doesn't really care about the data and wants to just go run and do these things.

Or you don't have this person to actually support some of the decisions like, “Maybe we should sell this at this price point”, or “Maybe we should refine who our ICP is based on the data we're seeing in the market on closed won rates or conversion through pipeline.”

So there are these little nuances where it's important that the Head really appreciates and understands data. They don't necessarily have to be the person that goes and pulls the data, but they have to have worked with strong analytical leaders in the past and want that to help steer their ship within their functional area.

They need to be able to interface with the Execs and the Founders, but they also need to be the ones wrangling the Salesforce objects on a day-to-day basis. So it's, you have to live in these two pretty different worlds and you have dotted lines.

And so I think overall, the arc of Sales leaders and Marketing leaders at these stages is trending towards being data-driven. I don't think there's a lot of, you know, sort of gunslingers that are, that are left, but it, it definitely creates a bit of a sticky situation if there isn't alignment there if they're not open to, you know, listening to feedback and trying to see the data as a guide.

How do you define success for Biz Ops?

Yeah, it's a really good question because it's one of those roles where again, to put it harshly, you're more of a cost center than you are directly aligned to shipping products or selling products.

In my eyes, the successful Biz Ops person does two things. They give the executive team more clarity on how the business is operating and understand where they need to push and where they need to pull. And so I think when it comes to how you measure that, it's really just talking to the CEO, talking to the rest of the C-Suite and understanding, like, do you feel more comfortable?

Do you feel as if you have a better grasp of how the business is performing? That's first and foremost, and the second is really accelerating making decisions. This is a really funny point because when Biz Ops is implemented incorrectly, you end up running into analysis paralysis and they end up being blockers.

You have these entrepreneurs that are like, “I wanna run fast, I wanna do things. I wanna break things.” And so they say, “If you introduce Biz Ops, you're introducing more overhead into our decision-making process.” That's actually what failure looks like. Some of the more negative comments around Biz Ops are, “Someone's gonna come in and start introducing an OKR framework so that people have like a new spreadsheet or thing to fill out.” That is absolutely not the role of Biz Ops.

Nor should it ever be because A) people aren't going to like you very much and B) you're slowing things down. So, what does success look like? It's actually accelerating decision-making by giving people the ammunition to make decisions with a little more confidence without perfect information.

You'll never have perfect data, but it's moving slightly away from just purely gut-based decision making and substantiating that with some analytics to make you feel more confident in the decisions as a functional leader you're making and as an executive team to have more confidence around how the whole ship is steering in the right direction.

One example of this success vs failure state, especially for product-led growth businesses is pricing. “How do I price it self-serve? Do I add a free tier? Do I do a trial? What do I price the self-serve module for? And then when I go to teams and enterprise, how do we set the pricing module for that's something that?”

Biz ops can come in and help in the early days if you don't have enough money to go hire consultants. You're definitely not going to hire a pricing person. And then like who owns that decision? Is it Sales? They're the ones that have to sell the product. Is it Marketing? They're the ones that own the landing page for what the pricing modules look like.

Is it Product because they're the ones that are gaining certain features? Everyone has an influence on the decision of how to price. And obviously, the final decision maker is the CEO. It's the executive team, but who is the one that gathers data and input from all of those people and comes up with the recommendation for how we should price the product.

That's when you need that arbiter. And how do you measure success for that initiative? Well, now you actually have something that's pretty quantitative. If a person comes in and says, “This is how volume is going to be impacted, this is what conversion is gonna look like, and this is what the ACV is going to be.”

And we expect these material changes based on some of the work that we've done. Let's run a test and see how that works. It'll be successful if the things you predict to happen end up happening. If it’s not successful, is that Biz Ops's fault?

Not necessarily, but at least like having what the predictions aren't having, everyone aligns on those things. It gives you some visibility into, “Hey, we didn't just switch something for the sake of switching it. We're putting some real robust thinking into this decision.”

Why is Biz Ops so controversial? What is the stigma today and how do we change that?

The real stigma is just around what role does Biz Ops play? And I think you hear two main pushbacks. One is that it introduces too much overhead. These people are getting us to do things and getting in our way as opposed to giving us some extra jet fuel.

And so the question becomes, “How can you structure your Bizos role in a way such that the person is assisting in helping and driving things forward as an accelerant versus a blocker?” Think of it as like a, like a hall monitor, like no one likes the hall monitor it's telling on people that are moving in the halls, right?

Especially when they're running to try to get things done instead of this person helping them get to the place that they need to get to. And so that's that one thing. The second is, “How do you actually hire the right people for these roles?” I think the main reason this is becoming more and more of a topic today, and why I wrote that post, to begin with, is that there is a new breed of people that exists. Long gone are the days when the first job you do for the first couple of years out of college is consulting.

More and more people are going into the tech industry and more and more people are getting their training for the first two to five years of their career learning at a place like Plaid, Stripe, or Ramp, which just launched a Biz Ops rotational program. There are so many of these places where you can learn in really high-growth, stressful environments with different business models.

These are the things people are doing at 24-25 years old. So now you have a new breed of people that will eventually want to move to the startup side. And this is a great crash course for them on how to run a business. And so there's, there's actually mutual benefits for both sides.

Those that are hiring for really smart people that understand. In the last decade, everyone said don't hire generalists for your startups. And what I would challenge is saying they're not just generalists anymore.

I wanted to be hesitant in using the word specialist because these people have more than just a general skill set.

What do you think about the evolution of data tools for Biz Ops?

Well, I think first and foremost it enabled this role earlier on. This wasn't possible before the modern data stack, because it was almost impossible to find an early-stage company with that sophisticated of a data stack.

We hired a Biz Ops person at one of our companies post-Series A and the amount of data that she had access to and was able to work with was unbelievable. And it absolutely helped the company steer the ship far more effectively, and you can talk to the CEO and he raves about that hire because they have the data in place.

And so first, first and foremost it is, it's now possible to leverage that data, but then going a little further, when it comes to what tools are now necessary, like what does the modern data stack enable beyond just it being possible? Well, now you have people that aren't technical but they can do lightweight things like build data pipelines. Working with Airflow has become easier than ever.

And more and more people are building this as a skill set. So 10 years ago, people were on Wall St. doing Excel. They're now learning things like workflow executions and tools like Airflow and they're learning basic SQL for things like transforming data and they're understanding how to work with data more than ever.

I took an Excel course, but I also took a SQL course and a Python course. And these skill sets are just becoming far more commonplace. And now tools within the modern data stack are being built around it to just lower that friction and lower that barrier, such that even those simplest programming languages and data analytics, languages are, are available to more and more people. You see dbt’s rise because it's a simple SQL interface, allowing people to write transforms as Business Analysts, not just Data Scientists, and you’re seeing more WYSIWYG interfaces.

Any other tools that you see Biz Ops teams using?

Honestly, I think this is the opportunity. I think Canvas is an example of one that's providing data access to things like your spreadsheets, making it easier to work with and giving you a place that becomes both your working space and the destination that you're working with, but there aren't many solutions.

What you find mostly are a hacked-together set of solutions like your traditional BI tools. So when I was in a Biz Ops role, I was working very closely with Tableau. We had an internal BI tool at LinkedIn. We had a bunch of internal workflow execution tools, but there hasn't been a perfect tool that caters to a Business Analyst or Biz Ops persona.

How can people learn more about you and EmCap?

Our website is emcap.com. We publish a lot of our thoughts on emerging trends and what we think the future of work for the enterprise is going to look like.

You can find me on LinkedIn and Twitter.

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