Expert Insight Series - BI Strategies for PE Portco Acceleration with Marty Moore of Tenex Capital Management

Click here to watch the video on YouTube.
Read the companion article: Tenex Capital: How Private Equity Uses Data to Improve Portfolio Operations

In today's podcast, Jon interviews Marty Moore of Tenex Capital Management (private equity) as part of our ongoing Expert Insight Series. They discuss private equity's use of advanced data analytics to improve portfolio company operations.

Blue Margin helps private equity owned and mid-market companies organize their data into dashboards to execute on strategy and create a culture of accountability. We call it The Dashboard Effect, the title of our book and podcast. 

 Visit Blue Margin's library of additional BI resources here.

For a free, downloadable copy of our book, The Dashboard Effect, click here, or buy a hardcopy or Kindle version on Amazon.

#BI #businessintelligence #reporting #dashboard #datawarehouse #PE #portco

Transcript

Jon Thompson: 0:05

Audience, welcome to our Blue Margin Expert Insights Series. Glad you joined us. This series was developed for the benefit of mid market executives and private equity partners who are looking to use data intelligence to create a culture of accountability around growth and profitability, and thereby increase the value of their companies. Today we're talking with Marty Moore. Marty is an operating advisor for Tenex Capital Management, an operationally focused PE firm investing in mid market companies. Founded in 1999, in New York, Tenex has over 3 billion in assets under management across commercial services, energy, healthcare, retail and IT sectors. Tenex acquires control positions in companies and emphasizes operational improvement to drive portfolio companies' performance. And apropos to our conversation, Tenex uses data analytics as an ingredient to their success. Before Tenex, Marty spent a decade in digital marketing and analytics at pharma company Loeb Enterprises, the startup Blink Health and AI service provider IP Soft. He joined Tenex almost four years ago and was tasked with building operational systems in portfolio companies using technology. As a BI firm, we were impressed with Marty's advanced use of data analytics. And we're also excited for our conversation today. Welcome, Marty. And thank you for joining us.

Marty Moore: 1:32

Thanks for having me.

Jon Thompson: 1:33

Yeah. So Tenex is unique in that your firm focuses heavily on cultural and operational change more than things like financial engineering. Tell us about your team, your unique approach, you could even touch on this thing, The Tenex Effect, whatever would be helpful for us to understand the firm a little better.

Marty Moore: 1:52

So the Tenex team is born out of operational improvement. The leaders believe very strongly that if we improve the operations at the ground level, the financial impact will follow down the road. That said the PE firm is sort of split, we're sort of a hybrid team of half investors, half operators. And the investment team does what your typical PE firm investment team does, it builds out a pipeline and negotiates deals. Our team builds out initiatives with the strengths of their operators in mind. So of the operators, I work with the data team, and we love to bring automation practices and best practices around their data up to speed, up to competitive levels and even beyond to be able to advance their capabilities, for when we part from the investment.

Jon Thompson: 3:05

That makes sense. So your your firm is made up of a much higher ratio of operating partners to deal team than the typical, is that reasonable?

Marty Moore: 3:16

I would guess, I don't know, per se, but I would guess yep.

Jon Thompson: 3:20

Yeah. Okay. And your focus is on data, has been for a long time. Are you seeing a lot of impact from the work you do around data? Has it been a significant competitive advantage? To be able to apply that to companies in a more complete comprehensive, I guess, cutting edge way?

Marty Moore: 3:38

Yeah, absolutely. We've seen a dramatic improvement. When we build what we call a data driven culture, managing towards the exception, bringing data to the forefront for employees to be able to see take ownership of and improve on a daily level, for a weekly level to meet the goals of the month, to beat the goals of the year. We've seen improvement in terms of the sort of lowest common denominator and being able to change the data, to accentuate some of the other projects that are being done by other operators, whether it be in the warehouse, whether it be in the finance department, or wherever that might be. So we have parallel projects going, where data analytics is meant to really drive the initiatives that have been set, by the investment team.

Jon Thompson: 4:36

Yeah, so it touches all operating areas of a company. If you don't mind, I'd like to just go down that vein for a second. So you mentioned that data driven culture and people taking ownership of the numbers that they're accountable for, to paraphrase. Do you ever find resistance to people adopting data as a way to run their company? Similarly, how do you get that ownership to take hold?

Marty Moore: 5:01

Yeah, absolutely. And I think it's sort of something to expect when you have a person who's been doing a job for a period of time, to come in and tell them that they haven't been doing it right is kind of the wrong approach. You want to come in and ask the for their insights, ask them for their feedback and build together. Pretty early on set that standard to develop a partnership rather than a sweeping overhaul. If a sweeping over overhaul is needed, that person still has the insights and understands some level of data that we will we will need in the process to understand it. So at no point do I try to avoid that resistance. I take that in stride, and want to work through it with the person so that eventually we can try to win them over?

Jon Thompson: 5:55

Yeah, so I'm guessing that came through school of hard knocks. I imagine you tried it the other way of being more dictatorial top down, what do you find to be the case when when that approach is taken?

Marty Moore: 6:07

When that when that approach is taken, you end up not getting the answers as quickly as you want them down the road. In parlance, we say,"Where all the dead bodies are." Where the data doesn't necessarily align, can be a real rabbit hole in in different ways. Missing the personnel that know where that data exists, and how to either get around it or improve it is ends up being very, very important for us. So where that resistance lies, it's always important to tackle it front and center.

Jon Thompson: 6:48

Yeah, so I appreciate that. So do you collaborate with them, both asking them, "What data do you need to see," and also steering them in the right direction to fit with the value creation plan? Or is it more just, "Tell me what you need to see, we'll put that together?"

Marty Moore: 7:04

A little bit both. It's a little bit of taste, of appetite, for the person that you're working with. What ends up happening a lot of times is we're asking people to do more work in their day to support our project. You're asking someone to work an eight hour day and then "Okay, but can be add an ninth hour so you can help me advance my project?" You want to get them on your side so that they're wanting to do a little bit of work for you to get that project moving, and so that they can feel some level of commitment to it and and work with it. So that they know it can improve their day to day business. I wouldn't say that, you know, every person steps into a conference room and has the same reaction. So its coming upon us to sort of read that reaction to understand it a bit better.

Jon Thompson: 8:06

Yeah, okay, we're aligned on that we have nothing to argue about there, we found the same thing. If you if you dictate, that doesn't work, if you just ordered take, that produces marginal results as well, you've got to collaborate. It's a team effort. It's positioned to help them succeed in their work. And you want their input because they are the subject matter expert. So that's great. Does that sum up how you approach it?

Marty Moore: 8:30

More or less, each different projects where it comes in different waves. A lot of times we'll have an operating adviser on the ground who's been there for maybe for a year or so. So we'll come in, and we'll be able to work much more closely with that person. We don't need to build the relationship, it's already sort of built. Other times we're going cold, and you have to build those relationships.

Jon Thompson: 8:53

One more question, do you typically put one of your operating partners on the ground for an extended period? Is that almost standard?

Marty Moore: 9:01

It depends upon the portfolio company. Honestly, if if it's struggling in different capacities, if there are initiatives that call for personnel to be on the ground, then yes, I think that would be the case. For other companies that are swimming high afloat, I don't think it's as much.

Jon Thompson: 9:25

Yeah. Okay. That's great. I appreciate that. So, Marty, data analytics technologies have developed rapidly alongside what's an explosion in data that's being produced in business. How should leaders think about using their growing amounts of data to improve business outcomes? How do they first of all wrangle all this data and and what's the role of data in helping them to improve operations and outcomes generally?

Marty Moore: 9:51

Sure. So I'll come back to the notion of building a data driven culture managing by exception rather than managing by overhead. The notion of building goals ends up being a big deal for us. A number of the portfolio companies that I've worked with have goals, but they're at the highest level. They're not broken down to the day to day breakdown that allows an employee to be super focused on their performance, whatever that task might be. If they can break down the tasks to a very common denominator, and we can build goals around them, and we can automate them, that's a huge step forward in terms of building this notion of a data driven culture. Then, the minority becomes decisions made without the use of data support. That's sort of the goal for everything that we do, we tend to focus on different departments at different times. But overwhelmingly, if we're looking at a company, we want to make sure that most every decision, most every review level, should be supported by some level of data.

Jon Thompson: 11:07

So a big emphasis on this distributed communication using data as opposed to just the top down.

Marty Moore: 11:14

Yeah, absolutely. We want to make sure that an employee feels that they can see... not just that they feel it, that they can see it on the walls or in the reports... that their contribution, their sale is helping that number get pushed up on the team level so that your manager can relay that to the CEO and ends up getting closer to a sales goal for the entire company. That's an example of one that's sort of the entire trickle down effect of the reporting structure we're trying to put in place.

Jon Thompson: 11:53

Yeah, again, we're in alignment, there are no arguments. How long does that take you typically at a company to get where all of the key roles have some sort of visibility into their metrics on a regular real time easy, accessible bases?

Marty Moore: 12:12

I'm sorry to keep answering "It depends upon the portfolios," but sometimes it does. We try to work with six to 12 week sprints. The first go at it took a lot longer, because we were trying different things. And that was about four years ago. And we were finding our stride, so to speak. Now we're at a place where we have templates available, we have a tech stack that we feel somewhat comfortable with being able to absorb different integrations, different connect API connections and whatnot. That we can move a little bit faster. So I would say the mean, or the average, would be roughly around 15 to 20 weeks.

Jon Thompson: 13:03

Okay. And, not all PE firms, their operating or portfolio support teams or resource teams, have such an emphasis on data and enough resources to really execute in a comprehensive way at the portfolio companies. What's your argument for bringing that in house versus working with consultants as most do?

Marty Moore: 13:28

The argument for bringing it in house from the PE standpoint is that we can then look to standardize across portfolio companies. The dream has always been to apply the same sort of reporting structure that we have each of the portfolio companies up to the PE level, so that, you know, our CEO can just swipe his phone and show them the latest data for each one. Still working towards that. But in terms of bringing consultants, it makes sense where you only have a certain amount of capacity on the ground that we can't necessarily gain traction with. Or like I said, they're too busy throughout the day to be able to provide us some time and help.

Jon Thompson: 14:21

What size is your team, how many FTE equivalents that are really dedicated to instilling these data systems at your portfolio companies.

Marty Moore: 14:31

So our team is spread across a number of different portfolio companies. So my data team at the moment is five or six, and we touch roughly thirteen companies I would guess. I myself am on three at the moment. So we each sort of carve out our own time and work with each other very closely... we have the sort of startup mentality using slack and being able to instant message each other very easily across portfolios to share learnings and share strengths

Jon Thompson: 15:11

So would you recommend to other PE firms to and weaknesses. develop a data team or work with consultants? Are you guys particularly oriented or equipped to do this data work internally? Or is it something you recommend broadly?

Marty Moore: 15:25

Yeah we feel comfortable with our structure that we can take on lots of different projects. But we'll be very clear about projects that we aren't capable of, or at least we don't have the bandwidth at the moment for. Something like an entire CRM replacement, we could stop what we're doing and really focus on it, but that would require that we stop over what we're doing. So certain specialized events, we certainly will say, "Lets bringing some some level of expert." But for most of what we're we're trying to accomplish, we're pretty well equipped.

Jon Thompson: 16:09

Yeah, great. And then thinking about the standardized reporting across the portfolio, that's something we hear from virtually all of our PE partners, "We want a standardized approach, we want economies of scale." That's part of being a PE firm. The challenge there, of course, is that every company, even if they're in the same industry, are distinctly different and unique. Different maturity level technology wise, different culture, different processes, etc. And most PE firms have multiple industries, or certainly a lot of sectors within an industry. How do you think about normalized or standardized reporting, given all those variables?

Marty Moore: 16:49

We have our templates. And the way I think about a template is starting a brainstorm with a template. Bringing them into view of some personnel at a portfolio company who don't understand what we're meant to bring to the table, we can tell them what the timeline is to spin up this template that speaks to sales pipeline and wins, or something to that effect. "Tell us what you would do differently about it. Where does your mind go when you see this? Where are the pitfalls? Where are this certain specific strengths? And also tell us what your audience is going to be? Are we going to be giving this to the employees, is it's going to remain only in upper management is there's going to a third party of some kind?" That ends up being very helpful in the initial mock up phase.

Jon Thompson: 17:46

Yeah, so you start with templates, I assume you're improving those all the time. And that becomes a standard approach for discovery. It gives them more than a blank page where they're still trying to figure out who you are and what you're trying to do, it gives us something tangible to look at. I assume also, there are some standard metrics across companies and industries, depending on how high you're willing to go. You could standardize there. And then as it goes further into the organization, operationally, you can have a similar look and feel so that an executive or a partner of the PE firm can look across the companies and it's familiar, but it's going to be different dimensions and facts from one company to the next. Is that what you guys are working towards ultimately, when you mentioned the person just flipping through on their phone?

Marty Moore: 18:31

Yeah, absolutely. In my interviewing period, someone that I interviewed with said, "Here's my phone and look at this app. It's an airliner, and it's advertising San Francisco, how do they know that I want to go to San Francisco? That's where I want to get with my portfolio companies." And I said, "No, no you don't. You understand that, yes, that is something that you want to put in place, but the arsenal of engineers that you're going to need to employ, the time and the effort is not going to pay off the way that you want your investment to necessarily go." So it's important to note what the upper limits are, when we go through some of those processes, and it's important to know what you can do and what you've done and be able to demonstrate some level of work product to get confidence in those initial kickoffs.

Jon Thompson: 19:30

Yeah, we're certainly looking at the whole picture. I mean, you can do anything with technology, presumably. And you might want the moon, but it's really that desire is a function of the benefit that you get, versus the cost. And so you have to look at that. You know, "Nice to haves" that cost millions, maybe don't make the cut. So are there any emerging technologies in this data realm that you see as potential disruptors in the context of data analytics and business? And what steps might leaders take to prepare themselves or to position themselves well for upcoming?

Marty Moore: 20:08

Yeah, in terms of advancements, I gave some thought to this. And, you know, I just signed up for YouTube TV, and I'm just absolutely kicking myself for not doing it sooner. What they're doing to the Netflix, Amazon Prime, streaming space is really very interesting to me, it's so, my wife kind of laughs at me, I'm almost more attentive in the commercials to understand what's going on there, and how they're structuring their live TV feeds. I see that as something that's gonna impact dramatically. I've always thought that there's more analytics to be had behind TV, which is still a massive facets, market leader in the marketing space. I think blockchain is being seen to be very successful, and it's going to work its way down to users. In the future, it's gonna become much easier to understand and put in play in terms of protections. And then data analytics itself, Internet of Things, has shown levels of promise, even though it's slower than people want it to be. Smart devices and the like, are very much top of mind. In terms of data practices, and in terms of implementing some of those concepts in the business, my only advice to a CEO or leadership would be to adapt to the current structures and build that notion that you will always need to be adapting in the future into your regular practices. Just know that tech should take a space on the budget every year, and pay attention to the new trends. Don't fall behind too dramatically. Too many portfolio companies that I've met, haven't really invested in tech in an X number of years. And so you find yourself in need to play catch up, because you haven't really been adapting with the times.

Jon Thompson: 22:36

Yeah, just to touch on one of those, there was a company that pitched our company on marketing through TV, digital TV, and claimed that they could segment our audience to a specific title for specific industries in a specific geography. And serve up to them advertisements, as they're watching YouTube TV or whatever, that would hit the mark, as far as the demographic target that we're after. Have you used any of those or looked at those in your portfolio?

Marty Moore: 23:10

I haven't, we haven't really had any need in my walk. But at a point in my career, I worked for a very wealthy person who just sort of said carte blanche, "Bring ideas to the table, and we'll see if we can put something to market." And I was really hyper focused on this notion that analytics around computers were just wildly stronger than analytics on TV. So as TVs and computers continue to merge closer and closer, and the smart TVs become available, there's quite a lot more data you should be able to work with.

Jon Thompson: 23:47

Yeah. So here at Blue Margin, we're proponents of an agile methodology for project management. I know many of your Tenex partners are black belts in that methodology. Can you give us your perspective on using an agile approach when working with portcos?

Marty Moore: 24:05

Absolutely. Some of the most productive times of my life have been working in startup methodology, that the Agile structure of weekly or daily stand ups, specifically, really in tech, where I think Agile is the strongest, being able to develop large projects by splitting them down into into very minor tasks, and touching base on the development of the tasks and the prioritization of the tasks, and therin. We do try to implement that, not just in tech projects, but also in management levels as well. One of my bosses speaks very vehemently about the notion of meetings, not broadcasts. We want these meetings to be interactive, specifically citing data, so we have to build the data to support that meeting beforehand. Everybody gets the data beforehand. Everybody knows if we're managing towards exceptions. We already know what we're gonna start talking about in the meeting. So every everybody has some level of preparation, prior to the meeting. The notion of Agile has sort of flourished amongst Tenex, because everyone can see the continuous development of work brings value and helps to support all the different projects that are going on.

Jon Thompson: 25:41

Is that something you instill across the portfolio? Is that almost ubiquitous there?

Marty Moore: 25:45

No. It's really project by project basis.

Jon Thompson: 25:49

Okay. Yeah, that makes sense. Just broadly thinking about the private equity business model, and what you need to do to invest in companies and increase their value and exit from them and so on. I know, we've touched on this in many ways, but how do you view the role of data intelligence, ie dashboards, business intelligence, etc? What role does that play in best practices for successfully executing on that PE model? How important is it and what are some of the high level impacts that you've seen?

Marty Moore: 26:27

From a high level, it ends up being pretty important. But as you take a step back and look at each individual, and as a group, you start to see some trends that we've sort of employed. In almost every circumstance, we're tightening the belts on KPI. We're putting brighter lights on more important KPI and we're sort of, not archiving, but pulling back the secondary tertiary KPI to make clear that our end goal is to be able to tell the whole story of a company's performance on a wall of monitors. Right we should be able to walk across the watercooler and be able to see exactly how everyone is doing. I've had salespeople pacing behind me in excitement, knowing that the operations team is going to be held to the same standard as the sales team, because you come in with this notion that the sales team is blaming the ops team, the ops team is playing in the sales team, for various different things. So we break down the silos within the business structures. And we leave that as an operational best practice, we say that, "This is better to be able to show clearly what everybody standard is being held to." We try to define the completed state before we start our scope. We try to work with the teams to understand what the definition of done is, we have 11 steps to building a dashboard. So we just load up JIRA as a project management tool with the 11 steps across however many dashboards we need to do. We implement recurring reviews. So building towards that concept of managing towards the exception. But we also want to make sure that we give a high five to high performers, and try to coach the lesser performers through what's happening on the dashboards. So those are some of the best practices that we try to implement when we walk in the door. When we walk out the door, we certainly want to take away understandings of how we can improve them and how we can sort of flex different things in different ways.

Jon Thompson: 28:59

Have you come up with a good approach when you are no longer taking the lead on developing data infrastructure, data systems, and helping them become data driven... When you back out of that have you got a good methodology for them to carry on not just hold it together, but continue to advance it? Have you ever run into challenges with that transition?

Marty Moore: 29:21

We try to hire, insofar as it makes sense to, we don't want to be perpetually managing a specific portfolio. We certainly want to make sure we build the documentation in a way that we can pass it on should we part ways with the portfolio company. And what we end up seeing is the portfolio companies that we work with end up being very, I would venture to say a grateful, for our leadership in the search for a candidate who can not just handle the analytics, but is excited by the foundation that we built for him or her. We very much sell it as, "Okay, here's a modern stack, and here are all the opportunities that you have in front of you to be able to build further. And we will be right there hand in hand, if you want to go into predictive analytics and you want to go into internet of things, if you want to go into some of these newer concepts. All yours, all guns forward for it." But that's more or less kind of how we've structured our approach.

Jon Thompson: 30:38

Do you help them or get familiar with your best practices? Do you encourage them to continue to follow those, or just hire the right person who's got a good methodology and let them do their approach?

Marty Moore: 30:50

In my personal experience, I've made clear that I'm open to whatever perspective that they have on best practices. But while we're working together, we already have the structures put in place let's continue these rather than overhaul everything. That depends upon the level of the employee coming in, but for the most part, we've just carried on our structures.

Jon Thompson: 31:19

Yeah, have you had enough companies exit where you've been able to implement fairly robust data intelligence, infrastructure, and systems, where you could say if it's had an impact on the exit, on valuation, on differentiation among other companies for sale in their sector, those sorts of

Marty Moore: 31:40

I've been with the group for four and a half years, things? coming up on my fifth year. We've had two or three exits that we can point to and say absolutely. In terms of the actual valuation because it hits so many different projects, it's more of a concept than a hardline number that we should say. But there's certainly data points that we can put together that can show improvement, dramatic improvement, where something like customer service has changed dramatically, missed shipments. So customers are getting their, their packages on time at a clip that's 20% or 30% better than it used to be. You can start to build values around that. But it's a little less than sturdy, in terms of a hard number.

Jon Thompson: 32:37

And you can tell that value story more successfully, more effectively, when you've got good data systems in place?

Marty Moore: 32:45

Absolutely.

Jon Thompson: 32:45

You could pull that out of any company and still tell that same story at exit.

Marty Moore: 32:50

Absolutely. What we try to employ is, "Okay, we're putting together a dashboard, let's put together a separate dashboard that is just chart over time. And we're going to mark the day that the dashboard goes live. And we'll just let it live. And we're going to see how that that impacts that KPI that we're really trying to impact." That's one of the standards that we are still trying to employ. But that at the end of the day provides us with a plethora of charts to choose from, with regard to the impact.

Jon Thompson: 33:29

Yeah, just sort of a background monitor that has a very distinct day marked when you started. I love that, that's a great idea. Well, this has been incredibly helpful. What's next on the horizon from you? I know you've had significant life change recently in moving, one of the top five stressors according to psychologists. How's that going? And what's next for you?

Marty Moore: 33:50

The move is going great. Thanks for asking. It's been a nice change. We tagged summer to not move to Arizona, wait until the fall months, and we're now here and enjoying it. For me, what's become clear in my career is that I really enjoy the impact that I have on personnel at either portfolio company or within the organization at the PE firm. I'm going to continue to work towards advancing the automation capabilities at portfolio companies. ESG continues to be a concept that we're trying to impact via automation. And for me personally, I want to continue to have some level of impact on that, in that capacity. So, things are moving in the right direction. We feel that that PE is kind of in this cultural change period where data analytics is such a growth in terms of the capacity, or I should say the investment theory and whatnot. We're trying to merge together, the strengths of tech, the strengths of finance, and from each new iteration, build upon it, get better at it. So there's still a lot to be done on that front, and we're sort of enjoying that ride at the moment.

Jon Thompson: 35:35

Yeah, that's a great summary. For people who want to get in touch with you further, what's the best avenue?

Marty Moore: 35:41

I think LinkedIn is probably the best. I started to build a website, but then the move across the country got in the way a little bit. So it's a little bit in shambles, but LinkedIn is probably the safest way to find me.

Jon Thompson: 35:56

Okay, we'll put it in the show notes to make it extra easy. Thanks again for your time. It's been a real pleasure, some great insights there and we appreciate you.

Marty Moore: 36:04

Thanks, Jon.