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Financial Services Blazing the Trail with Data

Salema Rice

Chief Data & Analytics Officer @ Geometric Results, Inc.

Salema Rice is the Chief Data Officer for GRI (Geometric Results Inc., a Bain Capital Company) and a member of the company’s executive management team. Salema is a senior executive with over 25 years experience directing data management strategies for large complex organizations.

Transcript

Andy Palmer:
Salema, it’s great to meet you.

Salema Rice:
Thank you.

Andy Palmer:
Your background is incredibly impressive. You’ve done so much with data for so long. Could you just take us through your careers and kind of what brought you to the point you are in your career and how you sort of fell in love with data?

Salema Rice:
Yeah, I had a… I’m kind of aging myself, I guess. I have about 30 years of experience with data. I started as a management consultant. I did that for about a little over 20 years. During that time, I spent about 12 hours in the banking and financial services spaces and then I think the chief data officers that experienced those 2008-2009 years, we learned a lot of lessons. And in 2014-2015 time frame, my consulting company actually asked me to come in house as their chief data officer, which I thought, how are we doing to apply best principles in banking and financial services to human capital management, but I’m ready for the challenge.

Salema Rice:
I think that what was really phenomenal at that time was that we saw a lot of chief data officers in financial services starting to imbed themselves in other industries because of the fact that we had so much experience in data quality and metadata and data governance and data management during those years, that other industries could benefit from our gains and our losses. We failed a lot of things really fast during those tough years. So kind of joining the human capital management space, it was really easy for me to say, yes. Especially in the position I’m in now with bank capital in GRI, I love GRI, I love being in the human capital space. Mostly because I have an opportunity to really make a difference. And I think that that’s something that in those years of 2008 and 2009, we knew that the foundation that we were laying was going to last forever. That things would never go back to the way they used to be.

Salema Rice:
I’m super excited to be in an industry that really didn’t use data the way they could, and now we’ve developed products, data products, and teams where we can really make a difference in workforce decision analytics.

Andy Palmer:
That’s amazing, this idea that financial services is kind of blazing the trail in terms of data, and now you’re part of that. And now you’re bringing that expertise in data to other industries, in human capital management specifically. What projects are you doing? What is data as an asset and next gen data look like in human capital management, and what are the projects that you feel are the bread and butter, like the core things? And then also, what are the ones that are more advanced, that you’re most excited about?

Salema Rice:
So for me, we actually have a data platform called ENVISION at GRI. And it’s really around workforce decision analytics. But what is does is, it goes beyond that typical rear view mirror that I think was the standard for report is, look in the rear view mirror, see what happened. Where we’ve taken it to a different level of, here’s what happened, here’s why it happened and here’s what’s going to happen next. Being able to rebuild a lot of the old legacy systems onto new, modern systems of intelligence that are able to ingest any data from anywhere on any format. But I think even what maybe might be even more greater than that, is some of those lessons learned around data quality and metadata and data governance that now we can apply to that, so that they’re not looking at models, whether they’re machine learning models or AI models, and feeling like it’s a black box. We can easily lift the lid and see where the data originated, who touched, and how it actually became ingested, prepared and transformed to where it is today.

Salema Rice:
So I was super, super excited about that. We’ve developed several different models within the ENVISION platform that look at things like, where do I find purple squirrels. Helping our customers to identify where hard to find talent resides. We build models around consumer competencies or using external data to help us predict labor tends. Things that this industry really never even considered five or 10 years ago.

Andy Palmer:
It’s so fascination. So do you feel like in human capital management, in GRI, do you feel like you’re still putting the basics in place to kind of catch up to where financial services was five or 10 years ago? Or do you feel like you have an opportunity to kind of leap frog and adopt next gen tech that avoid some of the legacy stuff?

Salema Rice:
Oh, that’s a good question. I wish we could just jump frog all the problems. But legacy systems are around. Human capital, we’ve been doing human capital management for a long time. What’s unique about our situation is that GRI specialized in contingent labor. Contingent meaning anybody who’s not a full time employee. But what our customers are realizing now is that with the data environments that we have today, we actually can tell. We can give them total talent. We can give them total talent strategies. We can give them total talent management. We can tell them, are they finding talent on an SOW or statement of work at the same skillset as their FTE or their competitive bid. Things like that, that, again, this industry wasn’t capable because the foundation wasn’t there.

Salema Rice:
We spent the first two years building that foundation. So the core was really to architect the data for analytics. We’ve spent a good two, two and a half years now, really building out an architecture using a system of intelligence that could, not just ingest the data, but ingest any data from anywhere in any format. So that hybrid technology has to be there in order to ingest things from tables and columns, but also you have massive amounts of blobs of text from job descriptions of PDF files. And a lot of that data has to be transformed. And then really, I think where we can apply some of the lesson we learned from financial services, is around that data quality.

Salema Rice:
Honestly, a big problem that they had in human capital was that a lot of the fields are free form. So how do you create standardization? For us, it was let’s start at the… We literally started at the bottom to build that foundation to standardize all of those things in order to apply things like master data management, to apply reference data and data quality and metadata and data governance. And I think that really was the foundation for architecting the data for analytics.

Salema Rice:
Then you get into building a semantic view and things that will enable your data scientists to be able to get to the models faster, without having to do any of that data scrubbing.

Andy Palmer:
That’s fascinating. So during that two year period that you’re sort of building up the core infrastructure, what was your trade offs? When I was a CDO, I was kind always making these trade offs of build versus buy. What was the mix like that you ended up with? And what are some of the tools and techniques that you found most useful? And what are some of the things you’re like, we have to do that ourselves because there’s nothing else out there?

Salema Rice:
That’s a good question. I would say that a lot of the stuff we build in house. I will tell you that. I have an amazing team of leaders, of engineers, of data scientists, analysts, that I call my family. Our motto on my team is, I’m the CEO of the data company and we’re family, and so family’s first. A lot of the people on my team have worked with me for five to 10 years. Some more. Which is amazing. We have very little attrition. We respect each other and we have a great amount of innovation and creativity.

Salema Rice:
The master data management was all built in house. It wasn’t an initial choice, but I think in this industry, investing millions of dollars into large, complex [inaudible 00:10:35] data management, and the time that it takes to stand up, some of the larger MDM and even data governance tools, we didn’t have. We had to move very fast.

Salema Rice:
One of my goals for our organization and me as a whole… It’s kind of interesting because being a chief data officer, this is the first time really, I think in my career, where the data product that we’re using are really changing the industry. So, we’re not just managing behind the scenes. I’m kind of like chief product officer and chief data officer. It really gives us the ability to build some things that are kind of tool agnostic. The ENVISION platform that we built is .net, which is not even a typical CDO platform. But we’ve really gotten a lot of help from Microsoft with their new data factory. We’ve been able to utilize the data factory to be able to be very hybrid, to be able to have the structured and structured data capabilities.

Salema Rice:
We’ve also used a lot of Tableau in our development. Tableau allows us to kind of get to the why, the correlation of the data. So in this industry, it’s really important not to just know what happened, but when you think about something like if you’re hiring hundreds, maybe even thousands of developers for an application development, you want to know not just that you’re getting a fair market rate, but how does that rate actually impact you. So now, we can actually correlate the data so that we can not just show the customers what happened, but really get to the why. Then using our machine learning and AI models, we can get to insights that tell them actions about, hey, here’s what might be happening next.

Salema Rice:
Or when you think about predicting where we’re going, one of the things that’s been interesting about COVID is that for the first time, we don’t have any data. This never happened before. So how do we predict how we’re going to come out of this? Right now, our predictive models use really a combination of historical data and seasonality. A lot of what we do is industry based. We have very large customers in online retailers or healthcare or consumer goods that weren’t necessarily impacted the way manufacturing or light industrial was. So a new level of seasonality I think is going to come out of this current season we’re in.

Andy Palmer:
It’s really amazing how you think of yourself as the chief, heading product as well as data and that the data is kind o woven into the core product. Correct me if I’m wrong, but that’s kind of what happened in financial services as well, right?

Salema Rice:
That’s right.

Andy Palmer:
And so you’re kind of bringing that expertise. How open was the leadership team and the maybe more traditional folks that weren’t sort of data savvy, how did you convince them that this was important? Or did they just know and is that why they brought you in? The human elements are always so hard. How did you make this happen?

Salema Rice:
Well to be honest with you, I report to the CEO and he actually sought me out. I think that, let him tell it, he interviewed a lot of people before he found me. I think that part of it is that you have to have a mindset that you want to do something different, that you want to make a difference. I think that a lot of leaders in our space are great leaders, managing people, managing data, but we had to go further. I have a great amount of responsibility. Probably even more than what… Even though I don’t have as large of a team from a data perspective, what we do in terms of data management, data governance, metadata, machine learning, AI, product development, it’s very broad. I can’t really kind of narrow it down.

Salema Rice:
In some ways it’s actually good to have oversight into all of that. The DBAs report to me. Even the Microsoft Azure admins were reporting to me until just recently. Just because I think launching the product from the start and really building our entire data management strategy from the bottom up was something that they really wanted somebody who had a diverse background. I think being a management consultant working in multiple industries really helped me come into a company that services so many different industries. And it’s just something I never really thought about as I was progressing in my own career, I never realized maybe what I was being prepared for.

Andy Palmer:
It sounds like you had a enlightened CEO who really believed that data was a part of the core fabric of the future of the company, and prioritized bring you onto the leadership team. Because sometimes the CDO kind of falls under the CIO, but to have a CDO that’s independent on a leadership with such a broad mandate, that sounds pretty unique and pretty forward thinking.

Salema Rice:
Yes. This isn’t the first time. The last position… A couple of the positions I’ve been in, I’ve reported to the CEO now. I think it’s a great thing. I don’t necessarily think that CDOs belong under CIOs. I think that depending upon the company, it can work, but I think that the CDO and the CIO need to work hand in hand. I think that the business need to own the data and that IT needs to own the processes. If you have somebody that’s going to have both, then they kind of have to own both. And that’s difficult to say. As a CIO, do you really want to own the data? I think when you start having global responsibility for things like data governance, for machine learning, for AI, for data science in general, the data scientists that are building the algorithms, that’s generally not a typical IT function. But then again, a lot of CIO roles are changing as well.

Salema Rice:
So, I am very fortunate. I think that another thing that we see in the data space, and especially in a role like mine where I do kind of wear the product officer and data officer hat, is that there is a direct line to how data is an asset for the organization. Data is truly a major asset for us. We can quantify data based on volume of data, based on products that we’re able to develop with data. Having data that enables us to build models that are unique for an oil and gastroenterologist industry, or unique for the consumer goods industry, this has really changed the course, I think, for data practitioners to have a seat a table at the CXO level.

Salema Rice:
Even with our customers, I think it’s fascinating that when I joined this industry in human capital management, I would often meet with chief procurement officers, HR, and that’s not the case anymore. Now, what we’re developing from a data perspective, some of our customers I meet on a monthly basis with their global CIOs. Several of our customers, I meet with on a quarterly basis with their CFOs. It’s really amazing to me that we have the ability now to reach so many different personas.

Salema Rice:
I don’t know where you’re located at right now, but here in Ohio, it was so fun to watch our governor talk about our data lake and how many attributes, how many data elements they’re looking at in their data lake across the state. Just hearing that type of terminology and the data literacy come out of even a public official really kind of makes you feel like data’s kind of sexy right now.

Andy Palmer:
It’s incredible that it’s gotten so mainstream to have people that never would have thought or talked about data to have it be top of mind. Also, as you start to think about the next two, three years and as you take your organization and your tech to the next level, what are the things that are most important to you and that you care about the most in terms of driving even more value or building on? What are you most excited about going forward?

Salema Rice:
Well, to be honest, I’m really excited about the models that we can build. Because we’ve spent so much time building the foundations, it sometimes takes precedence, being able to get all of our customers, the new customers that we’re adding because of our data and analytics offering is phenomenal. So we spend a lot of time still in kind of building out and continuing to build up our repository of data. We’ve built the foundation, but I think that as we move more in 2021-2022, really where we’re going to be focused is on the actual model development. So, the machine learning and AI models that are really going to take us to the next level to really understand and predict and learn from the data that we’ve been collecting for so long. To build out, kind of answers to questions that are still maybe taking us a day or a week to answer, that we’ll really be able to answer in just a matter of seconds.

Andy Palmer:
That’s amazing. It’s kind of the velocity of it is all increasing.

Salema Rice:
Absolutely.

Andy Palmer:
One other question around open-source. How important is open-source? You mentioned you use [inaudible 00:22:20] a lot. Are there a set of open-source tools or tech that you really like, that you think are important?

Salema Rice:
I do. There are some things that our team uses, definitely are thinking about on the statistics side, rather than in the past I’ve used some more robust, not open-sourced tools. But I think that-

Andy Palmer:
Maybe three letters that start with s and end with s. That kind of thing?

Salema Rice:
Right. That being one of them. There are others. Yeah, I think that definitely comes to mind. I just think there’s so many opportunities right now that technology is ever-changing, that the more things that can help us to do our jobs faster and more efficient and give us greater visibility. When you think about this industry, honestly, whether you’re on the staffing or the supplier or the manager service side like we are, it’s all about visibility.

Salema Rice:
I joke with my customers now, I get to actually sit in on a lot of their, as an executive sponsor, sit in on their business reviews. And I say, what we’re giving you is visibility on steroids. You said you wanted data and analytics. Welcome to my world.

Salema Rice:
But in all fairness, sometimes you’ve got to spoon feed them. And I think that as we move into the next generation of this, it’s really about problem solving and having those models available to be able to solve problems faster. So now we have laid the foundation, we’ve architected the data for analytics, we’ve done all of the kind of descriptive and predictive… We’re going to be doing more on the prescriptive… But those tools that allow us to get there faster, to maybe even allow us to do more storytelling with the data, are definitely things that I might be looking at.

Andy Palmer:
Wow, that’s great. I love that framework, that descriptive, predictive, prescriptive. That seems to apply very broadly and work really well for lots of folks.

Andy Palmer:
Not to spent too much time on tech, but cloud versus on prem? How do feel about it? Where are you in the journey? And what are your opinions about what people should be thinking about in their data organizations about leveraging the cloud or not?

Salema Rice:
Well when I found out that we didn’t really have a data strategy, there was no data strategy, there was no data environment per se, I felt like it if I had to manage all that, it had to all be cloud.

Andy Palmer:
Got it.

Salema Rice:
There wasn’t an on prem option at the time. I don’t know that I… I have pros and cons for each. Everything’s not for everybody.

Andy Palmer:
But you’re mostly cloud.

Salema Rice:
I’m 100%.

Andy Palmer:
100% cloud, wow. And mostly Azure, Microsoft, or a mix of some?

Salema Rice:
Mostly Azure, but some AWS.

Andy Palmer:
Gotcha, gotcha. That’s great. We’ve heard, many of our customers at Tamr really have warmed up to Azure and they seem to be doing really well. Cloud Data Factory seems to be a really fantastic offering.

Salema Rice:
Yes. I love the fact that, like I said, when we did it… Well, one, the cost. It cost much less for us. And the support is a lot less. So not having to have a large, full time ops team has helped dramatically because I have a much smaller… I went from companies where I had 200 employees to having a fraction of that.

Salema Rice:
But what is amazing to me with my team is how much we’re able to produce. So I think we’re on maybe sprint 42 and we’ve developed an entire data management architecture, a strategy, an environment, dozens of models built inside of a product, all in 42 sprints. I mean, it’s phenomenal.

Andy Palmer:
Yeah. Well it’s incredible just to hear a data management hero like yourself actually talking about sprints.

Salema Rice:
I know, right?

Andy Palmer:
I mean, there was a time, like old world MDM project took years and waterfall. For us, we like to use… We talk about data ops as kind of this more agile approach to data management, but it sounds like you’re practicing this every day.

Salema Rice:
I lived those years with you. I want you to know that. I lived the six months, two year MDM.

Andy Palmer:
Oh, so brutal. Brutal.

Salema Rice:
So to be able to produce stuff so fast, honestly, I’m blessed. I’m blessed to work with Bain Capital and with GRI and to be given this opportunity to be the CEO of the data company, to be kind of handed that reign to say, you know what it’s going to take to make us better. You know what we need, just do it.

Salema Rice:
To have some guardrails, but to have the ability and the trust and the confidence in my management to say, you’ve got our best interests at heart. Do what you do best. It’s been a lot of fun. It’s definitely [crosstalk 00:28:36].

Andy Palmer:
So cool. Sounds like you really, truly have a seat at the table.

Andy Palmer:
Tell me about your organization. How are you organized and how do you see that changing going forward?

Salema Rice:
So right now, we have everybody kind of in one development team, which I’m not sure that down the road I might split that out. Because it’s more than the dozen I think that typically most agile development that I’ve done in the data space, has worked well with kind of that 10-12 people. So we probably put a little too many products into one sprint at a time. So we might look at how we break out the MDM projects, versus some of the other… A lot of our models that we’re working on right now, we might have visualization, we might have data scientists, as well as data engineers that are individually grouped in maybe a group of three, rather than even the groups of 12. To kind of create smaller, agile teams that can come together.

Salema Rice:
But we’ve tried it a few different ways and obviously right now it’s really working. It’s just thinking down the road with all the different products that we’re developing, does it make sense? I really love having everybody on a daily stand up. Although it doesn’t take 15 minutes, it usually takes us about 45 to an hour. But it’s good for me because another thing that’s really unique about my organization is that it’s 100% remote.

Andy Palmer:
Really?

Salema Rice:
Not because of COVID.

Andy Palmer:
Wow.

Salema Rice:
We’ve been 100% remote from day one. One of the things that the board gave me was the ability to hire who I needed, wherever they were. And I think that because of that, I’ve been able to acquire great talent that, I don’t want to move to Detroit or I don’t want to move to Denver, where our core offices are. So we’ve been able to have people in different time zones and to be able to come together every single day, face to face, to talk about what did you get done in the last 24 hours? What are you doing today? And what risk do you have?

Salema Rice:
So because of that, I think that they are incredibly talented and we’re able to get so much done. The volume and the velocity of the team has really, it’s four times what it was two years ago.

Andy Palmer:
Wow. So it sounds like you have a lot of these things that many other companies are striving for. Cloud based, virtual teams, everybody remote, very agile approach. It sounds like you’re practicing those mainstream every day at scale. It’s like a role model for-

Salema Rice:
[crosstalk 00:31:58]Except it’s ours, all of it.

Andy Palmer:
There’s so many people that would love to have just one or two of those things, and you’re doing all of them in real time.

Andy Palmer:
So what do you think it’s going to take? What advice do you have for other organizations? Do you think that they should, as they go through their digital transformation and start to desire to be able to manage data as an asset, do you think that they should green field things and kind of start from scratch? Or do you think that they should take their time and kind of move incrementally? What do you think is the general orientation or center of gravity they should have in terms of how they approach that kind of digital transformation to data as an asset?

Salema Rice:
I would say first, start small. Give good wins. You want raving fans. For me, we had to have raving fans all over the… We had to have different types of raving fans. Customers that are raving fans, C level executives that are raving fans, managers and directors that are raving fans and even employees that are raving fans, right?

Andy Palmer:
Yeah. Right.

Salema Rice:
And so I say when you start small and you can get big wins, then you can share those big wins and word gets out. Happy people, happy customers, does a lot for you. I think that’s number one, is don’t try to bite off more than you can.

Andy Palmer:
So don’t boil the ocean?

Salema Rice:
No. Don’t boil the ocean. No matter what it is. Whether it’s for master data management, we picked one subject area. For data governance, one subject area.

Salema Rice:
And do stuff that you can do fast because for us, getting an MVP out there is really important. I never had global responsibility for products before either. I was the data diva for a long time, so this was a whole new world for me. But one of the things that I learned really fast was that we can get a product out and get all the other stuff afterward. We can enhance it and enrich it, but getting it out there, getting it in people’s hands… Use it. Tell us what you like, what you don’t like. Tell us what data it needs. I mean, these are data products. These are not application products. These are products that enable you to make decisions about your workforce. So getting it into their hands and getting that one on one feedback and being able to be agile enough that, I would say for the first maybe 36 sprints, we ran biweekly sprints and monthly releases.

Andy Palmer:
Wow. Wow.

Salema Rice:
With COVID, we’ve been running biweekly sprints and biweekly releases.

Andy Palmer:
Seriously? Oh my God.

Salema Rice:
Seriously. But after 40 sprints, these guys know each other better than they probably know themselves. But I think that having those quick wins. And the customer, whether the customer is internal or external, because we have both… I have global responsibility for enterprise data as well as customer data… But I think, one, I would definitely say trust. That was a big part of it. Making decisions about data you trust. You can lose a raving fan very quickly by having data quality. So invest the time in those types of things that will help them to make confident, fact based decisions.

Salema Rice:
Now, if the data is bad at the core, do not fix it in the front layer. Go back to the source. Because otherwise, every time you go to the well, the bad data’s still going to be there. No matter what, we always take the time to go back to the system of origination, and not the system of record, and fix any data quality or any anomalies at the source. So that if the customer were ever to look at something without being in one of our products, we want to make sure that they trust it.

Salema Rice:
I think the other thing is the visibility about the black box. We have a lot of competitors that have, I would say… I’m obviously biased, so I’m never going to say anybody’s baby’s cuter than mine… But what makes us different is that we don’t have a black box. We open the lid. Throughout every product we do, we provide all those things. We give you what was the data competency, what was the data quality. What is it, what is the data definition, how is it being used, where did it originate, what date is it based off of. Those types of things really helped our customers, internal and external.

Andy Palmer:
So Salema, one last question. If you think about the new people coming into data, the younger folks, what’s your advice as to what they should focus on and what they should emphasize in terms of the skills they’re developing and the kinds of areas where they should develop professionally?

Salema Rice:
I think that it’s interesting, the way data has evolved over the years. Critical thinking, I think, is a lot more important than it used to be. In some ways, I’d rather have somebody who can think outside the box, and less important about what tool they can use. I can teach you a tool. It’s hard to teach you how to get that mindset of critical thinking and creativity, innovation, ideas.

Salema Rice:
I often ask people in an interview, what kind of things do you do with data outside of work. Pretty unfair, but I’m curious. I think that because there’s many areas in our lives where data does impact us, and how they’ve used data to affect something that wasn’t work related speaks volumes for the type of person they are and how they’re using data.

Salema Rice:
Number one, I would say it’s not just about the data in this case. It’s really about the problem solving. A lot of times I’ll joke with my team and say, we’re taking all your titles away and you’re going to be problem solver one and problem solver number two. Because that’s really what it comes down to is, we use data to solve problems. I guess from a technology perspective, a lot of the newer tools do a lot for you in terms of the user interfaces, but I think the sequel skill set never goes away. No matter what tool you\re using, having that back end expertise to be able to get in and kind of use or see kind of where there might be issues.

Salema Rice:
Obviously visualization and storytelling right now is really important. Being able to… Depending upon what path you’re going. If you’re going the engineer path, then I would say absolutely, you can’t stop it, data. You’ve got to go to big data because there’s so much we do now that’s commingled, especially in my world. We look at skills rather than jobs titles. Well, skills come from things like resumes and jobs descriptions and blobs of text that we have use some complex natural language processing on to get the engineers to that level to… On my team, the engineers typically have extended numbers of years in both Python as well a seek or SSIS type application.

Salema Rice:
And then on the analytics side though, I think having the ability to really have that education around some of the different visualization tools, whether it’s Tableau or Power BI doesn’t really matter, or any of the other dozen or so that are out there. I think that what’s more important is what type of problems did you solve with the tool. Because if you were… The tools all kind of work… You’ll find similarities and you’ll find good, bad and different things in every one. Having specific tool sets really isn’t a requirement on our data science side.

Salema Rice:
Most of my data scientists actually have backgrounds in physics I think, strangely, just because they came up through-

Andy Palmer:
Amazing.

Salema Rice:
Yeah. And another thing we look at is on the data side, I think beyond kind of the story telling, is just the analysis. It’s hard to find analysts who have both the expertise to kind of look at the wall of data and visually know with their eyes, this isn’t right, this is an anomaly. Maybe it’s more of a data mining exercise more so.

Salema Rice:
Obviously having class work and things like master data management and other things is helpful, but I think if you have the core, I think really more than anything, you’ve got to have the desire to want to use data to solve business problems.

Andy Palmer:
Yeah. Well, it’s been amazing talking to you and I can tell you, even at my stage in my career, listening to you talk, I would love to come and work for you.

Salema Rice:
Aw.

Andy Palmer:
You’ve got all the right principles at work. Truly inspirational, what you’re doing. I really, really thank you for taking the time to catch up and share your thoughts.

Salema Rice:
It was my pleasure. Thank you so much. This was a lot of fun. I don’t do this too often, so I really enjoyed it. Thank you.

Andy Palmer:
Great to catch up. Really would love to spend more time together at some point, if you were up for it.

Salema Rice:
Yeah, absolutely.