Lessons from the Quantified Organization - Insights on Data Driven HR
by STACEY HARRIS
Stacey Harris is Vice President of Research and Analytics for Sierra-Cedar, in charge of Sierra-Cedar's Annual HR Systems Survey and Research. She has been a leading member of the HR practices and technology research community since 2007, with groundbreaking research on high-impact HR organizations, enterprise HR technologies, and key practices across the talent management spectrum.
Prior to joining Sierra-Cedar, Harris held executive level research roles with research organizations Bersin & Associates and Brandon Hall Group. She has launched multiple HR, Talent, Management and Learning research practices and personally led key research initiatives in strategic HR, talent strategy, organization and governance, measurement, and total rewards. Harris also served as director of strategic services for three years and worked with companies such as McDonald’s, Lockheed Martin, Cisco, and Pfizer on a variety of mission-critical talent initiatives.
Harris has M.A. Ed and B.A. degrees from Kent State and Ashland University.
Woman: Stacey Harris, former research executive with Brandon Hall and Bersin & Associates, is vice president of research and analytics for Sierra-Cedar, in charge of Sierra-Cedar's Annual HR Systems Survey and Research function.
A leading member of the HR practices and technology research community since 2007, Stacey launched Bersin & Associates HR research practice and conducted groundbreaking research on high impact HR organizations, enterprise HR technologies, and key practices across the talent management spectrum. Stacey's research and consulting work afforded her the opportunity to work with large global companies around the world such as McDonald's, Lockheed Martin, Cisco. Prior to joining the research community, she led multiple HR, talent management, and learning initiatives as both a leader and practitioner. She is a frequent speaker and facilitator at HR events in the U.S. and abroad. Please welcome to Elevate 2015 Stacey Harris.
Stacey: Everyone, thanks again for joining me. I am Stacey Harris. I'm the VP of research here at Sierra-Cedar, and I'm very excited to be able to share with you some of the lessons from the quantified organization, which is a really great data set that came out of our annual HR Systems Survey that we do each year between May and June.
Let me talk a little bit about the organization that runs this research. As head of research within the organization, I am very very lucky to have recently taken over this 18-year-long research effort. Sierra-Cedar is a managed services organization that focuses on business intelligence, hosting and managed services, infrastructure services for the entire HR technology environment. But particularly, they have been the organization that has spent an enormous amount of time and energy in the last 18 years investing in a service to the HR technology industry which is running this annual HR Systems Survey.
And what I'm really excited about is that I got to take over the research about a year and a half ago, two years ago, from Lexy Martin, who you might now. And we are going to continue to run it for a very long time in the industry as a service to the market and continue to cover all the wonderful areas that we have covered and continue to include even more stuff over the next few years.
So if you haven't had an opportunity to look at the full research before, it covers strategy, process and structure, all of the application areas from an HR technology environment all the way from payroll and administrative to workforce management, talent management, BI and analytics, what organizations are adopting today, what they plan to adopt in the near future, and what they're doing from an integration and emerging technologies perspective, as well as the vendor landscape and how organizations are resourcing, and the expenditures they're putting into these technologies. So it's a huge research effort.
Today, though, we're just going to take a small slice of it. And to understand the research that we're going to be talking about, it's important to understand a little bit about the scale and scope of the total research effort that we go through in this process.
So one of things that Sierra-Cedar does is that we really reach out to everybody in the HR systems environment, really trying to get a good sense of the market, what's happening, a lot of different places: magazines, industry associations, organizations who support HR technology environments, and try and make sure that everybody is reached in this research effort.
Usually we get about anywhere from 4,000 to 3,000 individual people who sort of hit and touch the survey. We clean that down extensively to individual organizations, and this survey covered now 101,204 individual organizations. That's individual organizations, not just people who took the survey. And those organizations covered 21 million employees and contingents in the workforce. And on average the employee sides of the organizations is around 17,000. But as you can see, we have large, medium, small organizations that cover anywhere from organizations up to 450,000 employees all the way down to organizations of 50 employees, so we cover all industries in this research.
And the breadth and depth of this research allows us to really cover an interesting area, which is, what's the difference between various types of organizations? Because oftentimes when you have a small sample set, you might be able to get an indication what's happening on the technology front, but you're not really able to see the differences between different types of organizations, and I'm not just talking by industry or size, but the makeup of an organization. Well, one of the organizations that we wanted to look at last year was really to understand what we called data-driven organizations, those organizations who were doing something different on the front around data analysis and leveraging it to make decisions within their organization.
And this conversation started around a dinner table when we were talking about the emerging conversation around the quantified self. If you haven't had an opportunity to take a look at what the quantified self is, it was a term coined by Wired editors Gary Wolf and Kevin Kelly in 2007 to basically explain this group of people who were becoming almost obsessed, if you want to use the word, with sort of tracking and monitoring data and information about themselves. They were using wearables in their phones and eyeglasses and watches and all kind of things to capture data about their heart rate and their health and their walking and activity exercises and their sleeping practices, and that momentum turned into something called the quantified self.
And around the dinner table, myself and a couple of my colleagues kind of said, "Could we be starting to look at what's the difference with organizations who are more quantified, organizations that really take a look at what's happening in this market around measuring their own internal practices, measuring what's happening around them, the environment around them, and making decisions based off of that?" And so we took a look at this large data set that we have each year and we said, "I think we can start actually take a deeper dive and understand organizations who maybe do things a little bit differently." And we came up with what we called the quantified organization index, and that index really was created by four areas that we were looking at. Were there organizations who had better BI and analytics process maturity? In other words, they were the highest quadrant of BI and process maturity of all of the organizations that we had within our research.
Were there organizations who were giving managers more access to analytics on a day-to-day basis? So what was the highest percentile quartile of those organizations giving access to analytics? Were there were organizations who were just leveraging more data sources to make decisions across their HR function, and were there were organizations who were leveraging more metrics to measure their HR function?
We took the top quartile in all of these particular questions in our research, and we said, "What's different about these organizations," and we called them the data-driven organizations. And then we took the rest of the organizations who were not in that, and we call them non data-driven organization.
You'll see sort of a comparison over the next couple of slides between these very data-driven organizations and those who are not as data driven as these particular organizations. They was a small subset of organizations that fell into this bucket. We're not talking hundreds, we're talking about 50 to 60 organizations that fell into this quantified organization bucket out of that 1,204 organizations that we were talking about.
And what we found is that not only do these organizations outperform across the board, and sort of being a strategic business partner compared to all those organizations who are not data driven. Basically we asked organizations, "Is your HR function seen as a strategic business partner by your peers and your business colleagues?" And the answer unanimously for these data-driven organizations was much higher, 61% higher than it was for the non data-driven organizations. But they also were organizations that generally rocked the business numbers as well. So what we really saw is that those organizations, they had a 27% return on equity. Now, return on equity is one of those financial metrics that organizations use to say sort of how are organizations leveraging and getting an outcome from the capital investments that they make in their organization, which is a good way to sort of do apples to apples in organizations.
We also look at things like revenue per employee, margins per employee, profit per employee, operational costs. We gather that data separately in all of our research and put it into our data sets. And they outperformed in some of those areas as well, but particularly in this return on equity, 70% higher than those organizations who are non data-driven organizations. That is really really high.
If you look at any financial investment firms, one of the things they're looking at is at return on equity, and that really is a big differentiator. So we were like, "Great, this subset of organizations is doing something different. They're making a difference in their organizations and they're having an impact at a financial level." Now, we don't know if that's causation or correlation, but know it's tied at some level.
So what are they doing differently from all the other organizations besides sort of the four metrics that we were capturing? One of the things we noticed is that these organizations by and far were more likely to have updated HR system strategies. They were also more likely to have an enterprise integration strategy, almost three times as likely in some cases, and really much more likely to have a constant consistent culture of change management. And I really can't emphasize this enough that a consistent culture of change management has some real impacts across the board for organizations, and these organizations definitely outdid their non data-driven organizations in that particular area.
Just to get a sense of what this looks like in our research on a total front, only about 30% of organizations across the board have an enterprise HR system strategy. And why is this really important is that generally we see that those organizations that have enterprise HR system strategy not only outperform from a financial perspective, but also do better at an enterprise level in their approach to data and business management as it comes to HR systems.
Forty-three percent of organizations this year plan to develop or improve strategies this year at an enterprise HR system strategy level. That's a really big number. That's the highest we've seen it in several years, 30% higher over the last 3 years. So this is a really big topic for a lot of organizations. And again, those data-driven organizations are more likely to be doing this.
We also know that the creating your enterprise HR system strategy is more than just saying, "We have it done once, we're never going to look at it again in three or four years." It really is those organizations who do annual benchmarks, annual blueprints of where their enterprise environments are at from a technology perspective to an adoption perspective to an integration perspective, and then road maps and action plans for where they plan to be in the future. And so we think those are all elements of a really strong enterprise HR system strategy that's reviewed annually.
One of the things that we look at each year is the overall adoption of the key categories of annual HR technology environment.. That includes administrative technology, self-service technology and service delivery technologies, as well as workforce management and talent management technologies, and all the BI and analytics technology that goes into the HR environment. And what we're really interested in seeing is sort of on average how many organizations have in place certain applications and who plans to increase those over the next 12 months to 36 months.
On average, most organizations have administrative applications. About 66% of organizations now have some sort of service delivery technology including help desk and portals and self-service technology as well. And we know that workforce management and talent management are somewhere in the range of 50-some percent of organizations have those as well. And fewer and fewer organizations then have we call BI in and analytics technologies in place for an HR perspective.
But the reason I bring up this blueprint really isn't just to talk about sort of adoption levels, because data-driven organizations don't always have more or better technology. What they really do have is an environment where they're thinking about a strategy about how all these systems connect, how the data flows across them, how they connect to their business systems, the financial, vendor management systems, CRMs, project management systems. What's their approach to the network security and access from a mobile perspective, and integration in all those environments, data privacy concerns, content concerns, social strategies at an enterprise level? These organizations may not always have the most sophisticated solutions in place, but they always generally have a strategy about how all the data flows across these solutions and into their business systems. And I'll show a little bit later about why they need to do that.
The other thing we know on the integration strategies perspective is that really only about 19% of organizations have an enterprise integration strategy that they regularly update, and only another 8% have one that's rarely updated. This is something that really blew me away when I first did this research. I was like, "You have got to be kidding me," because enterprise integration strategy really is about how do we bring technology into our environment, and on average, organizations...Forty-five percent of organizations spend anywhere from 10 to 25% of their total HR technology budget on integration efforts each year, and if you're in implementation year, that might go all the way up to 40%.
So, what organizations generally do when they have any kind of a strategy at all is that they're still sort of making decisions on a case-by-case basis. Some of them are making decisions to integrate technology into their core HR. Maybe they're integrating into their talent management suites, but only 8% have a full integration platform.
These are the kind of questions that we see that the data-driven organizations are tackling more strategically. They're thinking about it more aggressively, saying, "Hey, if everything that comes into our organization, if we think about maybe connecting it through APIs or an integration platform, what type of fields are important? Where do we want to make sure that data sits? Where does our talent profile sit? Where does our core HR master file sit? Who gets access to that? What fields are we going to share?" Those are questions we see organizations struggle with each year, but a data-driven organization really has to understand all of that information.
And so for us, the integration strategy becomes really important. But the other side of that picture is people. People input data. People make decisions about how data is accessed. People make decisions about the type of data that gets entered into your systems. And so having an enterprise HR system strategy, having an integration strategy is only effective if you've also put in place some sort of change management practices within your organization.
And I can't say enough about having a culture of change management and how it goes with the modern HR environments today. Only 29% of organizations have what we consider a consistent culture of change management. Now, it's nice to see that it's about 36% of organizations are doing change management at least on key projects and 29% of organizations are doing sporadically change management and that only about 6%, or 8%, I apologize, of organizations are doing change management never. And that was nice to see that we really have some sense of change management across all of our HR technology environments at some level.
But I think if you're thinking about where the market's heading, particularly if you're an organization that's focused on moving your environment to a more cloud or Software as a Service based environment, consistent environments of cultures of change management are all about the idea that on a regular basis I'm updating, marketing, and really communicating what's happening in my HR technology environment. And more importantly, that that updating, communicating, and consistently ensuring that the organizations are sort of marketed to is connected with the other technology conversations that are happening in my organization. The reason that this becomes really important isn't just because it's a nice to have. One of the things that we found in our research, this is the second year in a row that we found this, is that organizations who invest in a change management environment, at the very least a culture of change management, but even if they're doing key projects or sporadic change management, by and far, their total HR technology cost per employee reduced almost by half if you're doing a culture of change management compared to those organizations who never do any change management. So if you're an organization that's been looking for a real business reason for doing change management, this is where it's at.
Look, two years in a row we found this data, and I will tell you that, that's hard to do if you're doing research. We normalized it for the organizational sizes, and what we really found is that the culture of change management, when you talk to organizations, allows them to use more of their HR technology more effectively. They're not often buying a lot of pieces and parts. They're oftentimes really leveraging the tools they have. They're making sure that it's being spread out across more employees within the organization, and they're getting more out of that technology. So the total HR technology costs generally go down.
They are also not having to invest in big change management projects every year. So when they do new changes, they're doing this constant PR. People know where to look for the information, what type of information is going to be communicated. So they're actually spending less on total in their change management efforts if they're in a consistent model of doing this.
We're also seeing these organizations are twice as likely to be seen as strategic value partners to their business peers and their colleagues within their businesses. Again, just another real added value for investing in change management. Remember, the reason that we're talking about this is because these data-driven organizations have taken the time to invest in this more often than those organizations who are not data driven. And so one of the things that we're seeing here is that these data-driven organizations also really focus on what we consider the basics as well. Not just sort of the technology components and the strategies, but also the basics of their processes and process maturity. So on average they're more likely to have standardized processes than those organizations who are not data driven.
They're also more likely to have effective process maturity, and I'll talk a little bit about the difference between effective versus efficient process maturity in a minute. And they're also more likely to have central shared services. I thought that was a really interesting one, because that really has an impact on the efficiency and the capability of an organization to manage their data. So we're going to talk a little bit about each of these as well.
In our data this year, we look at major initiatives that organizations are planning to do over the next 12 months, and one of the things we really saw in the top five major initiatives that organizations identified where they were spending both their time and resources was that business process improvement was by and far the most likely thing that organizations were planning to invest their time in this year. Sixty-four percent of organizations said this was the number one initiative for them. And I think it was more important, as you'll see, that this has been the number one initiative for the last three years. This is a big issue. Organizations who focus on business process initiatives realize that that has a big outcome for them as an organization.
You'll also see in this particular side that areas like HR system strategy, as I said, were up by 30% from last year. And then we see organizations investing their time in things like talent management, service delivery, BI and workforce metrics and analytics, all areas that have big process components to them as far as initiatives where they're going to be investing time and resources over the next 12 months. Why this is so important is that I think organizations are starting to realize that no matter the technology, without your processes, a technology is really not going to make a big difference. Process has all the components from a people perspective and a human perspective that make HR technology more effective within your organization.
One of the things that we're seeing is that those organizations who are data driven or quantified are more likely to have what we call effective business process maturity levels. What does that mean? So we look at organizations on a sort of a one-to-four scale, and one being they're sort of manual, paper based, not standardized ad hoc.
Efficient means that they're sort of transactionally focused. It means that we've just sort of reduced the paper based, standardized the process as much as we can take to make it more efficient to cross an organization, really focused on the transaction. But effective means that you are aligned with your business, you figured out the best practices. Some cases, organizations have gotten here by selecting certain technologies that are maybe more cloud based and have already built in some best practices.
Sometimes they built these best practices from their own research and studies. And in some cases they've said, "Look, let's talk to the business and figure out how we can most adequately meet their needs," and that's aligning that, and that becomes a best practice for them. But it really is a lot of concerted effort around these processes all the way up to what we consider transformational, which means that that process really makes a difference in your organization. It stands above any other processes. It has an impact on your organization's bottom line. The quantified organizations on average are moving their processes from this effective area to the transformational area, and that I think makes a big difference in how they're connecting with their business partners.
The other thing is that we see a lot more of their business processes are basically housed in what we considered shared service environments as well. Shared services without a doubt helps organizations become more efficient. In our research, you can go into it a little bit more detailed, you'll see that organizations who leverage shared service environments along with help desks and mobile technology are serving almost 51% more employees per HR administrative support role than those organizations who do not leverage some of those technologies and tools, but more importantly, that those organizations that have shared services are also able to think about their data a little bit more holistically. It's a little bit cleaner. They know the process that the data is going through. It's sort of some standard models around that.
And particularly those organizations who are data driven are more likely to have what we called a central or enterprise-shared service function. So they're in that 43% to 12% here group where there's basically an enterprise look or a centralized look at those shared-service functions. We also have in the research, if you're interested in what functions are generally in shared services versus those that are not. We didn't [inaudible 00:22:31] any real differences in the data-driven organizations around this, but we generally saw that they were more likely to have a shared-services function across their organization.
The other thing that we see with data-driven organizations by and far is that they are definitely innovators, not only in just HR technology, but in their approach to how they think about how technology supports their businesses. When we look at innovation in our research and emerging technologies, we're not just looking at the newest gadgets or the newest technology from the wow factor. What we're looking at is the innovation of how organizations maybe think differently about their business, such as are we a data-driven organization, and how do we leverage the tools to get more out of that approach to the world that we're taking?
And so what we saw is that top adopters of workforce management, talent management, and BI and analytics were all seven times more likely to be a data-driven organization. This I thought was just fabulous, because workforce management solutions and absence management, time and labor scheduling, generally we often see that that is really just used by a lot of hourly based organizations or maybe highly skilled project management based organizations. But what we often find is that those organizations who aren't managing absence and leave and even scheduling with the concept of skills and competencies connected to it, even in environments that aren't often leveraging workforce management tools, feel like their talent management solutions aren't quite getting what it need to really help optimize the workforce. And so with those organizations who have some sort of workforce management in place, some sort of talent management tools that also include recruiting and learning and performance management and succession, all the things that go under talent management, suites in place, and a BI and analytics solution, those organizations are really able to look at their workforce at an optimized level.
We also see these organizations are more likely to use mobile, and they're more likely, interestingly enough, to be early adopters of wearable technology. Now, if you haven't heard the term wearable technology, I would emphasize that maybe you should take some time and do a little bit of research on this. Wearable technology is more than just your Fitbits or your iPhone watches. They really are all types of things, like RFID tags, wearable technology in our clothing, wearable technology in the environment that we're working in. Sort of a stepping stone to what you might hear as the Internet of Things as well, but the idea that we're sort of tracking our environment. These data-driven organizations are much more likely to be doing these things.
So, let me talk a little bit about what each of these sort of best practices are. Those organizations who adopt those full workforce management, talent management, and BI and analytics suites, again, you might say, "Well, is that innovative?" Well, it is innovative, because a lot of organizations maybe adopt pieces and parts, but not the full suites, and not tying them together. They're more likely do not only have higher outcomes in their both HR talent and business outcomes area, right? They're also getting high on that return on equity, 31% higher than the average. So just doing that would get you a boost even if you weren't completely a data-driven organization.
We also see that those organizations who are adopting more mobile technology, we see not only do they have capabilities to really meet the needs of their employees with overall...not only just less HR administrative head count, as we talked about earlier, but also they're able to increase user satisfaction if they're using mobile technology as well. And so we were really interested to see how those things were connected. And so again, data-driven organizations are generally more likely to use mobile technology in their enabled HR processes. Not just we're going to put something on the mobile environment, but we're going to create an HR process that's mobile enabled.
And what's really interesting you see here is that mobile adoption has gone up in the last several years considerably. Ninety percent from last year, 65% growth expected for next year. We consider this to be a continuing trend across organizations.
We also see that other emerging technologies such as employee feedback applications, wearable technology, rewards and recognition applications, and talent acquisition tools all have some level of, I'd say, innovative factors that we see data-driven organizations particularly focus on. As you could see here, today very few organizations are leveraging many of these technologies at an enterprise level. But they're being evaluated and in some cases being looked at in long-term strategies. Particularly, though it is the data-driven organizations that leverage those wearable technologies that I had talked about, or that quantified self, the same concept here as "as much data as I can get." And 55% of those organizations are using wearables to benefit what they would consider the increased workforce productivity within their organization. That's the big benefit they're deriving from those technologies.
And I think that's a really important note is that a lot of times the big wearables may be as fitness or wellness or sort of the fluffier side of HR. These organizations who are leveraging them from a business perspective and thinking about workforce productivity, how can I help that end user and that employee sort of think differently maybe about their work environment? And that's the really important thing about technology and emerging technology.
So just to sort wrap up, one of the things that we talked about is that organizations who are data driven are really thinking differently about their business. They're wanting to measure and think about data as a tool that they can leverage across the organization. So, if you're really thinking about, "How can I start to do this," you need to think about both the whole total process of sort of data-driven decision making. Identifying a need, gathering data, collecting that data, clarifying it, sharing those results, and the fact that it's never a once-and-done process.
It's always a model that you're continuously looking at over and over again. That's how really data management is managed. It isn't a project, it's a process that we're doing, right?
The other thing is that you really want to think about things like centralizing that reporting, that shared services function. Remember I said BI process maturity was high? Well, to get high business intelligence process maturity, you really have to think about sort of getting standards in place for your reporting, your analysis, your benchmarking across the organization, building reports and conducting studies. Again, high levels of BI and process maturity, thinking differently about that approach than most organizations might. Creating a culture of analytics.
Remember that culture of change management? But a culture of analytics is a way that people can see those analytics across the organization. Maybe not just at the highest levels, but across the total organization. Providing an onsite consulting and client engagement.
That's a way of sort of measuring HR, making sure HR is doing what they're supposed to be doing in those environments, and giving the data back that the organizations need. And finally, focusing on things like workforce and HR planning and business planning. Again, all things that have to do with sort of HR and business measurements that we tracked in our index earlier.
Over time, that focus has to shift from reporting to analysis and decision making in an ongoing process. And why this is important is that we see that organizations who do this really have better outcomes. Generally, organizations who use any sort of analytics are always focus on what we consider backwards-looking metrics, right? Compliance risks, retention risk, HR benchmarking. Data-driven organizations just as well as non data-driven organizations who are doing any form of analytics look at these type of things.
When we shift to things like forward-looking metrics, the predictive type of things like workforce assignments, identifying future talent, improving employee engagement metrics, skills and readiness assessments, you'll see all of the sudden data driven organizations maybe a little bit ahead of non data-driven organizations in the focus that they have and the type of metrics that they're using. What's really interesting is that when we shift to those business-outcome metrics, the one I was telling about how...Remember we're going to shift that conversation? Data-driven organizations by and far are looking at their HR data and how it compares to customer satisfaction.
Increasing innovation, increasing competitive advantage, optimizing workforce productivity. These are business metrics and business decisions that you're comparing your HR data to. This is the difference between those data-driven organizations. They're not all big organizations, they're not all small organizations, they're not organizations who invest heavily in technology. They're across the board as far as global and non-global. The biggest difference is how they think about data.
So just wrapping up, I want to sort of give you an emphasis about why all of this makes a difference. Not only are these organizations seen as more strategic, not only do they generally have better financial outcomes. In the report, we look at three types of organizations. We look at what we consider top-performing organizations, those organizations who do financially well in all those top quartiles of these metrics that I've got listed here.
We also look at a group of organizations called talent-driven organizations. There's more details in the report about that if you're interested in it. but those organizations that are driven are a little bit more by talent decision-making processes. And we look at the quantified organizations or data-driven organizations. And they have the same indexes that we talked about earlier.
By and large, when we asked organizations about various outcomes that were improving or not improving within their organization, and we had out talent outcome, so is your attracting talent improving within your organization over the last 12 months or has it decreased in your organization over the last 12 months? Has the ability to do talent retention within your organization increased over the last 12 months or decreased over the last 12 months? Same thing with the HR outcomes and the business outcomes. Has your customer satisfaction gone up in the last 12 months or down in the last 12 months? Have you become more competitive in last 12 months or has it declined in competitive advantage in the last 12 months?
I can't emphasize enough, if you look at this chart, talent outcomes, about the same with the aggregate groups, right? A little bit lower than everybody, but our top performers do well here. Our data-driven organizations, that's the DD down there, and the talent-driven organizations do fairly well in the talent outcomes. And the HR outcomes, everybody but the aggregate group does fairly well in how effective they are at doing these outcomes. But look at that business outcomes. If I leave you with anything here, these business outcomes just blow away the organizations who are even top performers in financial outcomes.
The data-driven and the talent-driven organizations by and large are doing better in the total business outcomes. You can't say any more than that. This is why you want to think about being a talent- or a data-driven organization.
So, I'm going to wrap it up here. If you have some additional questions, we have a couple of links here on both additional papers on these topics as well as a couple of panels that we conducted on this topic with the peers network. We also have, if you're interested, some more details on connecting with me. If you have any questions, you're more than welcome to reach me directly on LinkedIn or connect with me on Twitter. And then, if you're interested in participating in the research, there's download links and the total material here for you to download the full research report or to participate in it next year.
But thank you everyone for your time. I appreciate it, and I hope we gave you some insight into data-driven and quantified HR organizations. Thanks, everyone. Bye.