In this video, HireVue CMO Kevin Marasco discusses what is increasingly becoming a critical business imperative for organizations of all sizes and sectors: embracing big data and predictive analytics, and the role of HR in using this to transform the process of attracting, engaging and managing talent.
Watch this on-demand webinar now to learn:
Kevin: Thank you everyone for joining us today for Talent Insights. We really appreciate you taking the time to join us. A very exciting time to be in talent. There’s a lot of really cool things going on, and we’re excited to be here today to talk about it.
We’re joined by over a thousand talent and business professionals. Really appreciative of everyone taking time to share their information and acknowledge over 20 thought leaders that are with us today and over 10 partners who are participating in this event. And if you haven’t done so, hopefully you’re familiar with a lot of these companies but there’s just a lot of great things going on, a lot of really cool technology and services, and these guys are doing some really cool stuff. So if you haven’t checked them out, definitely be sure to do so. I promise it’ll be well worth your time.
We have two tracks today – one on talent analytics and the second on recruiting innovation. We’re also going to be tweeting, so please use the hashtag, #TalentInsights. That’s Talent Insights T-A-L-E-N-T-I-N-S-I-G-H-T-S. A lot of our speakers and partners are going to be using the hashtag and will be responding to questions. So definitely feel free to engage on Twitter. It would be fantastic.
My name’s Kevin Marasco. I’m the CMO of HireVue. I’m actually filling in today for Mark Newman, our CEO and founder who had a last-minute medical emergency that was unexpected. And I’m excited to join just to talk about a really hot topic that I’m very passionate about. And that’s using big data. I have to tell you what it’s been really neat to see this this transformation take place. Just a few years ago, a lot of folks considered things like predictive analytics and big data. It’s progressive and something that’s nice to have. Really what we’re seeing is a transformation take place, and now it’s truly becoming a critical business imperative. Organizations of all industry sizes and functions are really embracing data. And it’s really becoming a matter of survival. We’re going to take a look today why the movement and the evolutionary rise of big data, HR’s role in that… At the end, we’ll take a look at some examples, how HR organizations are embracing it and applying it to improve performance in terms of how we attract, engage and manage talent.
One thing that’s fascinating is the rise of big data and really to see something evolve at such a velocity. A few years ago, the category was roughly $8 billion and we’ve seen 400% growth in just 48 months; now approximately $40 billion category and it’s just truly exploding. And we’re seeing this not just in a couple of industries. This is not just limited to, for example, technology, Silicon Valley. It’s a cross-sector – financial services if we think about how banks have transformed, how they connect and engage with customers, and provide them with more personalized and better experience, software, internet. Online retailing is one example again become just more personalized and truly delivering a world-class experience while also improving operations for retailers. And even organizations, and energy utilities, government are also embracing big data and predictive analytics to improve operations, to accelerate growth and to provide a better customer experience.
And it’s impacting backend operations. It’s impacting customer service and customer engagement. Certainly this will take a look at transforming how we connect and engage. It’s the lifeblood of our organization, our own teams, our own people. It’s also impacting organizational changes. Accenture recently found that 2 out of 3 organizations have hired a chief data officer within the past 2 years alone. This is the position that you rarely even heard about before and so it’s really neat to see how organizations are transforming themselves to accommodate and be proactive when it comes to things like big data and analytics.
A lot of folks get caught up in the hype of talking about the technology. It’s certainly a part of that but it’s not really what it’s all about. It’s not about technology for technology’s sake or, “Here’s this cool, new metric or KPI that we can track now.” It’s really about enabling better decisions, enabling faster decisions, smarter decisions and empowering people who make those decisions with data they need when they need it, so that they can move faster, so that they can improve the customer experience, so they can improve their own operations. So it’s important to focus more on the outcome, not just the input and the technology and how things are made, but what we can do with that and how we drive those decisions forward.
At the heart of this, this is an interesting report that they did and they found that organizations that are embracing big data analytics are five times more likely to make decisions faster than their competitors. So you can see that this has truly become a competitive advantage, and one of the reasons that so many CEOs are really digitally transforming their business and embracing data. Organizations were also found to be three times more likely to execute decisions as they originally planned, twice as likely to have top quartile financial performance. Organizations are also twice as likely to use data very frequently when making business decisions; historically where decisions based on gut and instinct now being backed or even driven by data. And we’re seeing this again across the business in all areas.
A hot topic and also a question we hear a lot: What’s the difference between big data and predictive analytics? How is that different that things that have always existed like business intelligence? Is there a difference? Is it really just the same thing or the next version of it?
If you think about it, business intelligence, it’s been around for a while. It’s largely focused on looking backwards – analyzing, information in terms of what happened in the past and really giving you a snapshot of what’s currently true in the current state.
Predictive analytics, on the other hand, will use some of that data as a foundation, looking at internal data, but also combine external data. Tons of external data is very common and often very unstructured data to identify patterns and predict possibilities of events that could happen in the future. The car analogy is what I like to use a lot, and business intelligence is a lot like driving and looking at the rearview mirror. There’s definitely valuable information, things that you can take into consideration, definitely some valuable data points that can influence future decisions. But predictive analytics is like looking out of the front and [inaudible 00:08:13] more data points and analyzing all these external data points, to take into account speed, velocity and things that will help you get to where you want to go faster.
Holistically it’s good to have the entire view – being able to look backwards and forward. But what’s critical in [inaudible 00:08:34] moving is these new data sources and looking a lot of these mass unstructured datasets to move things forward faster.
What started as just a more of this nice to have trend is really becoming this imperative, and the ship is truly sailing. A question to ask was, “Are you in or out?” If you think about it and you see what’s happening across organizations, business in every industry are tapping predictive data analytics to accelerate productivity, to boost operating efficiencies and strengthen customer experiences. And every function is truly getting on board. So marketing, for example, is embracing predictive analytics to identify the most profitable customers, to anticipate their needs before they happen and proactively predict and prioritize the best leaps. Sales organizations are tapping predictive data analytics to anticipate sales outcomes and to do things like improve sales forecasting accuracy. Even service organizations, they’re using predictive analytics to preempt customer issues before they happen to enable things like intelligence self-service and map scale in a much more modern way using things like mobile, social and of course predictive analytics.
And operation experts are also embracing predictive analytics across entire supply chains to further business efficiency, reduce risk and variance, and create tons of efficiencies and productivity gains.
What about HR? How are we embracing in a similar way to create similar improvements in terms of how we operate the service we deliver to internal customers like managers, line managers, business partners, executive and even candidates, and create cost-efficiencies, do more with less, and really drive the business forward? Where does HR sit compared to other functions like sales, marketing, operation, finance, and customer service?
A recent study that’s fascinating by Josh Bersin and Deloitte said that only 14% of HR departments have run business intelligence analysis on their own internal data. And if you think about it, we have people data, which is very valuable. A lot of the other data we’re analyzing in other areas of the business analyzes things; everything from supply chain, inventory, customers, financial data, capital assets and things, all important. But what about the people who are the lifeblood of our organization? And there are some very powerful data. It’s interesting to see that only 14% of HR teams are doing this analysis and only 4% of HR departments have started using predictive analytics, being even more progressive.
And so there’s definitely a lot of opportunity and that’s what we want to talk about today. One thing we want to look at is four reasons that I’d encourage you to adopt predictive analytics; four really solid reasons to really make a solid improvement and to keep up, so to speak, with other areas of the business in what they’re doing.
The first one is to get some respect. A study done by Deloitte showed that HR departments that used predictive analytics are four times as likely to be respected by other departments within their companies. And that’s just fascinating – four times as likely to be respected by other teams and servicing internal clients, which is critical. Other organizations have faced a similar C change when you look at marketing. Years and decades ago, marketing was known to be more creative and marketing has transformed and has become more data-driven. Behaviors tracked and the move to the digital world has enabled marketing to be much more analytical and bring to the table analytics and more informed quantified decisions that totally slingshot performance and customer service. Instead of relying surveys that were very backwards-looking, real-time customer data is enabling customer service organizations to provide us a purer experience and really build respect within the rest of the company within the C suite. And HR has the same opportunity to earn respect.
A second reason to adopt predictive analytics is to become a better recruiter. HR departments that used predictive analytics are found to be twice as likely to demonstrate, as Deloitte’s defined it, effective recruiting. And you can see why the analytics – we’ll dig into a little bit of this in a minute – just really opens up new opportunities to add algorithms to instinct and intuit, and not necessarily rely on that as much but provide data that makes more informed and enables faster decisions and high quality decisions as well.
A third reason to adopt predictive analytics is to build a leadership pipeline. HR predictive analytics adopters are 2.5 times as likely to have good candidates lined up for leadership vacancies. Obviously this is critical now with the transformation of the workforce, and management and leadership skills are just in high demand particularly with the gaps in the various generations in the workforce. This is a huge opportunity and so predictive analytics can help close the gap.
A fourth reason is to make more money. Organizations whose HR departments use predictive analytics have shown to have 30% higher stock market returns and market caps than the S&P 500. Just huge opportunities. These are companies that are innovative, that are leading the charge and driving growth.
So there’s four reasons why to do it. The question we often get is: How do we do it? What are some actionable next steps? It really starts with moving towards a data-driven selection model is the key. Like other functions that have had digitized and built out a more data-driven process, the same holds true for HR.
One of the fundamental problems is where things start. As much as the world has evolved over the years, something as fundamental as a resume which is archaic is still a fundamental part of how a lot of organizations recruit. And quite simply they don’t work; profiles which are often just an evolution of a resume, even job applications which in some cases could be worse or truly archaic. They’re backwards-looking. They don’t consider much data. They’re not digital. I’m not just talking about [inaudible 00:16:51] resume to make it digital, but it’s not digital on a true form to drive big data that we can extract from that to truly drive world-class talent acquisition and talent management.
One of the fundamental reasons is that people aren’t just a resume. They are, as we like to say, not… People are who they are. They’re not just what they write. People are more than a couple bullets on a page, a couple of positions in this timeframe and a couple of skills articulated on a piece of a paper. People are voices, their experiences, potential and passion. You just can’t represent that on a piece of paper.
You’re truly empowering and engaging your people, your candidates and your employees to bring these stories to life and showcase their true skills, their true potential as really the future and the first step to going digital and creating a comprehensive and deep big data set that can be tapped into for more modern talent management.
And one of the key is to see people for who they are and look behind the resume, because otherwise people would look so generic. One of the reasons is that profile data is often very generic. By generic, it’s often not in context of a particular organization, particular position, particular culture, team [inaudible 00:18:25]. And it’s just like looking out at a rearview mirror – work history, things like references, education, [inaudible 00:18:32]. But data shows that those are not the things that matters. When you talk to managers, executives, any recruiters that are making decisions, often there’s deeper information that’s imperative. It can be for sales, for example, the soft skills. Someone [inaudible 00:18:51] engagement, [inaudible 00:18:53] communication skill all in context of a particular organization and culture and position. And that varies from organization to organization, team to team. What’s important is that there’s a fluid approach to this deeper base of information that truly pulls out, and it’s a basis for finding a better fit between people and the right jobs. This data doesn’t just come from profiles, but it actually comes from interactions.
So the new model, we break down to these four components. As we transition from and shift from a traditional model to more of a data-driven selection model, it starts with empowering people and empowering candidates to tell their story. Not just be a piece of paper that doesn’t tell you much but actually enabling them to tell their stories and showcase their true potential in a way that’s contextually relevant. And second, to showcase their true abilities and actually demonstrate their abilities to work. By doing that in a digital form, we can actually empower data-driven decisions for recruiters and managers. The key is to do this in a way that provides a totally modern, digital experience using things like digital-video, mobile, social, predictive analytics that’s a fantastic experience for everyone involved including candidates and line managers.
Every step through the process starts with displacing static resumes or resume [inaudible 00:20:40] approach with a digital approach using digital-video that captures a deeper level of interaction that allows people to tell their stories and demonstrate their ability, and showcasing these skills in a way that is contextually relevant. So if you’re hiring an engineer, it’s actually capturing how they code. Not just how they see their code, but actually how they code. If it’s in healthcare and we’re looking for an x-ray tech, providing scenarios where we assess someone’s ability to dissect that x-ray. So in a customer service role in retail or hospitality, what’s important is how that person is going to react on their feet and react to customers that may be an angry customer or may be a happy customer.
We’re looking for things like engagement, personality, ability to think quick on your feet. It’s tough to get that off of just a profile or a job application, but it’s important we provide scenarios that actually allow candidates and employees to showcase his true ability. This is true for hiring new candidates into an organization or for things like internal mobility and succession readiness since we’re developing talent for leadership roles. It’s taking a deeper dive than just asking a few questions on a static survey or something like that.
Once we do that as we start to digitize these interactions, we can then validate decisions or drive decisions through a much more meaningful dataset, and then lastly again providing this extremely modern and digital experience that just totally kicks ass and wows candidates and wows managers and recruiters and everyone involved.
A lot of folks often say, “Okay, that makes sense but what are some of the actual examples of this in action? How are companies embracing data to drive, to empower more informed, faster and higher quality decisions? So I thought we’d just take a couple of quick looks at how companies are doing.
One is adding intuition to instincts for hiring decisions. A common challenge we see is that someone will have a gut decision on someone based off of various factors. And those factors could be based on a variety of things, and how our C organizations use data is to actually prove some of those gut instincts both [inaudible 00:23:27]. When a great application is finding overlooked talent, talent that was missed, that someone perhaps rated low and we did not want to bring into the organization, but predictive analytics show that based on interactions of that candidate that they strongly correlate to the existing top performers. Because this digital data coming from interactions including things like audio, video, and word choice, word selection, it’s much deeper than often just the human eye/ear can identify. You can find talent that could normally just quickly be overlooked.
Another use case is uncovering completely overlooked talent that never had an opportunity. A recent report by the Talent Board showed that for big organizations, 94% of candidates did not even get a chance to interview. They submitted a resume often going into a black hole, and they didn’t get a chance to interview. We’ve also seen clients where maybe they got an interview, but they were overlooked for whatever reason and were not watched or rated. By using predictive analytics in showing that that person strongly correlates to an existing top performer, that someone absolutely needs to be taken a look at and it could be [inaudible 00:24:55].
For certain demographics like military veterans, working moms returning into the workforce, long-term unemployed, college graduates, often their profiles in particular can limit themselves to be easily looked especially by legacy applicant tracking systems and things like that, that unintentionally just basically overlook folks unless they have a good profile and robust data that would be in the profile or job application. So this is an area where the predictive analytics combined with video can be a complete game changer.
Another area is really digging deep to discover candidate personalities and things that matter for particular positions. A lot of organizations are drilling in to finding that their ideal profiles, what they look like for their top performers, and it varies by role. And certain roles, for example, customer service, folks are looking for people who are very even keel and can handle tough, stressful situations and predictive big data analytics takes things like traditional behavioral assessments to a whole new level, because you are able to pull this data. You don’t have to force someone to go and fill out a long survey, answer a half-hour’s worth of questions. You can just pull this information and refer it off digital and video interactions and looking at language, word choice, word complexity, audio, video, and so on and so forth to really get a deep view into people that you can’t get through resumes and the like.
Another area is deciding who interviews and also calibrating those folks. Both managers and recruiters, often are… We’re seeing clients who are finding that the people who have been interviewing and making talent decisions were not necessarily… They didn’t have the best batting average, as we like to call it, based on their recommendations and how well those employees when on to perform. Uncovering those helps organizations better to find who should interview, who should not. It also helps calibrate recruiters and managers.
These are just a couple of examples of how organizations are really starting to embrace data, big data and predictive analytics to make more informed decisions faster and improve the performance of the business. And back to the respect, what’s really needed, is it really brings relevance to HR inside the organization, able to speak the language of the business using data and quantify and deliver fantastic experience for the customer, internal customer as well as candidate, and enabling people to tell their stories and demonstrate their abilities and stand out in a way that traditional methods have not been… Data really truly levels the playing field and give a lot of folks a change that they may not often have. And companies are producing fantastic results.
I’d just like quickly highlight some more organization we’ve been fortunate to work with that are seeing some really incredible result and we’re connect with to see some of the things they’re doing on the talent acquisition and talent management front. If you have time, connect to some of these folks. They’re doing some really cool stuff.
With that, we’re just running out of time. We have about one minute left. I just want to thank everyone again for the time to join us today and explore both the current state and the future of HR and talent and how companies are embracing data and talent insights. If you’re available, on the first week of June, we’re going to be joined by a lot of these organizations who are embracing a lot of this technology and improving their process fees and to really drive digital transformation, change, and improvement in the organization. We’re going to be together in Salt Lake City, an event we call Digital Disruption. Check it out online at hirevuedisruption.com or just Google it, and it will pop up. We encourage you to reach out and connect with us. We’d love to see you there.
Thanks everyone. We appreciate you joining us today, and look forward to a lot of great presentations throughout the day. Thank you.