The perennial challenge organisations face of matching the right people with the right roles is becoming even more complex in the age of AI, analytics and automation. In parallel an increasing number of companies are turning to a new generation of assessment tools, harnessing AI, gamification and data science. Not just for hiring but to support areas such as coaching and development as well. My guest on today's episode of the podcast is Uri Ort, who is the co-founder of behavioural insights company Deeper Signals and is an adjunct instructor at NYU.

You can listen below or by visiting the podcast website here.

In our conversation Uri and I discuss:

• The key trends and evolutions in the assessment space

• We talk about personalisation, algorithms and ethics and how technology is making assessments more precise and less biased

• We look at how to measure the business impacts and outcomes of assessments

• We delve into some of the latest research findings on personality and talent signals

• As with all our guests, we look into the crystal ball and ponder what the role of HR will be in 2025

This episode is a must listen for anyone interested in how assessments can support talent identification and development as well as HR and business professionals who are interested in how technology is being used to improve hiring and reduce bias.

Support for this podcast is brought to you by Gapsquare, to learn more visit www.gapsquare.com/accelerate.

Interview Transcript

David Green: Today, I'm delighted to welcome business psychologist Uri Ort to the Digital HR Leaders podcast and video series. Great to have you.

Uri Ort: Thanks, David, great to be here.

David Green:  Could you give listeners an introduction in to you, your background and what you are currently involved in please?

Uri Ort: So I'm an organisational psychologist and I specialise in assessments. I started my career in engagement assessments, and that was really leading the engagement initiatives. So how do we take a workforce, a global workforce, and, engage them in what they're doing in all different regions and areas. That's how I got into the engagement space. I then kind of moved, well what I realised in doing that work is, people aren't engaged in the same way, right? People are different and so if we had to take an extreme example, if we had a workforce in Saudi Arabia and a workforce in Williamsburg, New York, we weren't going to use the same tools and the same strategies to engage them.

So that kind of led me to personality, individual differences, how do we look at people and customise and personalise the HR tools that we have to enhance their day to day and therefore increase organisational performance. I then moved to the personality space, I went back to school, got trained up in assessments, and now I have co-founded a company that works in talent assessments. I also teach talent assessments at NYU.

David Green: Okay. Assessment is a really fascinating area because we hear a lot about it and there's a lot of technology coming into the space as well and disrupting it a little bit. So we hear a lot about AI and gamification, for example. What impact are these developments having on assessment and more importantly, what challenges are they helping to solve?

Uri Ort:  Well I'll take the second question first.  What challenges are they helping to solve?  I think is straightforward and that is the traditional assessment space I ask you a whole bunch of questions, about 250 questions, and then I get a read on your future performance or a cognitive ability assessment, right? Where I challenge you and I get a read on your ability. I think that is challenging to the candidate and the candidate experience, and more and more we are challenged by organisations, how do I get the same outcome, the same predictions but in ways that are engaging and that actually attract talent, right? Because the dynamic of “I have a job and let's see if you can come and get it” has completely reversed itself and now it's like how do we get out there and attract the best talent? And if we have a lot of friction where we'll turn away the best talent because they have the most options.

And so I think AI and gamification really both help in creating either a frictionless experience if it's AI or at least a more engaging experience, hopefully that would be the goal, a more inviting experience through gamification. So I think that's the challenge that they are trying to solve.

I think in terms of the impact though, if anything, the AI impact has been predominantly to scare people away, if you want to be honest that has probably been the biggest impact. The idea of there being some kind of algorithm or I mean AI, even the word AI is challenging to use here, it's a bit of a buzz word, but of there being a machine learning algorithm that's going to predict whether or not I will perform well on a certain job and I'll use that to make a decision for whether I get the job or not. That's scary, and that turns people away. So it defeats the purpose of attracting talent where you find out that this organisation will automatically decide whether they hire me or not without human intervention. I think that's scary and so I think that the impact has kind of undercut what we're trying to do. But there's obviously a lot of opportunity there for enhancing it and for communicating the tools in a better way, actually using them in a better way so that we can actually attain the goal that we were going for to begin with.

David Green: Have you seen any really good examples of using either AI or gamification in assessment? Also you talked about experience, are there any examples of how that supported that kind of frictionless experience?

Uri Ort: Well, there are a number of examples out there. HireVue is a company that is doing, you would call it AI, they use video interviews and then they give you a kind of a black box prediction of performance. They train the model on future performance based on micro facial expressions. I think that would be the one of the better examples of AI out there that's both scary, but also probably accurate in predicting some level of future performance.

Gamification would be actually, so HireVue just recently purchased a company called MindX and I think they do one of the better jobs of gamification out there, because gamification has to make a more engaging and interesting kind of experience. Many of the games you see out there you wouldn't play those games if you weren't on an interview, so if that's what you're doing, you might as well just ask the candidate questions right? You're not really helping and so I think the games that are actually interesting and fun and that people will use even when they're not in the assessment experience that's the bar we have to reach for in gamification.

David Green: Assessment, obviously we hear a lot about assessments and mostly people associate assessments with hiring, but I know, and obviously you know that there are many other parts of the employee journey and coaching and development that they can be used for. Have you got some good examples of how that can happen and why it's important that we don't just think about them for hiring?

Uri Ort: It's actually an area that I'm quite passionate about. If you think about the assessment industry at a high level now. Right? The biggest focus is on selection, that's where 80%, maybe even 90% of the assessment industry is either on selection or maybe coaching at the executive level. C minus one or C minus two. Right?

However, if you hire the best talent and you can't engage them and you can't develop them, you will lose them and in fact, you'll lose them faster than you'll lose the worst talent because they have the most options, right? So you spend all this time and money selecting and maybe accurately selecting the best talent and then they're gone the next year. It's nonsensical to use assessment and essentially understanding to select the best talent and not develop them. Personality should be used for more than just the binary prediction of performance, right? The real value in psychology is to help people understand, help them understand themselves, help them understand others, right? And that's really what we can bring to the table to make people's lives better. You can almost say most organisational problems are people problems and most people problems are related to a lack of understanding. People don't understand themselves and organisations don't understand people.

If we bring assessments to the table, be it AI, gamification, or even traditional assessments in a way that's scalable, that everyone can use them and understand their own dispositions better and understand their employees and their teams better, I think we would have a really really big win.

David Green:  We hear a lot about companies going through a transformation at the moment, developing new products and new services, and they have a challenge identifying the skills that their people have got because they don’t necessarily have the data on it. I guess assessment can be a good way of identifying the people they’ve currently got in the organisation who maybe already have some of the skills that they're going to need more of.

Uri Ort: A thousand percent yes. Especially the soft skills, I mean, the hard skills are a separate problem but similarly organisations often don't know what they have. But soft skills are probably harder to detect and therefore harder for organisations to understand. For example I have this team and I really want them to innovate and they are supposed to be my innovation team they’re my disruption team, and they're just not doing it. Nothing's coming out of the team, and if you can't look at the profiles and understand why then you're really just blind. Imagine a world where you had an organisation maybe a large 250,000 person strong organisation and you have a dashboard where you can just search David Green and you can see this is what David is really good at it, super curious, super irreverent, disruptive.

David Green: Have you got any good examples of companies that actually are good at doing assessments on people that are currently within the organisation and how they've used that to either move those people forward and support business outcomes as well?

Uri Ort:  Well, business outcomes are a challenge to identify with these things, right? You're in HR, and I'm sure you've heard that before. You're trying to push the new initiatives, be it engagement, and the CFO or the CEO is like, well, what's my ROI? That's going to cost me a half a million dollars to implement and what am I going to see?

So I think there's an element of I'm trusting the science here. When it comes to measuring outcomes, it will take two or three years to see a reduction in retention levels and an increase in engagement and for it to hit the stock price, but you kind of have to trust that we've done a lot of research and we know that these things do matter. I think it's actually hard, you know, it would be hard pressed for me to point an organisation that's using assessments today at scale, at the level that I think is ideal, where everyone understands their profile. Most organisations are using assessments at the top of the house but there are a few that I think do it really well. I think Pepsi does really well and you get to a certain level and you take an assessment and you take a more complex or longer assessment as you get more senior. So I think there are organisations that are doing it but it could be a lot more widespread, It's an easy tool that we have at our disposal that I think HR should probably take advantage of.

David Green:  So in short, HR could do better?

Uri Ort:  Yeah. Yeah, I think HR could be doing a lot better in this space.

David Green:  Okay. So we've got to carry on playing buzzword bingo a little bit here. So we've talked about gamification and AI, and we're going to talk about personalisation, another much hyped term, but I think a good term that we're starting to see more of in HR. I mean we're seeing it a lot in relation to new technologies and everyone's talking about bringing Netflix like technology into HR, but how can you personalise assessments so you can help make interventions for leaders, for managers, for the workers.

Uri Ort:  It's interesting because my background, before I got into psychology, was is in eCommerce where a big part of the focus there is the user interface. How do you convert a browser into a sales or a customer, right? You have all this kind of nudging going on, you don't see the same advertisements on Google that I see. Right? So our entire world is personalised except for in HR and the workforce. There is basically one size fits all solutions for everything, so we have a way to go there as well. There's, there's clearly a lot for us to learn from industry, and I think the way to do it is to use assessments to understand how to personalise. The assessment itself can be personalised but that's the last thing I think to be personalised, the first thing to do is to give everyone an assessment. It's got to be the kind of assessment that's scalable, and then use it to start tweaking the engagement solutions. It can be everything from my job design to the salary, what motivates me, maybe I'm really commercially motivated and I need money. Maybe someone else is really purpose-driven and for them, we can give them a day off a week for the same price to go work in a homeless shelter, and that'll motivate them and engage them. So I think the personalisation of job roles, job design, HR initiatives, platforms, can be transformational if we properly understood our workforce on an individual level. Then yes we have the technology and the tools to personalise almost every single part of the work experience.

David Green:  I guess what it's about is the deeper we understand our workforce the more we can personalise and offer them stuff that's relevant to them, i.e benefits as the example you gave then, but also I guess interventions to help them be more productive, help their performance, help them help their careers within organisations as well.

Uri Ort:  Yes and you talk about AI, right? So let's think about, you have a problem, you have a respect problem in an organisation, let's take the me too movement, because we are doing buzz words right? So you're trying to do training on respect and diversity and inclusion and so you have this intervention. But if you understand that different personalities are different you can tweak the interventions for different groups of people. Some people have respect issues because they are too brash, they're too bold or they need to be coached and developed in a different way but then you also have people who have respect issues because of the opposite, their personal disposition is to be more leisurely and more withdrawn, more passive aggressive. If we had tools like an Apple watch that had an AI that was nudging us and recognising that your pulses has been up for the last hour so you're clearly upset today and you're anxious today. It would prompt us to take a deep breath? Be careful when you have your meeting with your direct report Ernie because he's stressed today and his personality is like this and you want to treat him in a certain way.

That's a really beautiful marriage between AI and the kind of interventions that we can do in a personalised way.

We're doing these things for exercise, and if you've got a company like Apple and Google behind it, and everyone is doing it like, oh you know, it's 11.45 at night and I didn't finish my circles yet and everyone's running around trying to burn 20 more calories. We're doing it we just have to apply it to our field.

David Green:  I think it's all about mindset and opening our minds a little bit more than we have in the past.

Okay, so we've talked about how we're effectively collecting more data to help personalise interventions for employees and hopefully identify what benefits will apply to them more. Obviously collecting more data we need to really make sure that we gain employee trust and the more data we collect about individuals, the more nervous individuals get as well. There are lots of concerns about ethics and trust not just in the workplace we've seen this outside in the consumer space as well. How do you believe that organisations can gain and manage employee trust within the workforce?

Uri Ort:  I think it's an important question. What we've seen outside of HR in the real world is organisations collecting an enormous amount of data. So we give it to them, right? A lot of the conversation is around what do we get in return, how do we give something back to us to make it valuable? Because it is a trade off. As the famous line goes, nothing comes for free. So I think in organisations, the dynamic is actually a bit different because organisations actually own all of our data or a good portion of our data. So when we log in at work now and we're emailing and we're chatting and we have user interface, we're moving our mouse, all of that information is essentially collected and owned by the organisation. The key question is, in order to get the buy in so that we don't seem like creeps in monitoring the information and using it to increase organisational performance is the same as industry. We have to give something back to employees so that they feel like they are getting something in the bargain.

I think that really goes back to a lot of the things we've been talking about. If as an outcome we make the work experience better for them, we help them fit into their job roles and their job design better, we give them better salary and benefits that fit their needs, their teams are working better, they understand themselves better. If we were really open around, this is the information we're getting out, what we've learned about you is this, and the reason why you often come to work on a Monday and feel like you're digging yourself out of a hole is because maybe you were really, really low on diligence and you can use these strategies to approach that. I think employees would feel more open and they would feel like they are getting something in the bargain.

I think to me that's where the key is in using this information. We have to genuinely use it to help employees, not to help the organisation and then everything will follow from there.

David Green:  I don't know if you've seen the Accenture research that they published back in January around the Davos conference they actually did a big piece of research and 92% of employees that responded to it said that they were happy for their organisations to have their data providing they get something in return. I think it's that trade off that you were talking about there. You mentioned around organisations using and owning mostly the employee data. Do you think that might change as we move forward?

Uri Ort:  Yes I absolutely do. I think organisations will always own it but in part of that trade off.

So what happens, thinking about the career journey, you leave college, you start one role and then especially these days, three, maybe four years later you’re moving into another role and you will pretty much have that revolving door throughout your career. In each organisation you start at the ground floor. You may come in with a different title, but your reputation has to be rebuilt. Also the stakeholder buy in, the trust that your team and your seniors have in you has to be re built, I think more and more what we will start seeing is owning the reputation and the performance that you have had in your previous organisation and taking it with you to the next organisation.As long as we can create some kind of consistency of data be it performance metrics or other tools, there was a lot of conversations around this during the Bitcoin cryptocurrency 2018 boom, maybe that has died down a bit now. But there is good application there where if we can have some kind of consistent language across organisations I would want to own that data. What happened to all the great performance reviews, maybe it was an employee motivation program or accolades or something that I got from my colleagues. Where did it all go when I left. So I think we should aim to transfer that information to the employee and allow them to take that with them.

David Green:  There definitely seems to be a bit of a movement around the ownership shifting towards the employee, individual worker, and then the individual giving access to the organisation or organisations they work for at the time, access to that data. So it'd be interesting to see how that evolves over this time. I know you mentioned the crypto stuff, I've been speaking to people that are heavily involved in Blockchain and they said that potentially is something that could happen with Blockchain technology is that effectively the shift in ownership comes more towards the employee.

Uri Ort:  Yes and the gig economy as well. You have lots of, I can't remember the number off hand but a large segment of the workforce is involved in the gig economy at the same time that they are in the traditional workforce. So how do I get that information?

I've got now 15 glowing reviews and in fact the dynamic is that I don't want to tell my manager that I'm doing this work on the side, so I keep it a secret versus saying, well I have a whole reputation on Upwork so how do I move that into some coherent language so that I can then use it to my advantage.

David Green:  I will be fascinated to see how it evolves. Let’s move on to another trade off now, so this is the trade off between using algorithms, because there's a lot of hang ups around using algorithms and everything else. There was the example of the Amazon one that was mentioned last year, I always say actually kudos to Amazon for actually validating and checking that it wasn’t fair. But we make bias decisions every day as individuals, whether they're conscious or unconscious. Now how do we manage the trade off between relying more on algorithms to hopefully eradicate, maybe that's a bit too ambitious, but certainly in a way to eliminate or to reduce bias.

Uri Ort:  I think a good place to look for the answer to this is the self-driving car industry. It's a really good place to look at because there you also have incredible algorithms and huge advancements in making decisions. So it's very similar to the selection process of an AI having to take a lot of data and information and make some kind of coherent sense and make a decision, thousands of sequential decisions and you still have a human involved in that process. So what you're really saying is augmented, I’ll augment the human capability with the AI, I think that'll be the model for us. What we want is AI to help us recognise bias and correct us, we don't necessarily want to move over completely to AI a black box algorithm that makes all these talent decisions for us as there are a whole bunch of potential pitfalls there, it may have similar biases which will be hard for us to detect. So I think the best is where we have an AI augmenting our capability and saying, are you sure you don't want to hire this person? What's your reason? This is their talent profile. Here's their reputation.

Actually, my algorithm is saying she's a go, maybe the reason why you're not hiring her is because she doesn't quite fit your profile of a macho, super confident male leader. It shouldn't be that hard because the biases as you know, HR biases are pretty superficial and easy to understand the tech. It’s a halo bias, It's a like me bias, so we can easily program algorithms to detect those and give us a warning flag.

David Green:  I guess it's also about checking the validity of assessments, checking the validity of algorithms as well, continuously.

Uri Ort:  Yes I think so. However, we don't need AI for that. So we need to do the assessments and there's a whole bunch of tools out there that are being used that I'm skeptical of how valid they are. So yes, it's super important that we do those kinds of checks. But that's even easier, that's just putting it into a regression model, collecting some data and checking if it has an adverse impact. The ownership is really on us and on the organisation and HR to really vet a lot of these new tools that are coming out that seem really cool and the UI and the design is really exciting,

but the science has to be really sound as well, it can’t just reflect our own biases.

David Green:  They would need to do some controlled experiments first before they roll it out across a whole 250,000 person company.

Uri Ort:  Yeah and it's a performance issue, isn't it as well. So it's not just the optics and not just the the legal liability, but your goals for the organisation will probably be impacted because you'll end up with talent that can’t properly perform. There's a reason why D&I initiatives help not just ethnic diversity but also cognitive diversity. It's also are you going to hire everyone who is one specific type of profile created by one leader, and if you do that you probably will see an impact on performance.

David Green:  On that subject we hear again a lot about teams now. A lot of work in people analytics is being done around understanding teams, successful teams versus less successful teams. I guess that's something assessment can really help with, as you've talked about getting a cognitively diverse team.

Uri Ort:  Yeah. I think the reason why we're seeing a lot of research around teams because we're working in teams so much more and it's becoming more and more important to design teams with processes that actually helped them accomplish the task. So again the traditional assessments model doesn't really work very well for that because the model there is, I will create a sales profile, I will create a driver profile and then I will just hire and hire and hire.

Whereas what we need to think about is I'm going to have a team of six people and I need at least one person who's super diligent so that they can manage process and make sure everyone stays on task. I need at least one person who's a rule breaker, who can cut through all the political mess in the organisation and step on toes and get things done, and I need one person who maybe is really, and I'm simplifying things right, but really agreeable and will help the team patch over some of the discord or some of the storming phase that might occur in the beginning? So when we think about it like that we can make really high performing and high potential teams.

David Green:  And I guess as teams become more cross functional as well, rather than just saying that we need someone from sales, someone from finance, someone from marketing, it's actually not just about what they do it's how they do it.

Uri Ort:  And that's a great point because teams are become more dynamic so it's not just that I'm going to create a team and now I'm going to use this team for the next couple of years, but because people are moving around so much I'm constantly recreating and creating new teams and change is happening at an ever faster pace in organisations. So I have a new initiative tomorrow, and then the next day I have another big initiative and there's a fire now that has to be put out there. If I can just think about the cognitive as well as the hard skills that I need that would be huge competitive advantage.

David Green:  So we talked a little bit about the business value of assessments, but how do organisations actually measure that and the impact, not just on financials, but also culture, performance and wellbeing.

Is there a secret sauce to doing it?

Uri Ort:  Two answers to that question. The simple answer is assessment and it sounds funny because the assessment and then again assessment. But there are different assessments and so if you can deploy these kinds of initiatives and then you can measure overall wellbeing, you can obviously measure engagement.

There's a bunch of really great engagement tools, that's one of the areas of assessment that I think in the last couple of years we've seen companies like Culture Amp and we've seen some great progress in that space. So you can measure culture and wellbeing and engagement and you will see an increase if you are properly deploying and developing talent. That said there are also magic sauces because things like passive analysis of text, email sentiment, chat sentiment, those are some of the better applications for, not AI, but natural language processing or natural language monitoring to measure and you can do that pretty fast. So if you've got it set up you'll start seeing increase in overall positivity and positive sentiment in the organisation.

David Green:  Yes and I think that you can use assessments to understand our workforce better, but as you said we can also use text, use more sophisticated engagement tools to understand the impact of some of this stuff as well.

Uri Ort:  Which is super interesting. It’s a cheap, fast way of doing it, which is what you really want. Because when you're selling these initiatives you don't want to have to say in three years from now when you may no longer be the CEO and you probably will no longer be the CFO we will have an increase. They're looking at you and they're like, yeah, but I don't care I want to see what's happening in Q4. Whereas these kinds of monitoring tools might give you dividends much faster.

David Green:  You mentioned that you were on the eCommerce side for a while and we are just playing catch up with marketing really.

Uri Ort:  Yes a thousand percent yes. I think HR in a sense is too often just playing catch up with technology that are already implemented in other industries. So yeah, all of these tools, far more complex levels are in marketing. There are companies now that are helping websites be completely dynamic, not just in advertising, but in the whole UI. For example I come on the first time and they get a read on me, which is not a personality read per se but it is a read,

and then the next time I come onto the website they already know, don't show me this tab, don't tell me the side navigation, show me the top navigation, et cetera. These are amazing technologies that we can be leveraging.

David Green:  Obviously you do some teaching at NYU and some research there as well. I think it would be really helpful if you could share some of the insights from the latest research you've been doing around personality and talent signals.

Uri Ort:  Sure. The main focus of our recent research has been passive talent signals and also understanding how we can profile people without any kind of intervention or disruption. We've seen how you can use text to get a pretty good read of someone’s personality, we did that on Facebook so similar to some of the stuff that we've seen in the news, we were actually doing it at the same time. It's quite impressive and it's the application for us in HR is obviously more using texts that's internal to the organisation versus social media type text but we've gotten pretty good read from there.

We've also got some good reads on likes and personality. So what you like on Facebook and how that predicts the dark side of personality. So that's when you're looking at risks, where do you derail? when you're stressed where will we see the most risky kind of behavior and hotspots?

So that has been the primary area of our research and we've also been looking at adjective assessments, and that relates to our work as well. So how can we move away from questions that can be subject to different contexts and different interpretations and get old and just look at if I choose different adjectives to describe myself or other people, how does that profile personality?

That research as well shows that you can get equally as good of a read of the five factor model in personality from having people identify themselves based on different adjectives, single word adjectives than you can by asking them a long questionnaire.

David Green:  For those that don't know what is the five factor model?

Uri Ort:  So the five factor model of personalities is probably the most scientifically founded model of personality out there. There are lots of models that are based off of it, either lower or higher than the five primary factors. That's ocean, so it's openness, conscientiousness, extroversion, agreeableness, and neuroticism, or stability.

You've got lots and lots of good models based on the five factor model but in science, when we talk about it, we're always referring to the five factors.

David Green:  So it's a fascinating area. Looking at things like Facebook likes other companies have got themselves into a little bit of trouble, but it's probably not from actually doing the analysis but more who they sell the data to and what that data is then used to do.

Uri Ort:  Yeah, I think so. Again it goes back to the trade off. Do I really care if someone looks at my likes on Facebook? I know I liked it and it's public information and is it really surprising to me that someone who likes anime and nine gag and various others is probably a lot more introverted than someone who likes sports and basketball games and rollerblading. It's pretty intuitive actually, that these likes can predict personality there's nothing inherent in the science that's surprising and the way I often talk to my students about it is, when I come into class and the first class or two, I usually give them a personality assessment and there's a period of ice break, which is like, Hmm, do I want everyone to see my personality assessment? Is it confidential? The reality is we're signalling our personality every day, all the time, so we never stopped. When we do it intentionally, we want people to understand us and know us are constantly getting signals, and that's how we're trained. So it’s no secret our personality is actually on display all the time but now we're learning how to quantify it to help you, and in that sense this research can be really valuable.

David Green:  That's the trade off that we were talking about. I think that this is probably a topic we could do a whole podcast on, but are you using some of this research in your work at Deeper Signals? It'd be interesting to know a little bit more about what you're doing there.

Uri Ort:  We absolutely are. The main objective of our work is to make assessments more usable for development, as we were talking about, and make the experience more engaging and interesting so that it can be deployed at scale so that it's actually used to help employees at a much larger volume.

Our adjective type assessments we're focusing those on those particular signals, I think that helps the whole experience of assessments. As well we're working with some organisations on the passive stuff as well and that would be just looking at the data Lake that organisations have and thinking about it through the lens of personality profiles. So at a high high level is your organisation more introverted or extroverted. Then looking at a slightly lower level, maybe regionally or functionally. Do you have the right personality profiles in the right teams? So those are the two areas of the research that work really well with the work that we're doing as well.

David Green:  What are some of the data sources that you would use on the passive side?

Uri Ort:  Email would be an ideal source. Email or chat would be an ideal source.

David Green:  So it's quite fascinating because I do a lot of work around organisational network analysis and the passive side of that is looking at email. Its not necessarily the content it is looking at the metadata.

Who sends messages to who, how strong the nodes are things like that. This sounds more like it's looking at the content but presumably at a company wide level. So you are actually not specifically getting down to the individual level, but you're looking, as you said, in to how introverted a company is.

Uri Ort:  Yes so it has to be anonymised for sure from the individual level. You're not just reading someone's emails and thinking hmm this seems like that kind of person. Even the content itself can be turned into an algorithm so not even the algorithm is not looking at the text. It'll first go through a sentiment analysis and it'll go through other analyses, and then we'd look at the data and then we can kind of factor it into different kinds of profiles.

David Green:  That's fascinating stuff because I know that Textio for instance, is now being applied to email. It's helping people construct better emails too, which I guess lends itself to some of the stuff around influencing and stakeholder management and stuff like that.

Uri Ort:  Well you will know the person who you are emailing, right? So then you can kind of coach them, like that's someone who needs a lot of context versus that's someone you just want tobe really blunt with.

David Green:  Gosh it really is a fascinating topic and what an insight. This leads on very nicely to our final question that we ask every guest on the show, and you can feel free to go beyond 2025 if you want, but what do you see the role of HR will be in 2025?

Uri Ort:  Okay. It's easier if you say 2050 because I know no one will come back in 50 years and correct me.

David Green:  That's true. That's true. It is a bit close.

Uri Ort:  I think what I hope is that the role of HR in 2025 is to use the enormous amounts of data that we have to make smarter workforce and people decisions. That's what I would hope. I can't say If you asked me to predict if we'll actually get there, I don't think that we will as it moves slower than we'd like, but that's what I'd hope. I’m not going to go into Terminator type, in 2025 it'll all be gig economy and everyone will be working from their little pod with VR glasses, I don't think so. I think it'll be a somewhat similar set up to what we have today. We are moving towards a more employee focused or employee centric work environment or moving towards a more gig economy. It'll have some changes into the processes and how we hire and how we promote but at the highest level, we have this huge opportunity to take the data that we have, turn it into personal insights and help people. I hope that HR can actually live up to that.

David Green:  So what we probably need in HR is a little bit more courage, a little bit more vision.

Uri Ort:  A little more disruption, more psychology, become less transactional and really buy in, right? That's on us to get that buy in but we always end up at the mercy of how much does the organisation blanket invest in the initiatives we come up with and so we have to really sell that strategic value in the plans that we have on why it's important that we get that buy in.

David Green:  Fantastic. Well Uri thank you very much for coming and being a guest on the show.

How can people stay in touch with you via social media and also learn about the stuff you're doing at Deeper Signals?

Uri Ort:  LinkedIn is probably the best way to get in touch with me. So it's Uri Ort on LinkedIn. I'm also on Twitter and email as well, If you go to my website www.deepersignals.com you can email me.

David Green:  Perfect well thank you very much again. It's been a pleasure.