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What Do People Really Want? · Humanity Working

0:06
SPEAKER_02: But I think in the next 10 to 20 years, you will see more people having multiple jobs uh rather than the same one single job nine to five, five days a week.
0:18
SPEAKER_02: It's gonna look like maybe three days, one job, two days, another job.
0:21
SPEAKER_02: It could be three days, one full-time, one job, and then one day each with other companies or with other things completely.
0:29
SPEAKER_02: And that is not driven by money, by the way.
0:31
SPEAKER_02: The other two are not driven by money.
0:33
SPEAKER_02: They're driven by your individual passion.
0:37
SPEAKER_01: All right, today I'm joined by Sharek Shaikh.
0:40
SPEAKER_01: And Sharek is the founder of Clever X, a platform that powers market research teams by providing them with access to the tools and hardest-to-reach commercial audiences.
0:49
SPEAKER_01: The company's platform allows users to build a network with business professionals and fellow entrepreneurs via video calls, enabling entrepreneurs to avail expert advice and grow their businesses.
1:01
SPEAKER_01: Before becoming a tech entrepreneur, Sharek worked with Gartner.
1:05
SPEAKER_01: And many of you obviously will be familiar with them, but they're considered to be the top technology research organization in the world.
1:11
SPEAKER_01: He assisted them in developing initiatives that enable technology leaders from many industries to work together in a secure environment.
1:19
SPEAKER_01: So welcome to the podcast, Sharek.
1:21
SPEAKER_01: Thank you so much for having me, Braun.
1:22
SPEAKER_01: Pleasure to be here.
1:24
SPEAKER_01: All right, let's start with something nice and easy.
1:26
SPEAKER_01: What gave you the idea for CleverX?
1:28
SPEAKER_02: Oh, that's uh yeah, that's that's a pretty good question.
1:31
SPEAKER_02: I think uh it all started when I was working with Gartner.
1:35
SPEAKER_02: And uh as you rightly mentioned, it's one of the most uh you know leading technology research companies.
1:41
SPEAKER_02: And we had access to some incredible people uh, you know, who were analysts at Gartner, and the job is to work with CIOs or CTOs and head of technology departments in the largest companies, governments all around the world, and help them make informed decisions about investments in technology.
1:59
SPEAKER_02: But the big component of their value proposition is also research.
2:02
SPEAKER_02: So Gartner does a lot of research where they conduct online surveys, you know, connect with uh very senior business professionals to get their insights and then they translate all of that into trends and uh you know different research methods and pass on those findings to their customers.
2:19
SPEAKER_02: Customers use those findings to make those decisions, right?
2:22
SPEAKER_02: So imagine if you're a CIO of a bank, you would want to know what other banks or their CIOs are thinking about investing in the next two to five years.
2:30
SPEAKER_02: So it just gives you a good picture in the future and you can make decisions based on that.
2:36
SPEAKER_02: For me, that was very intriguing.
2:37
SPEAKER_02: I've never heard of Gartner before before I joined Gartner, right?
2:40
SPEAKER_02: I didn't know what they were doing, right?
2:42
SPEAKER_02: So I was getting ready for the you know the interview process and things, and then I just entered into a world where um I could see you know how research market research really works.
2:52
SPEAKER_02: Uh, I come from a technology background, so I'm a software engineer by trade.
2:56
SPEAKER_02: So for me, um that was like a learning where how could I bring you know technology and market research together?
3:04
SPEAKER_02: And we wanted to make sure that uh when when when I wanted to start CleverX, the idea was Gartner is great, but it's it's only you know, it can only be used by the top three to five percent companies in the world who can afford Gartner, right?
3:19
SPEAKER_02: But the rest of the world does things on LinkedIn, right?
3:22
SPEAKER_02: So if you want to conduct an online survey, you go on LinkedIn and find those 100 people that you want to uh interview in an online survey or you know, conduct qualitative calls with them or research interviews.
3:33
SPEAKER_02: So there was really no good way of doing it.
3:37
SPEAKER_02: Um uh and and the the way things are done in the market research industry, especially when it comes to business-to-business market research, has not changed in the last 50 years.
3:47
SPEAKER_02: Uh, and we wanted to bring a new novel approach to it.
3:49
SPEAKER_02: So we built a platform which looks very much like LinkedIn with thousands of senior business professionals on it, people who work at the White House to people who work at Apple.
3:58
SPEAKER_02: Um, and you have the ability to direct connect, directly connect with them and engage with them for research purposes.
4:04
SPEAKER_02: Uh, and I think that that that giving that platform to people who can't afford a company like Gartner or McKenzie, you know, in consulting would was our our segue into that space.
4:16
SPEAKER_02: So we we we are kind of somewhere in between rather than you trying to use LinkedIn to do it, which is not the best experience.
4:23
SPEAKER_02: I'm sure a lot of your audience would understand what I'm talking about, because if you reach out to 20 people on LinkedIn, there's a the the chance of getting one acknowledgement, there's a chance of only getting one acknowledgement out of 20 emails that you send.
4:36
SPEAKER_02: That's actually legit numbers, you know, if you run experiments.
4:39
SPEAKER_02: Um, and then on the other side, you can't afford a company like Gartner to conduct research or a big large enterprise market research company.
4:46
SPEAKER_02: So you wanted to give something in the middle and where even smaller researchers, you know, small research firms or you know, an individual market researcher can come to the platform and conduct the research process instantly rather than relying on third parties to get that work done.
5:00
SPEAKER_02: So it's been a pretty exciting journey for us in the last three years.
5:03
SPEAKER_02: The company has grown its revenues by leaps and bounds uh in multi-million dollars.
5:09
SPEAKER_02: Uh, and uh we have some of the largest uh you know brands uh research powered through our platform from Google to TikTok to Twitter in technology or research companies like Ipsos, Cantar.
5:22
SPEAKER_02: Um, you know, those companies use Claverex to conduct research.
5:25
SPEAKER_02: Yeah.
5:27
SPEAKER_01: Fascinating.
5:28
SPEAKER_01: I know that this is a field that is really starting to um to heat up a little bit.
5:35
SPEAKER_01: Um and we've you know, for years and years and years there's been uh consumer-based uh research, and it's a very uh mature field.
5:45
SPEAKER_01: But the the whole business-to-business uh research um is something that is a re is a relatively new field.
5:53
SPEAKER_01: So that leads me to kind of my second question, which is that um let's say that you've got uh an individual who's trying to trying to use your platform and they've got a specific set of questions that they need answered.
6:08
SPEAKER_01: Um how are you uh how are you helping them get the answers to those questions as quickly and as efficiently as they could possibly can?
6:16
SPEAKER_02: Yeah, that's a very, very interesting question.
6:18
SPEAKER_02: Um the the the biggest thing that we learned while building this company, a lot of people in your audience probably wouldn't know this.
6:27
SPEAKER_02: Almost 40% of the data that a company, research company gets out of an online survey is fraudulent.
6:36
SPEAKER_02: And this is not us saying this, this is SMR, which is one of the largest, you know, um nonprofit organization in the market research space has analyzed multiple data points to figure that out.
6:50
SPEAKER_02: Now, when um you know people come to a platform, usually they already, you know, they they've already programmed a survey or they've already thought about whom they want to interact with.
7:01
SPEAKER_02: What happens is when you when you go on the platform, you can very transparently know real identities of professionals and you know whom you're gonna talk to, be it a qualitative research interview.
7:12
SPEAKER_02: So people usually have that information already in place, like what are the questions I'm gonna ask?
7:16
SPEAKER_02: But there's a chat feature on our platform, which is free, by the way, for every user, so they can connect with each other and they would generally ask those questions in the chat, like, hey, I have these five questions about this topic.
7:26
SPEAKER_02: I know you work for this company, would like to pick your brains on it.
7:30
SPEAKER_02: And that person might respond back to you and say, like, hey, I can answer three questions, the other two questions probably are not uh something that I'm great at, you know, giving you insights about, but at least you get into a conversation with a set expectation.
7:43
SPEAKER_02: When you use the other alternatives like the expert networks, you don't even know whom you're talking to.
7:47
SPEAKER_02: So there's no visibility on the person that you're going to be connected to, and you don't get the ability to ask questions before you interact with them.
7:54
SPEAKER_02: So that's a very different industry altogether when it comes to um you know these video research interviews.
8:00
SPEAKER_02: On the other side, which is these online surveys, um, people usually uh our tool is very um the platform is very tool agnostics.
8:09
SPEAKER_02: What I mean by that is you can program a survey on Caltrix or on ConferMet or FourStar, these are large online survey creation tools, and you can just directly connect it to the audience on our platform.
8:20
SPEAKER_02: So we are like an audience discovery platform.
8:22
SPEAKER_02: So you can bring your survey, connect it to the audience, a known audience, and you know exactly whom you're gonna ask to participate in an online survey, which doesn't happen in the traditional world today.
8:33
SPEAKER_02: So even the research isn't doesn't know who's taking which survey.
8:38
SPEAKER_02: So when you go to your customer or your board to share that information saying, like, I got this out of 500 CIOs who have given me this response, you have no idea are they really those 500 CIOs that you got solved for, right?
8:53
SPEAKER_02: And that's the problem we're trying to solve.
8:55
SPEAKER_02: So going back to the question about how do we help them, we are building this, uh we're getting into the segue around AI now, where the AI would be able to look at your project and give you or throw up some questions to say, like, hey, did you incorporate these questions uh in your research, like you know, in an online survey or in your video interviews that you're gonna do?
9:18
SPEAKER_02: What are the questions that are good, what are bad?
9:21
SPEAKER_02: So things like that are gonna become a norm in the market research space.
9:25
SPEAKER_02: Uh already companies like Qualtrics are working on it where you program a survey, let's say you're doing a survey for truckers, right?
9:31
SPEAKER_02: Just a random example.
9:32
SPEAKER_02: What are the kind of questions you should ask?
9:34
SPEAKER_02: So they've got all this data for decades probably, and they're gonna use that data to recommend certain questions.
9:42
SPEAKER_02: So the job of the market researcher becomes easier to put those questions or improve on their questions in that online survey.
9:48
SPEAKER_02: So I think we're heading into this direction where these systems will recommend and suggest you a lot of things that could make your job faster and easier, and even the quality of the insights might improve out of that.
10:02
SPEAKER_01: Yeah, you're touching on an area that I actually want to go into a little bit more deeply, which is what constitutes reliable data, right?
10:12
SPEAKER_01: You've you talked about one aspect of that, which is um which is talking to people that are actually real people.
10:19
SPEAKER_01: I think that statistic will surprise um will surprise and alarm alarm quite a lot of people.
10:25
SPEAKER_01: Funnily enough, it's a stat that I just heard a couple of uh a couple of weeks ago, but it surprised and alarmed me when I heard it.
10:31
SPEAKER_01: Um and so that's one aspect of it.
10:35
SPEAKER_01: But to me, when I think of reliable data, I'm not just thinking about whether it's the genuine answer of genuine people.
10:44
SPEAKER_01: What I'm thinking about is almost like the like is it useful, actionable data?
10:50
SPEAKER_01: Or in a sense, is it is it something I can rely on to help me make business decisions?
10:57
SPEAKER_01: So when you think about reliability from that from that perspective, what do you believe constitutes reliable data that I can actually act upon?
11:06
SPEAKER_02: See, there are two ways to look at insights.
11:10
SPEAKER_02: That's how you have the qualitative and the quantitative methods.
11:12
SPEAKER_02: Um when you want to go deeper on a specific topic with a few individuals, uh, and that's your goal of getting an insight.
11:21
SPEAKER_02: So let's say you have an understanding of a particular, let's say you're trying to understand what is hype versus reality in the world of AI.
11:30
SPEAKER_02: You're a researcher, you want to figure that out.
11:32
SPEAKER_02: What you want to do, you you'll have like some basic information about what are the things that are applicable in that world of AI that is happening right now, like what can ChatGP2 do versus what it cannot do.
11:42
SPEAKER_02: You have a basic understanding.
11:44
SPEAKER_02: What you want to do is talk to 10 people who are working with OpenAI or similar companies to understand what's hype versus what reality, what is visual thinking, what is actually possible by this technology to accomplish in the next two to five years.
11:58
SPEAKER_02: So you do those interviews to get very specific insights, go deeper on that topic.
12:03
SPEAKER_02: When you're looking at um collective intelligence, which is like a bunch of people, hundreds of people, how do they think or what direction they're thinking into?
12:13
SPEAKER_02: That's when you get into quantitative.
12:16
SPEAKER_02: So, for example, I want to know what does the sentiment look like for the SMB sector in the US in 2024?
12:25
SPEAKER_02: What are like the senior execs in the SMBs are thinking about business around risk and revenues and growth?
12:32
SPEAKER_02: Um, you want to do an online survey because that gives you a good indication.
12:36
SPEAKER_02: So even if like individually one person's data is not that reliable, the overall collection is a good indicator for you to find that reliability in making that decision.
12:48
SPEAKER_02: And I think that's a huge distinction when you're trying to do a project or when you want to decide what path to take.
12:55
SPEAKER_01: How do you deal um with I don't know, the the human human nature, cognitive, uh I mean broadly captured as c as cognitive biases, I guess you could call it.
13:07
SPEAKER_01: Um I've been thinking about this quite a lot recently because we had um uh just very recently um on our podcast, um we had a guest, uh Zach Ratner.
13:20
SPEAKER_01: And um and Zach was was talking about at one at one point we were talking to him about how you go about gaining or understanding negative sentiment, negative sentiment towards a a product or a service, right?
13:31
SPEAKER_01: Really hard to do.
13:32
SPEAKER_01: And one of the reasons that it's really hard to do is because the vast majority of people, if you uh you if you ask them for sentiment, they don't want to tell you that your idea sucks, right?
13:43
SPEAKER_01: It's the calling your baby ugly problem, right?
13:46
SPEAKER_01: So they don't they don't want to look you in the face and tell you that they think your idea is really stupid.
13:50
SPEAKER_01: There's very people few people that will do that.
13:52
SPEAKER_01: And in fact, in many cases, uh the collection of people that will do that are people that have a strong bias themselves towards providing negative feedback.
14:01
SPEAKER_01: Whereas there's a whole group of other people out there that might think your idea sucks, but you're never gonna hear it, you're never gonna know about it.
14:08
SPEAKER_03: Yeah.
14:08
SPEAKER_01: Um and so Zach proposes some some techniques, but I'm I'm curious as to how you're dealing with the fact that ultimately you're dealing with a collection of human beings and that and that set of human beings are gonna be wired in a certain way in terms of the type of feedback they're likely to give you versus the type of feedback they're like to hold back.
14:28
SPEAKER_01: Is that around how you frame questions?
14:30
SPEAKER_01: What is it exactly?
14:31
SPEAKER_02: Yeah, I think uh one way I've seen research companies do that is um let's say they're contacting an online survey too and they want to make sure that they're not gonna fall fall into the trap of cognitive bias.
14:42
SPEAKER_02: Uh they repeat questions, but they frame it differently multiple times.
14:47
SPEAKER_02: So, what they want to do is like ask you the same question in two or three different ways within the same survey.
14:52
SPEAKER_02: And if that is consistent across those two, three times that you've been asked that question, they know that you genuinely have uh uh you know a feedback that you are sure about, and you're not just saying something because it hit you in in a certain way, like one question.
15:09
SPEAKER_02: So they try to validate in multiple questions, uh, but just framing them differently and get inference out of it.
15:16
SPEAKER_02: That is one way that I've seen market researchers do that.
15:19
SPEAKER_02: There's also another statistic, which I think was from Nielsen, if I'm not mistaken.
15:22
SPEAKER_02: So don't quote me for it.
15:24
SPEAKER_02: But um, when you get one wrong bad feedback, there are seven other people apparently who feel the same.
15:30
SPEAKER_02: They just don't want to talk about it.
15:32
SPEAKER_02: Or they don't want to like, they don't have the time to tell you like your product is bad or your baby is ugly, right?
15:37
SPEAKER_02: Um, so it takes like eight people, there are eight bad experiences for that one experience, bad experience that you've got.
15:45
SPEAKER_02: So I think brands should care about those kind of statistics as well to know like it's not just this one single person, there's probably another seven, eight people out there who also feel wrong about this situation or this experience or this product, right?
16:00
SPEAKER_02: Um, but I think asking multiple questions, reframing them differently would be a good way to get the cognitive bias out.
16:09
SPEAKER_02: I've also realized one thing biases are not just based on human beings as an entire race, it also changes based on the kind of people that you're working with.
16:19
SPEAKER_02: Interesting.
16:20
SPEAKER_02: So, what I mean by that, when you talk to when you conduct a survey with like very senior business professionals, you don't want that survey to go beyond 10 to 15 minutes.
16:30
SPEAKER_02: The longer it goes, the questions, answers to those questions start turning to be negative because they're already losing the temperament of being in that service for a longer time.
16:40
SPEAKER_02: Uh and it could be different for students versus it could be different for housewives, and it could be very different for ex.
16:47
SPEAKER_02: So it's very interesting the kind of people that you're also surveying or trying to do research on, uh, their day-to-day life, how busy they are, how frustrating those jobs are.
16:58
SPEAKER_02: There are multiple reasons uh, you know, that that bias can come from multiple, you know, different directions.
17:05
SPEAKER_02: Yeah.
17:06
SPEAKER_01: All right.
17:07
SPEAKER_01: One last question on that, and in terms of like trying to trying to eliminate the biases.
17:14
SPEAKER_01: Um When I used to work at Microsoft, um, we did a lot of um in a couple of the groups that I was in, we did a lot of um of outreach to develop to the developer community.
17:25
SPEAKER_01: This is like prior to things like Stack Overfile and stuff like that.
17:28
SPEAKER_01: Right.
17:29
SPEAKER_01: Um as we were doing that, um, we gathered uh terrific data, or at least we thought that was terrific data, that really was started to guide um the content that we were producing.
17:43
SPEAKER_01: Um and about six months later, what we found is that having acted upon all of this and having reconfigured how we what we produced and how we produced it, um, that the overall uptake of what we were uh of what we were producing was going down fairly dramatically.
18:00
SPEAKER_01: And this took us a while to figure out.
18:03
SPEAKER_01: And what we ultimately figured out was that um uh the nature of the people that were talking to us defined them as a as a group.
18:13
SPEAKER_01: In other words, there was a there was already a bias, a very significant bias, in terms of when you reached out to people and they actually responded, they were reflecting a small subset of developers who responded to these types of questions.
18:28
SPEAKER_01: And uh and so we went on this quest, um, which I think we were probably slightly successful at, but not completely successful at, to try to find what I like to call the silent voices or the hidden voices or something like that.
18:42
SPEAKER_01: So I would imagine this is a problem in almost all uh realms like this.
18:47
SPEAKER_01: How do you go about addressing whether the the potential bias of the only people you hear from are the people that are willing to talk to you?
18:57
SPEAKER_02: Yeah, uh it's a very interesting question.
18:59
SPEAKER_02: I don't think there is a perfect way to do that.
19:01
SPEAKER_02: I don't think any company will can very confidently say that we can we are in a position to remove bias, right?
19:07
SPEAKER_02: But uh now with with technology improving so much, um, there are two kinds of feedback that you can get.
19:15
SPEAKER_02: And I can speak specifically from a qualitative standpoint, which which we are seeing in the in the space a lot.
19:21
SPEAKER_02: So you can answer a question to me on this video, I can answer back a question to you.
19:26
SPEAKER_02: But how's my how how's my body language?
19:29
SPEAKER_02: How am I responding?
19:31
SPEAKER_02: Like so the softer body language behavior, my expressions or microexpressions are actually being taken care of uh in in those qualitative interviews as well as a part of the finding.
19:42
SPEAKER_02: You know, how do you feel when you say a certain word, it be positive or negative, uh, things of that sort.
19:48
SPEAKER_02: So they're they're getting into these weeds of uh body language, microexpressions to give that feedback, which is not just reliant on my words, which is one way of input of my findings to you.
19:59
SPEAKER_02: So we've seen that.
20:00
SPEAKER_02: Uh, but uh uh my question to you, I'm really curious to know when you did this developer outreach, did you know individually who these people were?
20:08
SPEAKER_01: Uh we did.
20:10
SPEAKER_01: So what we found was that when you reach out to certain people in a certain way, like for example, through user groups or whatever, the people that are prepared to put the time in to participate in the in the user group, they're wired in a certain way.
20:24
SPEAKER_01: They're excited by what you're already doing, they are willing to put in the time investment.
20:29
SPEAKER_01: Maybe if you you know work at a company like Microsoft, maybe they want to join Microsoft someday, right?
20:32
SPEAKER_01: And so there's a whole bunch of different like motive motivations that they have.
20:36
SPEAKER_01: And that that alters their feedback.
20:40
SPEAKER_01: So for example, as a classic example, we just talked about negative feedback, right?
20:44
SPEAKER_01: In most cases, right, if I'm responding to a to a survey from you and or on a user group with you, and my ultimate goal is to work for you someday, I'm not that likely to say, I think everything you do sucks.
21:00
SPEAKER_01: And you know, et cetera, et cetera.
21:02
SPEAKER_01: You're you're trying to convey a positive impression associated with it.
21:06
SPEAKER_01: And so what we found was number one, ask questions in a bun uh in a bunch of different ways.
21:12
SPEAKER_01: Number two, go through a variety of different forums and actually have even different styles in which you uh in which you ask your questions.
21:21
SPEAKER_01: And then as you do that, start to analyze the differences between them.
21:27
unknown: Yeah.
21:28
SPEAKER_01: And they at least give you clues as to how you can adjust for or adapt to the feedback that you're getting.
21:35
SPEAKER_01: It kind of relates to what you said before about the negative feedback.
21:39
SPEAKER_01: Like you get some person one person who's prepared to put their head above the parapet and say something negative.
21:44
SPEAKER_01: That's probably a stronger signal than you would like to admit that it is.
21:48
SPEAKER_01: So it was, it's it's those things that again, we never we never found a perfect answer, answer to the solution.
21:56
SPEAKER_01: But what we got better at was understanding what adjustment.
22:00
SPEAKER_01: To make and what adaptations to make based on the feedback that we were getting, versus just taking it as red that it was completely accurate.
22:08
SPEAKER_01: And of course, this fee this all elements of this are challenges right now.
22:13
SPEAKER_01: It's why opinion, you know, why opinion polls are, you know, have to be adjusted and adapted and all that kind of stuff when we're looking at political opinions and things like that, because different groups of people will answer and some and those of people that group of people might have some other correlated collection of biases that shift your data set ultimately.
22:34
SPEAKER_02: Yeah, yeah.
22:35
SPEAKER_02: No, yeah, you're absolutely right.
22:36
SPEAKER_02: I've also we've also learned that the incentivization that you do for users could also impact the responses.
22:44
SPEAKER_02: Um some people are incentivized by money, some people are incentivized by a job, then I might get a job at Microsoft in the future.
22:51
SPEAKER_02: Some people are also responding to based on how they're feeling on that day.
22:57
SPEAKER_03: Yeah.
22:58
SPEAKER_02: Like what's happening in their life on that day, right?
23:00
SPEAKER_02: So if you're in a good mood, usually your answers are not that bad, or you're not going to be so brutal to the to the survey.
23:06
SPEAKER_02: But maybe you're just in a bad mood, your car broke down, you know, or or or whatever.
23:10
SPEAKER_02: And people tend to do that.
23:12
SPEAKER_02: So yeah, you're right.
23:13
SPEAKER_02: Like there has to be at least 10 to 20% of this like adjustment that needs to be done for those kind of respondents or participants.
23:22
SPEAKER_00: Hey there.
23:23
SPEAKER_00: Glad you're still here.
23:24
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23:33
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23:35
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23:52
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24:07
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24:16
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24:26
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24:33
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24:43
SPEAKER_00: All right, let's get back to the episode.
24:46
SPEAKER_01: All right, let's shift to my my uh hidden agenda on this pod.
24:51
SPEAKER_01: So one of one of the reasons that I really wanted to get you uh to get you on the pod was um that I'm really interested in how you take these same techniques that you're describing that your uh that your organization offers and apply them as a lens within your own organization.
25:11
SPEAKER_03: Yeah.
25:12
SPEAKER_01: Um so let's start by kind of understanding the backdrop to all of this.
25:15
SPEAKER_01: So what's your what is your opinion as to how the world of work is even evolving at different levels within organizations right now?
25:24
SPEAKER_02: Yeah, I think um, you know, there's a there's so we've got close to 20,000 users on the platform.
25:32
SPEAKER_02: Thousands of people earn money in terms of millions of dollars every year through our platform, right?
25:36
SPEAKER_02: And these are people who are manager above positions, so and to up to CEOs of very large companies.
25:44
SPEAKER_02: What we are learning, or what we've learned in the last couple of years after and the time of uh COVID and pandemic is like there's a lot of emphasis on the conversation around you know the location, right?
25:55
SPEAKER_02: I don't want to drive to work.
25:57
SPEAKER_02: There's this um, you know, medical emergency, so offices had to keep certain levels of standards when people come into the office, be it like a co-working space or your actual office building.
26:09
SPEAKER_02: A lot of companies laid off people, they shut down offices so they that everyone can work from home.
26:14
SPEAKER_02: I think the bigger trend that we noticed personally was not around just this whole physical logistical aspects of hybrid work or remote work.
26:23
SPEAKER_02: That is a debatable thing.
26:24
SPEAKER_02: And I think each company should find their own way of working.
26:28
SPEAKER_02: And most of the companies would look like hybrid in that particular realm.
26:32
SPEAKER_02: I think the biggest trend that we see, we are seeing is like people will do multiple jobs in a week, be it senior position people.
26:41
SPEAKER_02: We are seeing that a lot in HR space right now, and that will spill over to other job roles as well, where people are saying, you know what, what did COVID teach me?
26:53
SPEAKER_02: The most important thing was not just about working from home, but I can work for three to four days full-time with one company and I can spend the other day doing things that I love doing, or I can work with another company for a day or two, maybe consulting, advising them.
27:07
SPEAKER_02: It is not necessarily could be an HR work, it could be something totally different.
27:11
SPEAKER_02: That is a passion for that particular individual.
27:15
SPEAKER_02: So this could be a bold, bold prediction from my end, but I think in the next 10 to 20 years, you will see more people having multiple jobs uh rather than the same one single job nine to five, five days a week.
27:30
SPEAKER_02: It's gonna look like maybe three days, one job, two days, another job.
27:34
SPEAKER_02: It could be three days, one full-time, one job, and then one day each with other companies or with other things completely.
27:42
SPEAKER_02: And that is not driven by money, by the way.
27:44
SPEAKER_02: The other two are not driven by money, they're driven by your individual passions.
27:49
SPEAKER_02: Because now what if what the internet has done, which AI will also complement, is like your jobs are going to get easier and easier in the future, especially the mundane tasks that we do.
27:59
SPEAKER_02: And people are gonna look forward towards how can I make my life more fulfilling?
28:04
SPEAKER_02: Because these mundane tasks are done by technology and I can focus on things which are that I enjoy.
28:10
SPEAKER_02: So we've seen that trend, and I I talk to hundreds of people uh, you know, from our platform as well.
28:16
SPEAKER_02: I get that sense that people are moving in that direction.
28:18
SPEAKER_02: I think that's a bigger change in our workforce than anything else, rather than the whole remote hybrid, where should we work, how much should I travel to work, you know?
28:26
SPEAKER_01: Yeah, we track this quite a lot.
28:29
SPEAKER_01: And I will say that um you've up you've opened up an area that is um, I think increasingly well understood at senior levels inside some organizations, but that is an area of huge controversy um for many individuals and for um and actually for some uh for some leaders inside organizations.
28:55
SPEAKER_01: What it really comes down to is the fact that while we are in the midst of a transition away from work happening for a certain number of hours and having a certain number of defined tasks associated with that work, and towards work being um measured by outcomes that are driven inside organizations, we are still in that transition, right?
29:27
SPEAKER_01: We haven't changed fully how people are rewarded, we haven't fully changed how how these things are uh are even measured.
29:36
SPEAKER_01: And here's where it gets really complicated, which is that the vast majority of us we've always got more stuff we could be doing in our work than we have time to do it.
29:50
SPEAKER_01: We monitor um how this is um tracked about and talked about on social media, but we also talk to leaders and we talk to employees about this this challenge specifically.
29:59
SPEAKER_01: And what we see is a lot of you know fear, uncertainty, and doubt asso uh associated with this, and sometimes kind of you know, a reasonable amount of of anger, particularly lower down inside inside organizations, when they see people potentially at higher points in organizations that like doing this.
30:16
SPEAKER_01: And and so I think there is I think there is tension that has to be worked through um in order for that to uh in order for that to to fully um become the norm.
30:28
SPEAKER_01: But I agree with you.
30:29
SPEAKER_01: I think that ultimately we're gonna get we're going to get to a point where you're gonna have a human um who is determining where they're gonna spend their time to spend their time.
30:43
SPEAKER_02: Yeah.
30:43
SPEAKER_01: But it's gonna be a long and bumpy road, I think to get there.
30:46
SPEAKER_02: Yeah, you you remember the uh sorry to interrupt you, no, no, no, no.
30:50
SPEAKER_02: But uh the Reddit post, it was very fascinating where this guy who's a software developer, I think somewhere in New York or Silicon Valley, who said that he's working for the top, you know, two tech companies at the same time, takes away home like 400k, but both the companies are not aware that he works for these two companies.
31:07
SPEAKER_03: Right?
31:07
SPEAKER_02: It's the same thing, right?
31:08
SPEAKER_02: Like if companies don't take a lead in managing these expectations or relationships or kind of like punish people for thinking that way, people are just gonna be not honest about it and still do what they want to do.
31:23
SPEAKER_02: That's that's how it's gonna look like.
31:25
SPEAKER_02: Yeah.
31:26
SPEAKER_01: So with that as background, let's dive a little deeper into how you do go about um understanding sentiment, how you go about understanding how uh what the employee experience in a more effective way.
31:43
SPEAKER_01: Um what do you think are the best ways to use the sorts of techniques that you're talking about to gather information about uh to gather information from employees?
31:55
SPEAKER_01: Now that could be information about what the employee how the employees think the company should be run.
32:00
SPEAKER_01: It could be information about um or ideas or innovations that the employees might have, or it could just be, you know, sentiment of employees uh and measuring engagement of employees.
32:11
SPEAKER_01: What do you think are the best ways to be able to gather that type of data?
32:15
SPEAKER_02: I think you know, if people had the time, I I wish you know HR department had more free time and free space to actually go and talk to people individually and learn from them in a more qualitative way rather than just running surveys.
32:29
SPEAKER_02: Uh people like uh you've worked for big companies, I've worked for big companies.
32:33
SPEAKER_02: When we get a survey which is a mandatory survey, the last thing you want to do is take a survey about, and you want to go through it as quickly as possible, finish it so you can get to your work, right?
32:44
SPEAKER_02: Uh but your chart department has asked you to take up that survey, and you know, it's like it's a compulsion, you've got to get it done.
32:51
SPEAKER_02: Uh, I think online surveys are a bad way to do that.
32:55
SPEAKER_02: This is my personal view.
32:56
SPEAKER_02: Uh, and a lot of people might not like it.
32:59
SPEAKER_02: I would rather wanna go and talk to people on the front lines rather than asking their managers to tell you how the team is feeling.
33:08
SPEAKER_02: That's a bad way to do that again, even if you're doing it qualitatively.
33:12
SPEAKER_02: So, like talking to a leader who manages 20 people and asking them how's your team doing, they're most likely going to give you an answer that they're doing great.
33:20
SPEAKER_02: They don't want to look bad, uh, like I'm not handling my team well.
33:24
SPEAKER_02: I think talking to people who are uh at the ground level, you know, in the front lines, and HR team can probably do more qualitative discussions with them about how they feel, what are the problems, and bring that or surface that to the hiring to the to the manager or to the top management is a better way to do it.
33:41
SPEAKER_02: That's how we do it in our company.
33:43
SPEAKER_02: Like I do monthly to you know 45-day check-ins with every single person, even if they work with us for years, just to know how they feel about working with us, what are the challenges they have, and let people have the ability, let people have the permission to speak their mind.
34:01
SPEAKER_02: Like if you have this culture in a company, it all comes down to culture at the end of the day, uh, where if you have this culture in the company that you're going to be punished for saying the truth of how you feel is where people lie and they don't want to talk about things.
34:15
SPEAKER_02: So that has to come from the top to bottom.
34:18
SPEAKER_02: That's how it works.
34:20
SPEAKER_02: So if I give people the liberty to speak their mind for how they feel about a certain thing that we're doing, or me being a CEO of a company, or how we should progress, what should we look at in the year 2024, and and their opinions are at least heard, if not implemented, people are open to talk about it.
34:39
SPEAKER_02: But they should not be, they should have fear that if I answer a question about how I feel is is uh is going to create a problem for me or you know, come back to bite me later.
34:51
SPEAKER_02: Uh, those are the things I think companies should really be careful about rather than just running online.
34:55
SPEAKER_02: Because if you notice, uh take a company's internal online survey about how they feel about a CEO, and then go and look at on Glassdoor, which is anonymous.
35:05
SPEAKER_02: It's probably could contradict very like to the next to a different spectrum altogether, right?
35:10
SPEAKER_02: So that that that doesn't prove the point that both of them are correct.
35:14
SPEAKER_02: It just proves the point that people are saying something else in a different environment versus your own environment.
35:19
SPEAKER_02: And I think qualitative measures are better to do that, and and having that culture to be okay to speak about things.
35:26
SPEAKER_02: That those are two really important things I guess people should consider.
35:29
unknown: Yeah.
35:30
SPEAKER_01: Yeah.
35:31
SPEAKER_01: Uh look quickly, let's delve in just a little bit on the qualitative versus quantitative thing.
35:36
SPEAKER_01: Because I I I see I wouldn't say possibly increasingly, I don't know.
35:41
SPEAKER_01: But you see a lot of companies trying to address the whole issue of survey fatigue and and uh you know, and fatigue and assessments and you know, the length of them and so on by just zooming in on MPS scores and using it for that uh for that purpose.
36:01
SPEAKER_01: So um brief, well, number one, I guess we should very briefly explain what an NPS score is.
36:07
SPEAKER_01: I'll let you do that.
36:08
SPEAKER_01: But then number two, what do you think about trying to solve the problem of at least the surveys being long and cumbersome by replacing it with a simple measure like an NPS score?
36:19
SPEAKER_02: Yeah, I think NPS scores are good in certain scenarios, they're not bad, right?
36:23
SPEAKER_02: Like for example, you're buying a product.
36:25
SPEAKER_02: So just for the audience, what does an NPS score is a net promoter score?
36:28
SPEAKER_02: Uh, which usually companies use to know that are you gonna use my product in the future again?
36:35
SPEAKER_02: Uh, that's an example from a product's perspective.
36:37
SPEAKER_02: So are you gonna use my product uh in the future again?
36:40
SPEAKER_02: And if your score is above eight, sometimes nine or ten, then I know that you're very highly likely to refer my product uh with a word of mouth, or you're gonna buy or do a repeat purchase of that product.
36:51
SPEAKER_02: If it is anything below eight, sometimes seven, depending on different products and services people structure.
36:56
SPEAKER_02: The NPS, if it's lesser, then you're not doing a great job, right?
37:00
SPEAKER_02: Um, but NPS scores are like an overall experience that you have with that company or the product.
37:05
SPEAKER_02: So it could be possible that uh they are not the reflection of the entirety of the thing.
37:10
SPEAKER_02: For example, I might really enjoy my iPhone, but I had a really bad, horrible experience at the Apple store.
37:18
SPEAKER_01: Yeah.
37:18
SPEAKER_02: But for me, that's an entire experience.
37:21
SPEAKER_02: So I might rate Apple as six because on that day, my experience at the Apple store was bad.
37:27
SPEAKER_02: But the product might be nine for me.
37:30
SPEAKER_02: Right?
37:31
SPEAKER_02: So companies need to like really understand when they're like doing these NPS scores with company uh with their employees to structure it in a way that they can cover all aspects of that experience and get different NPS scores around it and then have an aggregated score for that particular individual.
37:47
SPEAKER_02: So it works, uh, but it could be misleading if you haven't done it well or done it properly.
37:53
SPEAKER_02: Yeah.
37:54
SPEAKER_01: Yeah.
37:55
SPEAKER_01: Excellent.
37:56
SPEAKER_01: Um all right.
37:58
SPEAKER_01: Let's finish off here.
38:00
SPEAKER_01: We talked a lot about understanding um sentiment, I suppose, and then also understanding um the views of people and how difficult that is to do um internally and externally.
38:15
SPEAKER_01: Um I'm curious more broadly about how you think the world of work um is changing.
38:23
SPEAKER_01: You mentioned you've got a huge platform at this point with people that are uh from that are senior leaders inside organizations all up.
38:31
SPEAKER_01: Um give me what you're seeing, what signals you're seeing in terms of um of how the world of work is is changing.
38:41
SPEAKER_01: And I'd like to know it from two perspectives.
38:43
SPEAKER_01: Almost like what is the most exciting about the way the world of work is changing and what scares you the most?
38:49
SPEAKER_02: Um I think um I want to go back to like the history of like where we we even started work like as a race, right?
38:56
SPEAKER_02: Is if you look at uh the the industrial revolution, companies which had the highest amount of workforce were considered to be the biggest companies.
39:03
SPEAKER_02: Today that's not the case.
39:05
SPEAKER_02: There could be a 20 or 100 employee company which could be worth 10 billion dollars in reality in revenues compared to a large company which has 10,000 employees.
39:13
SPEAKER_02: So the value uh created per employee is not a real metric of what it's gonna look like.
39:19
SPEAKER_02: So my understanding of how that's gonna change is companies are gonna focus on their core work and outsource most of the things in the future.
39:27
SPEAKER_02: Now, that outsourcing could be to human beings or could be to AI.
39:31
SPEAKER_02: And I'm pretty optimistic just being in Silicon Valley, meeting so many founders who are building amazing companies around AI, meeting investors who are who are working on investing into these kind of companies.
39:44
SPEAKER_02: There are going to be a lot of tasks which are mundane and administrative that are going to go away in the next five to 10 years.
39:51
SPEAKER_02: It could be even shorter, depending on how the technology progresses.
39:55
SPEAKER_02: So I think uh my my view is people are gonna focus on core jobs that only a human being can do, um, which where you are better than you know, an AI can do that, and all the other tasks would be outsourced to other people or maybe uh a technology itself within companies outside the company.
40:14
SPEAKER_02: So that's gonna be a big shift for us.
40:16
SPEAKER_02: The biggest worry that I have, I wouldn't say it's a scare, but the worry that I have is a lot of people are gonna displace from get displaced from their jobs.
40:25
SPEAKER_02: Um, so it there are two ways to look at it.
40:28
SPEAKER_02: One is um how do companies create like these cross-platform learning environments where you can shift from one job to another because your job or your task completely gets automated.
40:40
SPEAKER_02: And the other one is how do we as governments and countries look at that?
40:45
SPEAKER_02: Yeah, um, and I think those are the two things.
40:47
SPEAKER_02: If steps are not taken correctly, you'll see a lot of people losing financially, getting displaced.
40:54
SPEAKER_02: So that could be those things, and it could be like a slow drip.
40:57
SPEAKER_02: It is not necessarily gonna happen like one day millions of people lost jobs, but it's gonna be like a slow drip.
41:02
SPEAKER_02: So you wouldn't see the impact short term, like right then and there in that moment, but that could be like a percolating impact like over the next 10 years, 20 years.
41:10
SPEAKER_02: I think that's something that people should should really think about.
41:14
SPEAKER_02: Um uh job displacement is definitely gonna happen, if not um just completely losing jobs.
41:22
SPEAKER_02: Yeah.
41:23
SPEAKER_01: Yeah.
41:23
SPEAKER_01: All right.
41:24
SPEAKER_01: Well, we'll leave it on that down note, but uh sorry.
41:28
SPEAKER_01: Oh, no worries.
41:29
SPEAKER_01: Uh it was it was very nice to talk to you today and really uh gained a lot of insights there.
41:33
SPEAKER_01: Thanks so much, Shark.
41:34
SPEAKER_00: Yeah, I appreciate it, Paul.
41:35
SPEAKER_01: Thank you.
41:37
SPEAKER_00: Humanity Working is produced and edited for Billion Minds by Matt Neal.
41:40
SPEAKER_00: Our interviewer is Paul Slater.
41:42
SPEAKER_00: Music is by Dolo Records.
41:44
SPEAKER_00: If you like this podcast, please subscribe, like, and recommend us to others.
41:48
SPEAKER_00: It helps us reach more people.
41:50
SPEAKER_00: If you want to learn more about how Billion Minds gets companies ready for the future of work by building adaptable, resilient employees, look for them on LinkedIn or visit their website at billionminds.com.