Webinar: Predict future work trends & increase profitability with Predictive People Analytics


Predictive People Analytics

Predictive People Analytics.  It’s not a crystal ball exactly, but it can help you predict future work force trends you can use to optimize the talent you have and the business outcomes you want.  We use AI to turn your hiring data, current employee & performance data, plus your termination data into visually rich, easy to read reports. Giving you not only top-level trends, but also the ability to drill down a few levels to get to the source of that trend to take action. 


In this webinar you will learn how our Predictive People Analytics solution will help you:  

  • Identify and address small issues before they have an
    opportunity to grow into large problems. 
  • See how your company got to where it is, and what needs
    to be done for a more productive future. 
  • Obtain an overview of trends to understand why they are
  • Ability to investigate the future and predict optimal ways
    to reduce turnover and increase profitability. 

This demo was recorded on May 23, 2023

Presentation Slides


Session Transcript:

Jeff Plakans:

Hey everybody. Welcome. Thank you for joining us today. My name is Jeff Plakans. I am the president and founder of Commonwealth Payroll & HR. Today we’re going to dive into isolved predictive people analytics. We’re joined by Shaun Fowler and by Pam Kessler of isolved and thanks for joining us. Now a little bit before we get everybody going, I just [00:00:30] want to talk a little bit about isolved predictive people analytics and specifically about being predictive.

We talk to a lot of business owners throughout the course of the year. We always ask them, what do you guys need? And, more than one… More than once I hear the following statement, which is, “You know Jeff, if I had a way to predict the future, a crystal ball, I would be great.” With predictive people analytics, which we’ll [00:01:00] talk a lot more about here in the next hour, we really have some capability to see into the future based on what we’re seeing from the past. And so, there’s not a lot of products that are out there that help us with that and those types of insights are insights that can make us all better business owners, better employers and whatnot. So, that’s the sort of goal of today’s session is to show you not only what we can do with predictive people analytics but [00:01:30] how the benefits would accrue to you as an employer no matter whether you have a thousand employees or whether you have five or six employees. So, with that, Shaun, I’ll kick it off to you and to Pam.

Shaun Fowler:

All right, appreciate that Jeff and good afternoon everyone. As Jeff said, my name is Shaun Fowler. I’m account manager over here at isolved. So, today we’ll walk through the agenda, meet the presenters. In a moment I’ll introduce myself and Pam [00:02:00] and then we’ll go over a Predictive People Analytics overview. So, I’ll give you some idea of what the features are and the benefits to your organization and what that looks like. And then Pam is going to walk us through the solution demonstration, so you’ll be able to see the user interface, the functionality of it, and then of course we’ll have some time at the end for Q and A. But of course if you do have questions, don’t feel like you have to wait until the end. Go ahead and put them in the chat or the QA section [00:02:30] and we’ll address them as we go along.

So, you all know Jeff, founder, president Commonwealth. My name is Shaun Fowler, again, account manager over here at isolved, and Pam Kessler, who’s a solution consultant who is very knowledgeable on these solutions and she’ll be doing the demonstration for us today.

So, again, what is the Predictive People analytics? And, as Jeff said, it’s the ability to kind of look at the past and [00:03:00] see what kind of trends that you can pay attention to and how that affected key metrics and it’ll give you a good understanding of kind of what that is going to look like in the future if you adjust some of those variables. So, it’s a very powerful and intuitive AI powered analytic tool. It allows you to adjust some things, figure out what is the best path to take before you take it. So, it’s going to incorporate a lot of key people data sources within this isolved system and it’s going to provide it [00:03:30] in a visually rich dashboard driven display and we’ll see a little bit more of that during the demonstration.

But as you can see on the screen, there’s tiles that allow you to kind of move it around and you can adjust it and customize it how you want it to look and what is most important to you to be up there right in the front. And, of course it also has predictive modeling capabilities. So, we’ll take a look at what that means here now.

So, some of the [00:04:00] key features. As I mentioned, it’s about taking a look at trend data over key metrics and over a defined period of time. There’s one… That’s one way of kind of taking a look at how this tool is going to help your business. There’s different ways such as predictive modeling, so using some trend data to plot some scenarios and have the tool decide what are some of the best actions that you can take for your business [00:04:30] and for the workforce, what those outcomes would look like.

There’s predictive guidance, so setting those targets and having that recommended recommend multiple different methods of achieving that result. Of course, input in and finding data is also very important. So, having a voice navigation or a virtual assistant, being able to just ask for whatever you’re looking for out of the system and it being provided to you is going to enable your employees and your administration [00:05:00] staff to find what they’re looking for relatively quickly and get on with their day-to-day.

Natural language processing. So, the application is very robust and very complex. So, again, being able to kind of navigate that solution will help increase that efficiency and the efficacy of the solution itself. Key events overlay, so meaning that you can plot for key events. So, if you [00:05:30] see that there’s going to be a need for increased staff, what is that going to look like on your business as far as balance sheet and how are you going to get there in the most effective way?

Those are some of the key features. And, of course there’s many more and with the benefits that come with it, you’re going to be able to identify and address those small issues before they become a big issue. So, looking at it more proactively [00:06:00] rather than just reactively, kind of figuring out where your business is headed and what small adjustments we can make in the meantime. It’s kind of like the hurricane graphs. I live in Florida, so, very familiar with hurricane tracking models and when they’re out in the Atlantic, it’s very wide open. The pattern’s wide open because anything can happen, but as you get closer, the funnel narrows and you’re much more… You know, you have much more of a probability of hitting that goal. So, we’re going to be able to [00:06:30] provide and obtain the overview of the trends that you’re seeing and you can understand why those trends are happening and you’ll have the ability to kind of investigate in the future and predict some optimal ways to reduce turnover and increase your profitability.

That leads me to the next thing that I want to talk about is some sample use cases because yeah, it’s a great analytical tool, but what… And, it’ll [00:07:00] help us with some metrics, but what does it really mean? What does it really do for us? We have all heard the great resignation, quiet quitting. These are terms that are popping up and that are new to the HR industry and becoming more prevalent. So, we want to make sure that we have a tool that companies are able to reduce their retention. Or, sorry. Improve their retention by looking at key data and finding key metrics for the [00:07:30] high wage earners and understanding what they need to be able to retain in your organization. They’re going to have the ability to obviously with the virtual assistant, to save time in collecting all that data within the system.

So, really it’s about retaining the employees that you have, figuring out what’s the most effective way to retain them, what kind of levers can you pull and what that looks like to your organization. So, it’s as close [00:08:00] as a crystal ball as we can get. So, with that, I’m going to turn it over to Pam. I’m going to stop sharing my screen and she will be able to take it from here.

Pam Kessler:                      Okay, perfect. I don’t know that I have access to share.

Shaun Fowler:                   [inaudible 00:08:32] [00:08:30] Let’s see if I can make you a presenter. Did that work?

Pam Kessler:

I don’t think so. Oh, here we go. Sharing. [00:09:00] And, I’m not sure which screen it is, so we’ll go with this one.

Shaun Fowler:                   Looks good.

Pam Kessler:                      Is that sharing?

Shaun Fowler:                   Mm-hmm.

Pam Kessler:

Yes? Okay. Perfect. Okay. So, thank you all for joining us today and I am just going to turn that off so I’m not just distracting everybody as I’m looking around here. So, jumping into [00:09:30] predictive people analytics, it is exciting with the amount of data that we can put in here and information that you can have regarding your company. So, we can look in the past, we can look in the future, we can look at current. So, let’s go ahead and dive in and look at some of these amazing features that we have within the predictive people analytics or what we call PPA.

[00:10:00] So, here we’re just simply looking at the main dashboard. This is showing us some high level metrics. So, we have our time to fill, cost per hire, number of employees, hires versus terminations. It’s really any metrics that you’re wanting to see at a quick glance on one screen. Now, you can also go back in time. So, if we’re wanting to go back and look at May of last year for example, [00:10:30] I can absolutely do that. So, you can go. You can do a rolling 12 months, previous calendar year, whatever it is that you’re wanting to look at and when you’re wanting to look at that.

Now, as far as dashboard goes within the system, you can create and build as many dashboards as you want. Now, we can also create new dashboards and with this [00:11:00] there’s a couple different ways. See, we can have a blank template where you go in and create what metrics you want in there or we do have some templates. So, if we’re wanting to look over at or look at turnover analysis, I click on save. I can come right up here and look at that turnover analysis.

Now, with this you can change the look of these grids. Some people are wanting more of that pie look. [00:11:30] Here we have a rolling 12 month. So, if I just simply click on up over here, I can change the way that grid looks. So, if I have this as a bar, let’s say I want to do that donut. I can click on that and it then changes the look of that. So, really a preference on how you like to look at things as far as a grid or pie charts. All of that you can do right in here however it is you want to [00:12:00] look at that.

Now, with any of these dashboards that you build, you can also share them. So, if you’re going into a meeting and you’re saying, okay, hey, I’m going to look at our turnover rates, I figured this out. I now want to email this to someone or I’m going to download this to my computer. I can copy it or I can even share the dashboard within the system, so give somebody else access to it [00:12:30] and send that directly to them.

Now, let’s say that we’re wanting to take a deeper dive on specific details within let’s say number of employees. We can simply drill down on that. Now, you can see here we’re looking at our number of employees and under that chart view I’m looking [00:13:00] at totals. So, here I can see total number of employees. So, let’s say that we also want to break this down by gender. I can now see by gender how many employees I have.

Now, if we want to go even deeper than that, I can go to my settings and say let’s look at our job level and let’s say we want to just see my managers. [00:13:30] I can apply that here and it’s now showing me what employees are managers by their gender. Now, if we’re wanting to let’s say promote one of these employees, I can scroll down here and it gives me even more details. So, I can compare employees and I just simply need to select what employees that is I want to compare and I can compare these side [00:14:00] by side.

Now, these details here on the right-hand side, I can change. So, if I’m wanting to manage those fields and I also want to see cost per hire or what day did they start, what’s their job title, years of service, I can put all of those in there to see this and compare by employee those differences, their salary, their performance, [00:14:30] all of that or anything that I am wanting to see.

Now, in addition to metrics, we can also look at those analytics. So, if we’re going to do that, let’s say…. Let’s go to a different dashboard here and let’s say we want to look at the turnover by year with those analytics. [00:15:00] We can see here that it’s already showing me the last three years where we are. So, if I dig into that, into those analytics, I can see all of that. Now, you can see here again it’s those three calendar years that we’re looking at or let’s say we want to do fiscal, 12 fiscal quarters, or [00:15:30] if I’m wanting to look at the rolling 12 months. I can definitely see all of those.

Now, we do have in here… So, the metric, that’s our current time period. Historical would be analytics and going forward is where we can see that predictive analytics in here. [00:16:00] So, this here is showing us the last six months and then because of our going off of the numbers that we have in here, you can now see the next 12 months of that predictive. So, that’s really exciting, especially when you know everything with turnover rate has been high or low depending on what industry you’re in. You can see [00:16:30] all of that.

Now, if I’m coming up in here into settings, you’ll see here now that I have my analysis, guidance, settings, all of that in here. So, we can see all of those details. My filters. I can still go through and do all of that. Again, we [00:17:00] can do comparative or compare those employees and also go into that predictive that way.

Now, with this, a lot of people ask, where do we get this detailed? Where is this coming into? That can be done a number of different ways. We can create [00:17:30] APIs with different data sources to have that detail come directly into the system so we can create those APIs. That’s saying if the company or the place that we’re wanting to pull that data in from will allow that API, we can put that in there. Now, hypothetically, let’s say that [00:18:00] there isn’t… The company we want are using. We want to pull that data in. They don’t want to do that direct API. That’s not a problem. There’s always a way to manually input data. So, if it’s not a lot of data, we can just go in and enter a specific number to get those totals or we can do an export and import in. So, really having all of those analytics, everything we want to do in that, we [00:18:30] can pull that data from any location.

Now, let’s say that we’re wanting to look for something, so we’re going to our dashboard and I don’t…. I’m trying to go through this. I’m creating different dashboards and I just need to search for something. I can type in any information and find that. So, if we do [00:19:00] show employees by department, it’s going to search for that and pull that information in and now here are all of my employees by department.

Now, let’s just say that you don’t feel like typing anymore or it’s easier [00:19:30] to just speak it, more of a talk text. We do have that bot. So, this here is Monica. So, if I activate that, Monica, how many female vice presidents do I have? [00:20:00] She can pull that up for me. Now, make sure that when you’re done using that, you pause it. Otherwise, she’s just going to listen to every single thing you say and type it all out at the bottom for you. Now, there are a lot of different ways again to search for those details. You can do metrics and drill down. You can do analytics and look at the past or we can also do the predictive all [00:20:30] within the one system and pulling data from any source.

Now, I know that we have looked at a lot of detail and information here in a really short period of time, so, do we have any questions that are coming in for me?

Jeff Plakans:

So, we do, Pam. [00:21:00] So, the first question is, and I think you might have gotten to this, but maybe reiteration of it is the… For the analytics data or for the comparative data that’s available, what are the different places you can get those or the different data sources?

Pam Kessler:

Mm-hmm. Absolutely. So, again, we can create APIs and pull information in [00:21:30] from an outsider third party. We can enter, manually enter in detail, or we can export detail out of a system and import it into predictive people analytics.

Jeff Plakans:

Okay. And so, [00:22:00] the other question just popped up was what are isolved benchmarks, which was something on the screen I think you showed earlier.

Pam Kessler:

Mm-hmm. [inaudible 00:22:13] get it to select. There we go. So, this is actually something that’s coming soon. So, these are just different benchmarks that within isolved they’re currently building out to pull in here. So, it’s not anything that is active currently, [00:22:30] so I have very limited input or knowledge about what that is until they release it. They don’t let us… They don’t give us a whole lot of detail on it because everything’s always changing. They’re adding things. And so, I really don’t have a whole lot of information on that except for the fact that it’s something that they’re building to have integrated into the system.

Jeff Plakans:

Okay, [00:23:00] great. All right. There’s another question here that says, on the predictive data, where is that coming from? How is that being calculated?

Pam Kessler:

That is data that is in the system. So, whether… Let’s say that this is brand new to a company and they have imported data from whatever source that [00:23:30] is. So, if it’s a point of sale system for example, that is that past data that’s in here. So, that’s how all of that is calculated. Now, we never purge or archive, so that data will always remain in there and as new data comes in, it’s going to recalculate those different numbers for that past. Now, the predictive is going off of more of a trend calculation. [00:24:00] So, okay, within the last 12 months or three years. Where were we with that? Where were maybe a higher number of hires versus terminations? All of that detail. So, it’s any detail that’s pulled in here.

Jeff Plakans:

So, the… So, just to be clear, I think that we want to make this clear. So, the data that’s in here is [00:24:30] being pulled from our client’s individual employee… Well, individual data that they have stored in isolved. What’s available here is would be more benchmark data. Would that be a good characterization of it?

Pam Kessler:                      Yes, yes.

Jeff Plakans:

Okay. So, many of you I know use or have used salary.com. There’s a wide variety of sources that are out there. Are there [00:25:00] additional APIs that are going to come online with additional data sources to use for benchmarks, Pam?

Pam Kessler:

Yes, absolutely. Absolutely. That is something that I know is on the current roadmap. I don’t have an exact date for that, but I do know that that is and there are other systems that we have APIs with.

Jeff Plakans:                       Mm-hmm.

Pam Kessler:                      This is just an example that’s set up in the demo environment.

Jeff Plakans:                       Yeah.

Pam Kessler:

But, really any system [00:25:30] that will allow an API, we can create that API and have that data fed in.

Jeff Plakans:

Okay. Now, we’ve had a request to see another example of the system predicting. Can you show us another example?

Pam Kessler:

Sure. [inaudible 00:25:56] Out of the way here. Okay. [00:26:00] So, if we want to look at that predictive… So, we can go into those settings here and let’s say we want to look at, for example, we’re looking at turnover, [00:26:30] our separation type. So, let’s say we want voluntary, so people that have left and let’s maybe say we want to look at their performance, so our highest performers who ranked at that four and five level, and it’s going to rate it that way. So, in here again it can be if we want to do [00:27:00] a rolling six months. So, if we want to look at, okay, where were we six months ago and we can hover over that to see those different trends and then it’s going to calculate, okay, based on the information that we have in here, this is what we are predicting moving forward.

Jeff Plakans:                       What’s the relevance of the sort of goldenrod colored box at the end or the chart at the end?

Pam Kessler:

[00:27:30] In all honesty, I have no idea. It comes up every time and I think that it’s just saying that’s where the end of that is. So, this is where it is giving you the total of six months.

Jeff Plakans:

Okay, gotcha. We have another. This one’s in the chat. But, on the dashboards, on the building the dashboards.

Pam Kessler:                      Mm-hmm.

Jeff Plakans:

[00:28:00] How wide is the variety of data that you could pull from or create from? So, I know you have the templates, but if you were building something without a template, is virtually every field in isolved available?

Pam Kessler:

Virtually yes. So, really it would be any data that we want to pull in and that could be from isolved or any [00:28:30] other third party database.

Jeff Plakans:                       Okay. All right. Let me just check, make sure. I think… Pam, I think that’s it for questions.

Pam Kessler:                      Okay.

Jeff Plakans:

So, I think. Okay. Any last minute questions? Anything else before we call [00:29:00] it a day? No? No? Okay. Well, on that note, thank for the… Oh, there he is. There he is. Shaun, I was worried.

Shaun Fowler:                   Oh, no. Not… I didn’t… Pam, are we finished or was that…? Are we good then?

Pam Kessler:

Yep. Unless there’s any other questions that anyone has. Anything [00:29:30] else? And, you guys, this isn’t definitely not an end all. So, if you’re anything like me, you’re going to come up with the best question right before you fall asleep tonight. So, if that is, sit up, write it down, put it in your phone, shoot us an email and just let us know if there’s any questions that come up or, hey, I thought of this. Can we? What if? Whatever it may be. Let us know. We’re always here to help.

Shaun Fowler:

[00:30:00] Yep, absolutely. And, thank you Pam for walking us through the demonstration. Before I let you guys go, I just wanted to touch on a couple of things as far as future-proofing our solutions here and intelligently connecting it to the HCM platform.

So, we are always looking for competitive updates and looking out there for industry and market appliance updates, things of that nature to make it a more well-rounded system. Obviously things change [00:30:30] in the world and we want to make sure that this solution is adapting with those changes so that you don’t have to look for another system like this somewhere else. So, just keep in mind that we’re always fine-tuning it. As Pam had said, we’re always looking for different APIs to connect to the system, so we’re enhancing it that way as well.

I will pause here just for a second to see if there’s any other questions that came in. [00:31:00] Otherwise, as Pam said, and like myself, I usually take some time to digest the information and then questions come later. So, if you do have questions, feel free to reach out to Jeff. They’ll be able to help you out over there at Commonwealth. And, Jeff, do we have any more in the Q and A?

Jeff Plakans:

Nope. I think we’ve either stumped everybody or we’ve wowed them with data. A couple [00:31:30] last thoughts on this. I myself am a big data geek and of course that’s why I am in the business that I’m in. But one of the things we see more, whether we’re talking to individuals who are in more of a finance perspective or whether they’re in a more traditional HR role or whether they have a hybrid role, at the end of the day, we are all responsible for people and as our organizations grow [00:32:00] and as conditions change, whether that be a tougher job market or a recession or all of the above, really looking for good answers is the thing that is going to help us not only be better as employers, but be better at our own jobs as well and most folks I know are the ones who are looking for as much information to help them in that process as possible.

With the Predictive People Analytics [00:32:30] platform, again, this is a bolt-on, if you will, to isolved. So if you’re already using isolved and if you’ve been using isolved for a number of years, you’ve already got a number of years worth of very, very detailed data waiting to be mined. The isolved predictive analytics piece allows us to attach that onto isolved so you have access to it in a very user-friendly, easy no programming, no coding kind of [00:33:00] way that’s going to give you those answers, that crystal ball I referenced earlier or that Shaun referenced earlier to help you.

And so, it’s a great product to have. It’s a great solution. We’re rolling it out amongst some of our larger clients right now. It is relatively newer, meaning we’ve only had it for the last couple of months, but it gives us… It takes what we have in isolved and gives it to us in a very, very consumable format and one that we can then use to shop around to justify [00:33:30] the next five hires or the next element of pay raises in the interest of retaining our employees or whatever the reasoning might be. It’s going to give us that data. It’s going to give those visuals to back up the arguments that we’re trying to make and I think that’s invaluable to everybody.

So, as Shaun mentioned and certainly as Pam mentioned as well, if you have further information about it or questions about it, mention it to your CSS or [00:34:00] mention it to your account manager or feel free to just give me a ring or send me an email. My contact information is there. Other than that, have a great afternoon and hopefully we hear from all of you or a number of you soon on the use of this product. So, thank you Shaun and thank you Pam and thank all of you for spending your lunch hour with us.

Shaun Fowler:                   Thank you everyone. Bye-bye.

Pam Kessler:                      Thanks everyone.



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