¿Ha llegado el momento de cambiar a las licencias basadas en el usuario?

[0:00] Sagi: Hello and welcome to a webinar of Open iT where we will be deconstructing the question is it time to switch to a user-based licensing model.

[0:14] So my name is Sagi and I will be guiding you through today’s webinar. I am a solutions architect in Open iT and I have one mission delivering results that add value to our clients. I’ve been working with high-profile clients for multiple verticals to ensure their goals are maximized in the efforts of optimizing their software investments.

[0:49] So, as you might know, there are various ways that software can be licensed. Various vendors use different ways to allow their customers to pay for application usage with options ranging from concurrent licensing, user-based, unit per cost, cost per token, distinct users, many more ways that you can be charged for application usage.

[1:20] Open iT is here to sort out the mess and help you figure out how well different models are utilized and even show you which ones might be the best for your engineers based on their usage patterns.

[1:39] Lately with some vendors there has been a shift in licensing models allowing for multiple pools of licenses adding named licenses as well as concurrent floating licenses or even moving to named models completely.

[1:58] Now, as you know, a concurrent floating license is a way for users to share a license between them where a server holds a pool of licenses, and each user that needs to use a specific application, simply connects to the server, grabs the license, then puts it back once it’s done.

[2:20] But now we are seeing more and more vendors shifting to use named licenses in some capacity, allowing a user to have his own assigned license which cannot be shared with anybody else.

[2:36] So you can tell if your organization can benefit from a user-based license with Open iT or maybe a shared license is better. Well, it all comes down to usage patterns, how the users use the applications. It can be easily identified with Open iT’s reporting and analysis capabilities.

[3:03] So, how do you know which license agreement is best for you? Let’s take a look at a few indicators which can show us the best way to find the well-balanced licensing inventory. We’ll go over a customer success case and all the indicators that they used.

[3:27] Now, first of all, Open iT offers various reports and dashboards that reflect the need for one model or another, whether it’s named, floating, local, global, meaning that you can easily compare different simulations of license models to decide which one is best.

[3:50] So to answer these questions, you’ll need first a bird’s eye view over your users’ usage patterns as not always will you be able to know the need based on the consumption alone. Sometimes a closer look is required. Various users might be using differently. We’ll need to know how they interact with the license inventory.

[4:15] So, let’s jump into a few critical indicators that might tell you if a named license or a floating pool is the right way to go or maybe a mix of both.

[4:29] So, first of all, one thing that indicates that you might be optimizing your inventory by switching to a different licensing model is how long your users are checking out licenses for and how active they actually are once they have checked out those licenses.

[4:50] So today we’ll be walking you through one of our customers’ story and the main indicators that the license administrator used in order to reduce licensing cost by $300,000 in under 3 months.

[5:09] Open iT has various user-based reports that show you just that. Let’s start with level one, which shows you the duration of time between check out and check in of a license. Basically, how long a user has been checking out a license for. You might find that many of your users have very long elapsed time just like our customer, associating them with high usage patterns meaning the heavy users.

[5:43] They might be checking out a license for the whole day, maybe 8, 9, 10 hours a day. And we have a report here that shows us three months of usage. And the client identified various users which have been using the application each day for the full working day. So if you think about it, they are basically treating the floating license like it’s a named license as they need it all the time.

[6:10] This is one indicator that shows you these users might be better off using a named license instead.

[6:20] And you can get a full view of your distinct users for a specific time frame. Is it something that happens regularly or is their long usage time just occasional? Maybe they had to use a certain application for a few months but beyond that they didn’t really need to utilize it to the full extent. So, Open iT showed this to the client and he saw that the amount of distinct users did not follow any seasonality or project-based rhythm but is fully operational along the whole year, prompting them to understand that the long usage time is sustainable and maybe a more sustainable licensing model is required.

[7:10] But wait, are all these users actually using the license that they have checked out? Maybe they checked out a license, but they’re not actually using it. You know, maybe they are leaving it on the workstation just in case. In case they will need it, but they don’t actually do anything with it. So this greatly skews the analysis as it might be showing high usage time while the actual usage times are much lower.

[7:41] So for that the client incorporated Open iT’s LicenseAnalyzer™ level two into the mix showing them exactly how long the users were actually using the licenses that they checked out.

[7:56] So they found users are checking out licenses for a long time. And here we see that the ratio of active versus inactive is high. Meaning once the engineers checked out the license, they are using it to the full extent, keeping the inactivity to a very short amount of time, prompting them to realize that these users might be the heavy users indeed benefiting from a user-based licensing model instead of the floating one.

[8:27] Now, it goes without saying that in case you analyze the license activity and find the opposite where the ratio shows you that people are more inactive than active or even just half and half. There might not be a need to switch to a user-based licensing model, but maybe find other ways to optimize their license usage, such as using level three that automatically harvests those inactive licenses back into the floating license pool and get you the optimization that way of your existing licenses.

[9:08] Another indicator that they followed is how many of your users are grabbing more than one license at the same time. Meaning a single user takes two, three, four licenses at the same time from the licensing pool.

[9:26] Now users many times they have a good reason to check out many licenses at the same time. One might be for operational work, designing, developing and so on. And the other licenses might be for running pre-made simulations, calculations or any other batch jobs that they require in order to make their work more efficient.

[9:53] But sometimes they might be checking out licenses just in case or doing it on various machines and forgetting some of them still open, which for this you can use level two as well and analyze that.

[10:09] But let’s presume that the users are indeed honest and they checked out duplicate licenses just to make their work more optimized and deliver their work faster. So having a large number of users who frequently use duplicated license usage might indicate that the licensing pool might be better off with assigning them named licenses instead of them hogging licenses from the floating pool. Just like our client found out, we have here a group of users with a max use of two, meaning that they indeed use licenses in a duplicate manner. And seeing as their elapsed time is high, meaning that they might be better off assigned with a license and not use the floating pool because these are heavy license users.

[11:04] Now talking about the frequency of license usage, this is also an important factor for determining the client’s inventories best mix of licensing models. The Open iT reporting data set allows to see when did the user last used the application. Have they been using it frequently? Meaning that the days since last used is a low number, utilizing the license maybe yesterday or two days ago, or maybe they have not really touched the application in weeks or even months.

[11:45] So our client ran that report as well and we can see a group of users which are frequently using the application. Some used it yesterday while others about a week or two ago. Indicating that these users which frequently use it for a long time stay active with the application and are very heavy users of the application, using it for their day-to-day operation and they might benefit from the named license.

[12:20] But what about users which are not using the application so frequently? This also was found on the client system. Well, for these guys, the floating license model is perfect. It ensures that they have a license available for them when they need it without reserving any license specifically for them.

[12:43] So they opened up the reports and they found users with named licenses but as you see here did not use the application in almost half a year and have pretty low usage duration, meaning that they found their light users. They don’t really require a named license and will be much better off in the floating license pool.

[13:09] So, they either don’t need their named license because they barely use it, or even worse, they might not be in the company anymore and still have a license assigned to them, helping further optimize license inventory by even removing any undesired license assignment.

[13:28] So in short, Open iT helps you gain a broad view on your license usage patterns, allowing you to greatly optimize license inventory, all while enhancing availability and the experience of your end users and we have many customers who did just that.

[13:53] Let’s take a closer look at the customer that we are referring to from the defense and aviation industry. We see here that at first they had a mix of both floating and named licenses for MATLAB. In this case on the left their MATLAB floating license usage almost always maxed out offering very low availability of licenses. They were generating many denials every hour of every day as we can see in the middle. And on the right we see their named license pool which had around 310 licenses assigned but were barely used.

[14:39] So on the one hand they had end users which frequently got denied and were not able to work and on the other hand many named licenses which were basically just sitting there with no assigned users actually using them.

[14:54] So analyzing the data with Open iT allowed them to first identify their heavy users as you see on the left, users with very high average usage time and that get denied often as you see in the middle, versus their light or medium users which barely use the application and once they do it’s for a very short amount of time, allowing them to mix and match the licensing type to the correct user, giving the heavy users named licenses while giving the light users a floating license.

[15:35] This greatly optimized their license inventory and allowed them to first of all make sure that no more denials are generated. Their users get high availability. Whenever they need a license, they got it. And secondly, it allowed them to reduce the amount of licenses that they have, renewing a smaller license pool both for the named and floating license pools, just because they made sure the right user got the right license. They were able to save $300,000 just by doing this mix and match. And they did that in under three months time.

[16:16] And this is it. Open iT gives you a complete overview of license usage, user usage patterns, and overall efficiency, allowing you to use various charts, graphs, dashboards to identify optimization options in your system. If it’s named licenses, floating licenses, token-based licenses, or whichever model is offered by the vendor, not only will you know how well your inventory is performing, but also simulate which mix of licenses and payment agreements will be perfect for your organization.

[17:03] And this is how it’s done. We put the client component on the license server to track the vendors there, the check-ins, the checkouts. Now, that’s level one. For level two, we put the same client component on the end user workstations to give us a more fine-tuned view into their activity with those licenses. All the information flows from all clients on the network to a single centralized core component where you can get all the analysis, the reports, the dashboards that you need in order to analyze the information gathered across the network.

[17:48] And now I would like to leave some time for any questions that you might have for me. So take it away.

[17:57] All right, I have a question here. How much data do you need before you can decide who are the heavy or light users? 3 months, a year, or can you do it with less? Well, of course that more is better. I would say that 3 months, 2 months is the minimum. 3 months is pretty good. A full year is the best option because then you can find the seasonality of usage. You can find maybe users that are just using it on a project basis and looking only at two or three months might not be enough. While looking at a full year, you’ll see that you had peaks along the year depending on the seasonality and patterns of that year. But you can of course do that even with just one month depending on how bad the situation is or how good.

[18:57] Is there an option to reallocate those named licenses? That’s another question I’m getting here. Well, we have the clims component which allows you to remotely access the options file and modify it in order to reserve licenses to different users. So, it helps you by not having to go to the server itself, opening the options file, you don’t remember what you changed. So you can do it using the clims module and it helps you not only modify it remotely but also saves all the history. So if you want to revert you can do that easily.

[19:43] Another question I get here is is there an AI component available for getting insights on usage? Yes, we have the license predictor as well that uses AI in order to analyze the patterns and let you know what will happen in the future based on let’s say a year, two years of information. It will know the seasonality and you can even feed to it how many users are you expected to increase and it will show you the concurrent usage based on previous patterns.

[20:25] How can you tell if a user is active or inactive with a certain license? Well, for that we have the client component and it tracks several key indicators. It tracks the CPU usage, memory usage, it tracks reading and writing to the disk that relate to the application itself. Now we can find if the application is doing something, the process will draw up CPU memory. It will read and write to the disk. So we’ll know that it’s active only when everything falls flat. Then the system will know that it’s not active anymore.

[21:16] You’re welcome to ask anything. You can put this in the Q&A section. You should have it in your Teams interface. Any question you would like to ask, we’ll be happy to answer.

[21:32] As you might know, we have a blog that we post articles on almost every week. You are welcome to scan now the QR code. We have two recent blog posts. Stop the 500k software license audit drain with Open iT, helping you with the dreaded audit on engineering software licensing. You can optimize e-plan licenses for engineering efficiency.

[22:10] You can also contact Open iT and connect with us. You’ll get a business solutions consultant for a free 30-minute consultation. So you have the QR code right now. Feel free to scan it and schedule a call with us. We can solve any issue you might have.

[22:36] Now if you’re interested which reports I’ve been using, you can find it in the denials report, days since last used report, and also in this summary report all in the SSRS report.

[22:58] And that’s it. Thank you very much for your time. Thank you for joining and have a wonderful day ahead.