アイドル・ノー・モア未使用ライセンスの回収と再割り当て

[0:01] Nix: Good morning, good afternoon, and good evening everyone. Welcome to Open iT’s webinar titled Idle No More: Reclaiming and Reallocating Underused Licenses. My name is Nix and I’ll be your host for today. In the next 20 minutes, our speaker will help you uncover license waste and show you how to turn underused licenses into active assets.

[0:23] You’ll gain clear, practical strategies to save costs, reclaim value, and align your license usage with actual business needs. Feel free to send in your questions via the Q&A panel at the top of your screen. We’ll answer them after the main session. If you can’t get to all the questions live, don’t worry. We’ll follow up via email or LinkedIn. Now, a quick intro to today’s speaker.

[0:46] As a solutions architect, Sagi has one mission to deliver results that add value to his clients. Highly experienced in customer relationship management, he has worked with high-profile clients from multiple verticals, helping them reach their goals by maximizing their software investments. Let’s give a warm welcome to Sagi.

[1:08] Sagi: Thank you very much. So, welcome to the webinar. At Open iT, our service provides a few value propositions. Let’s start with that. We ensure that you are fully licensed and compliant at any given time. That you can effectively plan for the future and plan budgets, reduce licensing cost, and avoid unexpected costs.

[1:38] We help optimize your license resources by making them more agile through better use of resources. We provide visibility into true active usage by user, department, application, or any aggregation that you’d like. And finally, you can justify your purchases and reduction of licenses by achieving cost avoidance based on true usage.

[2:06] So today we will be following a few indicators analyzed by one of our customers during their optimization efforts for lowering license consumption relating to license reclamation, user idle times, and overall maximization of usage patterns.

[2:33] Now Murphy Oil is a large customer in the oil and gas vertical. They had a unique challenge. They needed a companywide management view of their IT assets and engineering applications. Specifically, an overview of geoscience exploration software usage.

[2:55] Murphy Oil utilized levels 1, 2, 3 on their existing infrastructure for first finding any misuse of software licenses, finding idling users, and any mismanaged application usage.

[3:14] Secondly, they implemented successful license harvesting and reclamation methods in order to automatically optimize their existing software usage, resulting in a $1.4 million cost reduction after the first two years of implementing Open iT, stating that within the first year of implementation they were able to use the reports to make informed decisions about their company’s overall software portfolio.

[3:50] So let’s take a look at what they used and how.

[3:58] We will first start with a view into LicenseAnalyzer™’s three tiered solution where level one allows for generating analytics based on license usage, meaning license checkouts and checkins, generating various trends and important KPIs on license usage. First figuring out how much and how well license pools are being used, indicating if the portfolio is underused, overused, or maybe positioned just right.

[4:34] Level two allows for understanding the user’s usage patterns. Meaning, what are the users actually doing with the licenses after they have been checked out from the server? Providing analysis of active versus inactive usage on different licenses.

[4:54] Now the next logical leap is level three, meaning harvesting those inactive licenses which are just sitting on the user’s machine and retracting them back in the pool, allowing for automatic license reclamation of unused licenses, dramatically reducing the perceived usage of these licenses.

[5:21] Let’s dive into level two and find out how we monitor true active usage and report on idle licenses.

[5:33] So, what’s really going on with my licenses? Level one first gives your organization a look into license inventory, meaning the licenses that were purchased and installed on your system. Then it indicates the trend of your concurrent license consumption based on licenses leaving and returning to the server.

[6:02] You can see it here that it seems that we really needed more licenses as time went on, prompting us to purchase more and more licenses as the usage just kept growing.

[6:17] But starting up level two usually reveals a whole different story. Based on user usage patterns, we can see that many of them are idling with the application for a long time during the day. And our necessity of licenses would actually be much lower if everyone was using licenses only when they need them and were keeping inactivity to the minimum.

[6:47] Presented here is the true active usage line allowing to understand that if users manage their license correctly, we’ll basically need much less licenses than what we have and the false sense of needing more licenses basically goes away.

[7:12] But how is it done? How can we tell if a user is using the application license or not? Well, for level one, we needed a clear view into the server. So, we put a client component on the license server itself. But for level two, we need a more focused look into the user usage patterns.

[7:34] So, we take the same client and now we put it on the end user workstation. So it can give us a more fine-tuned view into what the user is actually doing with that license that he checked out. Open iT tracks various indicators. The application process might be reading and writing to the disk or using the processor or memory or even user activity with the application like clicking the keyboard, clicking the mouse.

[8:06] And in order to determine if the user is engaging with the application, we need that client component there. And we see if the application is running something or maybe the user is interacting.

[8:20] Now, a question that pops up a lot is what if a user is not actually using the application, but the application is doing something? Maybe it’s running a simulation or a calculation that takes a long time without the user actually engaging with the application. Well, will Open iT find it as inactive?

[8:42] Well, no. Open iT knows it’s active even if the user is not there. Let’s take this case. We have a user who clicked the mouse a little bit, clicked the keyboard a little bit, but then he’s gone. The line flattens. Maybe he went on a meeting, maybe he went home, maybe he’s still on the workstation but not actively using this application.

[9:07] We see that he left the application to do something as the process takes up processor power, reading and writing to the disk, using up memory. So, Open iT knows it’s active. Only when everything falls flat will Open iT start counting the idle time.

[9:28] Then Open iT provides various reports on active versus inactive usage per application, per user, over time, whichever report is needed.

[9:43] And here’s an example of such a report from our customer. First showing us the active versus inactive usage over time where we can see that the inactivity averages at about 44% for the whole usage time, which is very significant.

[10:04] Then we can layer on top of that the efficiency trend showing us that out of the pool of 21 licenses, we actually don’t need as much licenses as we think, as the 21st license was engaged only about one day out of the entire year. Same goes for the 20th and 19th license. We see that they actually barely used them, meaning that they are redundant, and to have an optimized licensing system we will need only around 16 licenses instead of 20, as over time we can find the licenses are checked out but not really used.

[10:56] So how can we mitigate that? How can we make sure nobody is idling with the licenses for too long? Let’s say that we have a user and he left for a long time. He left the application open and not processing anything. Well, after a predefined amount of time, his application will get suspended and the license will go back in the pool for other people to use.

[11:29] This automatically optimizes the license consumption to meet the true active usage in the reports because it ensures no one is leaving their application just open doing nothing. And we have robust reporting capabilities to show you all active, inactive, and suspended usage, painting a complete picture of license usage patterns after the licenses have been checked out.

[12:02] So how do we reclaim and reallocate on a large scale in our various teams? Well, first we’ll have to detect the users who are idling with their licenses for a long time and then find out if it’s a major issue in the organization.

[12:26] If we do find that many users are indeed idling, well, it’s inhibiting the workflow. We’ll set smart thresholds on license reclamation, basically defining the time span we allow users to stay idle before reclaiming that license.

[12:49] Once the Open iT system finds users who are past the threshold, it will pop up a notification for those users. And if they fail to respond, it means that they’re not actively using the application or might not even be next to the workstation, allowing the Open iT system to automatically reclaim their licenses back in the license pool and freezing their application.

[13:20] So now licenses can be redistributed to other users who actually need them, helping with a smooth transition of licenses from inactive users onto active users, offering higher license availability for everybody.

[13:41] Now that we understand levels 1, 2, and 3 and how they work, let’s take a look at a few customer success stories of customers who benefited from using our optimization modules.

[13:57] Aio Arrow from the aviation industry implemented levels one and three in two phases where level one was implemented first, providing 40% cost reduction with an additional 14% cost reduction after implementing level three and harvesting idle licenses, making sure that not only will they reduce the amount of licenses purchased, but also make sure to keep it that way using the automatic license harvesting capabilities of level three.

[14:35] They first found out what their users’ usage really shows on a daily and weekly basis, finding the different patterns and the different trends of consumption for their applications. And then they took a deeper look into how many licenses they actually need after implementing license harvesting. They found which applications needed the most, how they were used by the end users, and finally how many licenses they actually need based on all the parameters.

[15:17] Let’s take a quick look at another customer success story which shows a similar story but more dramatic. This is a major commodities company that were able to set up various reclamation rules for optimizing their license usage based on Open iT’s business inputs.

[15:40] They found that their license consumption is always going up over time and users often complain that they are not able to get a license when they need it, requiring procurement to always purchase more and more licenses as we see it with the blue line rising.

[16:04] But looking at the actual usage consumption, meaning active concurrent usage and excluding any idle sessions, they actually found that their consumption goes down over time as we see in red. So basically they figured out that their ever-increasing license usage consumption is falsely presented and is not really due to more users using the application but due to more users idling with the application, prompting them to initiate level 3’s license harvesting capability, suspending any application which is left idling for over an hour and reducing the need for licenses in a dramatic fashion.

[16:56] Thus allowing them to reduce licensing cost but also enabling their users to have more availability of those licenses, ensuring everyone has a license when they need it. They stated that for one software product alone they were able to get cost savings of $639,000 on one pay-per-use license just by identifying the different idle sessions where most of their sessions were 4 hours and more with the pay-per-use licenses that were used.

[17:43] And that’s it. I would like to leave the floor to any questions you might have for me. So, go ahead.

[17:52] Nix: Thank you, Sagi, for your insightful presentation. We’ve got some great questions lined up. Let’s get right into the Q&A.

[18:07] So, we have a question. Ever notice what usually causes licenses to just sit there unused, especially in engineering?

[18:19] Sagi: Well, there are many ways, many options for this. Now sometimes users retain licenses even if they are not intending to use it right now, just in case, how they say, maybe they’ll need it later and they just leave it on the workstation so they don’t have to fight over licenses later.

[18:47] Another reason might be that they leave it for hours on end idling overnight. Maybe they just logged out of a virtual machine and they don’t know that even if they logged out the application is still running, still consuming that license.

[19:08] So it really depends on the workflow of the user. Some of them just, you know, step away for a meeting, go on a break, or maybe just go home at the end of the day and forget it on. So there are many options.

[19:26] Nix: There’s also another question here, Sagi. It’s from Rhonda. Does this help find out who has subscription licenses that are not being used?

[19:36] Sagi: Yes, you can also find not only concurrent licenses, but also subscription and named and pay-per-use licenses and see if they’re actually being used, when they’re used, but you can also see when was the last time that they were used. So, you might have a subscription license for John, but you see that John didn’t touch the license for maybe 2 months. Maybe John doesn’t need it, maybe he’s not in the company anymore, maybe he left the project. So this way you can reallocate the licenses more effectively with subscription-based licenses.

[20:18] Now for those subscription licenses, people might also use them but just leave it idle for a long time, not necessitating a subscription license. Maybe they can just be in a floating license pool if you’re able to generate one.

[20:38] Nix: Next, we have another question. It’s anonymous. How do companies are getting solid returns just by watching idle licenses. Is that really common?

[20:51] Sagi: Yes. So, we usually see anywhere between 15 to 30% cost reduction, but it really depends on the usage patterns. If you have users that grab a license and just hold it for hours on end, you’ll have better efficiency if you use idle licensing reporting and if you harvest those licenses. But if the patterns show that they are idling for a few minutes at a time or just an hour at a time, then it’s going to be a bit more modest. So, it really depends, but we can see anywhere between 15 to even 30%.

[21:35] Nix: And another question, if a team’s just starting to look into managing licenses better, what’s something they should do first?

[21:46] Sagi: So, as we said in the webinar, first just look at the patterns. How are people using it? Are they using it for a long time? Are they checking out for a long time? Maybe they are checking it out for a few days. Then you look deeper. You see that users are checking it out and using it maybe four or five hours.

[22:15] You can better manage these licenses by finding out their idle time and see if you even need to implement license harvesting. Sometimes you’ll find that the idle time is manageable. Might be 30 minutes at a time. You look at the average and you see that the average is about 30 minutes, 40 minutes and it’s okay because it means it’s a part of their workflow. They work on it, they run a simulation, they come back to it and that’s okay.

[22:47] But if you see cases where I personally seen in my 10 years experience where users they know that they’re not going to have a license. They come in the morning and they’re like, “Yeah, I got a license. Oh my god, I’m keeping this license now all day. I’m not leaving that because if I use it, if I don’t use it, I don’t care. We don’t never have enough licenses. I always get denied and have to like sit on my hands.”

[23:20] So yeah, first of all look at the data, secondly if you see it’s correct, act, start with a modest harvesting threshold, meaning if you’re idling for 1 hour, 1 and a half hour, then you can harvest that license, but then after that you can move on to more aggressive thresholds and say if 30 minutes then you get the license harvested.

[23:47] And the best way to go about this is to educate the users, send different memos, trainings, just let them know that the license they’re consuming is interrupting with other people’s work in many cases.

[24:07] Nix: And we have a follow-up question from Rhonda. Idle time doesn’t mean that their computer is idle but only that particular app. Correct?

[24:16] Sagi: Correct. It means that this specific process, this application is not working. It’s not doing anything. It’s not receiving any clicks. It doesn’t use the CPU, doesn’t use the memory. It can be in the background, it can be in the foreground, doesn’t matter. It’s not receiving any interaction, not from the processor, not from the user, nothing. So the user might be on the same workstation, but doing something else.

[25:00] Nix: And lastly, another question wondering if it’s tricky to get these tools working with other license managers like the DSLS, not just FlexLM.

[25:12] Sagi: All right, that’s a good one. So for FlexLM we basically do an LM remove. We send a command to the server and tell the server, hey, take the license back, and on the other side we suspend the application. With the DSLS, it has a heartbeat, meaning that the license server gets a heartbeat from the application every, depends on the application, but it can be every minute, every 5 seconds, every 5 minutes, depends on the application.

[25:46] And what we do is simply suspend it on the end user workstation. And once it’s suspended, then it’s not sending out a heartbeat anymore. And the next time the DSLS server doesn’t receive the heartbeat, it knows to retract the license automatically. So we basically freeze it on one end and let the server do its own thing. Usually takes 1 minute. The longest I’ve seen is 5 minutes.

[26:14] Nix: And I think that wraps up our Q&A session. Thank you for those thoughtful responses. And thanks again, Sagi. And thank you to everyone who joined us today. This webinar was recorded and a link will be sent to your email shortly.

[26:29] We also have our latest blogs. Scan the QR codes on your screen or go to resources blogs on our website. We’re also offering a free 30-minute consultation with an Open iT business solutions consultant. So if you’re ready to explore license optimization in your environment, get in touch using the contact details on the screen and follow us at Open iT, Inc. on social media to stay updated.

[27:07] Once again, I’m Nix, your host for today. Thank you and stay safe.