John Cody:

Great. So we are going to get started here. My name is John Cody. I lead the product and tech team at Supply Hive. Very happy to be in attendance today. I'll mostly be in the background, but we are also joined today by Ryan Lakes and Anton Lag ak. I'll pass it over to you, Ryan.

Ryan Lakes:

Thanks John, really appreciate that and appreciate everyone joining today. As a team, we've had the privilege of collaborating with hundreds of enterprises, each with their own unique approach to supplier performance management from global Fortune 500 companies to complex multi-tiered programs. We've seen what works, what doesn't, and where technology can make a big impact. So today we're excited to share some of the best practices and insights and lessons we've gathered along the way. So really appreciate again joining as supplier ecosystems grow more complex and expectations of procurement teams continue to increase. We know the need to manage performance effectively at scale has never been greater. So many organizations are realizing that manual tools and fragmented processes simply can't keep up. So today's webinar, we'll walk through how leading enterprises are modernizing their supplier performance management programs using Purpose-built technology. We'll also share real world examples, explore strategies like combining qualitative and quantitative data and to unified scorecards show how AI can turn feedback into actionable insights. We'll also provide a brief overview of Supply Hive in a live demo. So you can see how these best practices come to life through technology. So whether you're just getting started on your program or looking to scale an existing program, the session's going to be packed with practical takeaways and proven approaches to elevate your supplier performance program. So thanks again. So to kick things off, we'll go to the next slide. Talk about the problem that we solve. So 75% of global Fortune 5,000 clients, our customers measure performance of their top suppliers, which is a great thing, but only 90% use manual processes or old technology. So this is costing corporations a tremendous amount of money and lost value. So over seven years ago, supply Highs started our journey to help corporations solve this gap in this problem of a very manual process. Going to the next slide, I'm going to spend just a few minutes giving you a very quick overview of Supply Hive. So we're headquartered in Chicago, but we work with corporations and teams all around the globe. We're focused on providing SPM technology to companies looking to get the most out of their suppliers. So S spms, not just about the numbers, it's about alignment with your suppliers and driving accountability towards being the best supplier for your organization requires a balanced scorecard approach with both qualitative and quantitative data. We also help focus scaling programs. That includes the number of things. It's not just scaling the number of suppliers and spin under management, although that's a big one. It's about scaling the frequency that you're capturing data, whether it be annually, quarterly, monthly. We're trying to increase that. It's about the number of inputs and data captured on the supplier. So it's scaling the participation rates on assessments, scaling the data coming in from the different systems. We also focus on strong partnerships that allow you to collaborate with suppliers to be at the forefront of innovation. We found that collecting qualitative data is extremely powerful in providing transparency and building those strong partnerships. We also have what's called the Hive 360. It's a supplier self review. So they're reviewing their own performance, which creates alignment with you and your team. Last around innovation is voice of supplier suppliers offering your corporation feedback on Haley Lake, working with you as you strive to be a customer of choice. All that transparency continues to lead to innovation and strong and strengthen partnerships from productivity and streamline process. Technology can automate a lot of the manual work being done all the way from the data collection to the reporting and output that's shared with the supplier. And last but not least, when you think about governance and compliance, governance is about providing structure, accountability, consistency on how you manage your suppliers across the organization. It's also important in order to align with the suppliers. You think about governance, you think about things such as action plans, granular permissions, templates, audit trails, they all come into play and technology can help with that. The other piece of it is compliance, which is focused on the contractual obligations. So tracking S-L-A-K-P-I, adherence documentation, ongoing monitoring, alerts, notifications, dashboards, reporting, all key parts of making sure you have a compliant program. So with that being said, technology can bring all these elements together to support really truly a world-class SPN program. If you look at the next slide, so we have over 8,000 suppliers and well over 25 billion in annual spend being managed in our platform. It's both across direct and indirect suppliers. So again, we work with a lot of large enterprises, a of large suppliers, and what we see and what we're going to share today is how technology's helping with that process. So with that being said, we're going to kick things off with several poll questions that will help guide us in today's overall overview. John, if you don't mind, can you please pull up the first poll question and the audience on today? We'd love for you to participate and select the choice that's most relevant for each conversation. Give it a couple minutes here, give about 10, 15 more seconds for question one. We'll move on to question two.

John Cody:

Alright, I'm going to end question one here

Anton Lagochniak:

And get into question two.

John Cody:

So you should be seeing question two now of what tools do you currently use for SPM or SRM? Alright, another 10 seconds or so. And our final question here is what types of data are you tracking related to your suppliers? Just another 10 seconds or so. Well we give everyone a chance to submit the response here,

Anton Lagochniak:

Right? Going to go ahead and

John Cody:

Close this out. So back to you Ryan.

Ryan Lakes:

Thanks John. So we'll be sharing those results here with you as we go throughout the discussion today and be highlighting some of the key points there. So with that I'm going to actually pass it over to my colleague Anton. He's actually going to walk through and share some case studies as well as walk through our platform and share some of the things that we've discussed today already around quantitative and qualitative data around AI and the use of AI within SPM and a little bit around reporting and the impact that's having on corporations. So Anton, I'll pass it over to you.

Anton Lagochniak:

Great, thank you Ryan. For those that I haven't met, thank you all for joining today. My name is Anton Lagochniak. I am the customer success and solutions lead here at Supply Hive. So excited to walk you through some scenarios, some trends we're seeing with our clients and prospects and how a technology like Supply Hive can tackle those opportunities to improve your supplier performance management program. So scenario one here, so power of a balanced scorecard combining quantitative and qualitative data. So what we've seen, and again, a lot of the companies we've seen that are just starting out their supplier performance management programs, a lot of times they're only looking at subjective data, qualitative data, asking rating typed subjective questions to their reviewers and different individuals internally that work with the suppliers and then asking for open text data. And then we see a trend as these clients mature where they start bringing in some hard metrics and quantitative data. So think SLAs phase, things like on-time delivery, percentage resolution time, things that are quantifiable and real hard metrics that give you a better sense of the true performance of the supplier against some key metrics. And then finally, and what we've been seeing most recently with our most mature clients is that they've started combining these two aspects. So the qualitative and the quantitative into the same scorecard in order to have a full consolidated view on how a supplier is performing at any point in time that incorporates those two very important pieces, which is the qualitative side and of course those hard quantitative metrics. So now not only are they able to track performance based on direct responses from reviewers to understand their perspective and sentiment, but now they're also adding in the hard data to measure the most important SLAs or other metrics which results in that complete overall score on the supplier's performance. Just as an example, one of our Fortune 500 global manufacturing clients that recently launched with this approach has already seen significant progress and improvements in both supplier performance as the culture of transparency that they've been able to enable. And just overall having all of that consolidated into one place is helping that performance improve as well as the sourcing managers that manage these suppliers be more efficient with their time as they collaborate with the suppliers to help them improve in specific areas. So that being said, I'll jump over to our live product. We have an example prepared that's based on a real client for you here today to look at how this will look like in a technology like supply hives. So for the demonstration piece, just imagine that I am a key procurement team member in your organization and I want to start by looking at how my top suppliers are performing overall. So if I head over here and head over to supplier matrix. So a lot of times when we're starting to analyze the data, I like to start and a lot of our clients will start in the supplier matrix. And this is currently we're looking at a project that combines that contains my most strategic suppliers. And of course this scorecard specifically, it aims to give me a complete view into supplier performance as it combines qualitative data or qualitative KPIs with the quantitative data that we have on these suppliers. So the supplier matrix is simply a snapshot of how all of the suppliers stack up with one another. You're able to sort the suppliers on any specific KPIs like customer satisfaction if I wanted to or even the number of reviews that were submitted. I can also, if I scroll down, let's filter it back to how we're looking at it by just overall score. I can also look at the data broken down by child record. So this is a lot of times what our clients are using to get a bit deeper and not just understand how a supplier is working at an overall level, but looking at different areas. So it could be categories like we have here for Microsoft as an example, if they're really performing well in one area of the service that they're providing you but they're underperforming in another, that's an important insight to have to then be able to dig into that a bit deeper and look at what's happening on the software side. In this case that isn't happening on the hardware side. You could do that for multiple suppliers like we have it here for Adobe. And then as I'm analyzing this, a lot of times, again, we're seeing your qualitative KPIs here at the top, but then we're also getting into some quantitative metrics. So for this one we have, I believe it's four SLAs that we have that we measure all these suppliers on. You want to have it be in a place where you're measuring your suppliers on the same things, whether it's different SLAs or the same SLAs, you're still looking at SLA performance to stack them up against one another. And then scores like risk score, sustainability, those can also be driven by hard metric, maybe something for EcoVadis or from your risk management system to incorporate that quantitative piece from that perspective as well. So now if I look through the data and I can again filter it or sort it on things like supplier spend, immediately I'm going to notice that hey, I have a supplier Siemens that I'm spending the most with in this case, but they are underperforming. So that's one that I will definitely want to look into a little bit deeper to understand what's going on. And to do that, we simply go into the supplier dashboard, which has all of the relevant data in a multitude of different helpful visualizations to help you understand how Siemens is doing in all of these different areas. So here we're in the Siemens supplier dashboard and this hosts all of the performance data for a supplier in various views, which are the tabs that you see here at the top. In addition to the performance section, there's a profile section, we won't go into that today, but that just hosts the non-performance data that you want to keep on your supplier. So right away you're going to be in the scorecard tab, which is a really great place to start to get an overview of how Siemens is performing. So you have these three scores at the top, and I'll just quickly cover what those are if you're not familiar. The performance index is simply a quantitative average of our scoring. The relationship index is now generated by our proprietary AI machine learning behind the scenes that analyzes the sentiment of every comment that comes through. So again, enabling better scalability, giving you a better sense of the story behind the score to understand how your stakeholders internally feel about working with the specific supplier, not just what the quantitative aspect says. And then finally, you have your HIVE score, which is a combination of the two. Generally we recommend 80% performance index, 20% relationship index in order to get a bit of that sentiment incorporated into the overall score. So as I scroll down here, you'll see by KPI, there's also being strengths. Again, you have your average sentiment, but you also have strengths and opportunities being extracted for each KPI. So again, this is our AI machine learning working behind the scenes and it's extracting the most positive and negative comments for you to highlight those for you. So in the cases where you have many reviews and a lot of different insights within those reviews, the tool actually helps extract those to again, to enable better scalability through a technology like supply hub. That is a big piece of what the platform will do for you is extract those actionable insights as we scroll down here as well. So for example, if I take a look at quality performance, that seems to be one that's underperforming. I can again see specific opportunities and I'll notice that durability is a concern and malfunctioning components, support materials, something for me to keep in mind as I work with the supplier to improve on some of these different areas or opportunities for improvement. Then as I go down, something like, and this is when we bring in the hard data, so looking at the hard metrics and SLA performance, you'll have your risk score of course, just a simple risk score. And then in sustainability we have a combination of ecova and a mid midwife score. So two softwares that help manage that and that's being brought into here. But then the SLA performance is where it gets really interesting. So here I'm able to see not just the percentage of SLAs that a supplier is hitting, but I can also see the target for each. So at a glance I can tell, okay, they're actually doing pretty well, they're hitting most of these, but resolution time is clearly something that needs to improve. So we see that that target is not met in that case and that's how we're getting to that SLA performance score that's now being rolled into with the qualitative data to give you an overall view of how your supplier is performing. Again, I forgot to mention this earlier, but please as we go through this, put any questions you might have in the chat so we can cover those. We'll have some time for q and a in the end, but please feel free to ask any questions you may have on what you're seeing here today. So taking this combined approach a step further, we have a number, a variety of views that are also helpful to look at. So something like benchmarks, you could look at one of the qualitative scores, and this is just looking at how Siemens stacks up with other similar suppliers, which is really helpful to understand, okay, I'm spending a whole lot with Siemens in this case. Are there similar suppliers that are outperforming them that we could potentially look to expand our business with? So something like customer satisfaction versus let's say SLA performance. That could be something that's interesting to see just to see where does Siemens stack up against other suppliers. So Cigna in this case is excellent in both of these. So that might be one that I want to look into further and just understand that Siemens is sort of middle of the pack in this case. The trends tab is also really helpful and again, something we see a lot of our clients using with these consolidated quantitative and qualitative combined scorecards. So something like high scoring, just seeing how that evolves over time and then adding in, so quality performance was one that was underperforming, maybe pricing and cost reduction. So okay, it's been going up, but why did it dip? Again, that raises a number of questions that I might want to look into further. And then of course SLA performance, if you have more data here than just one quarter, you'd be able to see how that's evolved over time and whether or not Siemens or any of your suppliers are hitting these targets over time at a glance. So I think that for the most part, that should give you a bit of an overview on how a lot of our clients are starting to look at supplier performance management and combining those quantitative and qualitative aspects. Of course, you always have the raw data in the reviews tab, but overall some of these more consolidated views and summarized views will help you scale your program of course, through the use of a technology like supply hives and be able to do more with your suppliers and really run a world-class supplier performance management program. So that being said, let's switch back over to the science and look at another aspect of what we see as a major trend with how clients are scaling their SPM programs using our technology. So scenario two here, and I'll just go back to the slideshow and then we'll jump right back in. So using AI to generate actionable insights, this is a really big trend we've been seeing with the explosion of AI pretty much everywhere we've seen that also become very relevant in the supplier performance management world. So it's becoming a much bigger trend with our clients and prospects, mainly because it is currently difficult for limited procurement teams to scale, to be able to extract both actionable insights and then actually be able to do something about that and collaborate with the suppliers to help them improve at those areas across their supplier base. There's a whole lot of suppliers. So what we see most often is without something to help summarize that and extract the actionable pieces and then actually help you plan and collaborate to improve that, it's really hard to manage more than a certain limited amount of suppliers. So we've seen a lot of our clients start to use our proprietary AI in our system more and more for this to fill this gap, both for those actionable insights and generating action plans to tackle areas of opportunity for improvement. So let's take a look at what this looks like in the platform. So first and foremost, we have a summary tab that is available for all of the suppliers. It is generated for every supplier, especially for a scorecard that combines those qualitative and quantitative pieces. It is especially important to look at something like a summary. So essentially what our summary does is it will take all of the ratings, all of the quantitative data, all of the comments, and summarize into just a couple of bullet points on the positive side and opportunities for improvement. It will do the same for every KPI. So for those KPIs that have OpenText responses, it will give you some more details, positive opportunities for improvement. It extracts themes for you. So again, the point is being able to scale to manage more suppliers through this and understand how they're performing with these automatically extracted actionable insights for you that you can actually do something with. So again, as you scroll down, then for something like SLA performance, you'll be able to see that as well and this consolidated scorecard. And from a scalability perspective as well, what we've seen more and more is using views like this one and the scorecard where it's extracting those actionable pieces for you to actually run the Q bs with your suppliers through this. So it just enables you to do that a bit quicker, a bit more efficiently, and actually have that conversations or those conversations with your suppliers right here in the platform looking at these consolidated summarized views and focus in on specific areas. So again, looking at quality performance, that's the one that I've been focusing on. There's positive feedback, there's negative feedback, and on top of that we take it a step further with suggested action plans. So the system is also able to generate fully fleshed out suggested action plans for you based on all of the data that is coming through in the scorecards. And that's something that really helps scale your program as now you're able to get those insights and also generate action plans to use the suppliers improve all in one place. So yeah, just to cover that a little bit further. So in the action plans tab, you'll see those suggested action plans. Again, those are automatically generated through our proprietary AI and they're fully fleshed out. So they have all the details, a full description, action steps, and again, they're very specific to the data in the scorecard. When you're looking at your quantitative and qualitative data and you don't know what to do about it to help the supplier improve, you can use functionality like this to help decide what to do with your suppliers and what they can work on. You can also create action plans, of course from scratch, but won show that right now. The key thing is, is that you do have that ability to do it through AI where you can just accept this action plan, mark it not started, assign it to the supplier, and then they know to start working on this and working to improve that specific aspect. Another way that can generate these action plans is this button actually right here in the corner. So if you had some kind of context or some specific data set you wanted to generate an action plan on, again, our AI can help you do that where you can just give it some context or attach something and ask it to generate an action plan based on that. So just as an example, quality performance as a KPI have been focusing on throughout this demonstration. So I could ask it something like, please generate action plan around the performance API, and then the system will know to look at the data within Supply Hive and actually generate that for you. So again, something we've seen throughout our client base become more and more adopted, leverage further and further as teams are really looking to scale already successful programs to more of their supplier base going past just the A level strategic suppliers that they might have. So as you can see, we have a fully generated action plan with specific steps based on the data within the scorecard itself, which is something that cuts down on the amount of time needed to actually actively manage a supplier relationship and help them improve in certain areas. I'll pause here, Ryan. John, are we seeing any questions in the chat that we should address right now before we move into the last scenario here?

Ryan Lakes:

Yeah, Anton, I know we're looking at time too and be respectful of time. I think we could, there's a couple of questions that we had to come through and also maybe share a couple examples of the poll results, but if you do have any additional q and a, again, have some here that we can talk through and happy to stay on a little bit longer. But I think moving on to the last slide would be best and we can talk through the webinar coming up here later this month where we can cover more.

Anton Lagochniak:

So sounds good.

Ryan Lakes:

If you don't mind moving to that. I found it interesting just looking through a couple of full questions. The first one being, what is your biggest challenge in managing supplier performance today? And the top four answers too much time spent compiling data, lack consistent metrics across teams, difficulty translating scores into action, poor visibility and supplier issues was pretty staggering and we can share this, but it was really spread out between those four all about the 2020 5% range, which is pretty common with the clients we see. Everybody has different challenges based on the stage that you're at. And so again, when you think about technology, it helps a lot of these, but some of 'em around consistent metrics across teams, we help a lot of clients help get to a point where they can get consistent metrics and what they should be tracking, what SLAs they should be looking at. So we kind of have that consultancy approach as well. So technology solves a lot of these, but there's also a component where there's just internal alignment that needs to happen. Question two, what tools do you currently use? Again, kind of spread out, it was heavy on spreadsheets, it was 70% right at 70%. If you notice the slide that I had originally, we had originally up, I mean that's pretty common. Also, legacy tools about 10 inhouse systems, about 5%. And third party SPN platforms about 10%. So again, heavily on spreadsheets, which is very common and typically that's what we see prior to supply hive. You're either using a very manual process or you're using some type of legacy system that has a module. And so that's where we've had a lot of success sharing our technology and solution to help with the things that we discussed today. The last question, what types of data are tracking related to your suppliers? Again, not surprising, about 75% was quantitative only. So SLA targets and deliverables, qualitative, a small percentage in both pulled up was the second in line, that was about 20%. Again, I think this shares to what we talked about today of getting past just the quantitative metrics. They're extremely important to measure, but also adding the context, the qualitative data, the sentiment and feedback really helps the relationship component. We typically ask clients that are not doing qualitative or a lot of qualitative data and the answer that we continue to get back is just the time that takes to read through the reviews, aggregate the data and report on it. And again, that's the value that with technology and artificial intelligence and how we utilize it, not only to summarize the data, but to drive action plans becomes extremely important. So again, we'll share those results but thought very interesting and pretty close to what I would've guessed prior to the call. So thank you for participating. For those that continue can stay on for a minute. I think we may have, I know we have some questions here.

Anton Lagochniak:

One more scenario to cover really quickly, Ryan.

Ryan Lakes:

I'd say we probably hold that Anton and move to the final just based on time. And then we can cover that in our next scenario on the next webinar. I think that is on the next slide. Yeah, coming up. So we have an upcoming webinar, transforming Supplier Performance Management through Technology. We'll also put a link in the chat here as we're talking and I'll do that. And John and Anton, if you want to look through some of the questions here, maybe you guys can tackle those, why I bring that link into the chat.

John Cody:

Sure. So there's a couple of questions here. Let's start with the first one. What's a typical implementation timeline for a company transitioning from Supply Hive or I'm sorry, transitioning from spreadsheets to supply Hive? Anton, could you take that?

Anton Lagochniak:

Yeah, absolutely. That's a great question. Thank you for asking. So generally, we see that implementation timeline to be anywhere from three to six months. I would say in most cases, usually closer to a three month mark depending on how mature the spreadsheet process may have been. But we can adopt any spreadsheet process and bring it into the platform and enhance that pretty quickly. So I would say closer to three months, rarely do we ever get to six months, but in some cases when there is a very defined scorecard and we have a good idea of what information we'll be looking to collect, that can be as fast as a month and a half, two months even in those cases. So it's not a very long implementation timeline. I will say most of the work is just configuring and setting up the platform the right way and having those discussions where since our platform comes with a whole lot of configurability and a lot of different options, that all needs to be covered prior to a product launch to make sure that we're getting the client the most value they can get out of the system.

John Cody:

Great, thanks. And yeah, I guess this is really a question for either of you, Ryan or Anton, do you have any examples that we could share? The question is, can you walk through an example of how AI generated action plans work in real world use?

Anton Lagochniak:

Sure. I guess in most cases it is a true collaboration, and I could show this in the platform as well, but I don't want to take up too much time here. But in general, it's a real world collaboration between some internal stakeholder, like a sourcing manager and maybe an account owner on the supplier side. But for example, something like quality performance where you have those specific steps, we can actually quickly go back to that just to illustrate the example. So these are ones that we've actually seen we walk through for our existing client base, but let's take this one, enhance customer engagement to strengthen supplier management team. The way it works in the system is you'll have this ready to go if you want to accept it and then assign it to a supplier you can or you can make edits to it prior. So that's usually the first step in that process, but it is very detailed and has all the steps that you would need to really work through something like this. And then once that's accepted and it's assigned to a participant, let's say, I dunno, I'll just use Abigail as an example. We have a number of notifications and alerts available in the platform to help with this collaboration piece that happens through the action plans where if anybody's assigned or an action plan or something becomes past due or there needs to be some commentary. So for example, if I had an Abigail here and assigned an action plan too Siemens, she would be notified that, hey, there's an action plan here for you. And then it would be on the supplier to work through that action that's been assigned to 'em. Once they're done, they can mark it complete and then that notifies the internal stakeholder in that case. But lots of different ways to collaborate while the action plan is open. One of those that we see being utilized quite a bit is the comment section. If I add and then add Abby here, please give me an update on this, that would also notify her that there was a comment here for her to respond to. But again, all built in order to enable easy collaboration. So in general, there's a lot of different examples that we could give of AI generated action plans that have been accepted and then worked through with the supplier. But in general, that's all done through that collaboration within the system. Once that action plan is edited, accepted, and assigned for the supplier to begin working on it. So it truly is a back and forth between the internal stakeholder and the supplier.

John Cody:

Great. Thanks Anton. One thing, maybe just to add too, from what I've seen with this is it's really common to have the leading into A QBR. You've gotten all your assessments, all that data has been collated, aggregated, and then the AI generated action plans can help steer the category manager, whoever's owning that QBR to help direct the conversation and point out some action items that could be a priority for going into the next quarter. We just have one last question here, which I'll take. It's more product centric, but the question is, can supply of integrate with our existing tools like SAP or other ERPs? And the answer is yes. Essentially we have an open API both inbound and outbound where as long as your system can make an authenticated HTTP request, we can work with it. So with our customers, we can happily provide documentation on it. So there's a little bit of setup that needs to happen, but out of the box we do support working with our rest API, which is how that solution would sort of work. But that wraps it up for questions unless there's any others, feel free to put them in the chat here. But with that, I think we are probably good to close out this webinar. Any closing thoughts, Ryan?

Ryan Lakes:

Yeah, thank everyone for joining. So we have the upcoming webinar in the chat, so we'll go into more depth. I know there was a third scenario we weren't able to cover today that we'll go into on the next call, along with some additional scenarios that would be of interest to you based on the topic. We also have a video recording of today's webinar that we can send out. And if you have any additional questions, please reach out. You can contact [email protected] and somebody will be in contact with you to respond and happy to set up a call. So appreciate your time and thanks so much and look forward to continuing our conversation in another time. So thanks so much.

Anton Lagochniak:

Great.

John Cody:

Thank you everyone.

Anton Lagochniak:

Thank you everybody.