Peter Dorrington, ELN: Hello everybody and welcome to this Executive Leaders Network webinar brought to you in partnership with KPMG. My name is Peter and I'm going to be your host today. Now, today we're going to be talking with leaders from both KPMG and Microsoft, a modern smart warehouse, and how advances in transformative technologies can help you modernize operations and build a modern warehouse and that will help you operate at scale. So today's webinar is meant to answer some really key questions like what is a modern warehouse and what are their capabilities and how can that technology help generate benefit in all industries and business functions? And what are some of the key things we need to think about in order to ensure we have a successful implementation? Now, in a moment, I'm going to ask our expert speakers, Chad and Brian to introduce themselves, but before we do, let's get the housekeeping out of the way.
This is a webinar so you don't need to worry about your webcam or microphone being on, but we do want to hear from you. So please do put questions or comments or observations in the chat tab. I'll be keeping an eye on that all the way through our webinar and I'll try to leave some time at the end to answer as many of your questions as we possibly can. So at any point, ask a question in the chat channel and we do want to hear from you. We're also going to have a poll today. You'll find that under a tab, it will go live in a few minutes time. I'll explain the mechanics as we get into it in just a second. We will also record today's webinar so that can watch it back on demand and we'll send you instructions on how to do that after the webinar has concluded. So anyway, I am delighted to firstly ask our two expert speakers if they wouldn't mind introducing themselves. So Chad, let me go to you first, A brief introduction please.
Chad Jones, KPMG LLP: Thank you, Peter, and thanks for being here. Chad Jones, KPMG LLP, managing director with KPMG. I lead our global government supply chain and operations. Thank you.
Peter Dorrington, ELN: Thank you Chad. And Brian, if you wouldn't mind a brief introduction from you.
Bryan Hunt, Microsoft: Yeah, thanks Peter. I'm the director for our federal business applications business. The focus is predominantly on DOD.
Peter Dorrington, ELN: Right, thank you. Now we're going to come back to both Brian and Chad in a moment, but let's have a go at that poll. So you'll find that goes live in just a second. And the question is this, what is the biggest challenge that you face in your current warehouse operations? Is it inventory management, space utilization, labor efficiency, technology integration, or something else? And if it's something else, please put your answer in comments and I'd be interested to see what those are. So the question again, what is the biggest challenge you face in your current warehouse operations? Is it inventory management, space utilization, labor efficiency or technology integration? We are going to let that run for a couple of moments and whilst it does, what I'd like to do is to hand over to Chad and Brian to set the scene for us and describe a little bit about what is a smart warehouse. So Chad, let me hand over to you and if you wouldn't mind, a fuller introduction would be nice too.
Chad Jones, KPMG LLP: Thank you so much, Peter. So as I mentioned at the outset, I lead our supply chain and operations service network. This is where all our capabilities and approach align to warehouse, operations depot, repair operations, and so on. To Peter's point, exactly. Let me answer that in two ways. When you think about a smart warehouse, we think about seamlessly integrating and moving gear and supply with personnel throughout all six phases of operation. And that's receipt storage, inventory issue, shipping and delivery. But there are two main components of this, Peter that we typically address. First is the seamless movement of people and personnel. So integrating the personnel within this operation, we have to make sure that the material handlers and supply tech throughout this operation are integrated into the technology and solution that we deploy. A second, we want to digitize the operations or the paperwork in this process.
What you find in a non-smart warehouse, Peter, is typically those items that are moved manually, clipboard, pen and paper require people calling out, recording, highlighting or hand keying information. And this is where most of the mistakes happen. Thirdly, is automating those mundane movements and that being MHE or mature handling equipment manually moving across any one of those operations. But finally it's the metrics that matter. It's the KPIs and metrics that matter to our clients. So we want to make sure we are able to deliver bottom line results and those typically fall into a couple categories. Mission readiness, we want to increase speed or throughput of product, we want to reduce cost and overall we want to make sure we enhance mission readiness. So integrating all of those into a smart warehouse is kind of the basis at the 10,000 foot level.
Peter Dorrington, ELN: Right. Thank you very much. Chad. Brian, would you like to add anything to that?
Bryan Hunt, Microsoft: Yeah, the only thing I would add to what Chad shared is that the real power of the solution and the platform is beyond the speed to delivery. It is the automation. Most of the things that we find in any broad solution, especially in warehousing, the interaction points with human elements are where things either have challenges with data entry or input or follow up. So having that all be basically pushed into a business process helps for both speed and also helps for accuracy.
Peter Dorrington, ELN: Great. Thank you. I'm just going to, Chad, if you wouldn't mind, I'm going to come back to an interesting point you just made there about our role when we're looking at a smart warehouse, which is not only having the material in the right place at the right time, but also the people. So we've got the right people with the right skills in the right place at the right time, ready, willing and able to make a difference to our organization. And I think that's something that's very easy to overlook. And of course one of the things about any transformation project is that it's an opportunity to improve things, not just speed of throughput, but actually that we work smarter rather than just harder or faster. Take a look at some of that in a little bit more depth. If you wouldn't mind. The first question I'm going to ask you, and we'll come back to the poll results in just a second, is as we go through this discussion about automation and the smart warehouse, how is Biz apps being leveraged to accelerate supply chain solutions for the organizations you've worked with? And what does that look like? So I can envisage warehouse, but what does the Smart warehouse look like for some of the organizations you've worked with?
Chad Jones, KPMG LLP: Absolutely. Thanks, Peter. That has a great question. Let me start with the umbrella or overlaying part. When you talk about biz apps, what Microsoft Dynamics 365 does for us, what it creates for us is a way to integrate all components of this process. And I'm not just talking about the people as you focused on a few minutes ago, although that is a very compelling point of this process, but every conveyor, every autonomous robot, every tablet, every scanner, every headset, every digital component of this process, we're able to integrate using D 365, the PLCs that run all of these components, create that integration to where basically our material handlers and supply techs, Peter can walk into a warehouse, perform their function starting at seven 30 in the morning and they can operate off of one headset, one tablet, or one scanner. We want that seamless of an integration to take place and D 365 allows us to go do that.
Now how does it do that? It creates that integration point. If we think back just 20 years ago when at the height of when we started modernizing warehouses, we were asking material handlers and supply techs to sometimes wear 2, 3, 4 different types of scanners, have multiple input mechanisms because we couldn't integrate effectively across different platforms. Just there wasn't the API interface or connectivity that allowed this to take place. D 365 not only allows us to go do that, but allows us to configure it very easily. So when you think of biz apps from that point of view, if you walk into any of their smart warehouse where I'm sitting right now at an aviation site, you can walk into this site and you can see the material handlers, the supply tech, the artisans operating within all of these pieces of equipment. They don't have to switch gears; they don't have to switch tablets.
They're seamlessly integrated in this process. And what we want is those KPIs and metrics to really resound or come forward in this process to see this in the dashboard output, to see this in the Power BI output through this process to be able to see throughput go from three to five days from dock to stock. In some cases we're getting down to six tenths of an hour, arriving at the dock onto a shelf in six tenths of an hour, somewhat unheard of in cases of this type of government operation. So that integration point has been probably one of the more compelling sides of the equation that biz apps D 365 have created for us.
Peter Dorrington, ELN: Great. Thanks very much Chad. Brian, does that reflect your experiences as well?
Bryan Hunt, Microsoft: Yeah, absolutely. And we'll talk probably a little bit more about this, but most of the business applications solutions are built on top of what we call a power platform or a low-code, no-code solution. Previously we used to really relate to D 365 as a rapid application development platform and it's because of what Chad shared, it's mostly configurations, it's not programming. So the ability to take the different modules based on the solution set and apply those against really any solution challenge allows us to be almost 80% there from the start.
Peter Dorrington, ELN: Thank you. There's a couple of things again I'd like to just touch back on because I think they're important. I don't want to brush past them too quickly. So Chad, one of the things you were describing there sounds to me like an ecosystem environment, and I'm thinking of generation now. I don't want to label people of a particular age but generation app are used to things just seamlessly working that you can switch between this platform, that platform, and it all works together. It just works. You don't have to worry about, as you said, I've got multiple devices, different inputs, different processes I need to get my head around. And I think that's one of the things we've seen with labor entering into this field. They expect that they expect that level of seamless integration. And then Brian, your point about low-code, no-code is I suspect that that is part of a solution where almost every organization I talk to, and it's hundreds in every year have said that one of their key themes for 2024 is more agility.
That they need to be able to adapt quickly that even if it's something like a merger or they're looking at acquisition or they're taking on a new business nine or a new product set. So anything that stops 'em from doing that in a world which is moving at the velocity that it is, is really hampering them. And that's I think what a lot of senior executives are more concerned about than that. There's pent up demand, there's clearly demand in the marketplace. What they're worried about is can I service that demand quickly and efficiently? Do I have everything I need to Chad's point earlier, have I got everything in the right place at the right time so that I can do that? Because if not, I'm leaving money on the table. So a couple of points that I think you raised that really resonated with me as I said that point about this seamless integrated ecosystem where it just works. We don't have to worry too much about retraining people or acquiring new skills. We'll come back to that in a moment perhaps. But also that we have this low-code, no-code environment where we can do more self-service and not wait for several weeks for the IT department to come around and write a new interface for us. So Chad, lemme come back to you then with something else as we were talking about, and it's actually that technology front. But before we do, let me give you the results from the poll because I think actually this resonates with what you said. So we asked, what is the biggest challenge you face in your current warehouse operations? And the answers were these inventory management, 10% space utilization, 20% as indeed is labor efficiency, 20% technology integration far outstripped them with 45% of our respondents said that was their biggest challenge, technology integration and 5% answered something else. So lemme come to you Chad then. I mean is that what you expected to see? You just actually talked about the challenge of integrating technology. Nearly half of the people who responded said that's their biggest challenge in warehouse operations today,
Chad Jones, KPMG LLP: Peter. Exactly. So you'll find that our smart warehouse solutions working with Brian and his team is that our challenge to ourselves is that soon as gear arrives at the dock and gets in the door, we want to digitize that immediately. We want to be able to scan, get that into a format that we can pass electrons around and people can see status, understand where the gear, equipment and supplies is moving through this process. Technology is an enabler in that part of that process. And Brian hit on a keyword. Configure is where we want to drive to. Every time we want to change something, modify, tweak, we can't go back to source code and make those changes. It just takes too long. So I absolutely agree with technology integration. The one other thing, Peter, I'll add to this space utilization at 20% cube space utilization density of pack in a warehouse is so critical. We leave so much wasted space as we think cube space utilization as we go up in the process, we've measured consistently over time about 46% of a warehouse is occupied in storage. They're storing basically air, not utilizing effectively those storage positions. So our goal is to get that to the higher end of that spectrum. So good to see the 20% there. And the natural outcome of all of this, I think is the labor efficiency.
If someone has to call out, highlight right down fingers on a keyboard and do this over and over again, and what we've measured is about 37% human error rate in this process, it just creates labor inefficiency. So switching that around to efficiency is key. But yeah, this aligns. Thank you.
Peter Dorrington, ELN: Thank you. Brian, what about you? Any surprises for you there in that result?
Bryan Hunt, Microsoft: No, no. And I would say it's typical challenges. I would say in this space, a lot of entities use SAP, Oracle for ERP systems, hr, et cetera. So those integration points can be challenging at times. And one of the things, I think Chad can probably comment on this in addition, but we've made several acquisitions, one of those being technology we bought a couple of years ago that focus very specifically on those types of integrations to SAP and Oracle and those ERP environments. And it makes that connection point, that integration really seamless. It's really just establishing a connector and then you're off to the races.
Peter Dorrington, ELN: Yeah, thank you. And I think again, one of the things just talking about that, Chad, that you raised the labor issue. Now I certainly can say that with some of the organizations I've been dealing with recently, that is actually a real concern. We just don't have enough people, we can't bring them into the business particularly in what is often perceived as a low skill role. And we have to find way to get more with fewer people without actually burning them out. We just can't have people running around a warehouse trying to find things hunting and pecking as they look to fill a pallet. So anything we can do that makes their life easier, makes their life more productive without actually just cramming on the workload, I think is important. I also suspect, and we may come back to this in a little while, that this is one of the necessary steps towards more automation in the warehouse that you actually do need to get control of what you've got.
And if you're not ready for that right now, I suspect it's part of the route there. Now let's come back to technology for just a moment. So Chad, you mentioned the role of technology here. So what I'd like to do is just ask you about how the utilizing the underpinning technology of power platform helps integrate with other business systems and automate these processes. And if you could give some examples, because I suspect for many of the people right now rip out and replace isn't really an option. We've got stuff that we have got to accommodate and we want to take a pleased approach. So how is your experience showing that we can achieve that with some of the underpinning technology of power platform?
Chad Jones, KPMG LLP: Sure, and thanks Peter. That's a great point. One of the things that we do as we look at, and most all of us do the same thing, you do it in your garage, we all do it as we approach our different problems or requirements, is the idea behind of how do we set up a process that flows through these six stages, if it's a warehouse or if it's a depot operations, how do we remove parts, we repair, we reassemble, we test, we check out. So that part of the process along the way, there's all this different equipment that's required to go do this. We've created a couple of things. One, we call the connected worker. So every material handler, every supply tech, every artisan, every mechanic in this process has access to three different things. We want headsets where they can voice talk to each other and communicate by commands.
And in some cases they're receiving commands from D 365 or the power platform itself instructing on next set of pick operations or put away or cycle count operations. Secondly, the same command can come across in a tablet maybe people aren't comfortable with that process, so they use tablets and it's easy to see that same information. Thirdly as a scanner. So any one of these components, those material supply techs can utilize to do their task each day. If you've ever worked in an operations environment and which I know many people on this call probably have a webinar have nothing worse than standing 45 minutes at a tool room at the beginning of the morning getting your equipment, tools and gear. It's just wasted time. It's inefficiency in the process. So where we use D 365 to help with this is it connects, as I mentioned earlier, integrates all of this together.
We have a system, a messaging broker that we use in the center of this that receives messages from all these different peripherals, all the PLCs from all the components in one warehouse. We have 10 autonomous robots moving around in choreography. So we receive signals from all of those and where they're at in this process and they're also getting tasked. So we create that messaging broker that commands that whole process. This is all powered by these 365. There is no way to, I shouldn't say there's no way it would be a very efficient or ineffective method to go do this individually teeing each one of these 40 plus different peripherals and components and aligning them to their task area. Something has to link or integrate them together. And that's how we do this. It starts from digitization of that first document coming in the door through issue shipping and delivery, going out to the users or even cross docking into another operation.
Peter Dorrington, ELN: Lovely, thank you very much. Before I respond to that, lemme go to you Brian. I'd love to get your experiences with this as well about the use of power platform.
Bryan Hunt, Microsoft: Yeah, I'm going to talk it just a little bit lower of the platform capabilities. The real value, this is what you hear from my team when we talk about all code, no-code and power platform. It's really speed to delivery. Great examples is like when we look at app rationalization at modernization, those projects are typically slated when they look at the portfolio of applications of anywhere from six weeks to six months to modernize each of those applications or deploy net new. We typically see that with low-code, no-code and being three days to several weeks. So the speed to delivery is the power. So in addition to that, and Chad mentioned this at the beginning, one of those powers in power platform is all the connectors that are applied by default when you buy or have the license effectively. And that's through D 365 or power platform.
We literally have hundreds of connections to on-premise to cloud systems, really anything that you would want to connect to optimize. So the integration portion that everybody mentioned in the survey, that's basically a part of the platform when you have a license. The other thing that I would say is that if there isn't some one off capability or a connector, we have custom connectors that are easy to establish. We also have the ability to do something that's recorded like an RPA capability. So if an API doesn't exist, we can literally go through the interface on the computer, record it and then use it as a playback mechanism to create an artificial API. So the speed to delivery, the ability to connect all systems is really where the power is.
Peter Dorrington, ELN: Thanks very much Brian. So again, reflecting what you said, Chad, I did like the idea knows where optimize that. I think it's
Bryan Hunt, Microsoft: Chad, I think we lost Peter for just a second. I think they're going to bring him back in.
Chad Jones, KPMG LLP: I think so I was just seeing that, I think Brian, what Peter was driving at was the connectivity that you talked about, the integration that you spoke of a few minutes ago. And just for everyone on the webinar, I can validate that on the user end of this with significance, we see those type of turnaround times, the three days to three weeks for round numbers consistently. As we modify, as we move things around, as we reconfigure add connectors to this process, it seems to work just effectively in that way and in its seamless to the users in this process. We do this, we test it and bring it back into the equation. And even the design parameters that we do with the teams work really effective in that way. Brian? Yeah, so well put,
Peter Dorrington, ELN: Right. I don't know what happened there. So technology came around and bit me. It looks like I've got an unstable internet connection. So sorry, I was just saying that this point about being able to use technology in RPAs, so important in this volatile world we face ourselves with now it wouldn't be a technology about a discussion about improving if we didn't talk about artificial intelligence. It is the topic of the moment and personally I'm convinced it's going to be one of the transformative technologies of the future. But Chad, let me ask you this. Artificial intelligence, including generative ai, and perhaps you can give a definition for us of that as you get into it is all over the news. Everybody's talking about it. Whenever I ask for a show of hands, it looks like everybody's experimenting to some degree, but could you describe how you might utilize artificial intelligence in order to benefit your client's smart warehouse solutions? So how does it play in your world when we're building this smart warehouse?
Chad Jones, KPMG LLP: Thank you Peter, and I'll tell you how we're using it now if you don't mind because I'm excited about what Brian and team have been enabled us to go do and what we've developed internally. So one, I mentioned 10 autonomous robots moving around a 80,000 square foot area across two bays of a warehouse. You understand the choreography and the synchronization that needs to take place. So we've used artificial intelligence or AI machine learning coupled with it to create the shortest path to algorithms for these pieces of equipment and also for them to communicate back and forth with each other. So not only does D 365 task them in the morning to go pick up for example, 10 pallet positions, it tasked them through the AI to go take the shortest route to go do that. So instead of going A, B, C, D, E, they may start with E, go back to B, go to C, jump to A, because it's the shortest path within a allotted time.
Secondly, when we received this requirement from the first warehouse and been a subsequent so far forward, I mentioned a stat of around 46% storage space, Cuba, storage space utilization. Our client gave us a goal of 90% in any one storage space we call density of pack. To do that you basically had to pay to some degree play Tetris with the gear and supply and storage. So we use AI to help us heat map three dimensionally, see where everything is at task, the equipment to place it in the spots where it may go so that it can fill to that 90% or greater space utilization. We use not only standard security cameras,
Peter in the warehouse to do typical security, but what we do is we look at what D 365 is, tasking this equipment or people to move and are the cameras seeing this movement take place in synchronization of that task area?
And if not, we do the analytics behind the scenes to understand why or why not or we seeing this take place. So for example, if D three five task a pickup to move from one place to the next, we should see some piece of equipment moving that are we seeing that take place? Why didn't we see it take place? Or did it create a congestion in a certain area with people or technology? And then finally we're using or we're starting to use facial recognition as a way to do labor accounting. So instead of asking everyone to clock in, report their labor clock out, clock off labor each day starting to recognize when people walk into a cell and see Peter, Brian or Chad recognize those personnel, start recording time from there. Now we're only doing this in a test environment or POC type of environment now. But utilizing all of those functions to help advance beyond how many times people have to touch a keyboard, have to go log in, make transactions, letting the system or equipment help do that through ai, ML and other forms is our next step into this process of smart warehousing.
Peter Dorrington, ELN: Thanks very much Chad and Brian, let me come to you. ai, it is the watch word of the moment out there and I know that Microsoft are doing some interesting things with things like copilot, but perhaps you could tell us about some of your experiences with using it.
Bryan Hunt, Microsoft: Yeah, and I would say pushing out to the end users. One of the things that we find traditionally with any deployed solution is there's always elements that the end user would like or want, but because of the challenge of basically interfacing or making those requests back in for changes or modifications through it, it can create delays. It can go slow. So the nice thing about copilot is the ability to use natural language, whether it's looking at something that may be a business process that you want to create as a part of the elements where you can use natural language to create that business process as opposed to programming it natural language query and reporting through Power bi using things like in supply chain where if you are trying to effectively order and your supplier may or may not have the available inventory, seeing a suggested list of additional suppliers and then even going further using AI or copilot to do what's called business process mining. So as we build and deploy applications, as smart warehousing is deployed, there may be things within the system that it can actually identify on its own as business process improvements and make those recommendations to the end users.
Peter Dorrington, ELN: Thanks very much about that, Brian. Now AI is something I guess like everybody I've been exploring and I've got a background in data science, so I'm a little closer to it perhaps than some others. One of the things that I found was interesting, Chad, what you said was that most people are aware that AI is very good at understanding what normal looks like and therefore it can identify exceptions or anomalies. But you mentioned how it can find new solutions where perhaps we as humans might bring our bias into it. I've always done it this way. I walk the floor this way round because that's the way I've always done it. It's not necessarily the most efficient. And I think this is for me something that's really exciting in that not only does it recognize what the world looks like, but it can help us optimize that better future. So I wonder if that's something as you look to the future, you see as having an even greater role as we get there. And I think that a lot of organizations are hoping that through the use of ai, they can augment their stuff. I don't think it's about replacing people. I think it's about giving people the right tools so that they can do a better job. I mentioned earlier, ready, willing and able to contribute to success,
Chad Jones, KPMG LLP: Peter. Exactly. And thank you for foot stomping that last statement. Nowhere in this that was hopefully my message came through that we're trying to minimize or get rid of people. We're actually looking to change position descriptions with our clients to add those digital features that you just talked about to entice a different type of warehouse person material handlers and supply tech, this process that are more digitally enabled. But also back to your point around using predictive capabilities of this process, we use multiple different functions to gather pings of where gear is going. We use passive R-F-I-D-I-O-T in some cases active RFID, and we're collecting thousands of pings of gear a day. So being able to take that much data and start to understand what we might be missing in just a normal view of how a warehouse operates. So that's one of the key points we're doing right now.
Chad Jones, KPMG LLP: We're looking at traffic patterns where human and equipment come together and integrate together where things during time of day takes place correlation with type of gear and supply type of year, time of year, excuse me, that has taken place in or you're in a training or a deployed capability. So starting to understanding how all these correlations take place to help us make better decisions about preparation. Again, it's all about readiness in some cases, I don't want to overemphasize this, but in some cases minutes matter, being able to get the right gear and supply down range to our clients. So if the data's there available for us to do that, we're trying to take advantage of it in every way possible.
Peter Dorrington, ELN: And I think again, just one of the points you mentioned about being able to streamline and reduce the time to act, let's be honest, our clients and customers don't care what it takes for us to deliver against their expectations. They just care that they get their stuff as quickly as they possibly can. So anything we can do to help meet that expectation with limited resources and say we're in a world at the moment, it's a great success story for the economy that there's a lot of demand for jobs out there that still unfilled, but it means that we have a rather big headache when it deals there. Now I just want to remind people, please do drop questions into the comments. We'll deal with them as many as we can right now. And we've had the first one, which is actually about artificial intelligence. So the question is this, Chad, let me come to you first. Do you integrate AI into WMS or the middle layer and what is recommended architecture for this? So where does it fit? Is it something right at the end point or is it somewhere in the middle and say the middleware?
Chad Jones, KPMG LLP: Yeah, so absolutely we do integrate and the great question, we do integrate all of these AI engines or optimizations engines using AI into our warehouse management system or D 365. It's the command that takes place through D 365. We have a messaging broker that does all the commands to send out to the equipment to tell where to go, what to do, where to pick up. In between those two is where we layer the AI component in this so that it will give the refinement based on the tasking of everything that's taken place through this process. We also feed back that data back into the WMS to make sure we have the latest one stop shop for all of this information. I will add also here, Peter, we deploy typically the Azure tech stack, which allows us to do a lot of compute power and bring into this a lot of the AI ML components into this process. So really helps us to drive to decision making very quickly within its overall effort.
Peter Dorrington, ELN: Thank you. And before I leave the subject of ai, Brian, let me come to you because I think it was you that was talking about the natural language interface with this, and I think I'd like to hear your point of view because as copilot rolls out and more people become familiar with it, I wonder whether we're getting away from the model which we had with home assistance where they actually teach us how we have to interrogate them. So if you've ever used something like an Alexa or Google Home, you know that you can't ask it long complicated questions, you have to be very direct. But I think that Microsoft are trying to get to something which feels much more natural that we don't need to be trained by the tool in how to use it. So I'd love to hear your opinion on that. Are we on that course? Are we actually making it more natural natural language processing?
Bryan Hunt, Microsoft: We are, and I'll use Power BI as an example. Most folks are at least accustomed if they've seen Power BI into natural language query. So a lot of times when we're trying to get to something from a reporting perspective, it's a series of interactions or steps that we're interacting with somebody who wrote the report or may know the report and we're saying, can you show me data that has these elements or this information? And sometimes that refinement takes time with natural language query. I can literally say, show me data that's related to this or near this or has some type of relation to this and Power BI will use natural language as a way to create that query on its own and then show me the results. Copilots will do much the same thing. So we can use natural language as a way to interrogate the data, the systems or to basically just run on our behalf to try to find elements that should be brought up or visible to us that maybe we're missing that may be important to our process or to our people.
Peter Dorrington, ELN: And I think this is a point I think relates to both of you have talked about the volume of data that potentially we have that we could analyze could be rather confusing and overwhelming when I have to worry also about how do I structure the questions, find the answer gets in the way and we can't fully exploit that. So for me, one of the great hopes is that this will help me find those actionable insights easier when we are dealing with vast tracks of data, which is moving at speed through our organization because the modern smart warehouse is often about speed. It actually is, I think it was Chad, you talked about eliminating those extra minutes we don't need. Now I'm going to ask a rather obvious question, but I'd love to hear your thoughts about how to, the question is this, when it comes to starting your transformation journey on how to modernize a warehouse, how important is it to have a clear roadmap or strategy right at the beginning or can we use some of this low-code, no-code approach to say, well, we may not know answers to all the questions when we start out that I'd like to get your view first.
Peter Dorrington, ELN: Do we need to have everything mapped out before we can start or is there an element of emergent strategy coming out of this?
Chad Jones, KPMG LLP: Great point, Peter. I think there's a couple of answers to this or linked answers to this. One is definitely important for us to understand the mission and vision of our clients and where they would like to be. I'd like to think that we have a KPI driven approach to how we modernize warehouses, meaning if they're really focused on a certain metric or KPI and it's around storage and inventory, we focus there and then we try to expand the input and output around those processes. But I do believe there's a pattern being developed that there's probably somewhere between a 35, 40 and 60% foundational element that applies to almost all warehousing operations, even crossing into commercial applications. I mean it's what you said a few minutes ago, Peter, it's how quick can we get gear supply, whatever someone ordered to their front door to them at that point in time. So speed, throughput velocity is critical. So if we start with those foundational elements and there's some key enablers that make that work, I think we can apply that across any spectrum. And then stitching that in to the client's environment, making sure that we have the ties, the integration point, understand their mission objectives, their systems that they're operating now is critical. So kind of a two part answer, but I do believe there is a launching point that's not at zero, but it's not at a hundred percent.
Peter Dorrington, ELN: Thank you. Brian, let me come to you and I'm going to add a little bit to that question because it actually comes down to I think, which is a corporate or organizational strategy I'm hearing from executive teams all over, which is about doing more with less time money people, less errors, less. So I'd love to hear how you think, is this something that has to have a fully baked plan before we start? Or to what degree have you seen that we have this flexibility to reflect what's going on in the world in near real time?
Bryan Hunt, Microsoft: And I would just say I would second what Chad shared, I would maybe say just as points of clarity is that if you're looking at modernizing a warehouse or a warehouse solution, taking the time looking at evaluating and creating an architecture that you won't put yourself into a corner with is absolutely the right thing to do. However, there are folks that are probably looking at, as Chad mentioned, they're not starting at zero. There's something there. There's something to work with. So there are elements that if it's not a full modernization, that we can actually use power platform and Dynamics 365 as a way to modernize those individual elements and then tie it back into a larger architecture. So I would say both are possible. It just depends on where you're starting at and then where you're trying to get to.
Peter Dorrington, ELN: Yeah, and I can sense that there's a good argument for dealing with a partner who can help you ask the right questions. Right now, one of the things I think we've just talked about there is we're not starting from zero in many cases. So it's not a greenfield site. So how do we deal with that? Clearly what we can't do is just, well, we're going to rip everything out and replace it in one big bang program. So what kind of capabilities do you see? Let me come to you, Brian, actually just change. Let's start with you. Some of the capabilities that you've seen that are in there, which are doing things like helping to generate cost savings so you can fund the next phase. Where are some of the priority start points
Bryan Hunt, Microsoft: And just gently touching and check and cover this in much greater detail as far as the individual cost saving elements. But I would just take in our space, the depots, the warehouses, there are sometimes challenges and Interac interacting with other DOD entities, whether it's ordering, acquisition, et cetera. So any place that we can make the process or the people be more accurate and be faster in that request approval and effectively procurement. And I think about ordering paint for a tanker or some element like that. If it's not an inventory that's a delay in that operation that costs money and it also burns time with the artisans that are working on those projects. So everything that we can do to optimize accuracy and speed provides call savings and efficiencies back to our customers.
Peter Dorrington, ELN: So Chad, let's come to you for some more examples.
Chad Jones, KPMG LLP: Yeah, Peter, let me dig discreetly and work my way up here a second. Some of the things that we don't consider, or maybe we think of second, third tier is old warehouses, power utilities, infrastructure and so on. When you think of a digital footprint, in some cases automation, you're adding power, you're adding different load on those systems. So assessing what's there first and being able to apply accordingly, not that that should be an inhibitor, but it's something you definitely have to address as part of this overall effort. Some of these warehouses that we're working in are vintage early 1950s, so that's a big part of the process. I think secondly is how do we build out from the integration point of this process is looking how we tie everything together through this overall effort. Thirdly, through this process is making sure that we understand the end in mind. It's one thing to automate and really do just a solid job within the four walls, but the old adage of digging a hole in water, it becomes into play because if you're cross docking or your next upstream activity is really inefficient, ineffective, you got to find ways to overcome that or integrate to overcome that part of the process. So having that, as you mentioned, that full roadmap or strategic view of making sure your end customer is in mind and how do you take care of that process is critical.
Peter Dorrington, ELN: And Chad, that relates to something else that I've talked a little bit recently with a couple of boards where they're looking at as organizations, many organizations are, they're vertically managed, so they tend to have teams, business units, warehousing, production and so on, but they're paying more attention to the horizontal process where you add value from goods in to stop being delivered to customers at the output end. And they're keen that all of that be as to use your word choreographed that actually we do have that insight about where everything is and we get some real, I guess it used to be called activity-based costing. We know where our costs are, we know where our bottlenecks are, we have that visibility. So let's think about another question right at the moment, we've mentioned automation a couple of times and robotics. I've got a robot warehouse just up the road from where I live right now.
How do we balance that? And as I said, artificial intelligence tends to be very good at recognizing a repeatable process, but how do we balance it with this need to have a flexible and adaptable supply chain? Because this is one of the things that really I think appeals to another board agenda item, which is resilience, that we need continuity of supply. We need not only just a plan A and plan B, but a cd, E and F so that we can look at different scenarios. So Chad, I'd love to hear your view. How do we balance automation, which tends to be focused on a repeatable process with that need for agility and resilience?
Chad Jones, KPMG LLP: Wow, it's a great question, Peter. The DC cd, E and F, get my letter straight there is in the form of how do we deploy these capabilities out beyond a concrete environment, a warehouse environment, a constructed environment, how do we get into, as we use the term downrange into contested areas closer to where the action is taken place less in the rear of the process. So that's our challenge. Now we're starting to prove collectively all of us are starting to prove the value of smart warehousing in the typical warehouse operations, but how do we take elements of this and move this forward? How do we make it deployable? How do we pick it up and move it? We take the communication mechanisms that Brian and team of Microsoft have enabled us and how do we make those more deployable in this operation? So exactly, you nailed it.
And not everything that we do is going to be in that operation, operation struck or mindset or ops around deployable, but it's the idea behind how do we create components of this to move forward. So if we take pieces of it and deploy with a unit to make their communication and digitization of gear and supply better, that communicates back through traditional means, secure means back to the overall operation. Now we've started to deploy or at least extend the capability set that we have. It's not perfect at the moment, but we're working through ways to get through that process.
Peter Dorrington, ELN: Thanks Chad. Brian at one point in my career did work on out load and resupply logistics analysis and one of the things that was very clear is that no plan survives contact with reality. So I'd love to hear your thoughts about how you deal with that. There's the plan, there's what we think is going to be are easily automatable tasks and then there's reality which is much more unpredictable perhaps.
Bryan Hunt, Microsoft: Yeah, and I'm going to take a step back, Peter, just to answer this a little bit differently. One of the things that we see, especially in our space with customers is, I won't say a high rate of turnover, but there is a high rate of turnover compared to most other industries and people are coming in and out of service. So there's an element that we can take portions of this, put it into business process where that training, those things that are constantly having to be retaught aren't necessarily having to be retaught. The other portion is that is over time the system becomes smarter collectively than the organism itself. Because as we hit those issues, as we hit those challenges, whether it's in integration with components or business processes, we refine those and make those better over time. So collectively, instead of trying to train and pass that training from one group of folks to the next, it's in the system itself and it gets better over time.
Peter Dorrington, ELN: Great answer. Now there's something to talk about. So when I was thinking, I was recently just speaking at a future of work conference and one of the things we were talking about, what are the skills we are going to need for the future when older people like me used to hand down our hard one knowledge to younger people? And now that's actually working in reverse in many cases. But one of the things that you touched upon, which I thought was very interesting, was this development of the institutional knowledge. How do we learn as an institution or as an organization so that people can focus on the things that they do best, like deal with those creative solutions to new challenges and critical thinking about is this the best way to do that? So I'm going to ask you both to do a little bit of crystal ball gazing now.
Peter Dorrington, ELN: So gazing into the future. Now we're often talking about here with warehousing stuff that doesn't go up in six months, typically it takes a little bit longer. So I'd love to know what your thoughts are about the future of smart warehousing over say the next few years and what indications are there or implications I should say that this will have for companies. So I think Chad, you said in terms of physical space, some of it's quite old, and yet we have to deal with a world which is moving at pace where standing still I guess is not an option. So what should we be thinking about for what do we need for the smart warehouse of the future? What should be on our watch list as we go forward?
Chad Jones, KPMG LLP: Thanks, Peter. I'll key on a couple of things. One, a couple of topics. One is the concept of dark operations. Can we take storage and inventory operations combined with autonomous equipment, RFID or IOT type technology and create a solution set to where we can turn the lights out and it can operate basically on its own. And what I mean by that is can we move gear, put it into storage, have automated means to inventory instead of annually doing the wall-to-wall inventory, can we do it nightly and can we do it by equipment that can scan gear, return this information the next morning and the systems compare. We start talking about biz apps, RPA and so forth, and bots being able to do comparative analysis between what was scanned and what's in the system of record and determine if I have a hundred percent match or a mile off by one or 2% or two items.
So I think the concept in this operation as we look the next five years is how do we start turning the lights off in certain areas and having this to perform on its own. And we utilize the material handlers and supply techs for their cognitive type capabilities. Let me analyze the results, let me look at the information. Let me sit at a control system and kind of manage this operation and manage the exceptions. So I think that's one big key that we're looking at through this process. And it's little things also, Peter, that we're, I say little things. We're looking at how we automate certain functions that we take for granted in one location. We have taken 82% of material handling equipment or forklift moves out of the operation through autonomous equipment conveyors. I mean conveyors have been around 60, 70 years or longer. I'm not sure how long they've been around. But by utilizing them and equipping them with RFID IOT sensors and using them to dispatch across the environment, can we then create more of an automated component within this process? So I think that's where we start to think through over the next three to five years.
Peter Dorrington, ELN: Thank you very much. Brian, how about you? If you gaze into your crystal ball, what do you see as being top of the agenda for the next few years?
Bryan Hunt, Microsoft: Yeah, what I see is kind of like a new kind of exciting future for us, Peter in this space is typically when we look at solutions deployed being built, been around for a while, the opportunity for enhancements or optimizations generally comes when we've painted ourselves into a corner because of scalability, lack of capabilities, lack of integration, or just something changing where it breaks the existing deployed solution. So the ability to have continuous optimization suggestions coming from copilot, coming from the AI that's suggesting either ways to do the process itself better or even optimizations within the code or the configuration. So instead of waiting for something to be broke, waiting for something to be a challenge, that continuous optimization because the AI and the co-pilots are making those suggestions to us because they see it as a challenge or some way to improve the process or the application itself.
Peter Dorrington, ELN: Thanks very much. I really do believe that there is enormous power being able to get actionable insights out of the data. It reminds me a little bit of the difference between being an accountant and a chief financial officer. So an accountant gives an accounting of what happened, what's where we might say we can do the inventory, but the chief financial officer is advising the organization about how to utilize and get best results for what we have, not just for today but into the future. And certainly when we get back into data-based decision making, I think this is something we can all get. I mean, the pace of change in delivery is amazing. As we've seen with some of the home delivery folks at the moment. The speed with which you can place an order and it arrive on your doorstep is phenomenal. And more and more businesses are trying to meet that expectation.
And it's not just consumer expectation. As businesses try to grapple with the challenge of just in time versus just in case, and they're looking at what can we do to perhaps reduce carbon footprint? So we talk to the ESG agenda, we're not going to do that today, but that's a big one. And CFOs are saying, well, we need to keep our capital busy and we don't want it locked up in stock. We want to be able to have things going through our warehouse really quickly. I think these are all things that add to it. The ai I think will help us get a better understanding of what's actually going on and what's possible. But I do believe it will still require the human touch, at least for the foreseeable future, perhaps make sense of some of the anomalies or the opportunities to make those decisions for prioritization. So before we sign off, let me just come to each of you. I'd love to get some final words from you. So Chad, let's come to you first. So as you look forward to just this year for the next 12 months, what are you excited about in terms of this is a very fast moving space. There's a lot that could be done, but what's getting you excited right now in terms of that short-term view?
Chad Jones, KPMG LLP: Thank you. What's exciting for me is not only the work we're doing within the four walls of a warehouse or repair operations or flight line type repair, but it's starting to connect the environment or the term you used earlier, Peter. The ecosystem is now how do I start to pull these together and integrate these together? So we look horizontally across that entire value stream and even backing this up to the OEMs and getting their engagement in the process and making sure they are a part of the solution. We drive this all the way to our clients, the customers, the end users, and then now bringing in finally the reverse logistics back into this process where I got to go calibrate, repair, restock, any of those other components, I've got a disposition. So it ties that closed loop process into this overall equation. To me, that's what's going to be exciting over the next 12 months as we start to integrate and move this to all those touch points.
Peter Dorrington, ELN: Thank you. Brian. I'm going to ask you to answer the same question about what excites you and we've had another question just come in. I'll come back to that in a moment. But before we do, Brian, what's exciting you about the next 12 months? What's on
Bryan Hunt, Microsoft: The piece of change? And that could be scary for some folks, but one of the things, and I'll give an example that I've heard a couple of times. So one of the things that technology's looking at is ways to talked about low emissions. So doing computers, compute inside of fluids that actually keep things cold right now today, those fluids that have to be used are forever chemicals. Things that we don't want to use kind of mathematically modeling to figure out how to actually make that in a safe way could take humans 500 years. But looking at AI and the speed at which it can evaluate and make those kind of recommended changes or adaptations and what we're using to get to the end state they're seeing we're going to be able to compress 500 years down into a five or a 10 year space. So for me, Peter, what I'm looking forward to is really that rate, that pace of change of where we're trying to get to something big and exciting much faster. And I would say for everybody is what they really are looking forward to is the ability to go fast.
Peter Dorrington, ELN: Thank you. And so I'm going to ask this question because it ties in with that point very neatly. So the question was, what type of change management initiatives have you introduced into the overall transformation plan to mitigate worker level concerns about being replaced by automation? And how do you integrate the voice of the employee in real time as you introduce or pilot these process changes? So Chad, let me come to you with that one. This is a screaming headline, right? AI is going to take 50% of all jobs within the next five years. People hear automation, think job losses. How do you bring about that change management?
Chad Jones, KPMG LLP: So we do it in multiple ways, Peter. So first and foremost, when we start a process, we hold a series of sessions where we gather requirements and feedback about the process from the people doing this work, the material handlers, the supply tech, their supervision, the logisticians, everyone involved, the artisans, mechanics, everybody involved in a process. And sometimes these are 10 sessions up to 30 sessions, hour and change. And we listen and hear and record everything they've done or are doing, excuse me. We create a system design document that maps all of this together and moving that into a solution set. And then when we start testing what the requirements are to what the solution is going to be, we start immediately with those personnel involved in the process. We let them help design the screen layout. And as Brian mentioned a few minutes ago, the configuration capabilities in D 365 allow us to make these type of changes real time.
We may hold a session in the morning, the next morning we can have, I want this button here, here, or I'm left-handed versus right-handed. So I'd like it in this equation. All of those components in the process, we hold conference room pilots where we test these from the very incremental solution all the way up to the final solution. It's key, and I'm embarrassed I didn't answer this question earlier or bring this forward around change management. Keeping the team members involved through this process from the very initial start is critical to make sure adoption is, adoption takes place at the end of this process.
Peter Dorrington, ELN: Instead of them being part of the problem, make them part of the solution and engage them. Absolutely. And I'll just share with you one insight, and I was talking about somebody recently that headline, 50% of all jobs that will be replaced by AI on AI in five years. I think, yes, we'll lose a few, but I actually think what will happen is those jobs will go to people who know how to use ai. So I think that that's an opportunity to develop people. After all, there are lots of things we were doing 20 years ago we wouldn't dream of doing. Now we've run out of time. So let me very quickly then firstly just say what's going to happen next. So we are going to reach out to you and give you an opportunity if you're watching the webinar today, to keep the conversation going.
Peter Dorrington, ELN: One-to-one. So look out for that email. KPMG has said, have graciously allowed us to say they want to engage with you. They want to hear what your challenges are. And with that, all that really remains for me to do is firstly thank our two experts today, Chad and Brian, and thank you for stepping up when I had a connection issue. So thank you very much, gentlemen. Thank you also to KPMG for their sponsorship because without them this webinar would not have taken place. And to the team of the executive leaders network who worked tirelessly in the background doing things like logistics. Most of all, thank you to all of you for your attention. I hope like me, you've learned some new things but are intrigued to find out more. And until the next time, take care now and goodbye. Cheerio. Bye-Bye.
