Episode Transcript
[00:00:00] Speaker A: Foreign.
[00:00:08] Speaker B: Welcome to the AI Driven Performance Improvement Podcast. I'm Anil Kumar, your host.
I lead the private equity AI practice at Alrest and Marcel and oversee A and M assist our AI Driven performance improvement platform.
Today we will explore how AI has the potential to address key challenges in facilities management.
Now when we think about facilities management we think about the operational complexity that comes with managing a dispersed workforce, handling long term contracts with large corporations, public sector organizations. We think about maintenance services related to H Vacs, electrical and plumbing system and then we also think about the software services, right that relate to day to day operations, cleaning, landscaping and so forth. And all of these facilities management businesses, a lot of them they just same challenges.
The challenges in bidding and coding meetings and contract and not spending more cost than the contract terms and there's almost always a constant struggle for better visibility into margins.
So in terms of AI, we are still in the very early days. I think AI tools are evolving. The vendor landscape is maturing and the technology is rising spectacularly fast. And we do think that in six months to a year it's going to start making a real impact.
Then we think when we think about the AI impact and we'll talk a lot about this is productive maintenance workforce scheduling productivity.
So really excited to have this discussion today. Joining me are two fellow managing directors from our private equity performance improvement practice and our corporate transformation services practice. We have Brian Long who with over 20 years of experience in strategic and operational consulting leadership positions with a global truck and engine manufacturer and an industrial focused PE firm. His focus for the last decade at A and M has been leveraging that background in the business services space.
Also joining me is cesare. With over 20 years of experience in senior strategy and operational roles in consulting and corporates. Cesare has significant experience in business services while at Brambles and has worked extensively with global and regional facilities management organizations.
Brian, it would be great to get a deeper insight into your background across business services, manufacturing and private equity. How do you see the operational complexities and facilities management play out in the companies that you work with?
[00:02:46] Speaker C: Yeah, thanks Anil. My work is primarily entirely focused on business services with a specialization with field services.
Many of the pain points across these subsectors of field services are similar in facilities management, which is one of the subsectors I would say, of my specialty. This includes complex pricing, disseminated workforce management, extensive contract management across those there's a lot of data available but it's often actually not effectively managed. And what I'm excited about here is that AI will help these companies effectively manage all the data in this very data intensive field.
[00:03:30] Speaker B: Thanks, Brian. Cesare, given your experience gained with facilities management operations, what excites you most about how this industry is evolving?
[00:03:39] Speaker A: I feel very privileged in working in facility management organization because they are the unsung heroes of big business. They are providing critical services that we often take for granted, but they are at the heart of any customer experience.
These services are often provided by dedicated personnel whose job is to make sure that everything works well as it should be. And customers are constantly increasing their expectation on facility management, aiming to provide an ever improving experience to their customer. Think about the pressure on real estate companies to provide superior office or retail experience to their tenants in order to entice office workers back to the office or to increase the footfall in brick and mortar shopping centers. And in all of this, technology plays a critical role in the experience of the customer receiving the service and the operators delivering it.
[00:04:35] Speaker B: That's great perspective. Let's break down the major challenges in facilities management services and and let's explore some of the AI's growing impact. So Brian, from your perspective, what are the most pressing challenges keeping facilities management executives up at night?
[00:04:50] Speaker C: Yeah, thanks Neil. I think there's five core that I see from the operational side. One is a bid quote management, estimating and pricing.
These are long term complex contracts requiring a lot of data intensive knowledge with enough knowledge to win the bid of course, but then also have the confidence that the contract is good. The contract is going to be profitable over like a five year period when a lot of the cost components may change.
So companies should leverage previous contracts of course, and that installed knowledge carry forward to understand how best to price the next deal. So you're not reinventing the wheel and also estimate the risk and the cost of ramping up because these are large contracts, a lot of workforce, light assets and such. If you ramp up that business when you get the contract, and inherently in something like that, there's going to be some surprises.
So minimizing those can maintain the profitability of the contract.
So that's one pricing bid quote management.
Second is customer satisfaction.
The key here is maintaining the balance of customer satisfaction on each of the subcomponent elements of the contract and the cost to serve to make sure that you maintain profitability as well. So companies should understand of course the SLA requirements, but do just that amount of work for the customer and then secondly innovate over time to continually drive down the cost to serve.
That's the second customer satisfaction. The third is margin visibility.
Companies should Understand the margins at the subcontract level. Very, very important in this sub sector of field services.
Those contract elements may change over time and so it could be up or down, but be very dynamic with the market and your cost structure to that contract and then apply that appropriately.
Then use that knowledge for the renewal to win the next bid and to adjust the areas of the subcontract that are unprofitable components.
The fourth is personnel productivity.
Managing a remote workforce is difficult. They're typically one on one on site without much oversight at the client.
So job scheduling is particularly important.
Supervisors need to know the non billable time of contractors, either subcontractors or their own technicians. Make sure that that non billable time is efficient.
And then the best companies follow a pretty strict standard operating procedure in a daily playbook of how to run their business.
So execution is key to this common business.
Fifth and last is a lean having a lean GNA. These companies are typically 3 to 5% EBITDA. So making a mistake on GNA is, can be very detrimental to the 3 to 5% because it's so tight.
So focus on those routine tasks that could be automated recruiting, training, onboarding, invoicing and payroll, things of that nature so that you're as streamlined and lean as possible. In general, profits are made. In facilities management, it's all about managing pricing, estimating contract management and high utilization of people. We've helped a lot of FM businesses get significant ebitda. Now what's interesting and why we're doing this podcast is that with AI can support even a higher EBITDA and improvement and the games can be much more sustainable.
[00:08:42] Speaker B: That's a really great point and I think the pain points that you laid out are pretty significant. Cesare, can you share some real world examples of where a company faced one or more of these sort of challenges and then maybe use automation technology, AI to help manage and address them?
[00:09:00] Speaker A: Sure, sure, I'm very happy to. I'll give you a couple of examples.
So first, we've worked with a large UK headquarter business achieving a significant uplift in their margins in line with their strategic goals. That's where they wanted to go. They wanted to increase their margins and we helped them in doing that by doing a few very important things that help them. So first of all, we started reviewing the profitability of the contract book to assess which one were accretive and which one were dilutive of the overall business performance.
This require the collection and processing of complex data sets, often scattered across different systems between financial and operational systems. Also, due to the fact that the business has grown through several acquisitions over time, the interpretation of the data required advanced solutions that can be highly innovative for this industry.
This has then enabled us to identify operational best practices in the higher performing situations and to propagate them to the lower performing ones, driving immediate impact and benefit on the overall performance as well as on customer and operator satisfaction.
Sizing, prioritizing and planning such intervention requires a complete balance of resources and activities to ensure you execute the activities and measure the impact correctly. Finally, we have reviewed the company target operating model in order to ensure that the central functions, as Brian was saying, would provide a lean and efficient support to the sales and to the operations team, enabling them to continuously manage and improve the operational performance.
Designing an effective operating model requires a deep understanding of the technology landscape and its potential evolution to ensure that your organization is fit for purpose today and tomorrow as well.
Similarly, very briefly with another global organization, following an initial assessment of their performance across contracts and support functions, we have worked extensively in improving their technology real estate as an opportunity to reduce cost on one side, but more importantly to prepare the organization to benefit from the huge amount of data that they have accumulated over the years, which has become a competitive advantage in service delivery and in winning future bids.
[00:11:25] Speaker B: So there's a lot of data out there, there's a lot of potential and opportunities to improve, but there's still a lot of bottlenecks, right? In terms of how to get started and how to think about it, how do you see companies currently approaching these challenges?
[00:11:40] Speaker A: Look, this is still a very contract based business, right? So losing or not winning a new contract can have a huge impact on your bottom line unless you have an appropriate operating model. The typical low margins in the industry leave very limited margin for errors and companies are carefully embracing new technologies to find a better way to deliver superior service at cost.
This is not a sector where you can test different solutions over a short period of time.
Facility management companies are carefully exploring new ideas across back office and front office to drive efficiency, customers and operator satisfaction. For example, some companies are testing new rostering technologies which enable them to provide flexibility to their operators while simplifying payroll processing and yet ensuring service excellence to their customer. This is just brilliant.
[00:12:36] Speaker B: I think AI is already starting to transform some parts of the facilities management and, and if it's early stages of AI, it's automation. A lot of these things are really low hanging fruits, right? Which is you have a lot of data and then there's a lot of manual effort. There's a lot of tribal knowledge and we can start addressing them in a very systematic, structured way. So we started to see some of these really very meaningful applications of AI.
And I think from that perspective, Brian, what's your perspective on how this is all evolving and what's your guidance on how companies should start approaching all of these new technologies in a way that drives real value?
[00:13:16] Speaker C: Yeah, there's a lot of change for sure in, in the market. I would say that companies should proceed with cautious optimism.
Think about your business and your processes and where there's variance in your process or improvement opportunities in EBITDA and start with that and then how can AI support that? So take your to be processes, figure out your to be processes versus your current.
Do that first such that when you apply the AI tools, it's applied to the future state of your business.
Don't apply software to old, outdated or inefficient processes across your business.
Then it's a much more simplified business that you're automating and you make sure that it's done in a very pragmatic and systematic way that when change occurs, it's dramatically changing your EBITDA profile.
[00:14:12] Speaker B: That makes a lot of sense and cesare right from A and M perspective, when they think about let's drive technology not really to make a real impact in business operations, let's not just implement technology because everyone else is what some examples in your mind where AIs can make an impact and starting to make impact in a very real pragmatic way.
[00:14:32] Speaker A: Yeah, yeah, sure. I can give you a couple couple of examples here. One is, for example, I think AI can help in managing suppliers and inventories. Gaining visibility on the future demand of consumables, for example, can enable businesses to engage more effectively with their suppliers. Giving visibility on future demand, optimizing deliveries and stock levels, reducing losses, damaging and so on.
Another interesting area, another interesting emerging area will be around the dilapidation risk. So facility management companies are sometimes facing hefty bills at the end of the contract related to the condition of the building at the end of the contract compared to the initial status when the contract started. Monitoring the condition of the building during the life cycle of a contract through predictive models can reduce the risk and provide insights for other ongoing contracts and future bids.
[00:15:28] Speaker B: I think for companies thinking about AI generally our approach has been crawl, walk, run, start small, focus on three use cases, not 15 use cases, focus on ROI and then scale from there.
It's about building momentum in a way that drives real impact over time.
When they think about crawl phase, this is where companies start with low risk automation AI for some pieces of work, order management, some pieces of maintenance, scheduling and technician dispatching. These are quick wins. You also want quick wins so the organization is much more open to change because change management is so hard with AI and new technologies.
But quick wins help you get these technologies adopted. Then we walk and this stage we go beyond simple automation and start AI to optimize more of the workforce, scheduling, customer support and then in the run phase, this is where AI becomes a true game changer and and helps you differentiate from your competition. Companies at this level are leveraging AI for predictive maintenance, energy management, space utilization and a lot of the decision making as well. So instead of reacting to problems, they are anticipating them. They're getting early warnings.
They have a lot more opportunities for early intervention and that's really where the real competitive advantage lies. Just in terms of the key takeaway, I think my advice to companies has been AI does not need to be overwhelming. Take a structured approach. Crawl, walk, run, and then there's really over the next one year we see a lot of this happening in very meaningful ways. Cesare, any final words of advice from you for companies getting started with AI?
[00:17:09] Speaker A: I think this approach fits very well with facility management sector.
So there is probably a step before crawling that you could call it feeding. For example, like every athlete needs to be fed before doing any exercise. And this feeling in this case for me refer to capture, clean and consolidate the data that you have scattered in your organization.
This will certainly enable you to start crawling very effectively.
In addition, I think the contract based nature of the industry can lend itself very effectively to a pilot based approach where new technologies can be adopted within a specific client or service or particular contract.
I would also emphasize that while AI offers tremendous promise, it's not a magic bullet. Success will come from a careful phased approach that prioritizes learning and incremental improvement. Companies should be cautious about over investing in unproven technologies and instead focus on integrating AI in ways that deliver clear measurable benefits.
[00:18:15] Speaker B: This has been a great discussion.
I think we just closing thoughts again. Thanks Brian and Cesare for sharing your insights.
Very very helpful to our listeners. The AI journey in facilities management is still unfolding, but companies that take a structured and data driven approach will definitely gain a competitive advantage. Stay tuned for future episodes where we continue to explore AI's impact across multiple industries. It.
