Tuesday, January 17, 2023
2:00 PM – 3:00 PM EST
This is an online event
Bob Stark, Kyriba
Craig Jeffery, Strategic Treasurer
As we leave 2022 behind us, we find 2023 starting with both high volatility and increased expectations for managing risks. What does this vulnerability mean to treasurers? What types of outcomes should we expect across the domains of credit, FX price volatility, elevated inflation, and increasing interest rates?
As treasurers examine the environment and how to address it, this dialogue will look at strategies for managing FX volatility, ways companies are thinking about data and artificial intelligence/machine learning, faster and real-time treasury (hype vs. the reality of everything moving faster), and the annual challenge of forecasting liquidity. Join Bob Stark, Kyriba, and Craig Jeffery, Strategic Treasurer, as they share their thoughts and draw out distinctions, useful frameworks for thinking, and practical approaches to help your organization succeed in 2023 and beyond.
If you encounter any issues with this webinar replay, please contact our team.
Okay, well welcome everyone to today’s webinar titled 2023 Outlook for Treasury: Strategies for Success. This is Brian from Strategic Treasurer. And we’re pleased you could join us as we consider how treasury can reduce vulnerability to market volatility and implement a playbook for more efficiency, optimized liquidity, and better forecasting. But before I introduce today’s speakers, I have just a few quick announcements. Zoom offers several different ways for us to interact today. If you would like to post comments or questions viewable by all attendees, please use the chat icon in the toolbar. If you’d like to ask your question to just the presenters, please use the q&a icon in the toolbar. You can ask your questions at any time during the presentation, and we’ll try to get to as many as we can. But if we don’t get to your question, someone from our team will gladly follow up with you. There will also be a few polling questions throughout today’s webinar, where you will be able to select your response from a list of multiple choices, you will need to click the submit button on the polling questions to have your response recorded. If you are here for CPE credits, you will need to answer at least three polls today. And last, please ensure that your zoom display name includes both your first and last name so we’ll know to whom we should send the credits. Our speakers for today are Bob Stark, Global Head of Market Strategy at Kyriba, and Craig Jeffery, Founder and Managing Partner of Strategic Treasurer. Welcome Bob and Craig. And I’ll now turn the presentation over to you.
Craig Jeffery 02:14
Thank you, Brian, and it’s good to see you again, Bob.
Bob Stark 02:18
You too, Craig. Happy New Year. Though maybe we can’t say Happy New Year anymore. Maybe it’s past that window.
Craig Jeffery 02:24
I think, I think you have to do it before the end of January and then your fine. Okay. Welcome, everyone. Thanks for joining us, either in your morning or in the afternoon. We’re glad you’re here. For those who are joining us via LinkedIn live, please realize that that may not be the best experience. This time. It’s only the second time we’ve done LinkedIn live. So we’re continuing to try out the different types of technology. So it’s on Zoom and LinkedIn live. So really glad you’re here, we have a lot to cover a lot of great topics. So what’s our agenda? It’s laid out on the screen before you. First we’ll talk about volatility, some of the contributing factors, things like interest rates, inflation, a couple of those items that show what’s going on. Next we’ll talk about what are some of the desired outcomes, and how to achieve those when we think about desired outcomes and treasury. Usually we’re looking at bringing our risks in line with our risk appetite, making sure we understand and can forecast our cash flows properly. And so on that we have a better understanding, then we’ll spend a little bit of time discussing what is data driven treasury. When we think about data, we think about lots of data speed, accuracy, and harnessing this large amount of data for better progress towards our goals as treasury professionals. So this is in the heart of every treasury department. And there’s a there’s a big tie in to technology, and how we think about things. And next we’ll look at forecasting and liquidity management, we’ll look at some of the distinctions between forecasting, cash flows, looking at different models, some of the different considerations that everyone pays attention to. And when we look at the importance of forecasting over time, we’ll also share how that has increased certainly over the last five years, it’s been highly elevated for forecasting, and it has certainly increased over the last five years to some new Levels. We’ll share a little bit about that. The last core area, we’ll talk about a stress testing, scenario analysis, some of these concepts around improving our forecasting accuracy and understanding it as a range as opposed to a certain point. How do we do that? How do we leverage our partners and our technologies to do so? And then finally, Bob, and I would go back and forth on four takeaways that summarize some of the application from from what we’re what we’re discussing. All right. So Bob, we can we can get started I’ll start us off on the interest rates. Now as we look at some of the curves that you see. The curves are what they are on the interest rate, you can see us on the left hand side and the UK on the right hand side, very interesting how they spiked up quite quite dramatically. You know, we’re all seeing that interest rates, usually controlled by the central banks, they’ve moved up to help tamp down inflation. And if you look on the lower charts, you can see some of the inflation numbers, which continue to get adjusted slightly, you can see what’s going on, you know, after, after we hit the very end of 2020, and then into, into 22. And to today, you can see some of the curve downward. So what are we seeing, we’re seeing, we’ve seen heavy inflation after a long period of pretty heavy stability there, Bob, and inflation rates jumping up. And this has an impact and in the world of treasury in the world of business, because if you’re borrowing, there’s costs associated with that inflation can impact our financial supply chain can impact the products and goods we sell or buy, and it has a ripple effect. So we look at volatility. Here’s just two of many examples, Bob.
Bob Stark 06:09
Yeah, you have to look bottom up, of course, inflation first, interest rates, second, inflation, we’ve seen bits of data that suggests that maybe there’s a bit more calm around inflation, although I don’t want to maybe I should knock on wood when I say something like that. Because obviously, we’re, we’re seeing a very different strategy in terms of pandemic coming out of China, which we all know started what became a supply chain tightening or challenges which led to inflation in many ways. The combination is that we have to look at our vulnerability to rising interest rates. And what does that mean for treasury? What do we need to do a little bit differently? And we’ll get into some strategies around cash forecasting and internal concentration of cash, but you really have to understand as those questions for for your CFOs. What is their vulnerability to rise in interest rates? What if rates go up a little bit? What if they go down a bit? What if they stay flat? What does that mean for our cash and liquidity planning? And that, to me, is the real question that needs to be answered very confidently with data so that treasury embraces that opportunity to go, Yes, we know what we’re going to do in these three or four different risk scenarios.
Craig Jeffery 07:21
Yeah, Bob, before we move on to foreign exchange, I’ll just mention, we’ve just seen some results from one of our large surveys about some of the negative views on the balance of power between borrowers and lenders. That shifted pretty dramatically. And so that should be out within a month or so. And it’s, it’s it moved quite negative. I think it’d be surprised by the level of negativity. But yeah, so with that with the inflation, then the interest rate adjustments meant to impact that pop. Now we see ongoing FX volatility.
Bob Stark 07:57
Yeah, and I like this slide for a couple of different reasons. Not, it shows a couple of different things. Obviously, if you flip it around, you can say, Oh, look, the US dollars rise, or in this case, the other ones are decreasing in comparison. It’s not the trajectory, though, that matters as much for treasury. And especially in the last two months, we’ve seen a bit of a retraction or movement in terms of strengthening of the Euro against the US strengthen the pound against the US, which is comforting for some that maybe we’re reporting on a constant currency basis, and we’re looking for just that little bit of relief to go into 2023. But what I like this graph is it really does a nice job without too much detail, but still showing off the volatility, the volatility and currency is what really matters. We obviously from a US, you know, for very international organizations, we definitely want maybe limited currency headwinds to slow down revenue, profitability, cash flow, protect our balance sheets, etc. But it’s that volatility that can really impact your cost of hedging. And that’s where a lot of treasures, they were running into issues halfway through 2022, saying they had these parameters that they had to stay within, and, you know, effectively a budget, if you will, and those guardrails, they blew through those guardrails in the first five, six months of the year because the volatility made the cost of hedging so much higher. And they were unable to protect the balance sheet unable to protect cash flows unable to protect the top end of the income statement. And those are the sorts of scenarios that are difficult to manage. And that’s where data, which is a theme that we’re going to use a lot here, Craig, that’s where data can provide insights in terms of being able to make quicker decisions to take advantage of opportunities in the market when you actually do go to hedge, but also be able to project that information to the CFOs that can provide a revised guidance to the market so that expectations are set appropriately. There’s a lot in here to be able to understand the impacts of volatility so that you’re prepared to communicate expectations.
Craig Jeffery 09:59
Yeah, some good point See some really good points there, Bob, you know, the good idea that right when you need it, because there’s volatility, you want that insurance on it, that’s when it becomes most expensive. It’s so much of life is that way, right? We measure things and expectations from calm, oh, I’ve got this much capacity on my card. If you actually start to spend it, all of a sudden your rate deteriorates. If you need a loan from the bank, you have to prove you don’t have to prove you don’t need it to get the money. You know, there’s a storm circling in the Atlantic, you can’t get flood insurance on your house in Florida. You know, it’s it’s these times of turbulence, where, you know, we have this mindset of things are really, really calm. They’re calm, calm, calm until they’re not. And that, that I think we have to just steal our minds to this, this idea of volatility when it’s volatile, that’s when everything gets harder. And, you know, Bob, that moves us to our first poll question. So everybody, if you’re looking looking alert and alive, this is these rounded squares mean, you can answer any or all of these options. So answer for your organization, it’s moderately to heavily concerned about the below which ones matter to your organization. And we’re gonna go with just 120 people typing the word poll in the in the webinar chat box, and we will send you the poll responses just 120. If I if I did a smaller number, that’s way too easy for Brian to count, and I don’t want to make things easy for him. That’s only fair. Right. Right Bob?
Bob Stark 11:39
Craig Jeffery 11:40
So what were you heavily concerned interest rates, inflation, deepening recession, FX, volatility, supply chain issues, or none of the above?
Bob Stark 11:53
I don’t want to leave the audience or anything, Craig, but I find it interesting that there’s, as we enter 2023, there’s definitely different points of view on what if there is a recession? And if there is a recession, then what does that look like? It seems to me, that’s the biggest point of uncertainty, just because we lacked data showing what is that really going to look like everything else? We have a lot of data to go, yes, there’s issues and all these areas. The recession seems to be the interesting discussion point, we’ll say.
Craig Jeffery 12:22
Yeah, very good. All right, Brian, you can let us know where we are. So you almost, you almost let’s be honest, just very few answered none of the above. So you’re essentially correct there, Bob. Now, you mentioned that inflation leads interest rates, because interest rates tend to be response to inflation above a certain point. They’re fairly close. But we’ve got a, we got a 10 point difference there. I guess inflation is what happens, interest rates may be a more direct impact on the business, even though it’s secondary. Any thoughts on the FX volatility, deepening recession, or other points?
Bob Stark 13:04
I mean, I’ll go back to the point I made earlier is that the, let me say it this way. The interest rates move not in sequence in different parts of the world. So that’s obviously why we see volatility and movement in currency markets. That the inability to foresee and then properly manage the impacts of that volatility causes as much problems as higher borrowing costs. And when we look at the impact on cash flow impact on balance sheet impact on the income statement. So I actually think it’s a, it’s an opportunity to provide more value to the organization to have a handle on what the impacts of FX volatility really are.
Craig Jeffery 13:48
Yeah, excellent. Yeah, deepening recession. You brought up a couple points there, whether it’s what is going to look like when we get into the recession? This is going to be regional global. Is it just gonna be pockets? How quickly do we bounce out of it? Those are all factors, which while you can take a position you don’t know. And so you have to prepare and steel your organization to handle whatever, whatever the situation is. So excellent. Thanks. Thanks, everyone, for responding to this poll question. We have more for your delight and pleasure. And, yeah, we’ll just continue.
Bob Stark 14:26
Sure. Well, I like this one, Craig, this is a fun slide. Because everyone, I mean, not everyone. 79% of everyone said that this was a big challenge in terms of how do I manage in a rising interest rate environment. Whether they rise further or not, is not as consequential because we need to create efficiencies right now. One thing that we talked about going into this webinar was one of the tools that the treasury team needs to really get better at or harness more in order to reduce that vulnerability of rising rates on treasury and on cash flow. And we always point to this cash forecast as being that very first item. And I think most people would agree, you just look at every AFP conference. And what do they all say? I need sessions on cash forecasting, they’re always the most popular ones. We’ve done stuff, Craig, cash forecasting has been very, very popular. So making sure that you have that visibility and accuracy. The key thing that’s probably changed around cash forecasting, which I’ll touch on a little bit in a later slide as well, is that it became more complex, because now we’re asked to forecast and project and understand our vulnerability in, say, different interest rate scenarios. And so we need to actually have different risk scenarios added to the forecast so that we have visibility and bank accounts, we can project our future bank balance, we can project our needs for liquidity across different scenarios that may or may not occur. And there’s a variety of tools that we can leverage internally, once we have that visibility. So once you have that forecast, then it’s a matter of looking at, Can I take advantage of more in house banking or intercompany loans? Can I take advantage of actually looking at more internal types of cash flow generation? Should I look at some of the different choices around how I’m earning a return on cash? Some organizations have actually made some changes to their investment policy. I was actually at a conference last week, that was on higher education specifically, so universities, and there was a couple of different organizations there that actually created a new sort of hybrid medium term policy that didn’t exist before. And the reason why is because they had a gap between you know, what they threw over the fence as long term sort of custodial type investments, and short term money market, they wanted to create an opportunity to earn a little bit more return on their cash and leverage some of the higher rates that were available in government and prime funds as an example. So there’s a lot of different pieces here from understanding, what can I do within working capital programs, all the way back to how can I ensure that I have what I think is perfection and accuracy across a number of different scenarios from a needs and uses of cash, Craig.
Craig Jeffery 17:09
Yeah, Bob, you know, one of the takeaways from what you said seemed to be that not only do you need to measure these different elements, but some of these are levers and the more you have, the more leverage you have, the easier it is to navigate or steer the ship through stormy waters. If we’re talking about volatility here, are some of these items, they’re so excellent, we will, you know, one of those one of those levers has to do with how well your structure is set up for managing cash, you know, cash management, cash management structures are foundational for all of treasury, how we design those, whether it’s a ZBA, or ZBA structure within the same bank in the same country, and the same currency or whether that’s the same currency across multiple jurisdictions, or whether it’s even multiple currencies, but how do we, how do we source those funds, that can be cash pools, it can be an in house bank, there’s a number of structures that exist. And you know, Bob and I’d have to do a couple more sessions to show all those structures and how they play out. But here is, here’s just one that you may be familiar with. So if you think about what’s your typical cheapest source of funds is, you know, it’s usually from a larger, higher rated organization or entity within your overall hierarchy of of entities in your company. And so the example as well, how do we source funds from there? Well, maybe we get a loan instead of trying to get loans from each individual organization, we get a loan from the head organization who maybe has the lowest cost of capital. And since that’s the case, here, we have a bilateral arrangement between the holding company and subsidiary one. So there’s that’s papered in a single place. And then the second one is, maybe the holding company is making arrangements and loans with different subsidiaries, maybe multiple subsidiaries. And there might be multiple bilateral arrangements either between the holding company and all the subsidiaries between the holding company and some subsidiaries who further paper the activity down below. The other method is also you have this internal internal in house bank, which takes care of receiving the best rates, they act as a market rate borrowing lending, they put the spread, so it’s competitive, yet they’re using all of the cash in the organization optimally across all jurisdictions across every area. And so, this is just another way of having levers that help the organization you know, optimize their use of cash and prepare for the difficult times while having that that overage capability by tapping into external debt credit facilities that they may have.
Bob Stark 20:03
Yeah, and doing so in a very efficient way, which is the part that I really like about the the in house bank, we see, I would say in the past couple of years, we’ve seen this emergence of, there’s obviously physical pools. And I think everyone on the call probably is very familiar with those. But this hybrid of physical and notional pooling, and part of that is just driven by regulation. If you’re doing business in China, or India, or even say, Turkey, as an example, you’re gonna find that there’s a necessity to have physical point of cash, you can’t get around that. But having that hybrid of notional and physical can really drive a greater level of efficiency, because when you’re doing notional pooling, you tend to have all the cash or at least almost all the cash that’s brought into the pool, whereas it’s physical, sometimes there’s these compensating balances are a little leave behind. And those are the things that ideally, we want to iron out and make the most efficient use of cash, especially as we see movements and interest rates when everything was flat, really, not to say it didn’t matter, but it mattered less in terms of that return on cash, as that opportunity cost of cash was increased and increased disproportionately in different parts of the world, there’s a lot of organizations are looking to create different efficiencies around, where should I put this cash and having that hybrid notional physical structure can allow you to do that, and actually take advantage of the best opportunities while still maintaining your liquidity. So if you combine forecasting and in House Banking, and you have that all in one platform, or at least the very set of connected processes, then you put yourself in a really nice position to reduce that vulnerability to rising rates.
Craig Jeffery 21:40
Yeah, and just like if you forecast at the macro level, and you don’t take advantage of some of these tools, like you don’t have physical pooling or cash concentration structure, and you look at it at all, you know, amalgamated number, you might be in great shape, but you’ve got these pockets that are massively negative, other ones that are positive. And now you got to do cross border transactions or, or other transactions to true these up and so it creates this whipsaw effect of operational activity to support what needs to go on.
Bob Stark 22:15
Yeah, excellent point, Craig. You don’t want to add cost and complexity, when you’re looking to actually create efficiency, it just goes against, like everything you’re trying to do to create a more efficient borrowing and cash movement structure.
Craig Jeffery 22:31
And did hear another poll is due? Yes, another poll is due. This is about banks and systems. So we have or don’t have the following. This is let’s get a measure of those that are on the webinar, how many have an in house bank you have it? Or you don’t? A netting system? Do you have it? Or you don’t doesn’t matter where it sits? Just you have it? And you use a single or multi currency pooling system? And I don’t just mean ZBA in a single bank, let’s say in the US, but maybe it’s single currency, euros or, or what have you, or it’s multicurrency, maybe multicurrency. It doesn’t matter whether it’s notional or physical. But how many have that type of pooling system or structure? Or don’t have it? So we’ve got three areas have and don’t have. And I see comments about consider cost and complexity. Yeah, some of that some of the solutions are too big, too small. And I don’t know where the poll question count is ending up, Brian. I think, after the first one, we had 38 remaining. So that means we had 82 responses. Some people are squaring or cubing, the poll responses, but that actually gets reduced back to a regular poll. So we’ll see how that comes out. All right. So we need 20 poll responses. Okay. Wow, these are these are quite, quite close, right? We have and don’t have. Those two together add up to 90. So some people didn’t answer. And that’s, you know, that happens. Maybe you didn’t know you didn’t answer. So it’s pretty even between those who use an in house bank and doubt. Did you have any comments on that?
Bob Stark 24:18
Well, I would say I’m a bit surprised, I actually would have expected a higher number when we get down to pooling. I mean, in house bank is obviously more formalized version of that. I would have expected a little bit more in the haves on those. What I’m unsurprised with though, is netting. That seems to be a reasonable proportion of what we see in the market is that netting it requires a little bit more interoperability with your ERP and having the data fully integrated. So you can actually run these in good frequent time frames. So that doesn’t surprise me correct, but I would have expected more on the pooling and certainly a little bit more on in house banking. We see more just within our own clients, so I guess I was using that as a proxy.
Craig Jeffery 25:03
Yeah, I think that I think that’s, that seems pretty reasonable for the midsize to larger organizations, you know, I’m in that inside, you have to have a certain amount of transactions between subsidiaries in different areas to, for that to make sense. Otherwise, you don’t have things that you’re going to net very well. So yeah, very interesting to see. I guess I was also expecting that we have or we don’t have a total to 100. But we also didn’t say in house bank, I don’t know are unsure, which would probably, perhaps tap the rest out. So great. Great. Thanks, everyone, for responding to this. This poll question. Now we’re going to move into data driven treasury, we’ve talked about a few things related to data. But you think about what is driving so much of treasury, it’s, it’s, you know, we have goals towards ensuring there’s visibility, there’s adequate liquidity for the organization. We’re managing risks. We’re forecasting our cash flows, we’re looking at different models. How do we do that and what’s required, and we look at data driven technology, this stylized, you know, concentric circles going out, you know, it gets more involved as you go out. So we have the, the three, I guess we’d call them axes, speed, analytics and visibility, when you think about speed, what’s happening with speed, we move from, you know, prior day, or we use move move from accounting statement timeframes to prior day to current day, to a need for faster, and in some cases, the need for real time. Now, whatever you think about is real time necessary, or same day necessary or prior day may be fine. Whatever you think about that, over time, the need has moved out more, more towards real time, more towards faster there’s, I would, I would venture a guess to say that almost no companies are moving slower. I may be in the same position for a time, but everyone’s moving faster. And it’s usually I need more information to respond quickly. And so I need faster, I may not need instantaneous, I mean, not the real time, but I need faster and more. So as we move across time, on the visibility side, you know, this idea of AI plugging things into a database, I have debt requirements, too, I need to be able to model and manage things more real time I need, you know, data, lakes and business intelligence tools, and those types of features in my treasury systems and my risk platforms, I want to be able to see this and have that visibility, you know, across these different dimensions, and instead of every time there’s a question, I’ve got to go source, the data hunted down, hope it’s complete, build in a spreadsheet, and then say, Here, look at my model of my counterparty risk, the need for better visibility across all these dimensions of information from balances, to exposures to future flows. That’s moving in one direction, we need better visibility and deeper visibility. Not everyone needs to see everything, but it’s moving in one direction, more information. So more speed, more information. And finally, Bob, and I’ll, I’ll let you get back to it, you know, this idea of analytics. So we used to think it was great if we could do, you know, a smooth average, a running average, awaited running average, then we started putting in some tools to pull scientific capabilities there. So we really need to see trends patterns. And this idea of I want faster insights as to what’s happening. That is that’s happening in forecasting in a fairly foundational level. But it’s also happening in a lot of others that we want to, you know, spot anomalies for a forecast or for fraud. We want to analyze trends and patterns across so many areas of finance in so many areas of business, that it’s moving in a in the direction single singularly in the direction of more analysis more rapidly across more data elements.
Bob Stark 29:21
There was a comment that came in I was just add to what other people were saying as you were talking and I think it was very motivational, Craig because there’s quite a few that jumped in. And there’s one that I saw that I thought yes, that exactly encapsulates the practitioner view, want to make more informed decisions. And to your point, Craig, it’s greater visibility. And it’s analytics on top of that data insight that allow us to make a more informed decision so we’re not just relying on Well, here’s what we’ve always done or here’s what I think which data is what’s going to supplement the here’s what I think to here’s what I know And there’s I, like I wouldn’t want to choose between any of these three, Craig. And so hopefully you’re not asking me to, which is the most important because they all have a role. But most treasury teams are have been highly focused on visibility, and very much embraced, being able to say, drive a forecast with greater data and greater insight from different systems and groups within the organization. The analytics, I mean, even just on the FX side, being able to look at a correlated value at risk to make a FX hedging decision is an advancement over what we did probably a year or two ago, being able to utilize data to then teach different parts of the model. So incorporating things like machine learning, which is very, very basic AI, to be honest. But nonetheless, it’s an advancement to be able to help that predict some certain streams of cash flows, whether it’s on the receivables, or payables side, alongside other inputs. These are the sorts of pieces of information that we want to be able to use. But analytics is not just about having additional data, it’s also about being able to visualize that data. So you look at these bi or data visualization platforms, you know, like the Tableaus, the Qliks, the Power BIs, that falls within the analytics, it may not necessarily be a new set of data, but it’s a new way to look at that, and then capture that and then drill down on that, to understand what is the impact of this on the decisions I need to make. And so that’s why I pick I love that comment around more informed decisions. Yeah, it’s about being more intelligent and being more insightful. So that when you’re bringing a forecast, or liquidity plan, or projection, or you’re reconciling free cash flow with FP&A, that you’re bringing a very fact base set of arguments to the equation to say, if this happens, this is what it means for us and our ability to manage cash or FX or balance sheet.
Craig Jeffery 32:03
Yeah, I like that. I like that comment from Mary as well, you know, the idea of, you know, it’s informed decisions more accurately and with greater speed. There’s there’s value in getting to the answer more quickly, having it having confidence that it’s more accurate than the past. There’s so many things that we know, we don’t know, we think we understand our business. And we understand that perfectly. And it’s changed over time. And so we’re naturally off by some significant percentage. Well, thanks for thanks for those comments, Bob. And thanks, too, for the chatbox. I think we’ve got about 10 more poll questions when they come up, I think we’ll be we’ll be done pretty soon. Bob, you want to start us off on the difference between cash forecast and liquidity planning or the similarities between these two?
Bob Stark 32:55
I like this one. And let me start off by an example I heard as recently as last week, so we had a it was actually for Kyriba, like our annual kickoff. And we brought in five clients on a roundtable to talk about a variety of things, basically teach us what they think and how they how they look at things. And one of the questions was posed, what’s the difference between cash forecast and liquidity planning? And what do you do for liquidity planning? There were almost five different answers, maybe more like three different answers, but it’s the the verbiage and then the practice of everyone agreed, there’s been an evolution. And that really has been driven the last three years really, since the most recent sort of a risk situation with a pandemic had driven yet another exercise around being able to forecast more precisely, and across different unknown scenarios. There’s a lot of uncertainty and we had to build plans around that. But there’s different versions of liquidity planning, which ranged from what we see here, like the duration based, you know, is Cash Forecasting, really an exercise that maybe used to be three months, and now is more to a 52 week. And liquidity planning is an extension of that. And then, of course, an extension of that with additional data and additional people, namely FP&A being brought into that equation. Others answered in the way that cash forecast and equity planning are both looking really from tomorrow forward. But liquidity planning is taking that forecast and surrounding with additional data around investing, borrowing and working capital, so that you’re taking your forecast, and then being able to layer on the ability to make decisions around what do I need? What levers do I need to pull from a liquidity standpoint? Do I need to look at my revolver? Do I need to look at certain pockets of cash and different parts of the world perhaps leveraging in house bank? Do I need to be able to increase or improve the DSO so I want to accelerate cash? Similarly, do I want to initiate a program or improve the program around payables so that I can actually monetize that supply chain a little bit more precisely? The Is it the decisions at the end of the day, however you want to define it in your organization, whether it’s time based, whether it’s database, whether it’s both? There is a practice emerging around making better decisions and more informed decisions, going to go back to that wonderful comment from our, our friend, Mary, around what levers do we pull to ensure that we have the appropriate liquidity in terms of investments, borrowing and working capital working as efficiently as possible for us? So I know there’s a lot built into that, Craig, but that’s, there’s two interesting, really a couple of interesting viewpoints in there. In the end, liquidity planning is an extension of forecasting.
Craig Jeffery 35:44
You know, when we think about liquidity planning, in some ways, we’re some something about liquidity planning, it’s, it’s the income statement focus. You know, FP&N a cares about what’s the margin? What’s the, what’s the focus? One second. Sorry about that. Yeah. So it’s, uh, you know, that tends to be the focus, where as you get a little shorter term, cash forecast, it’s, it’s about the balance sheet, day to day, week to week over that shorter period of time. But this, you know, as you were talking through some of those, those items, and the examples of the three different views of cash forecasts, and liquidity planning, you know, out of five people in five different companies, this, this idea that, you know, we’re looking, we have to look, as we look out farther, we have to do a lot more balance sheet planning, what does the organization’s balance sheet need to look like? And that that flow and the impact of profitability and margin has a big impact as you as you get farther out, so it becomes increasingly strategic, as you get farther out. The days don’t matter, once you get out two or three or four years, the days certainly do matter to get in closer. So there’s, there’s a lot of real good value in each of these, we can look down on someone else to a different type of forecasts. But I think really a summary of some of what you said is, what are you trying to accomplish? And how did you get there? And how these things dovetail together?
Bob Stark 37:16
Yeah, and I think, you know, one point you made really nicely there, Craig. And I want to emphasize just to make it incredibly impactful for everyone is that it has to be a connected process, ideally, a process as opposed to multiple, but let’s just say at its worst, it’s a connected process. You’ve connected tissue between these. So if it’s FP&A and treasury, you’re not having two different reports being presented a CFO, and they have to decide which one’s right. Like, those days are over. It has to be integrated and collaborative so that you’re able to look at for free cash flow, just use that example, the top down, which is what FP&A is going to bring, and you need to be able to integrate that and compare that versus bottoms up to give some guidance as to what should we be saying and setting expectations internally and externally? And it’s different people, it’s different processes and Craig, to your excellent point, it’s different data and different data sources that all need to be connected. If it’s disconnected, it’s really not helping anyone. It’s certainly not helping the CFO provide guidance to the market.
Craig Jeffery 38:23
Do you think the FP&A areas should say we’re not providing cash forecast certainly in within a three month period and leave that to treasury because, you know, for them a CapEx expenditure? You know, hits it shifts a month or two doesn’t impact their their model too much. But it’s certainly you know, a huge disbursement can impact treasury and treasury when you’re getting closer has, I don’t know, more, more adjustments day to day. And that front that should they should they avoid each other’s turf on the margins here, like close in, should be pure cash forecasting farther out. We look at FP&A.
Bob Stark 39:07
Well, if I dare answer with, with data in the answer, the data is proven that treasury is really accurate at short term forecasting. So that 13 week forecast, I think anyone would put up their hand saying that they’re in the region of high 80s to somewhere in the 90% accuracy, even if you measured a detail level and FP&A would say, Wow, we don’t even understand, we don’t have visibility, anything like that. So there’s definitely almost like a neutral zone, which is that six months beyond for treasury and for FP&A inside of two years, maybe inside of one year, where there is just a neutral zone using a Star Trek reference. That’s where there’s an opportunity to collaborate in a more meaningful way. But it all should be connected. And I think that’s, you know, the perfect answer, Craig, is bringing the best of what you’ve done, and then start to interweave that so you have literally a visual for the CFO and for the board to understand and make decisions on.
Craig Jeffery 40:12
Yeah, that’s, that’s good. Yeah. There’s there’s always sometimes they’re saying, I want a reconciliation of the two, for how we finished the month. Unless you said those days, it sounded like you’re saying those days are past. I think they’re past for a lot of companies. Hopefully, there’ll be passed for everybody soon. It’s like, that’s really not how it works. Right when you get close. Great. All right, we come to our third and final poll question. This is about forecasting and modeling. So you know, this is a head nod to what’s coming up. For forecasting for forecasting and modeling, we have a cash flow forecast that’s one month or more, we run multiple scenarios, and all the way down to the end. So I’m told that for, we need three more, more. Three more polls, okay, we’re there. Nobody needs to type the word polling. So we got our 120, we’re happy. Hopefully everybody can see the poll. I see there’s a note that it’s not showing maybe you can click on it, click on your screen or alt-tab, see if it pops up. But this is really interesting to see the extent of forecasting and modeling. And what goes on here. This is this is why everyone likes data, right? We take these polls, get hundreds of responses. It’s snap, it’s in context for what we’re talking about. We really appreciate you everyone taking the taking these polls. It’s both fun and, and helpful. Not just interesting, but helpful. All right. This is a forecasting group up 76%. And you know, on the bottom, only a quarter are using a TMS for some part of the process. So you’ve got you’ve got a lot of fields plow there, Bob, I think that’s good news. There’s a lot of opportunities for TMS providers. So that’s happy. Any comments on the scenarios and analysis? It’s less than half but but pretty close to half?
Bob Stark 42:20
Yeah, it’s pretty close to half. I’ll take glass half full and say that there’s a lot of organizations that have already embraced the need for Treasury to play a meaningful role in managing these different scenarios. I would say the 53% that didn’t say yes to that. Were, it’s been done by someone else. And this is a great opportunity for treasury to get involved because, Craig, as you made the point a few moments ago, there’s a fantastic track record for treasury fairly in close. And what we want to do is take those practices from treasury and extend those forwards so that we’re moving our cash forecast in horizons, those guardrails movement further, you know, further down the field, and then entering this practice of liquidity planning, there’s no reason that liquidity planning needs to be the exclusive turf of FP&A. It should be a collaborative area where there’s data from both and practices from both to drive better results there. I think 47% have already identified that there’s an opportunity here. So I like what I see in that regard.
Craig Jeffery 43:24
Yeah, we sometimes we we think artificial intelligence and machine learning and machine learning are buzzwords nobody’s doing it. But this capability, these capabilities are being dropped into different software, different tools that we have. And we’re almost at 10% for the the audience say it’s been used somewhere, as part of the forecasts and modeling process.
Bob Stark 43:53
It’s a really good start. You know, it’s interesting, there’s a correlation, though, between the 9% and the 24%. If you don’t have a good tool, and to be quite honest, every treasury management system, and I will hold ourselves up, as this example, as well, has historically not done a great job and making it very easy to forecast. There’s a reason that everyone uses Excel for forecasting. And it’s the responsibility of technology vendors to make that easier. And then to embed data driven technologies like artificial intelligence into those platforms. I mean, our advancements in this are relatively recent, but it’s a responsibility. Otherwise, of course, people are gonna say spreadsheets are easy. I can just type. You know, give me that. And maybe I’ll use your platform kind of thing. I think it’s a reasonable expectation of everyone.
Craig Jeffery 44:43
Nice. All right. We’re going to continue thanks, everyone for your responses there. So, the next the next few slides on forecasting. I’ll begin and Bob will finish out each slide with some comments or we’ll go back and forth. For those who have you We’ve been on some of these webinars that we’ve done when I, when I talk about forecasting, I love to talk about a paradigm and rolling them, you know, rolling the dice and you roll two dice, you get two ones, which is a two all the way up to two sixes, which is a 12. And then the frequency is shown on the tables, the potential combinations and how you can get those combinations, right, there’s only one way to get it to two ones, there’s only one way to get a 12. But you have more options to get a three, get a one, a two, a two and a one. I think everyone probably figures that out. Well, there’s one concept about, you know, a range of values versus expected value. Well, you roll two dice, what’s the expected value? It should be a seven. That’s in the perfect world, right? It’s gonna be a seven every time. But it’s not that right? There’s this whole range of what can occur. And life is not this, you know, life is not an expected value. And so you can see is like, we can think about, hey, this is a forecast. This is what my model is to a point. But when we think about what’s the confidence we have, if you look at the bottom, you can see standard deviations, and what’s the confidence interval of it, maybe I’m expecting a seven, but I feel like it’s above you know, 80%, that I’m going to be between five and nine, or whatever the particular scenario is. But this idea, here’s a range, I need to look at what happens if I’m at the low end of that range, or what happens at the high end of that range. And how disperses us, you know, I think we’ve we’ve heard the terms long tail and short tail, the farther these numbers go out, for example, if it goes out to really far to the left, or really too far to the right, we think about those long tail events. And if it, let’s say you’re cashflow in, it’s going to come in it’s kind of 1.2 million a day maybe only varies between 1 million and 1.4 million, that may be considered very short tail, everything’s concentrated, right around a particular number. But let’s say he might get nothing in on a day. Or you might get 3 million, and it can vary in significant ways. So what is it? What does it mean, when that can happen when there’s this range of values. And I think this idea of this confidence interval, we learned in statistics, we know intuitively, things happen, they don’t happen in the right ways at the right times, they happen the most inconvenient way, this is a key concept for forecasting. So it’s a level of confidence in the higher the low, if you have a little extra cash, it’s going to be a real problem. Maybe not, you go too short, you got a tap, you overdraft you do whatever the situation is there could be a negative consequence. So this idea of there’s a range versus let’s just focus on the expected value is a vital concept that Treasury has to understand and has to make sure that’s shared in the organization. Bob, I don’t I don’t know what you want to add here about this idea of expected value versus a range of values or an interval.
Bob Stark 48:00
Confidence interval is critical. And most treasury organizations aren’t using that right now. In part, because what we just saw on the poll, that they lacked the ability to have tools that leverage the data, and so have that confidence in the data to actually have a reasonable confidence interval to rely on the results. And then they don’t have the tools. You know, they don’t necessarily have a forecasting methodology or forecasting tool that actually allows you to choose your appropriate confidence interval. But this is critical when you’re looking to make decisions, especially in the near term, like in the next seven days, you’re very short term forecast. If you’re not using this, it’s I think I’ve said missed opportunity before, Craig. But at the risk of being repetitive, I’m going to say it again, this is something that we’re starting to see treasury teams embrace. But it’s hard to move from expected value, which is how we used to do it to a range of values and a confidence interval, what those range of values are, but you have to do it if you want to make more precise and better decisions, especially as rates are higher where they are on borrowing.
Craig Jeffery 49:07
Thanks, Bob. Now as we look at more accurate forecasting, I’m just going to say a few things about stress test and scenario analysis. And, you know, when we look at stress tests, what happens if we move, you know, one particular variable, if you have, let’s say, interest rates with stress tests, what if it goes up 300 basis points? 3%. What will that do to our cash flow for to our holdings to our position? You know, in our portfolio, what about the FX rate? Let’s say there’s a one, you know, a 50% or 20% shift in six months with a particular currency. What’s the financial impact to the business? So how do we stress test our portfolio? What’s the max like? What’s the take? What could the tail look like? For any of these variables? You know, on the scenario side, what about a combination of those events? It’s nice when there’s only one thing happening. But everyone has pilots is friends at Talk about their they put them through these paces, it’s like, oh, left engines out, there’s a fire in the cab of this, you know, they stack up a bunch of these things to see how you can handle and adapt to a range of variables. And so scenarios are, what happens if interest rates move between a certain model, certain level FX pairs move up or down, the cost of your goods and services increased or decreased by a certain percentage. As you can take these scenarios, you can run these through certain models to, or simulations, even to see what can happen over time around 1000, or 5000. Leads to see multiple scenarios happen at once. And this is a way of getting that realistic view of here’s a scenario, here’s the range of what can happen, not an expected value. This requires this requires certainly scenario analysis. So these models require tools to support it. Bob, any thoughts here?
Bob Stark 50:59
Everyone should be doing this. Yes, you’re right, that the tools maybe might be harder to come by and you think of goodness, how many different formulas do I need an Excel sheet to make this happen. And it’s a reasonable point, because you want to be applying this to your entire forecast. And you want to have that flexibility to say, all these scenarios that you put in the bottom of the slide at the top of the slide, you want to be able to talk around, what happens if we are still in an era of uncertainty, you can’t just have one version of your forecast, it just it doesn’t make practical sense. And so you need to be able to communicate the effects of this or that and the variables you listed plus a few more are the kinds of things that Treasury needs to have good answers for, if rates go up, if inflation goes up, if our supply chains once again, go haywire and Titan, what does that mean, for the performance of organization from a revenue standpoint, from a cost standpoint, from a liquidity standpoint, have to have answers to all this?
Craig Jeffery 52:01
Yeah, so a couple of use cases. And I see I’m leading off on this one, I was like, I was hoping to just listen to Bob talk about these. But it’s just just a couple of these, you know, this here, here’s an example. You know, you want to determine what’s what’s the maximum cash drain that can happen if this event happens, right? We stop, we don’t get these materials for that feed into our fine, finish. Good. And that delays US a month, what would the cache drain be if this happens, or if this other event occurs? And so you know, how do we react to those? What are some ways of minimizing those threats, if the even if these are longtail very, very low likelihood events, that would have a very significant impact on our business. So this idea of, we’re going to stress test it, we’re going to look at different scenarios or different events, that would have a very negative impact, even if we think that’s not going to happen. That’s not going to happen in 20 years, that’s not gonna happen in 40 years. But let’s look at that and see what that what what can occur. And do we have the ability to withstand that as it is? What would we need to do to blunt that impact to cut off the long tail? Same thing that scenarios, you know, different, different needs for cash based upon some of the models we talked about before? What are the different scenarios that can that can occur? How does it impact our investments, our cash? Is that going to require us to tap more or get an emergency line or sell something in a hurry basis, in a hurried manner that creates an issue? So there’s a there’s a number of items there that our use cases for a stress test, or for running scenario analysis. Bob, I’ll let you take us home on this one.
Bob Stark 53:51
Yeah, we could have a whole presentation on this, Craig. I’ll give the short version for now. And it’s kind of a fun thought. So we’re not that far removed from when stress tests were extremely important and part of our everyday cash and liquidity reporting is less than three years. So, what we saw was, and this was a KPI that was the most popular amongst our all our clients and one of our dashboards, days of liquidity left was the name of the KPI. And it was some number of days until you really had to make some different decisions. That’s an example of a stress test. It’s not a ridiculously complicated, it’s not in an incredible amount of math. But it is really important to be able to visualize that and see what happens if, so you need to be prepared. It’s just an, it’s just simple extension of the practice of forecasting and planning to be able to answer that question of, if the Euro bounces back another 5%. If we actually do see another 50 or 75 point hike in rates, if we do see a clamp down from an inflationary standpoint, what does that mean? Even if it’s just simple effects in our DSO and DPO, maybe, maybe it’s just as simple, you know, a certain number of customers are gonna pay us, or they aren’t gonna pay us. These are just simple scenarios, we want to build into it. So we can understand the impact and then make, I love that comment again, make more informed, data driven decisions.
Craig Jeffery 55:24
Informed, accurate, and more rapidly. That’s awesome.
Bob Stark 55:28
The speed part, yes, and more rapid.
Craig Jeffery 55:32
All right, we’re gonna go, we’re gonna go through a couple of the, the implications from this, how do we proceed, here’s some ideas for you to consider. And Bob and I’ll go back and forth on this.
Bob Stark 55:44
Yeah, let’s start off with cash. Cash is king, that’s never going to change. And so it’s that ability to forecast and plan for different scenarios, as we’ve just been talking about, so that you can pull the right liquidity levers to drive the right level of cash to support the business and whatever is going to happen. And be prepared and be ready. So that could be as simple as making sure that you have the right level and your facility making sure you’ve optimized and not left cash on the table in terms of days payables outstanding, making sure that you’ve put in the mechanisms to accelerate cash flow, and DSO or just simply getting a little bit more out of your investments, these are all things that can happen. It’s driven by efficiency, visibility in terms of your internal structure, and being able to optimize your borrowing, investing through things like in house banks, and multilateral netting. So understand complete visibility internally first, allows you then to surround it with data and external scenarios.
Craig Jeffery 56:46
And that’s great, Bob. You know, the little checklist clipboard here response plan is one is have this list of potential scenarios that can exist and what your actions item are, if they occur. At first, it seems this can be an exercise almost in futility that I’m making this list of things that I expect, that can happen every couple of years, that seems reasonable. And then you get down to things like this won’t happen, but maybe once every 20 years or 40 years. They may not ever happen in my career. But having this list of scenarios, figuring out what those impacts are, what would the level of impact be? And how do we respond? is really important for your your overall plan? How do we how do we respond to this inventory of items? What can the impact be? What do we need to think about first, it doesn’t have to be massively detailed, for every single item, but it should provide some rules of the road some guidance as to how we, how we proceed.
Bob Stark 57:43
Alright, point number three, visibility. I’m not gonna repeat anything that you can see here, and we’ve talked about different scenarios. The point that’s important is, Why do you need visibility? What is it going to do for you? And what can you actually action from that forecast or from that understanding of your cash flows or from understanding what your working capital programs look like? The power of visibility and the value of visibility isn’t what actions, it enables. And so visibility is first. If you don’t have that you don’t you can’t do the rest. But once you do have that, you’re in a position to make much better and more effective and cost effective, I should say, liquidity decisions around borrowing, investing, working capital, and even from FX standpoint, protecting against currency headwinds, tailwinds, and volatility. So, visibility is empowering. It’s important to have it and then use it.
Craig Jeffery 58:43
On the final pillar here, the preparation side, we’ve covered some of these already, and some some length, right? Don’t ignore the low likelihood items, those items out on the tail. Make sure you’re thinking about those and as Bob says everybody should be doing stress testing. The last point there is, you know, don’t don’t go it alone is really a summary there. You have partners and technology that can help. Whether it’s your bankers, consultants, your technology providers, other people in the industry, there’s quite a few resources to tap. And so preparation is about mindset and it’s about your support network here. So those are the four areas we have. Bob, and I thank you, Kyriba and Strategic Treasurer, thank you for today. And we’re going to turn it back over to Brian, who has done a great job of counting slides and keeping everything functioning behind the scenes. Brian, back to you.
Well, thank you, everyone for joining us today. The CTP and FP&A credits, today’s webinar slides, and the recording of today’s webinar will be sent to you within five business days. And for more on succeeding in 2023, be sure to check out the Open Treasury Podcast as well as the Treasury Update Podcast by clicking the links In the chat box. Thank you and we hope you have a good rest of the day.