Outcome-Based Contracting: Did It Work and Can You Prove It? | The BizTech Pulse Podcast

Krishna Hari (00:05)
Welcome back to The BizTech Pulse Podcast. It’s session three. Today my guest is Ian Thompson. My guest today’s spent more than 30 years doing the thing most people only write about — I mean actually running global finance operations at scale. Ian Thompson led order to cash,

credit and enterprise transformation at S&P Global across more than 10 countries before founding

Clear Cycle Advisors. He writes a blog and has become one of the very sharpest voices on the question every CFO is now putting to the shared service team.

“Did it work?”

and

“Can you prove it?”

Ian, welcome to the show. Wanted you to

say a few words, introducing yourself.

Ian Thompson (00:50)
Great. Thank you so much, Krishna. Thank you for the the kind words opening up. As you stated, yes, my name is Ian Thompson. I was a global business services leader and also a risk leader within S&P Global. And the topic of — “Does it work” and “Can you prove it” — is something that I think more and more we’re seeing in global business services, but also other areas. It’s really about the value creation, right?

We’re moving away from, headcounts and costs of items to true P&L impact, balance sheet impact. So that’s that’s what I’ve been trying to write about more often.

Krishna Hari (01:24)
Sure, nice. I went through a couple of your papers — very impressive, very focused areas which you cover.

What convinced you, what made you move into this advisory role? What’s the biggest misconception leaders have about order to cash that you find yourself correcting?

Ian Thompson (01:41)
Yeah, I think the thing with order to cash is that there’s one of two thoughts, I think. There’s the thought that it just works and so just leave it alone and it’ll work itself out. And the other one is well, if you just add more people to it, it’ll work better. And I think both of those are really big misconceptions. I’ve seen very large companies become entangled in multiple processes, ERPs,

people, location strategies and not really do the due diligence of of figuring out,

“Hey, what’s the best people processing technology?”

And that’s, you know, that is the kind of the it’ll work itself out mode. And then the add more people is,

“Hey, you know, we’re gonna start measuring things like how many accounts does a collector have, instead of how many dollars does it actually take to bring in, or how many people does it actually take to bring in dollars.”

With counting the wrong things, adding people to processes where you don’t need to add people, you actually need better tools, technology, and process review. So that led to me starting Clear Cycle Advisors. You know, small businesses need

maybe smaller answers or questions answered, you know, just like —

“How do I improve my cash flow?”

“How do I start measuring things a little bit differently?”

Then you have your medium-sized businesses that are really growing.

“How do I keep my order to cash ecosystem to scale with my revenue growth?”

Right?

And so those are the questions that I answer the most. But within that, I think one of the things we’re going talk about today is outcome-based contracting, which everyone should really be very interested in, whether you’re small, medium, or an enterprise business.

Krishna Hari (03:13)
I think that’s where we are heading. Also you have written

‘The era of paying for access, for activity, for effort, and for presence is ending.’

And “Did it work?”, “Prove it.” — is a new standard. What’s driving that shift now after years of GBS being measured on cost-per-invoice and the headcount benchmark?

Ian Thompson (03:31)
Yeah, I mean, I think it’s just the old adage, you know, “What have you done for me lately?”

I think it’s really, you know, “How much are you going to get out of the headcount change?”

Now, so I would say obviously there’s there are organizations who would benefit greatly from labor arbitrage, right? You’re going to see an immediate hit, and a benefit to your balance sheet. You’re going to see maybe some improvements depending on the BPO you’re you’re working with.

But by and large, most large enterprises have kind of wrung that dry and now it’s what are we going to get for our value? And really I think it is this outcome-based contracting where there’s just skin in the game across the board and everyone has to come to the table and share risk.

Krishna Hari (04:15)
I agree. I think the the other one which I which struck me is your argument that the vendors have done their hard work, baseline attribution governance, while most buyers haven’t. I mean, are they not ready and why is the buyer’s side so far behind? Is it a skill gap or data gap or a willingness gap? What is that?

Ian Thompson (04:36)
There’s a lot of all of that there. I’ve seen and heard about all of those things — the skills, the willingness, the data. I think by and large, it’s a it’s a structure gap. It’s a way that you’ve set up your global business services to just be reactive — reactive to problems, reactive to demands, reactive to initiatives. And instead of being proactive. And so I think where you see a lot of organizations that

do this well or have started to do this well, have CFOs in organization who really understand the value that can be unlocked with this type of agreement. And so you start talking about things like, you know, stronger cash generation, you start talking about, really big impacts to balance sheet and and P&L.

They they are the ones who are asking now,

“Okay, so what are we doing and why?”

And now “Prove it.”, right?

“So prove to me that it’s working.”

And it hasn’t been very well — it hasn’t been taken up across the board, I think, because a lot of times people are just keeping up, right? I think they are just keeping up with what it is that they need to do day-to-day. But really, the organizations that take a beat, take a step back and say —

“How am I going to enter into this world of AI a little bit differently?”

“Where do we see our opportunities to do things differently?”

This is one of the things I think usually comes out of it. And those organizations that continue to just kind of add people to problems or try to bolt on things to their processes to make things a little bit easier, but only incrementally, are behind the curve on this one.

Krishna Hari (06:09)
Absolutely, absolutely.

Ian Thompson (06:10)
Yeah, so this is a study that was done by The Hackett Group, right? And and this is you know, if if you’re not familiar with The Hackett Group, please look them up. They have a lot of great benchmarking. And this is one in particular that I found very compelling. It goes back to some of my earlier points. So process complexity is one of the top barriers.

Because there hasn’t been a willingness to kind of address what is in order to cash or address what’s in your accounts payable, because it’s all just kind of back office stuff and it’ll work itself out, or it will throw people at it, you see very complex processes for very really simple problems or simple processes. So you have multiple ERPs, you have multiple reporting tools, you have multiple

touch points. You have multiple teams in different locations that are very siloed in managing certain aspects of the business. And so that leads to this, you know, it’s a very real thing where I have too complex a process or a team or a function to have AI really help me in a meaningful way. And that might be true or not true. I think, some of this is also perception, but

you look at some of these other reasons, unrealistic expectations. I mean, that’s a that’s a top-down problem, right? You’ve got leaders who are coming to the table to say,

“Hey, you need to do ‘X’, ‘Y’, and ‘Z'”, and they they’re not able to do it, right?

They can’t do it for a variety of reasons.

Data quality and technology. Data quality is a tricky one, and I know you know, it’s one that we talk about quite a bit. “Bad data” doesn’t mean all data is bad.

Right. So that’s one of the things where I mean I tend to lean a little bit more optimistic in the data conversation. I think that there will be bad data and everyone is gonna have to deal with that and figure out what that means. But I do think that there’s an opportunity there to really, I don’t want to say “overlook it”, but just try to say,

“Okay, well, might we might have some data issues, we might have duplication, we might have missing fields, but we need to go ahead and move forward.”

AI talent shortages.

I think that’s real. It’s also very vague. Like what does that really mean? Are these coders? Are these people that don’t know how to use Chat GPT? I find that, you know, when we start throwing up excuses as to why we can’t do things, we start coming up with things like,

“Well, we don’t have the right staff in here to get these things done.”

I think there’s a lot of different ways to kind of overcome those barriers. And then change management.

I mean, I’ll be honest, I would probably put this at the top if this was my study. I mean, things that I’ve heard — it’s really a, it’s really a culture problem a lot of times, right? It’s the organization itself that really is throwing up the barrier or it’s the management team that doesn’t know how to overcome that staff that feels threatened by AI.

And that’s a real thing and it’s not unwarranted by any means, but there’s also a way to work through it that I think a lot of teams need to need to figure out.

Krishna Hari (09:00)
All this, I mean, the especially the change management and even the AI talent, right? Today, I mean everybody talks about Gen AI integration into the process. But I think what I like about HighRadius is — they have bisected every process in the “four algo”, they call it. And they have gone deeper into every process what

Ian Thompson (09:19)
Yes.

Krishna Hari (09:24)
AI ML can do, what an RPA can do, and what a simple formulas from Excel sheet can do, and plus the Gen AI aspect of it. I think that differentiates people who do in AI — filter certain processes and integrate various ERP platforms and stuff like that.

Ian Thompson (09:46)
No, I agree with you, Krishna. I think HighRadius is a great example of an organization I think is doing it right in a lot of ways. I mentioned them in a recent newsletter that I did about this topic, right? They’re putting a lot of things on the line, right, to for this for this space. And I think that they’re doing a lot of really good work.

Getting down into the the real detailed areas, again, one of the things that I’ve seen though is that that requires a commitment from the buyer. That requires a level of commitment and a level of I’m gonna say vulnerability too, from the buyer to say,

“Okay, we’re going to have to stand here and admit maybe we’ve been doing something wrong for 10 years.”, right?

That takes a certain kind of group and a certain kind of people and a certain kind of change management, right? So…

Krishna Hari (10:27)
Absolutely. And also, I mean, just to add to that, right? I mean, I’ve this this in the last two, three days, we were talking about this, how modular they have brought their solutions to, where people can look at certain modules on the AP side. Only the email automation aspect of it. We can, I mean, you can plug this in and see your benefits and then go step by step. It has become like a Lego, right?

Ian Thompson (10:28)
It’s it’s not true.

Krishna Hari (10:57)
Just like become like a building a Lego, you can plug these things very independently and then create your own AI based solutions around your order to cash process, AP, AR, whatever it is. That’s amazing. I mean, that’s something which mid level companies can adopt in a very structural, modular way and then build their solution as they see the benefits.

Ian Thompson (10:57)
Yes.

Guest.

Krishna Hari (11:23)
I mean i it’s a visible ROI or visible outcome which you can bet on — where the risk is very low from the adoption standpoint.

Ian Thompson (11:33)
I think that’s a great point. I think, you know, everything’s about risk and ROI. I think the more you can, you know, prove the the winning side of that, the better.

Krishna Hari (11:43)
The other one, you have cited the finding that most PE-backed transformation deliver less than half their planned value despite hitting every milestone. Where does the gap between activity and outcome actually open up?

Ian Thompson (11:58)
Yeah, I mean that’s it’s a great question. I think, when you’re talking about things like milestones, people have have replaced, outcomes, and goals, and metrics, with milestones, right? And so projects and initiatives and implementations are now all milestone-driven. And so, you know, everyone has a big party when the big milestone got met.

Right? And when go-live happens, right? There’s a big bash and there’s a big party somewhere and we all that. But what is the actual thing that’s that’s happening that we’re we’re trying to get to? And I think that, you know, from a gap standpoint, it really comes down to ownership and accountability. And

what you find is, there are lots of SIs, there’s the technology, there’s the project teams — but are there actual people who are accountable for outcomes that happen in the organization? And that’s to me where I see the real kind of the real gap, right? It’s the gap of ownership and accountability

for the execution of the outcomes that have been agreed upon before you even started the program that you’re you’re discussing, right? So whether that’s setting up a global business services, implementing an ERP, like those things become very very well seen when even with a successful go-live, things start falling off the rails because, you know, for lack of a better word or term, there’s not a throat to choke, right? Like you need that that person who’s now responsible for that outcome.

Krishna Hari (13:22)
Mm-hmm.

Ian Thompson (13:30)
And it’s not that the outcomes are going poorly, they’re just not being communicated effectively.

Krishna Hari (13:37)
Absolutely. The other one is attribution seems to defeat many outcome programs — separately, what the transformation delivered from market condition, customer behavior and seasonality. How do the best teams you have worked with actually solve that?

Ian Thompson (13:53)
Well, I think, again, it kind of goes hand-in-hand with the last question. They build the counterfactual first, right? So they’re they’re going into it with the variables being measured. And so you’ve got a baseline, but you also have a baseline that takes into account a lot of variables that you then can control. You can control for those variables in your in your baselining, and you know that —

Let’s say after an implementation of something, you know, the DSO went down, not because your largest customer paid you, but because, the tool that you implemented or the process that you implemented works. And so you have to be able to set that up specifically before you are actually going into this project. Again, if you’re just looking at getting this thing going live, if you’re just looking at

well, we want the DSO to drop three days. It’s going to be a bit of a problem because you’re not really going to be able to attribute the success to the project or the failure for that matter, right? I mean, it’s it’s it’s also the other side. But I think what the best teams do is they do that — and again, I’ll go back to the ownership and accountability — they have a person who is the owner of the outcome. So it’s

typically, you know,

“I’ll use GBS” —

some kind of leader,

right? Or a finance leader, or somebody is who’s the leader for that — they understand what the outcome is supposed to be, and they’re constantly reviewing the inputs to understand what the outcome is. And they’re taking into account all those first two things that I talked about, right? The control variables and the the counterfactuals, right?

There’s just a constant measuring and monitoring of that. And so that’s what the most successful teams do. They don’t get hit with a a question like —

“Well, our biggest customer paid.”

“Isn’t that the real reason?”

They don’t get hit with that because they’re already updating everybody on the status of what’s actually happening. So everybody knows it’s not the biggest customer that’s paid. It’s because, you know, our systems are X percent more efficient and effective.

We’re able to measure that.

Krishna Hari (15:59)
The other one is as AI agents start delivering measurable, attributable results in real time,

what fundamentally changes about how a GBS function is structured and staffed?

Ian Thompson (16:12)
Yeah, I mean the agents, they’re not just coming, they’re here and they’re they’re actually working and they’re doing really good work and the people that are looking at agents and orchestration of agents and the governance of agents are really ahead of the curve. And so,

GBS is really primed for change. It’s primed for, I think, less heavy-lift projects and more agentic builds, more agentic orchestration and more agentic governance. And so the value is going to be:

“How can I build

agents to do either the work or part of the work that’s going on, (and let’s say) in order to cash process?”

“Where are my roadblocks?”

“Where are the things that get stuck?”

“Where do I still continue to put humans in the loop? — Not because necessarily I think it’s a good value add, but because I don’t have another way to do it.”

And so getting agents in there and doing work either in whole or in part, and then

how do you monitor those agents? How do you keep control of those agents? How do you work them into your controls? How do you work them into the governance of your processes? And that’s really, I think, where we’re seeing GBS move. Like that is going to be the the next wave. And I know there’s companies doing, I’ve talked to companies who — that is their plan. That is what they want to do. It’s not just bolting on a tool, it’s the tool end, right?

And I have been really excited to see companies that are in this space. They’re not giant companies, but they’re smaller companies that have maybe some big customers, but they’re doing a good job, let’s say in the governance space, right? And so creating a single pane of glass to understand what your agents are doing, creating kill switches for those agents if they’re not adhering to SLAs and SOPs. Companies that are generating SOPs automatically based on

you know, patches and and ERP updates and whatever else might be going on, like that is the future of global business services. And then in turn, and this has always been true of global business services, I think, the rest of the organization, especially like finance teams and maybe HR teams, look at what’s going on or maybe they catch wind of it and somebody says it in a board meeting or something, right? And they’ll go,

“Hey, I want to do something like that too.”

And then now they’re showing others how to how to do this type of work. But I think

global business services teams are really in the in the right place to start this work.

Krishna Hari (18:41)
Cutting through the noise

where AI is delivering real provable value in order to cash today. Where is it still mostly? Earlier it was a s just a slide in the vendor’s deck. Now I think… If you can talk about this, I think that’ll be helpful.

Ian Thompson (18:57)
I think that, you know, if you look at order to cash and what they do, again, I said it earlier, but it in theory it’s a fairly simple process, but it’s not. And it doesn’t wind up being a simple process. I think what you find out, right, is that, you know, the notion that it all works itself out, there’s a lot of churn, there’s a lot of people involved, there’s a lot of commercial people involved in things that they shouldn’t be.

And really, you know, you’re at a crossroads a lot of times about where the real value of this team is, right? Of this of this string of teams, if you will. So you have your quote generators, you have your order entry team, you have your order management team, your collections team, your accounts receivable team. And you look at, you know, what that actually entails. There’s a lot of very actionable

data,

that’s in that stream of process. But it’s not always easily gotten to and it’s really crowded out by noise in the process a lot of times. And so what we wind up having to do is get really down into the weeds and spend a lot of time on very, detailed data where, I think where AI is getting, you know, very, very well-used in order to cash are in things like let’s say order management, right?

Where you have a team of people who are QA-ing things and you know, not really they’re box-checking, but they’re doing good work, right? But it’s still box-checking. It’s still like,

“Hey, does this look right?”

“Does this look right?”

“Does this look right?”

And the answer a lot of times is “Yes”, but do they make mistakes? Of course, right? Where AI really comes into play in places like this, you set the parameters, you set the guidelines.

And then now AI is coming in and agents for that matter are making decisions that a human can make. And you now can set good, clear guardrails around that. And you can also raise the level of human involvement, right? So you raise it up a few tranches to maybe your largest orders or your most you know, your your white glove customers or whoever they might be. But this is really where I think

for agentic AI in organizations and enterprises in particular, the rubber meets the road here in places like order to cash.

Krishna Hari (21:08)
Right, right. The next one is a rapid-fire round. Maybe a single line answer will suffice. What is the bigger risk to a transformation? Bad data or bad governance?

Ian Thompson (21:24)
Bad governance.

Krishna Hari (21:26)
Most overrated order to cash metric.

Ian Thompson (21:32)
DSO.

Krishna Hari (21:34)
Most underrated order to cash metric.

Ian Thompson (21:40)
Invoice cycle time.

Krishna Hari (21:44)
What is invoice cycle time? — for the audience.

Ian Thompson (21:48)
So your point of quote creation to invoice generation.

Krishna Hari (21:53)
Okay. AI in finance ops in five years. Augmented humans or autonomous agents?

Ian Thompson (22:03)
Mm, five years, I’d say autonomous agents.

Krishna Hari (22:09)
One word for the GBS function of 2030.

Ian Thompson (22:18)
Agile

Krishna Hari (22:21)
Absolutely. You killed it. Yeah. That’s nice. The good thing is, I mean, on the closing note, for the CFO or GBS leader who knows this shift is coming but does not know where to start, what’s the one move they should make before the next vendor contract or a transformation program lands on their desk? And where can people follow your work and connect with you?

Ian Thompson (22:23)
Yes.

Sure. I think CFOs need to understand what potential value your global business services organization or your shared services organization or your finance operations team, what potential value do they have to you? So what data do they sit on? How can they prove that their value can grow and can continue to enhance the business results of your organization?

Before you do another contract with a vendor, understand where those potentials are because you can get a vendor to come to the table and share in some of that risk instead of just paying for seats and having their win be their next renewal instead of sharing in the results of the company that they’re helping you succeed in. So that’s what I would recommend.

You can follow me on LinkedIn. I’m on LinkedIn. My company is called Clear Cycle Advisors. I have a newsletter. We’re approaching 1,500 subscribers. it’s called Clear Cycle Dispatch. I’m scheduled for every two week releases, but I’ve been doing it every week because things just keep coming up and I have conversations with people like you, Krishna, and and others. And, I feel excited about things that are happening in this space now. So that’s where you can catch me.

Krishna Hari (24:00)
Thank you, Ian. I just wanted to summarize at a high level. The first point is the bar has moved from being very efficient, and “Did it work?” and “Can you prove it?” to “benchmarks no longer win the budget” conversation. Demonstrable enterprise impact does, right?

Number two, attribution is a discipline that separates leaders from laggards. A clean baseline and a defensible method for isolating your contribution is a difference between proof and opinion. And it can be retrofitted after the work starts. The third one: the work starts before the contract lands. Defining success in CFO terms, setting the baseline and building measurement

in from day one is what turns the outcome shift from a threat into leverage.

I really thank Ian Thompson a very well respected person who had taken time to sit with us for this particular discussion. I hope everyone enjoyed this conversation and can take some messages from this and that will be useful

in their professional endeavor. One more thing I wanted to add is I think we are bringing such thought leaders to BizTech Pulse podcast regularly. I would welcome any suggestions, improvement you want to see in the future BizTech Pulse episodes as well.

We are listed in Spotify, Apple, iHeart, as well as in LinkedIn. We’ll be more than happy to hear from you guys, comments, if you want to see any specific topic covered in this session as well. Thank you very much, Ian. Thank you.