So What and Then What

Transcript

F: Welcome to Subject to Talent, brought to you by Allegis Global Solutions. Similar to you, we're always trying to learn more. On this podcast, we speak to talent experts around the world, covering workforce management, market trends, technology, and our foreverevolving dynamic industry.

Hello, hello. Welcome back to Subject To Talent. If you're listening on launch day, may the fourth be with you. And if you're not, I guess I just sounded a little bit silly. Today, we get to sit down with one of our very own, Jon Kesman. With more than 20 years of procurement operations, sourcing, and strategy experience, across various industries and global organizations, Jon Kesman leads our services procurement product line at Allegis Global Solutions. Jon is responsible for developing strategy, structure, and operations, whilst working to ensure that AGS's procurement solutions drive increasing and sustainable value for our clients. Additionally, having personally faced many of the challenges as a practitioner, he is now able to provide a unique perspective as a solutions provider. Welcome to the podcast Jon.

Jon, thanks for coming on today. How's it going?

J: I'm doing really well. Thanks, Frank.

F: Awesome. I'm glad to hear. Jon, the question that we like to start every podcast episode off with, how did you get into this industry?

J: Yeah, that's a great question. I think it's been a bit of a meandering road to get to where I am now, but I've been in procurement roles for the majority of my career, actually almost all of my career going back over 20 years now. And I started just as a basic buyer and started to get into the buying of what was at the time called technical subcontractors. Then I sort of evolved into other areas of procurement and sourcing. I was in the consulting side of procurement and supply chain for a while. Then I ended up coming back into sort of, I guess, steady-state procurement organizations and taking on responsibility for sort of more of the services side of things, so labor-based services in addition to contingent labor from a procurement perspective. And that's where I started to get involved with MSPs and even the self-management of contingent labor.

But that's really where at the time that I was getting into that was where sort of this industry really started evolving, and the evolution of MSPs and sort of the explosion of the market, I suppose, was starting to happen. And it just kind of dovetailed nicely, I suppose, where labor and services really started to kind of come together in the way the companies were looking at developing solutions for the acquisition of both of those things given the similar characteristics. So, it's been a procurement journey and kind of coming now to sort of the solution provider side with AGS, and looking at how we can solve for those challenges sort of with the procurement principles and the objectives of procurement in mind, but still leveraging sort of the value of the MSP and what solution providers can bring.

F: Amazing. Thanks, Jon. So, we know that before you joined AGS, you spent about 20 years in sourcing and procurement. Jon, what would you say are the challenges that procurement professionals are facing that are preventing them from being seen as strategic advisors?

J: It's a great question and I think that we see a lot of desire among our procurement sponsors and in my previous roles, there's sort of been this ongoing aspiration to be truly strategic advisors to the business. I think there's a lot of things that get in the way and we'll talk specifically about services procurement and the categories that comprise services, professional services, really labor-based services. But there's a number of studies and reports and all these things that are out there. But among the things that I think we typically see, and I've experienced personally, has to do with the complexity of the multiple categories that sit within the services portfolio. The fact that the relationships that exist between a consumer of the service and the supplier tend to be very deep and personal and very relationship-based, and it sort of hinders procurement's ability to sort of get in the middle of some of that.

There's also sort of a misalignment of business objectives in a lot of organizations where procurement is focused, in some cases, solely on cost savings, but the business may be focused on other things like growth and other objectives that they're measured to. So, procurement comes along and beats the savings drum and it often doesn't resonate with their stakeholders, who are trying to sort of go after something else. And we see that increasingly and I've experienced that firsthand many, many times. Capacity is an issue. So, trying to be strategic while balancing juggling all the day-to-day priorities can be almost impossible, particularly in this day where smaller teams are the norm and people are asked to do more, and really available talent that can do the work is also something that tends to be a challenge.

Then ultimately, which we'll talk more about, it comes down to data, and to truly be an advisor, you need to have data, you need to be informed, you need to be able to do something with that data. And while there's a lot of it out there, tend to see that it's often not very useful. So, those five or six sum up what we tend to see and what I've experienced myself.

F: Okay, so there's definitely some huge challenges there. Jon, can you tell us a little bit about your journey with data, and how you came to realize what kind of data will be useful, and what made you be able to share that with others?

J:Yeah, it's a good question. I think technology has really driven what we can do with data and clearly, the evolution of systems and different things that enable procurement as a profession, whether that's procurement suites and all the different components of those or sort of point solutions, it's sort of this huge accumulation of information. But I've been lucky, I suppose, over the last, throughout my career to see the evolution of a lot of these systems that can do so much and produce so much data. But really, it's about, you said earlier, doing something with that data. And we sort of have this phrase as, "Big data, little value," and you can have more and more of it, but if you actually don't know what to do with it, and it just becomes a dashboard report or more information that nobody really knows how to interpret, it's meaningless.

So, we're sort of in this weird spot where we have so much more available to us. It's really distilling that down and being able to do something with it. So, I went from early days in my career of very, very rudimentary reporting and super high-level stuff, to now having the ability to go much, much deeper into transaction-level detail, and using AI and other tools to extract that stuff. But it can't stop there. It has to actually then evolve into the analytics around it and then the stories that you can tell with it.

F:Okay. So, it seems like there's a huge amount of data. And is it a challenge for procurement professionals when they already have a lot of data? And then they may be realizing that they don't have the right data, and then they're trying to escalate that to senior leadership who are saying no, and they're realizing that they're on the wrong track. Can you talk about that?

J:  Yeah, I think it... I mean, that's a challenge because organizations invest tons of money in these systems and it takes sometimes years to really fully implement a full suite of tools. And most of the big systems out there are really good at spend data. That's what they're built for. That's what they do. But in my experience, I've found that all of the effort and sometimes the customization and all of the work that goes into making those systems and ultimately reports fit for purpose, can be time-consuming, expensive, drain resources, all those kinds of things. But in the end, sometimes you're left with reporting and information that's not really all that great. So, it can be very challenging because the business case is made to put in a procurement suite and then two years later, you're running reports and finding that spend data is inaccurate, and then you kind of have to figure out, how do you go back with hat in hand to ask for more money to fix it or do something different?

So, it's certainly a challenge, and a lot of those tools have certainly tons of value. It's just a matter of setting them up the right way in the first place to make sure that you can get out of them what you need to.

And it's also ensuring as a part of that overall implementation and the way that it's utilized, that the data that you put in is going to be quality so that what you pull out of it on the back end can be useful. So, I think that there's certainly a lot of kind of forethought that has to go into, where do you want to be two, three years from the start of an implementation of a system? And I would submit that it's probably not the right thing for procurement alone to think about that stuff. There needs to be lots of other people involved, and we're doing a lot of work around enhancing our business analytics skills and looking for people with a unique skillset around that, that can really understand and interpret data, and couple that with the subject matter experts that can then actually figure out, draw that map of, what do you need the data to be able to do for you?

F: Yeah, that makes sense. So, can you give us a snapshot or maybe an anecdote or something that you personally worked with? What did they look like before they were using the wrong data, and then the transformation when they use the right data?

J: Yeah. Let me give you maybe a couple of different examples because this is a journey, right? And I think there's still a lot of work that can and needs to be done around getting it right. As I said, there's a lot of systems out there that do it and do it well. But I'll give you an example of where we've done some work where, by shedding light on the right bits of data. So, for example, you take a spend report that will tell you, "We know the suppliers we're using, we know how much money is going to each supplier, we know how many purchase orders each of those suppliers had," some of that really higher-level stuff that's interesting, and it's visibility but it's not necessarily insight. And I've been in situations where we've tried to develop category strategies with that type of information, and it's a bit like shooting in the blind.

It's really not that helpful to be able to then make a difference in the business. You can look at a report and say the 80-20 rule, we've got 80% of our spend with 20% of our suppliers. That's great. Well, when it comes to services that might not actually be great. You may actually have other suppliers somewhere in the mix or a company that's just getting started out of their garage somewhere that isn't on the strategic list yet, that isn't high-performing in your organization or truly visible in your organization, that might be one of those suppliers that you want to explore more and do more business with. So, bringing that back to an example by marrying information around capable and emerging supply base, which is a completely different data set that might exist from within your internal spend reports and things like that, along with the ability to understand where the business is going from a strategy perspective.

So, this gets back to the strategic element of it, of being an advisor to the business, understanding what the business drivers are, partnering with those internal executives that can give the insight into where they're going and what those needs are, allows procurement to then be able to kind of bring all of those pieces together, marry all that up, and start to kind of create that advisory bit where they can say, "You're going this way. Maybe this is some of the pain points or challenges that you may have in getting there. Because we understand the supply base, we understand who's out there, who we're using today, and here's some of the data points that tell us why this one is good or this one is bad."

So, we've had examples and we've worked with clients where that's been very much the case. We're used to using this supplier just because. And back to what I said earlier, some of the relationships or some of just the business connections that exist there. But in this day and age, there's so much that's emerging and there's so many more opportunities out there that, with the right data, with the right performance, insight to performance of existing supply base, we've had the ability to sort of inject new sources of supply, to potentially shift away from longstanding suppliers that you're just used to doing business with, and improving performance as a result.

F: Okay, that's fantastic. I think you clearly showed how using the right data is really going to help people make that transformation and see what they couldn't see before.

J: And it's really important too because you're trying to change hearts and minds of people that are used to doing things a certain way. We all know change management is extremely difficult. Nobody wants to change just to change. And oftentimes, it's easier to just say, "Hey, I want to use that supplier because they did alright for me last time." Even if maybe they didn't, you just kind of feel like they did and it's just easier to get on with it. So, that's where procurement's challenge exists to be able to, again, bring all the data together but then turn it into the right story that can be convincing, that can create sort of that urgency to change, and be confident in doing so, so that it's not just a shot in the dark to say, "Well, let's hope this works."

F: Okay. You mentioned an interesting point there about sometimes the reluctance to change amongst procurement professionals. Is there a reluctance generally with those working in the trenches about adopting this new type of data? And if so, I know sometimes, there's reluctance to outsource part of procurement, and perhaps there's those that even see that as a risk to their career.

J: Yeah, I think, I mean, there are probably two different questions. One is the reluctance to accept the information or take the time to understand it. And I think that, I wouldn't necessarily call it a reluctance. I think it's probably just, a lot of organizations and a lot of procurement professionals don't actually really know how to consume all this data, right? We're trained in the skills that exist to do negotiations and run RFPs and learn ins and outs of complex categories. But when you start infusing the data piece of that and really doing the analytics around it, it can just be sort of a really daunting thing and really difficult for people to even know what to do. So, they often, they're not reluctant, they're just sort of like, "I don't really know how to do, I don't want to admit my deficiency, so maybe I won't pay attention to it."

So, that's where I think there's a huge opportunity to focus on, again, some of those analytic skills and supplement an organization with not quite data scientists necessarily, but people that are really good at data, and able to interpret it and know what to do with it. Which then kind of feeds into the second part of that question, which is sort of that reluctance to rely on an external party to help you with that. And whether that's outsourcing a function or a part of a function or even some point help that, come in and help me understand the data and make sense of it and figure out how to do it better. I think that increasingly, it's being recognized that organizations like ours, we're not in it to take it all and just do it all for you. We're there to supplement and add value to what's already happening.

So, we can help identify where a client has really strong skillsets and allow the capacity to be freed up so that the procurement professionals that are really good at strategy-setting or relationship-building internally or running complex RFPs and setting up preferred supply lists, those kinds of things, can be supplemented by the work that a company like AGS could do to come in, help you get your arms around the data, figure out ways to boost the data, and then turn that into the analytics that can drive all of those other things. So, I think it's certainly, there will always be some of that reluctance to change. But I think in this particular case, it's more about, just that you just don't know what you don't know, and getting some of that expert advice to help set in the right direction and then put you on a course for future success is the right way to go.

F: Yeah, and I think that's the key point that AGS and other companies like us, we're here to support them, not there to drive them in the wrong direction. So, for our listeners who are ready to look for the right data, they're thinking, "I'm not actually using the right data right now," what's the first step they should take?

J:Yeah, so, we've been spending a lot of time kind of shifting the focus of our procurement solutions to really using the insight to enable better decisions. And what that really means is, we've kind of dialed in on this concept of "so what? And then what?" So, when you look at your data, it shouldn't be data, like I said earlier, I can give you a bunch of great graphs and reports, but if I can't really articulate a story behind that, or actually drive that to decisions that need to be made within the business to make greater impact, add more value, whatever those metrics are that you're trying to achieve, it's data just for data's sake.

So, we focus on sort of this concept of "so what? And then what?" And when people are thinking about their data and what they do with it, the challenge that I would put out there is, if you can answer this question of, you get a report. Okay, well, so what? What is it telling me? And it gets then to the "then what, what can I do with it?" So, you kind of start interrogating the data and yourself to be able to get to that point where you can answer some of these questions. That's how we feel organizations need to be looking at the data. So, to take that to an example, you get a spend report that tells you, within a sub category of spend, you got 200 suppliers, and here's the volume with each of those suppliers and "well, so what?" That's just a nice graph. It's a nice report. What decisions does it drive? Do you have enough information within that to then do something with it?

And if the answer is no, you need to keep asking yourself, "So what? So what?" Okay, well, what can I do with that to take it down a layer? Can I get more insight into each of those suppliers and what makes up their aggregate spend? Okay, if I have that, well then, what does that do for me? And until you can really get to the "then what," we feel there's more work to be done. And some of that is inherent in some of the existing systems that they have in the way that they're configured and the way they're utilized. But some of it might also need to be some supplementary things that get introduced into there, whether it's additional technology, a different way that they process the information.

Take for example, a statement of work. So, a lot of organizations will have lots and lots of statements of work, and there's a lot of time and effort that goes into developing those. And they can be hundreds of pages long, in some cases. But what often gets captured from that SOW is really the supplier of the total amount, maybe some high-level metrics or dates or whatever. But then it sort of goes in a filing system or in a contract management system, and you don't really have the details that exist in all of that structure.

So, it's a great example to point out what you could do to get to the "then what" is, you start unpeeling and uncovering what exists in that SOW from a data perspective, and you start turning that unstructured data into structured data. It starts to then drive the "then what?" So, once you know dates that they were supposed to hit per the SOW, did they hit them? Resources that were on that, how much time did they spend on it? And you start to get a lot more informed around delivery, setup, did you actually get what you contracted for? Did you pay what you thought you were going to pay? All of those different pieces that allow you to then really understand the construct, not only of that deal, but in aggregate, all of the deals to then start to get to the "then what?" based on performance and based on those kinds of things.

F: That's a great point about the SOWs. I think that's an important place for organizations to dig in. Can you give us an example of when a company didn't have enough data or the right data and what that looks like? And then conversely, when they did get the right data, how was that different?

J: Yeah, I sort of alluded to it but maybe didn't go deep enough earlier. So, I'll start with the bad and we'll end on the good. So, this was a firsthand experience where we were responsible for developing some category strategies and ultimately, presenting that in aggregate to our CFO. We were looking at the entire services portfolio of spend, and we were using the data that was available to us out of our spend management systems.

And what we found was that, again, to the earlier point we made, there was a lot of investment put into this system and all this configuration and maintenance and all those kinds of things. But what we found was that when we ran some of these reports, it was telling us here's the spend by subcategory: legal, HR, benefits, all of these different things. And we were making some very broad assumptions and relying on that data to say, "Okay, this is what's in this category and now, let's apply some category knowledge," to say, "We feel there are certain savings percentages attributed to each of those, as we start to develop our financial targets for next year, and ultimately the strategy to achieve those. We were relying on that."

And what ended up happening and I'll make the long story short was, as we started to go through that with the executive team that actually knew more about what was happening in those categories. So, for example, the head of legal, who had a very good handle on what was happening in the legal space, we would go in and say, "Well, there's $50 million of spend here in legal. We feel that we could save acts based on these strategies. So, next year, savings objective and target for that will be Y." And what it turned out was that a huge portion of that spend was for some litigation that was over, and that spend would not be carrying through to the next year. So, we ended up finding ourselves thinking we had 50 million of spend and next year it was going to maybe be 20. So, you start kind of making assumptions on historical data without being able to look forward and understanding, again, more about the business strategy and what's happening.

And that list kind of goes on and on. A big chunk of the spend in HR was actually benefits and it was premiums that we paid on behalf of our employees. So, you can't really impact that in these kinds of things that, without the deeper level of data, you draw some very bad assumptions, and that fortunately, we were able to... We sort of looked a little bit foolish because we didn't have all of the information and made some really ambitious assumptions and goals of what we could do moving forward, only to be sort of beat down and said, "Well, that's actually not the case." But that's a good point around where, if you don't have all the data or if it exists somewhere but you're not pulling it together in a consistent and consolidated way to really gain that insight, you can really go off the rails and you can make some really poor assumptions and ultimately, set bad targets that you'll never be able to achieve.

So, that's sort of the bad. A good example, this happens actually frequently in some of the work that we do, where we look at the details of services as particularly on statements of work. And when we understand the way that many organizations will use statements of work to misclassify labor. So, they may have a staff OG MSP program, internal or external, and people go around that program and put labor on SOWS, either because it's the supplier that they want to use or they want to avoid the controlled process, whatever it might be. When you're actually able to go in and start pulling out the details in that SOW that identify the characteristics of the SOW, that would indicate it's actually more staff augmentation.

And then you're able to take that information, pair it with a roll and rate data that exists either in the market or through an existing MSP program. You start to generate potential savings delivery, and what could be a very big opportunity to mitigate risk, save money, and set a better course for how to buy in the future. So, that's a very real thing that happens. A lot of organizations look at that, and we have had a lot of success in helping uncover that, by pulling different data points from the details of the contracts, the SOWs, and then pairing that with other available data, to be able to generate really strong business cases for making some change.

F: Amazing. Thanks, Jon. Okay, so we've run out of time on this episode, but if you are interested in learning more, there's a great blog post that Jon has written in staffing industry analysts. There'll be a link to that post in the show notes. Jon, I want to thank you for your time today. Personally, it's been a great learning experience for me, so I'm sure that our listeners will find it valuable too. Thank you.

J: So, this was great. I just wanted to mention if any of this resonates with our listeners, if you're facing some of these challenges or have questions about how data can help drive decisions within your organization, we'd love to have a chance to talk to you. So, reach out to us, check out our website, lots of other information out there. In addition, would love to have the chance to talk to you further about that. So, thank you very much.

F: I hope you enjoyed the episode today. Thank you to Jon for sitting down with us and giving more insights to service procurement. If you would like to learn more about our procurement efforts, please check us out at AllegisGlobalSolutions.com. If you have any questions for us or Jon, please feel free to tweet @AllegisGlobal with the #SubjecttoTalent. You can also email us SubjectToTalent@AllegisGlobalSolutions.com. If you enjoyed our podcast today, please subscribe, rate, and leave a review. Until next time. Cheers.