EP 014: Provider of the Week: Sievo W/ Sammeli Sammalkorpi

0:15Sammeli Sammalkorpi: Welcome to this episode of Art of Procurement's Provider of the Week series. I'm your host, Jothy Hartley. These conversations shine a light on the established technology providers who are shaping, scaling and continuously evolving the digital procurement ecosystem. In just 20 minutes, we explore each organization's product strategy, market impact and the ways they help procurement teams solve real business challenges. Our provider and startup of the week episodes are the only formats at Art of Procurement that focus specifically on a company's product. And today we are featuring Siavo. Siavo provides actionable procurement analytics.

1:00Sammeli Sammalkorpi: They empower procurement finance, IT and sustainability teams to overcome their data chaos and capture all insights, drive bottom line savings, improve ESG performance and streamline budgeting and forecasting. By processing the spend data equivalent to over 2 % of the world's GDP annually, Cievo enables fast, informed decision-making and delivers high data quality with end-to-end data accountability. To tell us more about Cievo, I'm delighted to welcome Sam Samokopi, their co-founder and CEO and returning friend of the show. Over the past 20 plus years, he has helped grow Ciavo from a finished startup into a leading procurement analytics partner for Fortune 1000 procurement teams.

1:55Sammeli Sammalkorpi: Sam is a recognized voice in the procurement technology industry and a strong advocate for how data-driven procurement can create measurable business impact. He firmly believes that Cievo can succeed only by measuring its customers are successful and satisfied. Thank you, Sam, for joining me today as our Provider of the Week. Great to be here and thanks for having me. Exciting times, exciting topic. Very much so. Thank you, Sam. All right, let's dive in and get to know you a little bit better. um so in terms of your company and for anyone who may not be familiar with you what does Ciavo do today and how has your solution evolved over time thanks so basically as you already stated procurement analytics for for enterprises what we do so we basically help enterprises turn their dirty procurement data into insight actions and eventually business value be that cost reductions or be that sustainability resilience um kind of financial working capital improvements in in some ways we've been now in the business more than 20 years and in some ways the core of helping the enterprise with procurement data has remained quite stable but what it actually means that has evolved over time substantially so we pretty much started with spend analytics capturing purchase orders invoices classifying spend normalizing suppliers and basically creating traditional who you spend with in which categories where the opportunities are and that that was the foundation and still very much the core of our opening but obviously there's been multiple layers that we built on top of that perhaps the second edition if you may was around okay it's not only about spend and savings only it's about risk it's about sustainability it's about carbon and and do kind of cover the wider mandate of procurement from analytics point of view you obviously need to have new kind of data sets often coming from third-party providers or from public sources so at that stage we said okay we not only help these enterprises clean their data for savings insights but we actually are combine and bring all the external data to save the white procurement mandate so that was the edition two of CMO now the the current edition is very much around then okay yes we have all that data but we are not only providing dashboards or reports for humans but we actually actively analyze the data and provide a constant feed of insights to our users as a category manager here there's a working capital opportunity as a as a kind of supplier relationship manager there's a risk with this specific supplier and we are doing this not only based on internal external data but as you mentioned we process two percent of global gdp every year and with most of our customers we have this agreement that we can create there is a benchmark products out of their data so we can not only show this is how much you spend in certain category but we can also kind of reveal also and actually you spending more than your peers in same industry in same region for this kind of category so it's a constant feed of insights that we provide to our customers that's a kind of current edition now what we are very much building towards is that more and more the future procurement is human agent collaboration and there's going to be more and more agents that will do procurement sourcing on behalf of us humans.

5:18But for these agents to be reliable, they need high quality, reliable data. And we see that our role in the future is very much providing this data feed for humans, but also for these authentic AI users to drive procurement value.

5:32Sammeli Sammalkorpi: That's really interesting. I mean, I think back to my time as a practitioner, which wasn't that long ago. And I think it's a perennial challenge that data needs to be clean. And that's just for human consumption. And now you're talking about it from an agentic AI or even a bot consumption. I'd like to know a little bit more about how you see the areas of differentiation are between what you provide and what other solution or data solution providers can offer in the current market. And how does that data look different from your perspective? If I think of our differentiation, it really boils down to three components.

6:22The first component is just kind of building this enterprise-scale procurement data infrastructure. It's not trivial. Yes, you can take Claude and throw 1 ,000 items for classification, but when you think about building this data foundation, it is actually quite complex. And we've been building that for 20 years for these large enterprises. So that's definitely one differentiating competence that we have. Then at the same time, we also have this community data, 2 % of global GDP, out of which we can create benchmarks, price trends, opportunities. So suddenly we become this data provider as well.

7:00And this is obviously a very unique data set. I claim that on indirect, there's two such data sets in the world, us and Coupa. On the direct side, we are the only provider of such data set. So this data is the second component. But then the third component really is data is not valuable. It is the actions that we can generate together with our customers and their procurement decision makers. And we have the 20 years of understanding what actions actually drive value in different categories, situations and a lot of that sort of business logic procurement specific business logic is embedded into our solution so it's not only providing the clean data but actually providing the intelligence and the recommendations what should i do now in this condition in my situation with my data

7:42Sammeli Sammalkorpi: to drive procurement value so you're talking about um turning data into insights and helping and supporting with decision making which i guess accelerates um the point to at which people get to a decision-making point and reduces the time that people take. So, yeah, that's a gain. Yeah, there's two gains. There's the efficiency gain, and part of that is indeed we help humans need to use less time to make decisions, and there's a lot of value to be unlocked there. But actually, I do believe that in the next five years, and we are seeing it with the first customers of us already, in the next five years and even shorter, most of the new procurement value is not so much around doing same stuff more effectively, but it's using this cleansed data.

8:33It's using the agentic AI to do sourcing and procurement in the long tail, which this far has been unattainable. The value cost business case hasn't been there. But now with the great data that Cievo can provide and agentic AI, the cost of driving those execution of the long tail is going down. So that's where you can capture value. So I believe it's less about kind of making humans more effective. It's more about attacking the long tail in completely automated fashion. Okay.

9:05Sammeli Sammalkorpi: Yep. That makes sense. Thank you. I'm curious to know how has it from your from what you see is how have your customers how's their demand changed in the last few years? And how is that influencing your direction of travel and how you create your roadmap? Right now, we are living very interesting times. At some fundamental level, I would say, not until last year, but over the last 10 years, I do believe the procurement mandate has gone from, let's say, savings for CFO into much wider mandate. And that's been a kind of transition that I've been happy to follow, that it's kind of more nuanced, more complex, more challenging the ask that procurement is facing.

9:53so that has changed from the separate current use case uh point of view then at the same time i think right now we are living through the ai disruption obviously and i do believe it's the biggest transformation in in my career and your career and procurement career and and and with that of course of the expectation level of the procurement is is is raising up what today's stuff that was not possible a year ago that felt like science fiction three years ago is something that we can create our customers as of today so the expectation level and rightly so is is heightening okay okay

10:31Sammeli Sammalkorpi: and and what um what enhancements that have developed more recently or capabilities are you are you particularly excited about i think it's it's well first of all ai can do a lot of work in data cleansing classification data and we are applying all of that but that's not the the key source of excitement the key source of excitement for me is that like our customers have this valuable data set cleansed by cf this far the value of that they can actually extract out of the data has been constrained by human beings going into dashboards and figuring things out so it's like huge value of data but the consumption was very throttled in some ways but now with the new AI tools, we can connect Claw to CLAVO and suddenly users can much more effectively get value out of the data.

11:24And also we have integrations where CLAVO data is kind of integrated, for example, with the negobots. And suddenly the negobots can do the negotiation instead of CLAVO. So suddenly we see completely new ways of interacting with data and benefiting from the data beyond humans using analytics dashboards. That's quite exciting. It is.

11:44Sammeli Sammalkorpi: On the flip side then, so what is the capability or feature within Cavo that your long-standing customers talk to you about and they say, this is the one thing that, please don't switch this off. They rely so much on, even if it's not the flashiest one. What is that? I think there's a great question to ask because, of course, it's nice to speak about the flashy stuff. But I think if I listen to our customers, but also if I look at the usage statistics of the software, it all boils down to this kind of self-service reporting where users can very flexibly analyze the spend data and savings data and carbon data from multiple different perspectives.

12:23And I think we've sort of put tens of years of design work, how to make that very effective. And we see the results. Users love it. And also, as a business professional, I'm using a lot of different kind of analytics tools in-house otherwise. And I always, of course, have the lens, how does this compare to our own analytics and what can we learn? And I strongly believe, and our customers would agree, CIO analytics self-service reporting, that's the best piece of analytics UI ever made available to humankind. Okay.

12:59Sammeli Sammalkorpi: Talking of use cases, are there any new or unexpected use cases that your customers are coming to you with or from leading procurement teams? What surprised you recently? I think sort of what is the sort of new frontier we keep exploring at all times and that opens up a lot of, let's say, great use cases is the capability to combine structured data analytics with unstructured data analytics. Traditionally, procurement analytics has been all about structured data because that's the only thing software could process at scale. But now suddenly with large language models, software can process all the unstructured data, the contracts, the invoices, the material specification and so forth.

13:47And I had this discussion with one of the CPOs and I think here a great, great sort of use case around, OK, my procurement teams use years and years of negotiating these contract terms with suppliers where we agree on certain terms. and we use a lot of let's say time energy on that and of course our suppliers hate us because we force all of these clauses but then he was asking the question do we ever enforce these clauses so are we actually getting any value of all of this negotiation work can we go through all the unstructured data and see we've negotiated whatever liabilities for the last 20 years but we never enforce them and if that's the case either you should stop negotiating them in the first place, I've loaded the supplier, or then you would start, let's say, imposing it.

14:36That was a light movement for me.

14:39Sammeli Sammalkorpi: Ah, so you could embed some hard truth then into your feed into your product going forward. That's interesting. You mentioned earlier on some about efficiency gains, and other benefits for a procurement team or business, if we can talk a little bit about how your customers can track roi how can they justify the business case for for implementing you in the first place and i guess crucially i know the key the key connector here is connecting procurement's work to the broader business goals how do you help them track that and connect Great question. And to answer the first part of the question first, so obviously sort of the the role of procurement analytics or the business case of procurement analytics is very much around we help customers to identify and execute savings opportunities, cost reduction opportunities, which are easy to measure.

15:40But then obviously we help identify risk positions and so forth, which are more difficult to quantify. So when we build the business case, we typically build it, let's say on the hard benefits kind of the cost reductions and then we just state that there's let's say other more soft or harder to quantify benefits as well going to kind of the the hard benefits of cost reductions I think we are in a happy position that our customers they have billions or tens of billions of spend and if we are able to help them to identify just one more percent of cost reduction and execute that as well that means tens of millions of of of of euros those.

16:14Actually, we did a study by Hackett or Hackett did a study assessing our customers benefits and they figured out that the ROI for CFO implementation is 63 fold. So 63 fold ROI. And I feel that sort of probably should increase the prices and this being the case, but the benefit is very concrete. Then to your second part of the question around how to connect sort of the procurement with the, let's say, wider business value. I love the question because I it's been one of my missions over the last 20 years is that we should get procurement out of this category savings box because category savings that's a link only procurement understands nobody else cares about procurement categories and even the way procurement typically measures savings it's not related to p l directly so what we are trying to help our customers do is link the you need to measure category savings that's not the point the point is that you need to also be able to translate that to business language which quite often means in cost case what is the profitability impact that that this commodity change has on your end products or it is about okay i have a problem with supplier that may be a non-issue for for business but if i can point out that there's 500 million dollars of revenue at risk because of this supplier again i've translated the procurement challenge in the business language.

17:36And that's also a data challenge because for large enterprise, you have tens of thousands of procurement SKUs, you have thousands of end product SKUs, you have multiple plans. How do you create this data lineage from commodities to cost structures to procured categories to build-up materials to end products? And there's a lot of complexity, which, of course, we want to help our clients with.

18:00Sammeli Sammalkorpi: I think you've hit the nail on the head there by talking about sticking to the business language and keeping things quite simple um this is a complicated topic and i think we we don't help ourselves sometimes as procurement folk um with with that yeah that that does make sense if i can um pivot now talk a little bit about how your solution integrates with a procurement team's existing procurement ecosystem um and think and solutions that teams already work with. How does your solution, how does your product integrate? And second part to this question, what advice would you give an organization who is about to implement your solution or thinking about it?

18:45Sammeli Sammalkorpi: How do they get the smoothest outcome? So first of all, our strategy has always been focusing on procurement analytics. It's kind of a niche strategy, which means that our humble role is be a valuable part of, let's say, our customer's procurement tech landscape or procurement system. On a more practical level, there's sort of two kind of integrations. As analytics provider, obviously, we want to tap into all data sources that our customer has, the ERPs, the procurement systems, the external data fees around sustainability, carbon, market prices, da da da so bringing all the external data or internal data in and then we bring our own data assets on top of that so we kind of integrate from all different data sources and the reality is that if you are an enterprise you will always have your procurement data in multiple assets even if you support one sap say you will have category specific solutions you will have external data fees and so forth so so you have this data combination challenge and that's that's the first role of able to bring all of this information together be the information hub but then we also play a second role and increasingly so now that we provide these insights or recommendations you should do xyz with this supplier or you should source this category because the material prices are going down or whatever we are creating connectivity back to operational systems so that we provide the recommendation user accepts this still today user is in the loop user accepts that but then the execution is in the operational system so we want to think ourselves as the procurement brain and then the execution the hands and legs are the operational system so so that that that's how we see ourselves then you had a second part of the question that i already forgot it's okay i can repeat it that's not a problem at all it's uh what advice would you give an organization that's thinking about implementing a solution like yours um to get the smoothest outcome if either implementation or if they're looking to expand um into your platform i think there's two parts it's going to be let's say a roadmap you need to first kind of get the spend in place then you bring other data formats then you bring bring let's say the forecasting then you connect operational systems so so think it's kind of let's create the value quick and then build on top of that so i think that's my my first advice then my second advice is that sometimes i hear it is okay but we need to clean the data into erps first before we are ready all enterprises have multiple sources of dirty procurement data and and and you shouldn't let that stop you from benefiting from that data and i think there's also kind of positive feedback loop if you take your dirty data you create analytics on top of that then the data actually gets valuable and it gets used and when data gets used then people want to improve the data and you get the feedback loop to better data and that's how you get the data quality loop also going forward yeah i think from from my own experience i think you've got to start somewhere and even if you start small it's that crawl walk run approach i suppose even if even if it's a small set of data that um you can clean up in one instance of your erp at least you've got something and then you can replicate that across across the platforms.

22:03Just yeah, and I don't know that what we also recommend is that let's create very tangible, concrete business results very fast. And that just helps build the momentum. So so if you run, for example, proof of concept product for our customer, we don't call them proof of concepts anymore. We call them proof of value. And what I want our team to deliver after three weeks is not this is how dashboard works, But this is the prioritized list of opportunities worth 57 million USDs or whatever that you can act today.

22:34Sammeli Sammalkorpi: I like that. Proof of value. So on that, then, if somebody who's listening to this is thinking about contacting you, has been thinking about doing something in your space, how would they know that you are the right fit for them? And how do they go about getting started with you? my first advice speak with our customers sort of the the references are cf.com website and that you know somebody in your network that's our customer so don't believe me believe our customers i think that's that's that's that's the first call but then also of course super happy so just dm me on the linkedin go to our web pages we definitely are super responsive and happy to happy to explore okay and just as we're wrapping up here i've got uh one sort of i guess one major final question for you Sam and that is what should customers expect next from Ciavo what's on your roadmap what are you excited about delivering no I think sort of the the direction of travel for us and for our customers is that yes we want to continue helping humans make better decisions more informed decisions but it's definitely going more and more to direction we want to be the procurement brain that automates all of the decision making and and just tackling the the long tail in more automated way i think that's a great opportunity to deliver procurement value going forward excellent the procurement brain i like that thank you sam well thank you for this opportunity to learn more about sievo's impact and unique value proposition and thank you to everyone who joined us to learn more thank you sam and thank you take care everybody thanks for listening to this episode of ProcureTech Insider.

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