I’m joined today on the Procuretech Podcast by Sammeli Sammalkorpi, CEO of Sievo, one of the stalwarts of the spend analytics space. The well-known Finnish company were actually founded almost 19 years ago!
During this time, what started out as a simple spend analysis tool has grown to be a comprehensive best-of-breed solution for spend analytics. We discuss how this niche has matured over the years and what direction it’s headed in the future.
Spend Analytics: Maintaining relevance and continuously improving in a crowded market
Sammeli starts off by explaining how being from Lapland, his parents’ wish was always that he would become a reindeer farmer!
Instead, he landed into software development rather than staying in his hometown. This came about through starting out as a junior analyst in a procurement consulting firm and realising quickly that there weren’t any tools out there to efficiently analyse and report on what a client’s business is spending its money on.
In a crowded marketplace, Sammeli puts Sievo’s success down to staying on top of the latest technological trends as well as listening to and striving to satisfy their global, enterprise level client base.
Machine learning and AI is developing and evolving quickly. New technologies and more and more data is available. They have seen many well-funded competitors enter the market, and some of them fail. Even though Sievo have never received any VC money, they have gradually grown to 220 employees in their two bases in Helsinki and Chicago.
How has Sievo grown despite the onslaught of competitors?
There are 3 factors Sammeli gives as the main drivers behind their continued success:
- Procurement leaders who change companies and then lobby to introduce Sievo’s software in their new company because they have seen the value first hand.
- The data they have been able to gather and, with their clients’ permission, use it to provide benefits and insights to their whole client base to improve analytics and predictive trends. Big data enables the classification process to be more efficient and accurate, due to the learnings and previous spend which has been analysed and classified through the system. The most obvious example of this is the ability to recognise duplicate vendors e.g. IBM, I.B.M. and International Business Machines as being the same organisation
- Scale: being able to invest more into software development and marketing & sales as they have become a bigger company than most of their competitors.
Leveraging their data assets to add to the CX
Drilling down on this piece, Sammeli mentions three areas where they have been ableto improve customer experience through aggregating data:
- Incorporating client modification or customisation requests into the general product offering to bolster the capabilities of the tool.
- The aggregate intelligence gained from each spend classification / normalisation of supplier data to be able to have an ever-growing database of parent and child companies in the supply base.
- The ability to use this data lake to drive benefits across their whole client base through upgrades, feedback, insights and market intelligence.
Are new acquisitions coming from customers ditching the suites or greenfield digitisation projects?
Most of their clients typically have had some kind of approach to spend analytics in the past. There doesn’t seem to be a distinct split of whether that’s from an underwhelming experience with one of the major suites, or having tried to natively use a tool such as BI or Tableau in-house without seeing the anticipated success.
There is a growing acceptance that even those companies who are running suites still need to aggregate their data in one place for a single source of truth, at least for large, enterprise level companies. The assumption of a few years ago that a suite could fulfill all of a corporation’s digital procurement needs is now pretty much acknowledged to simply not be accurate. This will become even more pronounced as the technology ecosystem, capabilities and reach of procuretech grows and expands.
Going from descriptive to predictive analytics
The world is becoming more complex and volatile, as we have seen from COVID and the Suez Canal supply chain crisis. A procurement function will never be able to predict ALL of these events, but being prepared for them and being able to figure out the consequences from such an event quickly and efficiently is key.
Predictive analytics enables a procurement professional to be able to enact and implement a plan B much faster than an organisation that doesn’t have this capability.
We discuss the “if-this-then-that” ability to take spend analytics data in tandem with any other best-of-breed risk management technology to be able to visualise potential scenarios and solutions to them before they actually happen.
Procurement’s journey from savings delivery to value driver
We discuss the trend of how procurement is shifting from a cost reduction department, to be seen as a function that can drive wider value. This is also affecting relationships with Finance, with the acknowledgement that value and cost avoidance can’t be measured as objectively as P&L-visible hard savings. Sammeli describes it as being “unhealthy” that there is only one rule from Finance around how savings are reported.
Transitioning from “talk” to “action” on ESG topics
Building on existing collaborations with risk management, supplier diversity and sustainability providers, Sievo has also just launched a new solution based on CO2 analytics. This acknowledges that companies who are seeking to become CO2 neutral must spend time and resources into understanding the carbon footprint of their supply chain because that’s where most of their opportunity is hidden.