While the doctor has never covered Sievo on Sourcing Innovation, he did cover them in depth at Spend Matters, and, if you have appropriate Content Hub access, you can find the last 3-Part in-depth Vendor analysis here in Part I, Part II, and Part III.

A Quick Recap

Sievo was founded twenty years ago in 2003 in Helsinki, Finland and is probably the oldest remaining standalone spend analytics player, as a significant portion of all of the M&A that occurred in the 2010s was on leading spend analytics players. (The next oldest standalone vendor is likely Rosslyn Analytics founded in 2007.) While it started as a standard service-based spend analytics offering, by the time of the doctor‘s in-depth update on Spend Matters in 2020, Sievo had moved well beyond basic spend analysis and centered much of its value proposition on driving savings and improvement (as Sievo is not just limited to spend data and can also process compliance, risk, and ESG/GHG/Carbon data, for example) program identification (through automated insights), measurement and management across the full spectrum of spend, where they do the data management services, the foundations for savings and improvement program management, and even the meta-data management to power advanced organizational initiatives.

With regards to data management, it handles all of the system integrations; refreshes on your schedule; does all the classification (working with your team to build the classification you want); cleanses, normalizes, and enriches your data; and rolls out (customized) market and category intelligence to your organization.

With regards to classification, they use a mix of (black-box) AI and human (re-)classification and review, guaranteeing 94% accuracy, and usually achieving 98% to 99% accuracy. They use multiple techniques including customized in-house LLMs, DeBERTa Large v3, BERT, evolutionary algorithms, and NER models, with and without feedback. (And while the doctor knows most of you won’t understand any part of that sentence, it means their AI/ML team actually knows what they are doing and they are not just a bunch of college drop outs randomly feeding open models with random data and assuming anything that appears to give them 90% accuracy is good. Which happens quite a bit in “data science” consulting shops. See the doctor‘s post about how to do Analytics and AI Right.) Mappings, especially for low confidence, high spend, and new categories/customers are also manually reviewed on a regular basis, corrected, and the models retrained. In addition, a user can request a reclassification at any time, and once a customer admin approves, the data is reclassified (in an override) and the model retrained.

With regards to integration/refresh, they’ve integrated with over 100 ERP/AP/data systems and dozens upon dozens of market, risk, and ESG feeds that they can use to enhance your data and typically refreshes massive data sets daily (but can do faster or slower depending on the desires of the organization).

With regards to traditional analytics, the platform has the standard set of modern drill down dashboards, support for user-defined calculated/derived dimensions, and incredibly powerful filters that support functions that can be used on any dimension (base or derived) which collectively allow a user to break out, and drill into, any subset of data of interest.

With regards to out-of-the-box reporting and analytics, Sievo has over two-dozen out-of-the-box dashboards that provide deep insight into spend by category, PO, invoice, supplier, emission, cycle time, tail, geography, etc. There’s also pre-built insight dashboards for savings opportunities on price (variance), payment terms, currency exchange, and efficiency/cycle-time improvement.

With regards to savings tracking and management, Sievo includes a realized savings dashboard that can automatically compute the spend difference period-over-period, currency fluctuations, and changes due to changes in market indices (where a contract price is tied to a market index). It provides insight into spend that results from non-performance and allows Procurement to pinpoint the exact reason for deviation from a plan. Note that savings tracking is very extensive in the platform and users can define budgets, demands, expected trends, milestones, approvals, etc. and track each initiative as a separate project in the platform.

It also supports forecasting/budgeting, contract metadata management, and price benchmarking based on over $1 Trillion of customer spend (and their customers now represent 1% of global GDP) mapped to a common internal schema and with their deep knowledge of direct material pricing (from indexes, etc.), they can help customers benchmark down to the material level in a BoM.

So What’s New? (Since 2020.)

Since 2020, Sievo has made a number of platform improvements and included a number of new offerings in the spend analysis platform. The most notable of which are the following:

Integrated Actions

In addition to supporting (savings) action plan, some associated actions can now be initiated within the system (with more being added with every release). Email contacts relative to supplier performance / sustainability can be initiated with the system, automated negotiations through Pactum can be kicked off within the system, and Ecovadis requests (detailed below) can be kicked off within the system. A user can also access the Sievo Academy, Sievo Support, reclassification requests, associated contracts (not just metadata), and roadmap suggestions/product feedback directly through the platform.

Integrated Sustainability and Third Party Dashboards

When we last covered Sievo, it had an Ecovadis integration and could pull in select data for enrichment dimensions or measures, but, if you have the subscription, they now maintain all Ecovadis data natively in their platform and have a new Sustainability dashboard where a user can dive into the different Ecovadis scores (Global, Labor, Ethics, Environment, and Sustainable Procurement) by category, material, supplier, etc. and see the global score, assessed suppliers (as not all suppliers will be assessed by Ecovadis), assessed suppliers, score by top 100, score by category, score by organization, global score heatmap, etc. A user can drill down to an individual supplier (by category and material) and see all of the Ecovadis details natively in Sievo. If a supplier has not been evaluated and the organization would like it evaluated, they can even initiate a request directly in the Sievo platform. (Alternatively, if you have other sustainability/risk data feed licences, including [but not limited to] SupplierIO, RiskMethods, D&B, etc.] all of that data can now be brought in and maintained natively as well.)

CO2 Analytics

There’s also a new set of CO2 Scope 3 Emission management dashboards that can, at a category, material, and/or supplier level, summarize total CO2(-equivalent) emissions, related spend, intensity, carbon price amount, with breakdowns by category, GHG protocol category, organization, region, supplier country, share of emissions per higher level category/supplier, etc. A user can dive in and see the Unit of Measure (UoM) conversion rates, inflation rates, mapping quality, and types of estimates used at the meta-leval and the mapping source, emissions factor, validity dates, and associated backup (attachments, etc.) at the mapping level.

One unique feature of the Sievo platform is that the CO2 can be used as a second currency alongside spend and allow users to see the spend/carbon trade off of different decisions. (For example, switching to supplier S for Product P can save D Dollars but cost X emissions.)

Curated Data, including Science-Based Target Initiative (SBTI), Support

Sievo has not only started tracking supplier ESG and net-zero status data, but also correlates an organization’s spend against SBTI records and summarizes percentage of spend with SBTI suppliers (who have set a target), percentage of spend with SBTI suppliers with near-term targets, total spend with net-zero targets, and percentage of de-listed suppliers as well as spend by top 100 suppliers and net-zero status, spend by category and net-zero status, and spend by organization and net-zero status. It’s a great way to see SBTI spend coverage at a glance.

At a finer grained level, for each supplier, it summarizes the supplier’s general status, number of commitments, number of targets, net zero status & target year if committed, near term target status (targets set or not), long term target status, company temperature alignment, spend, sector, org type, region, location(s), etc. and all data can be accessed by a drill in to the supplier level.

AI-Extended Supplier Profiles with Feedback and Human Validation Available

In addition to spend benchmarks powered by community intelligence on well over One Trillion Dollars of spend mapped to a common, centralized, taxonomy, they have also been building a common supplier database which currently consists of over 6 M suppliers (with the goal of 10M by EoY 2024) with enhanced supplier profile data around geography, categories and materials, CO2/GHG and sustainability, SBTI, and other relevant data from a spend analysis perspective. In addition, they have been augmenting it using customized AI/NLP/LLM that uses web-based data (from the supplier’s web site, Wikipedia, supplier intelligence platforms, etc.) to provide a more complete picture in order to provide clients with deep embedded supplier insights, which will eventually support deep discovery in a future release.

Sievo manually validates a subset of high-spend suppliers for every client and every user can provide feedback on supplier data they feel is incorrect and request validation on a supplier if desired. Suppliers whose profiles have been manually validated are marked as verified (and data is not changed without human verification if such data comes from a data feed where the provider, such as Ecovadis, has manually verified the data).

Extended Supplier 360 Dashboard and CraftBoards

The dashboard summarizes total spend (for the given time range), it’s spend rank, PO coverage, avg invoice, spend share by category, by organization, by ERP supplier (instance/subsidiary), by payment terms, invoice-to-due days, due-to-pay days, [local] price [consolidation] opportunities, price opportunities vs. best price from a different supplier, top insights (from the new insights dashboard, discussed below), and, if desired, key metrics from the new SBTI dashboard (summarized above).

Since our last update, Sievo has also added CraftBoards, which allows users to build their own dashboards on any data subsets they like. Sievo can process and display any type of data, and the user can build cubes and dashboards on any data source they like.

Adaptive Insight Recommendation Engine

Sievo has doubled down on identifying all types of savings opportunities across price (variance), payment terms, process optimization, risk and compliance, and the (supplier) tail. Sievo has also doubled down on a new insights overview dashboard that currently summarizes system-identified opportunities across almost twenty (20) types of analysis across those five categories (with more coming in future releases). With regards to price optimization, it will summarize price (variance) opportunity and high price impact. With regards to payment terms, the outlier opportunity, the early payment impact, and overall consolidation opportunity as well as (interest/penalty) losses due to critically late spend. With regards to process, it summarizes order consolidation spend, hidden tail spend, non-PO outlier spend, and after-the-fact spend that is likely ripe with opportunity. With regards to risk and compliance, FX exposed spend, outlier sustainability spend, single sourced material spend, and hidden locally sourced high risk spend. Finally, with respect to the tail, they break it down by category, material, new supplier, new supplier non-PO, and supplier count increase which is super rife with opportunity. It’s super easy to drill into each dashboard metric, see the breakdown by supplier, category, or location, and quickly identify the top opportunities for savings. And, of course, dive into the suppliers with the highest opportunities as the Sievo platform was designed to automatically bubble up insights from the data in a manner that is relevant and actionable.

For each area, there’s also an insight dashboard that summarizes the total number of insights identified, and the breakdown by open, assigned, completed, and removed. One major difference in their platform is that a human user can identify when an insight is immaterial or non-actionable and the system will not only hide it, but learn from the feedback, and not show the insight again. For example, a payment term rationalization across a supplier’s location will not be possible if the average payment term is longer than legally allowed in France or the UK (as a result of recent laws designed to ensure [small] suppliers are paid timely). Note that insights can be assigned for action to a user and, once assigned, generates an action plan in the Sievo system.

The individual opportunity dashboards are incredibly detailed, and you can see prior coverage or a Sievo demo for details. For example, the payment terms consolidation dashboard, which allows you to dive into a category (as most contracts are category based), allows you to pick a supplier, see the supplier spend and summary, spend by payment terms, spend development opportunities by payment terms, totals by ERP supplier instance, best payment terms, overall working capital opportunity by ERP supplier, etc. etc. etc.

New Widget-Based Insights-Oriented Home Page

The main dashboard can summarize the top insights (as per the insights discussed above) across each area analyzed by the platform and provide quick links into each insight area and bubble up insight while also giving users quick access to:

• their current/open initiatives
• their bookmarked dashboards
• their current/open reclassification requests
• recent bulletins
• quick links to relevant courses in the Sievo Academy
• top CO2 emitters
• other widgets the user wants on their home page

Extended Do-it-Yourself Self Service Report Creation

Not really new, but as they have added dimensions and measures, they have all be included in the self-service dashboard (and organized by measure type such as spend, payment term, supplier, invoice, PO, material, category, etc. for quick location). Similarly, as new chart types have become available, they have been included as well. (And you are not restricted to traditional bar, line, pie, and table charts — full featured pivot charts, scatter plots, and mekko charts are also available in self-service).

Near-Term Roadmap

Community Data

Sievo users will be able to benchmark their data against anonymized data from other Sievo companies’. For example, a company will be able to gain insight into its payment term competitiveness with respect to market average. A variety of pilots are ongoing to determine the most useful data, but these insights will extend the value Sievo can bring to its users.

Index-based Price Forecasting

In the materials forecasting module, more functionalities are being integrated to ensure a deep understanding of future budgeting and spending and simplify usability. Soon (in Q2 2024), forecasting based on indexes will become available, making the process even smoother and accurate for Sievo users.

Supplier Portal

ESG emissions in the supply chain are largely related to those from suppliers, and thus collaboration with suppliers is a must for emission reduction. A new supplier questionnaire and supplier portal enables users to ask suppliers for information related to their emissions, sustainability initiatives, and more.

In conclusion, if you are looking for a Best-of-Breed spend analysis solution, Sievo continues to be among the best in the space and should be on your RFP short-list.