The Spend Analysis Category

Spend visibility is foundational to any procurement transformation because to better manage supply, you have to manage spend. Spend is what you pay and supply is what you get, and to manage spend you have to see it. Yet too many procurement organizations work hard to put basic spend analytics in place but don't have a broader vision, strategy and roadmap for strategic supply analytics (i.e., the analytic capabilities to support strategic supply management). We use the term “supply analytics” instead of “procurement analytics” to reflect procurement’s increasing role in managing broader supply outcomes than just its own performance – especially in direct procurement. This Spend Matters PRO article is designed to provide you such a roadmap. It is not a step-by-step, one-size-fits-all approach because every firm will have a different experience. It is, however, a map that can guide you through plotting out your supply analytics journey.

As we conclude our series on spend analysis, we turn our attention to how best-in-class solutions can support three requirements that go beyond the basics of what most organizations have implemented today. These enabling capabilities are already (and will become even more) important for procurement to be effective at addressing, through analytics, business objectives as it strives to become more effective as both a value-generating and compliance-oriented function. The three components are: providing specialized tail spend analytics, permissive analytics and real-time maverick (or off-contract) spend identification. The remainder of the series (see: Part 1, Part 2, Part 3 and Part 4) explores what the fundamental building blocks of best-in-class analytics technology and user design look like today and will look like in the future.

There are doubtless readers who have kept up with this Spend Matters PRO series on the intersection of best-in-class spend analytics technology and user design and thought to themselves, “I wish my solution did that.” But the most important thing to remember is that data is about telling a story. The particular narrative you decide (and are able to tell) from the insight to come out of your spend analytics initiatives will either make procurement more valuable or leave it to toil in obscurity. Spend analysis is an enabler — nothing more — but a critical one at making procurement better at everything it does. Yes, the “geek effect” of the best technology and user design considerations can make solutions buyers for it cringe (if they don’t have it). But ultimately, spend analysis is not about “the kit,” as the British would say.

It is within this context that we can observe that many procurement organizations today are making due with spend analysis technologies which, while helpful when it comes to teeing up basic sourcing opportunities and tracking savings, are a key limiting factor in enabling procurement to do more as a function, putting data front and center at driving the analytics to inform strategy and action.

As we continue this series exploring all the elements of best-in-class spend analysis approaches, painting a composite view about what an ideal solution should deliver at the intersection of capability and usability, we turn our attention to what optimal components approaches include for integrated reporting (and report design), as well as the core elements of descriptive and predictive reporting. See also Part 1, Part 2 and Part 3 of this series.

Evaluating the merits of spend analysis solutions (by user role) is inherently complex given that a spend data analyst, a data management QA individual, teams, category managers, other procurement users and business stakeholders will interact with the application in different ways. An ideal solution for one user “type” may be unacceptable for another. For example, some groups will care deeply about granular data import/export capability while others will judge an entire solution by its reporting. Still others will marvel over the ability to classify or reclassify data in certain ways on the fly. But one commonality regardless of user role or interest for spend analysis is that the intersection of best-in-class technology with best-in-class user design is becoming inseparable. Form and function are both leading (and following) each other.

This Spend Matters PRO series explores how these areas can come together across a spend analysis application to transform how users interact with data and what they can do with it as a result. In the Part 1 of this series, we explored what separates out spend analysis dashboard approaches that are a distraction (at best) from those that are an invaluable component of an overall solution. In Part 2, we analyzed all of the nuances of optimal filter definition and dynamic cube views (and creation), including exploring what a truly flexible and dynamic filter capability consists of, as well as explaining the essential elements of formulaic and ranged dimension capability and real-time/scalable spend cubes (and why they matter, even for a typical user).

In this installment, we turn our attention to the intersection of the best technology and user design combinations covering optimal approaches to data import/export in different formats, “idiot-proof” data categorization system design and reclassification of data.

Like many other procurement technology enthusiasts, the co-authors of this report tend to put quite a bit of emphasis on just the spend classification components when considering spend analysis technology. But just as important as accurate spend classification is what one does with the data once it is available in a usable format. In the first installment in this series, we provided an insider look on what differentiates spend analysis dashboards that are a distraction (at best) from those that are an invaluable component of an overall solution.

As this Spend Matters PRO series on what separates out best-in-class spend analysis technology and user interface capabilities from the vendor pack continues, we turn our attention to the nuances of optimal filter definition and dynamic cube views (and creation). This includes exploring what a truly flexible and dynamic filter capability consists of, as well as explaining the essential elements of formulaic and ranged dimension capability and real-time/scalable spend cubes (and why they matter, even for a typical user).

There seems to be a near universal playbook for spend analysis solution providers when it comes to positioning the capability they deliver. You’re not alone if you think many vendors sound interchangeable (despite claims of “enrichment accuracy” or dashboard superiority). To be candid, based on our survey of many solutions in this market as part of PRO Vendor Snapshot reviews and, more recently, our SolutionMap comparative analyses, a good many are. But they’re fungible in a way that is not necessarily negative, especially those that tend to rely more on services and less on technology to drive data management efforts.

Still, best-in-class technology and usability matter. And while we do not disagree that spend analysis must center on — and span the gamut of — spend data acquisition from disparate sources, data cleansing, data classification, data enrichment and data analytics via a BI/data presentation layer, the devil is truly in the details when it comes to what to look for in a best-in-class solution both from technology and user interface capabilities. As with e-sourcing (Part 1, Part 2), reverse auction capability (Part 1, Part 2) and sourcing optimization (Part 1, Part 2, Part 3, Part 4), the gap that separates out top performing solutions from everyone else is getting wider, not narrower.

This multipart Spend Matters PRO series examines the components of spend analysis solution capabilities in the technology and user experience areas that represent best-in-class today — and the intersection of how emerging features and capability are interacting (and driving) an optimal user experience. In this first installment, we consider the optimal interactive spend analysis dashboard.

We recently had a client ask us if we could offer specific guidelines or methodologies for creating a spend category taxonomy within the automotive and industrial markets. The question resulted in a discussion among a number of us with industry experience. And since we didn’t have any research already published on the topic, we thought we’d invest the time to document our findings. In this second installment of a two-part Spend Matters Plus research series, Chief Research Officer Pierre Mitchell explores how granular procurement should go in creating a spend taxonomy and concludes with practical tips for implementing a program.

We had a question from a client of ours about whether there were any guidelines or an overall methodology to coming up with a spend category taxonomy. It’s a simple question, but there isn’t a simple answer. So, we thought we’d offer some insights to help guide your efforts. But before we say what to do, there’s a quick recommendation on what not to do. In this first of a two-part Spend Matters Plus series, Chief Research Officer Pierre Mitchell explores how to think about creating a spend category taxonomy, pitfalls of incorrect approaches, and how to embrace an approach that cuts across categories and spend types.

Next week, I'm participating in a webinar, Oracle and Procurement Analytics: A Deep Dive Into Oracle’s Spend Analysis and Data-Driven Procurement Solutions, with the Data Intensity team. For those that do not know Data Intensity, the firm acquired Enrich in 2016. In various discussions with the Data Intensity team in preparation for the webinar I realized that Oracle has largely flown under the radar in spend analytics compared with many other procurement technology providers, especially independent specialist vendors. Still, Oracle has quietly built a solid set of capabilities in the spend classification area (and, more broadly, spend analytics).

Not only is the market for spend analysis solutions highly fragmented from a vendor “choice” perspective today, it is also characterized by solutions that are difficult to compare on an apples-to-apples basis between providers. Sievo is one such provider that makes cross-comparisons of vendors challenging because of some of the unique approaches it takes both to spend classification and, more important, to savings reporting and tracking. In fact, this latter element makes it one of the few spend analytics solutions that is as relevant for finance (and CFOs) as it is for procurement organizations.

This final installment of our multipart Spend Matters PRO Vendor Snapshot series covering Sievo offers a SWOT analysis, competitive assessment and comparison with other providers in the spend analytics market. It also includes a user selection guide and summary evaluation and selection considerations. Part 1 and Part 2 of this PRO research series provide a company and deep dive solution overview, product strengths and weaknesses and a recommended fit analysis for what types of organizations should consider Sievo.

To get the full benefits of Sievo, a novel analytics and savings management/tracking provider that delivers value to both procurement and finance organizations, customers need to get their hands dirty in their data — which can be a good thing. In engaging Sievo, it is the involved customer that becomes intimate at a deeper level with their data to drive true spending intelligence, in contrast to working with many other spend analytics providers that take ownership, on an outsourced basis, of data stewardship to drive cleansing, enrichment and classification perspectives.

This Spend Matters PRO Vendor Snapshot explores Sievo’s strengths and weaknesses as a managed services provider, providing facts and expert analysis to help procurement organizations decide whether they should consider the firm to support the procurement of contingent workforce spend and broader services procurement categories. Part 1 of our analysis provided a company and detailed solution overview and a recommend fit list of criteria for firms considering Sievo. The third part of this series will offer a SWOT analysis, user selection guide, competitive alternatives and additional evaluation and selection considerations.

The market for spend analytics reminds us of the evolution of the coffee market. It was not so long ago that we largely had a maximum of four choices: drip, percolator and then regular or decaf (this was when no one cared about the provenance of “the beans”). Today, this choice has exploded, and coffee is, well, not just coffee anymore.

Spend analytics has evolved in just about as many directions as a barista can provide in terms of java choice at the local coffee shop. But not all approaches are created equal. In fact everything from underlying data acquisition, classification, enrichment and analytics can vary dramatically from solution to solution.

Sievo is one of the longest running, still independent spend analytics providers in the market today. Founded in 2003, Sievo long ago moved beyond basic spend analytics and centers much of its value proposition today on driving savings program measurement and management. How they do this is complex, requiring all of the basics of spend classification, analytics and more. In this research brief, we get into the weeds on the “what” and the “how” of Sievo. We promise: Sievo is unlikely any other provider you have seen in terms of both methodology and solution.

This Spend Matters PRO Vendor Snapshot provides facts and expert analysis to help buying organizations make informed decisions about whether they need a solution like Sievo to drive spend analytics programs or in addition to their current efforts. Part 1 of our analysis provides a company background and detailed solution overview, as well as a summary recommended fit suggestion for when organizations should consider Sievo. The rest of this multipart research brief covers product strengths and weaknesses, competitor and SWOT analysis, user selection guides, and insider evaluation and selection considerations.