The Analytics Category

Spend analysis providers that tackled the “hard stuff” originally offered line-level visibility into buying activity based on invoice data. Such capability has now become standard. But what if you could go beyond line-level visibility when it comes to understanding spend data? And what if you could do this for supplier spending, as well?

For the majority of direct materials spend in manufacturing, nearly all approaches to analytics come up short when it comes to gaining insight into the underlying materials, spend and suppliers used for semifinished materials, parts, components, assemblies and finished products, either directly by the buying organization or passed-through based on supplier purchases. This lack of visibility not only increases both supply and commodity price risk but also stands in the way of driving innovative sourcing strategies that can drive hard dollar savings.

Yet one provider thinks they have the answer to this challenge: Supply Dynamics. Supply Dynamics combines its own form of spend classification, enrichment and front-end analytics based not just on information contained in ERP/MRP data but also on engineering drawing and bill of material information, using both data and metadata it extracts from design drawings. It also provides out-of-the-box capabilities to create material demand aggregation programs for metals, plastics, electronics and other sub-components (but that’s only one “savings” lever it brings, as we explore in this review).

This third and final installment of our Spend Matters Vendor Snapshot covering Supply Dynamics provides an objective SWOT analysis of the provider and offers a competitive segmentation analysis and comparison. It also includes recommended shortlist candidates as alternative vendors to Supply Dynamics, and offers provider selection guidance. Finally, it provides summary analysis and recommendations for companies considering Supply Dynamics. Previous installments provide an in-depth look at Supply Dynamics as a firm and its specific solution capability and a detailed analysis of solution strengths and weaknesses, as well as a review of the product’s user experience.

One of the major gaps today between supply chain planning and collaboration solutions and direct materials procurement technologies is the lack of spend/supply visibility for raw and semifinished materials used at different stages in the supply chain. These materials include commodities such as metals, resins, electronic components, chemicals and standard parts purchased by suppliers such as fasteners.

Granted, manufacturers are getting better at SKU-level demand planning and forecasting on both and inbound and outbound levels, not to mention managing all of the logistics associated with moving goods and materials. This is the basic “feeds and speeds” of the supply chain. Manufacturers also more frequently gaining visibility and orchestrating controls and processes around overall “spend” at the line item and supplier level, but this is only historical “spent analysis” of material consumption within their own four walls. Few companies have a true bill of material- and design drawing-level understanding of what upstream materials they’re buying vis-a-vie their suppliers. In other words, the lack of visibility into their suppliers’ spend and underlying costs prevents them from uncovering cost savings opportunities that are hidden upstream in their supply chains.

This is precisely where Supply Dynamics, a provider that specializes in multitier direct materials procurement, proposes to fill an important analytics and solutions gap through its SDX platform. It’s an area that even direct materials procurement technology specialists such as Jaggaer/Pool4Tool and SAP Ariba, with their new solution releases, do not begin to address effectively.

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

The term big data is not new in the lexicon of business jargon. After years of hearing how big data analytics will transform the enterprise by producing brilliant insights from reams of unstructured information, procurement observers are understandably skeptical about the promises big data’s marketers have made. It was no surprise to us, then, that for one of the first questions we received in our new series Ask Spend Matters, an anonymous asker hoped to find some evidence behind big data’s claims.

Tail spend frustrates many procurement groups. It’s messy, it’s complex and it’s time-consuming to tackle. Inking big deals and keeping stakeholders happy seem like far better priorities for the typical category manager, since that’s how he can turn executive heads and make his daily life simpler. At least, that’s how it used to be. These days tail spend is trending — and for good reason. Here are three reasons why this persistent thorn in procurement’s side is finally getting the attention it deserves.

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.

While some customers may protest that corporations already have us under heavy surveillance — spinning the metaphorical straw that is our purchases, internet history, socioeconomic data and more into predictive analytics gold — a majority of companies said in a recent survey that they are behind in their use of technology to understand and predict consumer behavior. And they’re very much motivated to improve.

Manufacturing giant Jabil launched recently what it calls a supply chain decision support platform, pitting its cross-industry expertise as a contract manufacturer against the services offered by point solutions. Called InControl, the platform offers five applications that provide visibility, collaboration tools and diagnostics for supply chain professionals. The apps cover supply chain visibility, event risk, design for supply chain, risk management and supply chain diagnostics.

One of the hottest topics in procurement these days is data analytics (including big data, artificial intelligence, machine learning, natural language processing and algorithmic decisioning). Therefore, in case you missed it, we’re dusting off this primer on data analytics from mid-2016. It's still valid as ever and ready to read in one sitting.