In the past few weeks, I've had a number of discussions with various colleagues who presented new approaches to managing, using, and analyzing information both inside and outside of an organization. What's been neat is that none of these individuals had yet applied these capabilities to Spend Management. At least not yet. In many cases, however, these approaches will be relevant for spend and supplier analysis and visibility in the future.
But before we dive into these novel approaches, I thought it would be useful to provide a little bit of background on the current state of spend and supplier analysis without rehashing my previous blog on the subject. So here goes...
To begin, the most elemental approach to building visibility and analysis flows back to that wonderful tool we all use, Microsoft Excel. Many companies have successfully used Excel (and Access) to analyze basic supplier and part information. But spreadsheet and database tools have limitations, especially when it comes to aggregating, cleansing, and analyzing part-level detail from multiple systems. It's a bit like using a $2.99 calculator to build and analyze complex financial models it's possible to do so (and it's better than trying to do it manually), but the results will be shaky at best, especially as the volume and sources of information scale.
The next type of approach to enabling spend and supplier visibility centers on third party services-driven but software enabled applications from the usual suspects. Early versions of these tools like I2’s Aspect essentially provided a master reference of part / supplier information with varying degrees of classification, cleansing, and analysis. We've heard that the rub of these approaches which many other vendors deployed as well was that information maintenance and reuse proved to be more challenging for many users than originally thought.
Following on the heals of these approaches were stand alone software vendors like Softface and Zycus who claimed the ability to enable auto-classification and analysis an interesting part of a broader analysis effort, but somewhat unproven as a stand alone approach without enabling services. Fortunately, Ariba acquired Softface, which enabled a broader software and services driven analysis approach. Zycus, however, still stands alone. Even Keterahas jumped into this act as well with an on-demand capability which is primarily software driven. But next generation approaches to supplier and spend analysis will incorporate new types of technology and information. For example, emerging applications will have the ability to look at spend data and understand it with the context and clarity as a commodity manager / expert while reducing systems complexity. For example, these types of systems will recognize and cleanse information based on a set of adaptive rules without creating a new system of record. The analogy here -- with credit to Martin Boyd -- is to think of these future approaches as a portable spend prism when you draw the prism over information, it automatically extracts what it needs to.
Previously, solutions to manage spend data would also rely on a subject matter expert to interpret it. But these new approaches will embed expertise which allows companies to manage the classification process while building new unique approaches to managing information. Many of these approaches will rely on a semantic knowledge base and natural language system. In theory, this new type of analysis technique – which is unproven in the spend analysis field but has already been used in other areas such as customer data integration (CDI) and catalog information management will work very well for spend and supplier analysis as well. The beauty of this is that once a system is set up and the rules are determined and embedded integration with new systems (e.g., those of a potential acquisition target), will be a breeze – at least in theory.
The flexibility and rules driven approaches these technologies use will enable organizations to pull and push information nearly instantaneously from multiple systems while applying any classification code / structure to it – even on the fly (e.g., UNSPC, Federal, maintenance, etc.) In essence, these future solutions will enable organizations to take spend data from any number of disparate sources, standardize it, and then classify it without expert intervention, in essence providing real-time spend classification, regardless of source and interface. The notion is that the spend / supplier analysis will be a rules-based outcome which can be displayed through any interface (a portal, web-service, etc.). These approaches typically will not require a new system of record, but rather, will serve only as a push / pull interface. In essence, this approach will mirror what companies like Silver Creek Systems, Initiate Systems and Ascential (now IBM) have done for customer (and enterprise) data integration.
But in the future, visibility will not just be about improving an organization's internal spend and supplier management capabilities. It will also be about incorporating external information to make more informed decisions to predict and model supplier and supply market performance. Open Ratings is probably one of the coolest vendors in the space today, yet their commercial traction has been somewhat limited by their small size. They claim the ability to predict both supplier financial and operational performance, based on comparing dozens of external information feeds (e.g., D&B) with internal information. In the next few weeks, we'll explore the potential for these types of predictive performance modeling and monitoring systems in more detail. Very cool indeed.