Spend Analysis 2.0--The Next Frontier
The global spend analysis marketplace has witnessed hectic activity in the past year, and is predicted to increase by more than 200 percent in the next two to three years. Large enterprises have realized the complexity of managing and analyzing spend data that is dispersed within their organization. Huge investments made in electronic procurement and sourcing systems (tens of millions plus) have failed to provide the promised return on investment, while transaction spend volumes languished between 15 to 35 percent.
There is a spend data crisis brewing within the industry. Dirty data (cryptic, incomplete, wrong code, etc.) volumes are growing, in multiple commodity schemas, multiple languages, and multiple currencies, along with duplicate supplier names and unstructured contract contents; within multiple legacy, ERP, and procurement systems. Unless this problem is dealt with globally, the vision of enterprisewide savings, spend compliance, and control will remain a distant dream.
Rewind
In the past, many organizations chose to leverage the services of Big 5 consulting companies (ATK, Bearing Point, etc.), supplier content providers (D&B, Austin Tetra), or niche spend analysis service providers (Tigris, Silver Oaks), to grab the low hanging fruits. Opportunity assessments followed up with aggressive sourcing actions resulted in savings of 5 percent to 10 percent for many organizations. Spend analysis was considered more of an art than science. The so-called spend analysis providers were essentially data management specialists (or self-titled hybrid solution providers) who used a mix of tricks from brute force, Excel-based data coding to unsophisticated tools using scripts and rules engines. These service providers offered spend analysis programs that lasted years and cost millions of dollars ($2 million to $5 million). For a while, the returns were easy to get - simple cleaning and supplier data offered the customer quick opportunities for negotiating savings.
Early Adopters
While others were spending millions in services and consulting fees, some leading-edge Fortune 100 companies chose to invest in a spend data management software infrastructure. These organizations benefited from the ability to get automated and repeatable spend analysis, and managed to get a global in-depth view of spend data (normalized to a single UNSPSC code schema). Few visionary leaders even adopted best practices such as automatic commodity coding at source (leveraging bleeding-edge AI tools integrated at the point of requisition). The benefits of in-depth (UNSPSC commodity level code) visibility were enormous. Additional 4 to 7 percent savings opportunities were discovered in many cases, but more importantly, an effective system was put in place to monitor enterprisewide spend compliance and control.
Point of Inflection
Customers who were leveraging the services approach (and who comprised the vast majority) soon realized that supplier data cleansing (within a region) was just the first step toward global spend visibility; (even then the challenge of consolidating global suppliers defied all available solutions). Now increasingly aware of the benefits of spend analysis, they were prepared to take the next steps. They wanted global coverage, in-depth granular visibility, and analytics on demand. Clearly this was an inflection point for spend data management software companies who were evangelizing the benefits of an automated repeatable spend analysis solution.
The Market Shakeout
While the market was just learning about the merits of AI-based auto-classification, the service providers were coming under increasing pressure. The cost of providing spend analysis services was growing, while revenues dipped because of competition. Many established spend analysis vendors were forced to seek for offshore data processing, but the quality and delivery stood to suffer immensely. Even where costs could be managed, the value proposition to end customers was on the decline. Top-level visibility provided by quick and dirty manual data categorization left much to be desired. Without a core IP and long-term vision, there was no way these organizations were going to be able to sustain themselves for the long haul. Interestingly with the growing need for spend analysis, customers now also turned to ERP, procurement, and sourcing software vendors, but none had a ready solution for this problem. The timing for acquisitions was ripe with the valuations of service companies being very attractive for potential bidders. After being up for sale for over a year, their management was impatient to close a deal. Anticipating the growth and criticality of spend analysis to their core business (i.e., selling sourcing software or managed solutions), many of these vendors decided to pursue an acquisition strategy. Since the spend analysis and sourcing software business were roughly equal in size, acquisition would also mean doubling of revenue for some.
While acquisitions are good to build an end-to-end marketing story, the success of any merger will come from the ability to deliver. The problems of a service approach (i.e., high cost of delivery and increased time-to-value), are going to plague the software vendors who will take time to determine a profitable managed service delivery model. On the other hand, developing core technologies (such as AI-based classification) inherently has a high entry barrier, and going live on applications with a software tool could take many years.
Global Spend Analysis - The New Game
The new game in spend analysis is going to revolve around the adoption of an enterprisewide vision of spend data management. In the absence of proper data descriptions and a universal code schema, there is no way to leverage global sourcing and even doing so locally will remain a huge challenge. Further analyzing spend is just one part of the problem. A bigger problem exists in the material, vendor, and product data masters, etc., of large ERP installations. Rationalizing assets such as inventory, and enabling cross-plant visibility drives hard dollar savings, just as is the case in better sourcing. The vision of send data management is very holistic. It calls for managing and rationalizing all transaction, parts, and products data to one universal code set such as UNSPSC - so an enterprise is better able to leverage spend information that flows through. Spend analysis 2.0 dovetails into the vision of spend data management. It calls for leveraging an automated spend data management infrastructure to rationalize and normalize all spend transactions to one granular code set, and enable in-depth analysis by sourcing professionals regionally and globally. That is the only way to discover maximum savings opportunities. Automated and repeatable spend analysis is primed to be woven into the corporate DNA - to facilitate better sourcing, category management, and tracking compliance.
Takeaway
The market will now have a choice of solutions from amongst the Big 5 consultants, sourcing software providers, and spend data management companies. The customer demands are going to be phenomenal - automated data extraction from multiple systems (SAP, Oracle, PeopleSoft, etc.), consolidation and normalization of data, categorization to one uniform taxonomy (UNSPSC/eCLASS), ability to handle multiple languages (German, English, French, as a minimum), embedded analytic tools, and spend portals. No one ERP system warehouse, BI tools, or procurement software analytics is going to solve the puzzle. It will be years before global spend is consolidated within any one system, and until then, investing in one automated spend analysis infrastructure will continue to make the most sense. This infrastructure will manage transaction data, master data, supplier, catalog, parts and contracts data, and leverage the UNSPSC glue to enable better sourcing, compliance, and control of spend.
A meaningful and strategic alliance between category leaders is going to provide compelling value over a marriage of convenience, and steer above the marketing hype.
