Endeca's spend analysis solution, built on its Latitude product, greets users with a logical dashboard format. Practitioners coming from solutions such as Ariba and Emptoris would not be entirely out of place at first, at least staring at a static screen from a distance. But as you begin to dig into the tools, things change rapidly. For one, you can begin to interrogate spend across a range of angles you might have previously never considered. In an automotive setting, to borrow a real example, this might include querying spend based on standard classifications such as exterior bodies, chassis, electrical, powertrain, interior, transmissions, brakes, etc. Or users may opt to drill into the same data but from a different vantage point, such as by company brand, part families (for a given component or area), by geography/market or by supplier geography, market or other variables.
The ability to rapidly explore alternative commodity classifications to UNSPSC and NAICS based on industry, company or geography-driving elements is straightforward. But where Latitude really begins to shine is when users incorporate detailed views of data in the context of other systems information (navigating on part technical attributes such as the size of parts, raw material components, warranty claims records, etc.) It's also possible to view part compliance information (against accepted defect rates, restricted substance usage, regulatory requirements, etc.) at the bill of material level. Users can also explore and map this information against forecast data to understand the impact of production schedules on budget, total cost, etc.
The value proposition for tools like Latitude extends well beyond procurement. For example, design engineers can begin to leverage extended part-level information in design decisions to understand all part alternatives within the context of a design decision. This can lead to greater reuse and standardization of parts as well as views into overall part databases that aggregate design engineering, procurement and supplier information. Designers can even look at both cost and quality data to understand not only how their decisions can impact unit cost, but quality and total cost over a product's lifecycle.
Even HR can get in on the act for non-manufactured items. Take contingent labor, for example. Using Latitude, HR and frontline hiring managers can begin to explore different "supply" alternatives for human capital based on availability (e.g., lead time required to staff), bill rates, industry experience, location and other variables. Users can also drill down on specific details for particular firms, regions, contractors, etc. including historic bill-rates, performance information and in-country (or region) experience. At this stage, users can use Latitude to chart and begin to correlate fields like utilization rate history against performance levels, bill rates and countries. Using its unstructured search capability, Latitude can also let users query and search resumes within the system, drilling down into past candidate history and experience which may only be a few clicks away from a higher-level query.
From this example, it's easy to see how one could apply Latitude as a mash-up capability across virtually any category of spend including complex services categories. But the most advanced use cases -- and likely the ones destined to generate the highest value and savings -- come on the direct spend side of the house. As we conclude this series on what Oracle has gotten with Endeca in the next post, we'll revisit the integration of Latitude with PLM and ERP/MRP data that would otherwise never make it into a spend analysis toolset together.