As users work their way through the various configurable tabs in the Iasta Executive Analytics (EAS) suite, they might create a tab to support specific project-based procurement initiatives not just limited to sourcing events. For example, the dashboard might show the specific initiatives tagged to either categories, commodities, or individuals. Specific initiatives might include cost avoidance scenarios, negotiation of contract renewals, initial source programs, claim/rebate initiatives or just about any activity within procurement that one can conceive.
The power of the dashboard framework for initiatives within the EAS suite, however, is about being able to tag specific employees, suppliers and third-parties to programs (in addition to other metric-driven data), all of which can roll-up to other views (e.g., show me the aggregate savings targets for David Smith across all of his activities and the percentage savings implemented for programs in the past 12 months). It's powerful stuff from a management perspective, especially given how one can both drill into results and then launch into actual initiative-focused tools from the dashboard (e.g., a specific optimization-based sourcing event).
By looking at initiatives in context, users can also discover insightful and previously hidden metrics tied to comparative program and category performance. For example, looking at "spend vs. savings" ratios for individual lines of business or categories such as HR benefits, IT software or finance-centric BPO. The ability to see details associated with initiatives, either user-generated within the dashboard framework itself or pulled from third-party applications – or a combination – provides granular visibility. This may include short- and long-text initiative descriptions, managers, tier one suppliers (or multi-tier suppliers, if the information is available) impacted by an initiative and specific financial metrics (e.g., savings, budget impact and budget-based cost avoidance).
The category analysis capability within EAS gives different levels of slicing and dicing area specific spending information. For example, users may pivot or drill into data based on category codes, business units, suppliers and the like. Nothing revolutionary here – really traditional spend analysis with the ability to include specific category datasets and types – but valuable nonetheless. More interesting is the ability to include and consider additional types of category-centric analysis than standard spend analysis type metrics.
For example, exploring working capital and payment term strategy in the context of the suite could prove valuable. In fact, payment term strategy can often yield more rapid implementable results – especially when tied to compliance-based tools for invoicing and buying across indirect (P2P), direct (ERP/MRP) and services procurement (VMS) type – than other sourcing focused activities. And it can do so without causing supplier switch-out headaches.
As an example, what if you could examine payment terms by category of spend, geography, or supplier? One might look at the number of suppliers in each category and then see the variance of days payables outstanding. By entering a cost of capital percentage, it is then possible to run scenarios to understand the potential savings from pushing out payments and/or bringing in a third-party to provide early-payment financing without impacting the actual working capital of the business. This is just the start, of course, of the types of working capital calculations that are possible. As one brings examines inventory considerations in the context of programs such as vendor managed inventory (VMI) alongside unit costs and payment terms, the ability to explore more robust total cost decision scenarios that cross procurement, operations and finance becomes possible.
Of course users may opt for simpler views and dashboard-based analyses and workbenches within the toolset as well. For example, a more basic dashboard structure within Iasta might show a list of top performing suppliers and bottom performing suppliers based on a combination of data (savings, price variance, risk, etc.) This can allow for the basis of creating a scoring matrix approach – available, depending on how one configures it, in the same dashboard – to segmenting suppliers based on which to maintain, develop, or eliminate.
As we conclude our analysis of Iasta's latest efforts on Spend Matters PRO, we'll consider the provider's Executive Analytics Suite (EAS) in the context of other types of related solutions.