Where a category falls under this framework will dictate the strategy a company should follow. For example, for a strategic category with low data granularity, Sievo recommends starting with high-level data and changing internal processes to collect more granular information for future measurement (this change piece is key -- superficial data may work for sourcing strategy and negotiation in some categories, but when it comes to implementing and tracking savings, granularity is essential). For categories that are both strategic and also have a high level of existing data granularity, Sievo suggests leveraging detailed measurement insights and causality analysis (i.e., identifying, rooting out and treating the causes, rather than the corporate spend patient's symptoms), in driving a savings implementation and category measurement program.
Putting to use this quadrant approach in terms of implementing a recently identified opportunity, Sievo enables users to create savings projects based on a form-based entry system (with significant workflow/configuration based on what an organization is tying to track). For example, someone can enter project basics (e.g., name, title, start date, deadline, overall responsibilities) as well as additional insights necessary to implement results (e.g., category, sub-category, status, creator, approver, savings component items -- and dollar amount -- currency measurement, stage of identification -- e.g., verified, initial verification, etc. -- verification source data, etc.).
And then, once a program is in place, users can measure against budgeted and forecasted savings, and are not only able to roll-up this data on a category basis across direct, indirect and services spend areas (e.g., MRO, IT hardware, marketing, stainless sheet, plastic injection moldings, etc.), but also to track and measure where savings leakage is coming from, in the aggregate or on a specific category or unit level. When measuring leakage, an organization might be able to pinpoint adverse movement of currency or commodity prices for example. Or perhaps, a volume forecasting error is to blame for the challenge of implementing a target savings program.
The main benefit users realize from Sievo is the ability to get a true "x-ray," in one user's words, into all of their spend and savings programs on a global basis which creates a shared language and definition to determine savings and ultimately the "real-time value" of the purchasing department. Based on statements like this, if you're thinking that Sievo could very well be the missing savings and tracking link in your direct materials sourcing environment, you might be very much be correct. One procurement executive we spoke with noted that there is no way "he would be where he was today" without the system, which has in fact not only driven measurement and savings into the sourcing process in the one company, but also changed the staff and hiring mix as well, putting in place a data-driven procurement culture.
From an integrated solution perspective, what Sievo has done looks closest in form to item-level spend analysis, data aggregation, reporting and project management workflow combined together. But the nuances of the approach are much more subtle than simply extending a spend analysis toolset into new areas. Indeed, with Sievo, spend analysis data is not the means to an end -- it simply represents the data and baseline measurement inputs in a broader spend cockpit and reporting orchestration. In this case, however, not a single element is playing second fiddle. It's the combination of components that make the output of what Sievo provides so special, and above all, useful.
Stay tuned as we continue our coverage of Sievo and report on one customer's specific experience.
- Jason Busch