Many enterprises are making significant investments in e-sourcing tools to boost supply chain management (SCM) productivity and effectiveness. However, a common pitfall is to squander that investment by not executing properly on the associated process integration, and therefore never realize the value projected in the business case used to justify the tool.
In terms of bottom-line value, effective process integration, i.e., development of process definitions, issuance of method and procedure-level usage guidelines, training of staff, and implementation of appropriate governance and compliance frameworks, is more important than the actual functionality provided by the software.
To facilitate a successful e-sourcing tool implementation for project management, reporting, e-request for X (eRFxs) and online reverse auctions, process integration is essential in adding value to the business.
Establish Uniform Data Definitions and Provide Training
Laying the groundwork for successfully utilizing e-sourcing tools begins with establishing uniform data definitions and training. One of the primary benefits of an e-sourcing tool is that it allows staff to enter information in an autonomous, distributed manner while also allowing management access to reports that consolidate and aggregate the information into a comprehensive picture of department-wide activity. However, if the staff responsible for providing the information are not aligned and using the same data definitions and usage guidelines, then the reports generated will have little or no value.
For example, if the tool's project management function captures forecasted savings on each project, but individual users define or calculate savings differently, the aggregate numbers lose meaning and management will be unable to calculate accurate total savings by group, division or business unit.
Build Data Collection Requirements with the End Result in Mind
Another fundamental principle is the need to rigorously define the data that must be captured on each sourcing project or event in order to enable the analysis on the back end that will drive sourcing policy or process changes. The organization should begin with the end result in mind, asking which types of questions it ultimately wants to be able to answer, and from there work backward to build the data collection requirements. For example:
- If the goal is to perform trend analysis and correlate sourcing process cycle time to the variables that drive the cycle time, the following data needs to be collected:
— Start and end dates of the various steps in the enterprise's strategic sourcing process
— Sourcing strategy selected, e.g., RFP, auction, sole source renegotiation
— Project spend and complexity
— Business unit
- If the goal is to determine the value or return on investment (ROI) of various sourcing project types and approaches, the following data needs to be collected:
— Savings realized
— Project benefit summary, e.g., improved service quality, enabled product launch
— Sourcing strategy selected, e.g., RFP, auction, sole source renegotiation — Project spend and complexity
— Functional business units sponsoring the project, e.g., IT, Marketing, Sales
— Project team resource levels, e.g., FTE, required to execute on the project
Project Management: What Data Attributes Should Be Captured?
To answer the types of questions above, a number of data attributes should be captured for each sourcing project and used for reporting. This enables valuable management decision-making. The following list sets forth 10 crucial (and often problematic) data elements:
1. Project Type — For reporting purposes, it is useful to group projects and aggregate reporting based on sub-types of activities performed or the functional groups performing the projects. Examples may include: competitive (RFx) strategic sourcing, sole-source renegotiation, vendor management, contract management and general (the "general" designation is used for any projects that do not fit neatly into any of the other defined Project Types).