For example, a large health care provider has committed to support the development of small businesses in the communities it serves by including metrics on suppliers — by ZIP code — to monitor how well it is doing.
Second, the procurement function must determine how to have the right work in the right place, which is known as the operating model. For example, a procurement function that wants to enable continuous innovation should co-locate its team with internal customers to facilitate communications and common objectives. A procurement function focused on cost leadership, however, will group activities into a global hub, or regional hubs, to benefit from scale. The chosen operating model will define work responsibilities, where to execute these activities, and the organizational structure and governance to best manage processes.
Within the operating model is the source-to-pay process, which splits into three key subprocesses:
- Supply portfolio optimization. Through rigorous evaluation, this process selects the optimal portfolio of suppliers to achieve the purpose and identifies contractual terms that align suppliers with the enterprise.
- Commercial excellence. This confirms that the portfolio of suppliers is fulfilling the spirit and intent of tailored contracts to help deliver on the purpose. It also actively monitors and helps to manage performance.
- Touchless procurement. This utilizes leading-edge digital assets to improve P2P processes and assists requisitioners to order and receive, in compliance, without procurement involvement.
Within the framework, the execution of these processes is supported by three enablers: utilizing data-driven insights; building a workforce of the future; and performing effective change management with team members and stakeholders, internal business partners and external suppliers.
To date, commercial and legacy systems to manage procurement have fallen short of the end-to-end functionality that allows for ongoing improvement. That is because the systems are often not well-integrated and support transactional execution, while not assisting dynamic optimal decision-making. For example, while category management is well understood conceptually, the tools to gather, synthesize, normalize and present data from multiple sources are lacking, which makes effective decision-making difficult. Worse, category managers and analysts spend too much time gathering data rather than assessing scenarios and making decisions.
There is a sea change happening. Emerging digital tools are complementing existing systems to add to the functionality map and are now developed and deployed at an increasing rate. Intelligent automation is eliminating many basic clerical tasks, freeing up resources for higher-value activities. However, one critical area still to resolve is data quality to allow ever-improving analytics.