How to Pass the Anticipate Stage of Supply Chain Maturity
By Bryn Lowry Organizations usually know that they need to improve their supply chain operations; however, often they find it difficult to identify which area to focus on first. Typically, the journey involves the development of several key capabilities in operations, but without a clear framework, it can be difficult to decide where to start. By understanding your current state of supply chain maturity, you will be in a much better position to map your journey to the next level of supply chain maturity, with a roadmap for reaching higher levels of maturity and increased business performance. In our previous blog post, we reviewed Stage 1 of supply chain maturity, which is the React stage, as defined by Gartner. In this blog, we’ll take a closer look at Stage 2 – Anticipate. In Stage 2, companies are able to leverage their scale to achieve some level of organizational consistency, even though they are still focused on internal operations and serve constituent businesses. These units tend to be focused on containing costs while increasing both productivity and proficiency. If you’re in this Anticipate stage, you have some visibility into project and application-based status, alerts, and events. In this stage, visibility feeds more data into analysis to identify areas for improvement. The Anticipate stage of supply chain maturity is characterized by the following:
- The centralization of the supply chain function is beginning to improve efficiency and productivity.
- There is a focus on creating standardized processes and methods to benefit from economies of scale and increased efficiency.
- Performance is internally focused on fulfillment percentage, productivity, costs and return on assets.
- Data collection challenges still loom large, with a reliance on large, legacy IT investments such as ERP systems, limiting an organization’s ability to collect new types of data, not just structured data.
- Supply chain activity and performance are captured and reported using an organization-wide model, enabling better anticipation of demand.