Firms mull automating planning systems amid supply chain issues

Global distribution issues and increasingly complex supply chains are forcing companies to modernize the tools they use in forecasting demand and planning how to meet this demand.

According to global management consulting firm McKinsey & Company, companies’ ability to forecast demand and determine how to meet it has been further challenged by the increasingly global scope of supply chains. This is not helped by supply chain managers’ tendency to cling to manual systems and antiquated software such as spreadsheets and SAP Advanced Planning and Optimization.

As a result, forward-looking supply chain managers are now adopting next-generation systems and new applications that incorporate artificial intelligence (AI), machine learning, and data analytics to speed up decision making and pave the way for autonomous planning, McKinsey said.

Autonomous supply chain planning leverages advanced technologies to evaluate millions of data points and generate insights from them, said supply chain management company Logility.

“Your business will gain a better understanding of historical and current supply and demand to determine the best course of action to keep pace with customer requests, regardless of market conditions,” it said in a blog post.

“Autonomous planning for the supply chain ensures your company can accurately forecast how myriad conditions may affect its operations. For example, it can forecast what would happen to the supply chain if its operations came to a sudden halt. This allows you to plan for worst-case scenarios and limit their impact.”

It added that these solutions can provide time and cost savings as well, since companies can use autonomous supply chain planning to identify performance issues in their early stages.

Plus, businesses can produce reports to track supply chain performance over time and find ways to enhance supply chain operations and keep the costs associated with them as low as possible, it continued.

But modernizing, while it can make supply chains more resilient and efficient, requires a major investment, and success isn’t guaranteed, said McKinsey.

Several challenges stand in the way of implementing new planning systems, it said. For one, upgrades are time-consuming and expensive. The resources required for an upgrade depend on the complexity of the company’s supply chain. Companies average 2.8 years from vendor selection to complete rollout.

Another challenge is conducting vendor selection, a critical but also difficult process, with companies evaluating two potential vendors on average to ascertain which system best meets their specific planning challenges, McKinsey noted.

Further, implementations don’t always go as planned. Some companies encounter project difficulties including a lack of consensus on a new system’s technical and process requirements. Others find that the impact of a new planning system does not meet expectations, or they struggle to create a compelling business case to justify switching to a new system, said the global consultant.

It stated that companies can improve the outcomes of upgrade efforts by incorporating three critical elements into the process of adopting new supply chain-planning IT systems: a forward-looking process design, well-defined vendor selection, and an implementation road map that prioritizes getting basic features right before adding more complicated use cases.

For process redesign, steps include the following: identify pain points within the current planning process, define future processes and align responsibilities, and prioritize pilots needed for testing and implementation.

For vendor selection, outline high-level business requirements for the proposal request, define two to three use cases for vendor demonstrations, and create a single page of vendor-selection criteria for final evaluation.

For implementation of the roadmap, prioritize features into “must have” and “nice to have,” organize development into sprints of one to two months, and increase user acceptance through early, intensive investments in testing/training.

To maximize the sizable investment that an upgrade represents, companies must reinforce those elements with the appropriate organizational change, business process updates, and upskilling, McKinsey added.

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