Navigating a Confusing Tech Landscape in Supply Chain Planning
- Many businesses continue to rely on legacy planning technology that is costly, time-consuming and outdated
- The need of the hour is to leverage advanced technology that can factor in real-world events and anticipate their impact on the supply chain
- Advanced technologies such as AI, machine learning and predictive analytics can transform the way planning is done
Choosing the right technology is vital to streamlining supply chain planning. Simple as it may seem, this is easier said than done.
For decades, the supply chain planning landscape has been dominated by what we can refer to as “old tech.”
Even today, many businesses continue to rely heavily on big, expensive ERP implementations, and often an accompaniment of best-of-breed tools that bring optimization or simulation capabilities to the transaction-focused ERP system.
Not only are ERP systems costly and time-consuming, these focus merely on transaction processing and master data management. Additionally, they require a large team for internal and external development and production.
Time to Digitalize Planning
Amid growing uncertainty, there is little doubt that a business must revamp its supply chain planning mechanism.
Robert Giacobbe, vice president of global supply chain consulting at GEP says there is a revolution going on in supply chain planning tools and techniques. “GEP sees formerly immature clients leapfrogging into a new set of planning capabilities by embracing new tech and taking a thoughtful, digital-first approach to solving their planning issues,” he says.
Here are the new-age technologies that can help you transform the supply chain planning process:
1. Artificial Intelligence:
From demand forecasting and should-cost modeling to inventory management, AI-powered tools are now extensively used in supply chain planning. These tools can assess the impact of changing market indices in real time, thereby enabling a business to quickly adjust its plans.
2. Predictive Analytics:
Predictive analytics can be instrumental in redefining the planning function. Giacobbe says, “We are only at the tip of the iceberg in developing predictive analytics applications. Most clients have large volumes of unexplored data in storage, waiting to help with supply surety, supplier capability, asset reliability, strategic demand analysis and customer demand forecasting.” Clearly, there is a lot more that analytics can do than what it is being used for currently.
3. Demand Sensing:
This technology can help a business “sense” demand and create real-time visibility of the changing demand patterns in accordance with market shifts, weather changes or changes in consumer buying behavior. It can be extremely useful in the current business environment that is prone to disruption and sudden changes in demand.
4. Autonomous Planning:
Autonomous planning seeks to combine new planning technology and tools with business rules and exception-based planning models. The objective here is to let machines work in sync with humans to achieve optimum performance. It also aims to minimize human intervention and eliminate the possibility of error.
5. Rapid Simulation:
Before launching a new product, businesses often struggle to predict demand due to lack of proxy data. Digital supply chain planning tools can offer quick simulation and data-creation engines that can intelligently create demand history proxies for products with similar demand profiles.
Clearly, traditional planning procedures are giving way to a digital, automated function that can work with real-time data and adapt to a quickly changing market.
Such a transition is vital, given the instability in the current business environment. Businesses that continue to use old tech and delay the adoption of supply chain planning technology may find it hard to compete in the new normal.
Additional Read: Supply Chain Management Guide