Supply Chain Innovation: The Final Planning Frontier
In last week’s post we discussed how supply chain planning and execution are converging. This week we’d like to take the concept a step further and describe where this trend could ultimately lead to and what the final frontier could look like.
Analysts like Lora Cecere of Supply Chain Insights have criticized the slow pace of innovation and progress in the supply chain, calling it a “circle of stagnation”. We believe companies will break out of this circle when a new paradigm emerges that dramatically rethinks the existing roles of technology, people and processes. And we believe it could look something like a modern control room.
Consider the control room of a large operation such as an oil refinery. The heart of the operation is an important piece of technology: a control system that monitors the status and key performance indicators, generates predictive alarms to operators well before a mishap, and translates high level operational targets into precise control actions. Detailed and robust models of the process allow the system to translate huge amounts of incoming data into meaningful information for a team overseeing a stable operation.
Essentially a modern day control room moves the operator from being “in the loop” to “on the loop”. That is, the operator is no longer running around making on-line adjustments to set points and struggling to keep everything under control. Gone also is the over-correction problem and the time delay between the operator’s action and the process’s reaction, causing process instability. Instead, operators can manage at arm’s length.
Today’s supply chains are also dynamic and complex processes with control delays, but without the benefit of this advanced process control. This explains why planning teams spend most of their time tuning forecasts, expediting goods and fighting replenishment fires. Alarms may come after it’s too late to gracefully resolve problems, if at all. Everyone is busy trying to keep the supply chain under control, but the results are noisy. Forecasts are off, inventory is out of place, and service levels aren’t what they could or should be, despite expensive inter-depot transfers.
In a vision based on a control room model, powerful statistical engines and machine learning crunch quantities of data behind the scenes, adapting to plan and optimize heterogeneous demand (fast-moving as well as the long tail). Inventory optimization automatically translates customer service policies into optimized inventory mixes to create profitable responses. Planners and business managers take a low-touch approach that involves fine tuning the demand planning, applying their creativity and specialist knowledge of the business.
Recent developments have conspired to make this vision more achievable. Downstream data is more available. Demand sensing techniques are maturing. Demand analytics and big data techniques are becoming available for analyzing demand and recognizing underlying behaviors. Supply chain planning and execution are starting to merge. Progressive supply chain executives have started to see the benefits of letting the technology handle more of the day-to-day workload, allowing planners to plan and focus on business intelligence off-line, rather than fire-fighting most of their day.
As a technology-based society, we have been through this type of transition many times before. For example, in the 1960s and 1970s machine tools migrated from manual to numerical (NC) to computer control (CNC). More recently, planes now “fly by wire” rather than via direct manual mechanical control. The transitions often posed challenges, but the end results always improved dramatically and people moved into more knowledge-intensive activities. The decision to migrate involved a leap of faith, but after which, nobody ever looked back.
Next week we’ll see one company that has taken a serious look at their supply chain vision and has started to make this transition.
Click below to read a brief on Digital Transformation in Supply Chain Planning.