I recently rented a car featuring steering assist and intelligent cruise control. Now, I’m used to driver assist technologies as my vehicle has blind spot warning and front and rear collision warning, and braking.
My wife’s car has a heads-up display as well as steering wheel vibration when you stray onto the lane lines, but when driving this rental, I felt the car was actually steering itself back into the lane when it drifted astray.
Since I wasn’t familiar with this feeling, I was compelled to try several different things to see how the car would respond. If I made the car move to the left side of the lane, would the automatic correction over-steer so that I would drift to the right?
Designed as a “hands-on” driver assist system rather than a “self-driving” feature for use in both heavy and flowing traffic situations, the car did self-correct and did so continuously as I experimented with the feature.
For example, I tried setting the car on a course to cross a lane line and would then nudge it to oversteer, hovering my hands about an inch or so away. But before the car drifted into the other lane, an auditory warning sounded, followed immediately by automatic braking. (Had I actually fallen asleep and my hands were off the wheel, this definitely would have woken me up!)
Later, as I read more about the car's technology online, I realized that I didn't actually push the feature to its limit. In more extreme situations, the function would correct course, slow down the car down, turn on the hazard lights and come to a complete stop. Now that's truly impressive.
The Self-Healing Supply Chain: The supply chain planner's driver assist feature
By now you must be wondering this driver assist feature experience has to do with supply chain management? Well, the symbol on the dash of the car being in the lane and drifting to the left and right boundaries made me think about statistical quality control and x-bar and R-charts. When the vehicle drifting left or right of lane center, it was akin to being above or below the mean, and the left and right lane lines are like the upper and lower control limits. This led me to think of this driver assist feature in a supply chain management context:
- Supply chain business experts define key supply chain measurements along with the boundary – or lane – limits process and timing of data collection along with monitoring for impact and priority.
- Progressive warnings are sent when key supply chain measurements drift towards control limits WITH the ability to make automatic corrections – without over-correcting. If automatic and/or manual intervention doesn't bring the system back into balance, the ability to slow down and put on the hazards (escalate alerts) and maybe even bring some activities to a complete stop come into play.
In RapidResponse®, I liken the driver assist feature to the Self-Healing Supply Chain™, which automates functions to help:
- Enhance performance through the automatic correction of inaccurate supply chain design assumptions
- Avoid risks by interpreting the impact of incorrect design assumptions like lead times
- Boost productivity by allowing planners to focus on what matters, alerting them to high impact exceptions between designed and actual supply chain performance
- Drive profitability by increasing business growth with automatic, continuous improvements to the accuracy of planning design assumptions
In closing, I want to assure you that my experiments with this driver assist feature was on a four-lane highway with little to no traffic at the time – after all, I don’t want anyone to think I was being reckless. What other 'driver assist' type features would like to implement in your supply chain management process? Where do you see this type of supply chain automation being most valuable? How do you see the Self-Healing Supply Chain streamlining your management and planning? Let me know in the comments!
Thank you for the response and for following 21st Century Supply Chain. It will be interesting to see how AI and Machine Learning transforms supply chain management. Don't hesitate to jump in and share your insights!
Leave a Reply