There has been a lot of news about driverless cars, and at the Supply Chain Insights Global Summit there was also some news about “driverless” supply chain planning when two companies described supply chain planning with almost no human intervention.
More on this later, but to start, by driverless (whether referring to vehicles or supply chain planning) I don’t mean completely no touch at all times. Complete autonomy, for vehicles or for supply chains, is a ways off in almost any scenario. The more immediate, and interesting, question is how long before cars or planning systems can become largely autonomous, with only periodic minimal human intervention.
For driverless vehicles, regardless how far off you think fully autonomy may be, a highly autonomous vehicle appears increasingly at hand. Here’s just one data point. Tesla reports that their cars have already logged 14.5 million self-driven miles. At that point the first death occurred -- which Tesla pointed out was already better than the average human driver. But what’s sometimes lost in that statement is that Tesla cars have already logged 14.5 million self-driven miles.
There is a flurry of similar activity. Uber is test-driving autonomous vehicles in Pittsburgh. Singapore has a fleet of self-driving taxis that will go into service by the end of the year. Google’s self-driving cars prowl Silicon Valley. And so on.
At the Global Summit, Crowd Companies founder Jeremiah Owyang generalized in his keynote address that the next phase of our technology revolution is “the autonomous world age, a future state where intelligent technology systems operate without or with only limited human participation.” Owyang helped put this in personal perspective when he said his 2 year old daughter would likely not ever need to learn how to drive a car.
So what about driverless supply chain planning? Supply Chain Insights founder and CEO Lora Cecere imagined that in five years a planner will come to work, open a desktop, and talk to the network like consumers talk to Siri. The system will report what actions it took overnight, and suggest open items the planner should review. Streams of data will be pooled, and analytics will make sense of it.
It sounded a bit futuristic until two early adopter presenters stepped to the podium and described just how far they had already come.
Keith Nash of Lennox Residential described how they achieved 99.7% no touch, computer-controlled automation in their planning and replenishment. At Lennox, 997 out of 1000 planning decisions have been automated to the point where there is no manual intervention at all.
In addition, Lennox is starting to redefine their customer service around autonomous operations and new business models. You can’t predict when an air conditioner is going to break down, but with Internet of Things (IoT) data streaming from the AC unit, Lennox will be able to diagnose impending failure points and contact the customer to arrange a service visit, enhancing the customer relationship and balance their workload.
In a presentation about Costa Express, Chris Clowes described how just one planner handles the planning for 5600 points of sale. Unmanned coffee stations transmit POS data every 15 minutes to help forecast demand, optimize inventory, and generate replenishment proposals for distribution and procurement; SCP software calculates the refill order requirements nightly for frequent, low-volume deliveries.
Both companies described their implementations as transformational. Lennox believes they are laying the foundation to immense returns in customer lifetime value. Costa calls their transformation "revolutionary" with significant improvements in operational and logistics metrics and an approximately 10X increase in points of sale.
By the way, both Lennox and Costa have both won awards for their supply chains. For Lennox it was at the Council of Supply Chain Management Professionals (CSCMP) Supply Chain Innovation competition, arguably the top supply chain awards in North America. Similarly, Costa Express won the “Technology” category award at the European Supply Chain Excellence Awards.
Companies like these are approaching the day when supply chains work like process control rooms, where systems monitor status, generate predictive alarms, and translate operational targets into direct control actions. In SCP, powerful statistical engines and machine learning crunch huge quantities of incoming data behind the scenes. Inventory optimization automatically translates service policies into inventory mixes for profitable response. Planners and managers take a low-touch approach, fine-tuning the demand planning by applying creativity and specialist knowledge of the business.
You may remember that Joe Shamir and I wrote a blog where we called this change in the planning process as taking the planner from “in the loop” to “on the loop”. We didn't make this phrase up. It came from the world of semi-autonomous drones, where operators can leave much of the detailed decision making to the drone itself and only intervene with higher-level decisions.
Cecere added one extra step to the above scenario with her description of a “networks of networks.” Just as driverless cars will one day talk with one another and other entities across an interconnected environment, autonomous supply chains will network with unstructured demand signals and multiple points of sale, channels, and suppliers to automatically adapt the plan to changing demand—perhaps making it easier for customers to hail products like they hail an Uber.
Click below for an Infographic depicting Costa's highly autonomous supply chain planning.