The digital smartening of manufacturing has provided new tools for companies to advance their drive toward “pull,” where you make goods based on actual orders and current events and data instead of hit-or-miss forecasts. This has led to what is being called “smart pull,” where a digital collaboration platform capitalizes on big-data synergies—from domains like point-of-sale (POS) data feeds, social media consumer sentiment streams and manufacturing execution and intelligence systems—to help you calibrate production in closer proportion to actual demand.
It might sound like ancient history to some, but there was a time not that long ago when companies routinely built things and then “pushed” them toward buyers. They did their due diligence, of course, trying to ascertain beforehand if there was a market for their wares. But the market was largely “radio silent”—hard to fathom, and slow to give up its secrets.
The digital age has put that into the dustbin of history. Advanced sales and operations planning apps run frequent iterations to stay current with demand data. Sales data, both historical and timely, is accessible from enterprise databases and live flows of POS updates and social media sentiment. The marketplace is essentially hooked to an electrocardiogram, signaling continuously across a fog of pervasive computing so that any manufacturer with a modicum of data science smarts can see what’s selling where, in what volumes and at what velocity.
That’s the smart in pull—the market revealing its innermost secrets to “pull” a manufacturing “push.” Digital manufacturing is then more than up to the task. Manufacturing execution systems can quickly adjust the extant production plan, factoring in capacity and work-in-process to issue production signals and work instructions and execute to the live demand pointers.
Manufacturing intelligence systems further up the game, giving companies visibility into things like cycle times, scrap and rework totals, facility utilization, out-of-tolerance quality issues and conformance to schedule. This means digital manufacturers are not only producing to the pull signals—they are fine-tuning their push response to operate more efficiently and profitably.
Of course, demand and inventory never attain a 1:1 ratio. No one gets it completely right—as good as today’s puzzle-solving supply chain planning and optimization systems have become (and they are crucial to pull strategy). You may not like to see stock loafing around the warehouse, but you have to buffer goods, to satisfy demand hot spots that can’t be served fast enough through ramped-up production.
Pull is dependent on more than market signals and manufacturing adaptability. Partners across a multi-echelon supply chain must be similarly equipped with the ability to receive signals to stage lead times and production in sync with the final goods producer. That’d be pretty much enlightenment: everything aligned, such that pull and push become one.
Not going to happen, you’re thinking. But you’ve got a better shot at it when you have a collaboration platform in the cloud that your partners can access for their pull cues.
John Martin writes about technology, business, science, and general-interest topics. A former U.S. correspondent for The Economist (Science & Technology), he writes for the private sector, universities, and media, and can be reached at jm@jmagency.com.