....and the answer is: REAL TIME supply chain management
IT companies have for years talked up the idea of manufacturers using software that provides Supply Chain Planners with real time visibility & control. In recent years we have seen the arrival of systems that supposedly get close to it such as SAP with their IBP and Kinaxis/O9/OMP/Blue Yonder etc with 'concurrent planning'.
For instance, Kinaxis claim the latter is a "new holistic model that takes into view the whole planning network and aligns data so that a change in one part of the supply chain triggers corresponding changes and communications in the rest of the chain, in near-real time" (1)
Really?
But let's think about it - how can visibility & real time control have any benefit? After all, materials move through a supply chain relatively slowly - any particular piece is static, experiencing no value-add for >95% of its lead-time. So what's the rush, how will real time visibility & control enable materials supply to move faster &/or be better aligned with demand?
One answer might be that it would allow Planners to update and amend their SCM/Manufacturing activities in line with actual demand much more frequently (maybe continuously & automatically with AI) ? Yes it would but is that really such a good thing? Every time a Planner intervenes to amend the schedules, interrupted items get delayed and their lead-times increased, leading to further expedites later on when a delayed arrival / backorder threat is envisaged (b/c. lead-times are not fixed, they increase as capacity tightens). In addition, interventions cost unplanned change-over capacity and the interrupted upstream inventories become congested, build and grow.
Given that Planners already spend a lot of time expediting, is more going to help? Clearly not, in fact it'll make things worse, read here about the experience at Premier Foods and others.
How to Align Supply with Demand
So what can be done to continuously align material supply with demand ?
For a start you could drive ex-stock replenishment with actual demand instead of with inevitably inaccurate forecasts, master production schedules and lots of corrective expedites (2). Simple re-order point/cycle pull mechanisms (ROP/ROC), despite not being a "hot topic", actually do this very well by simply replacing consumed inventory, thereby being demand-driven and not requiring interventions.
With periodic parameter management ROP/ROC pull can also easily handle trend and, with timely collaboration between Supply Planning and Commercial, they can support, when necessary, advance stock builds for exceptional promotions, tender wins, cap.constrained seasonality, NPL etc.
Secondly, we all know that sometimes things go wrong in manufacturing so re-double endeavours with Lean TPM/TQM/Standard Work/Mistake Proofing etc. Even that, however, will not eliminate all supply side variability, so to avoid natural variation propagating up and down the supply chain and disrupting material movements, use multiple pull re-order point/cycle de-coupling points - not just at a single finished goods location but also across the distribution network, at raw materials, break-bulk/dis-aggregation positions in the factory, behind & in front of bottleneck work stations, in front of ATO operations etc.
ROP/ROC pull also allows those activities to operate completely independently of each other, with their own cycles and lead-times: effectively each work centre is able to identify its own maximally efficient replenishment sequence/cycle and just get on with topping up each item to target, without being actively scheduled, thereby providing seamless down stream service and autonomously supporting end-to-end flow.
How to Align Supply with Demand (in Real Time)
None of these actions, however, are going to deliver material movements that align in real time with demand. That's because we're usually using batches to enable us to process multiple products through the same work centres, so individual pieces inevitably have to wait to be processed, get processed and then wait again for the rest of the batch to catch up.
The way to reduce this waiting / non value-add time is to use split batches (ie. don't wait for the entire batch to be processed before moving the pieces onto the next process) and/or reduce batch size, without losing capacity, using quick change-over techniques (ie. SMED). If you could get batches down to a size of one you'd be achieving perfection with 'one piece flow': every piece would move forward in synchronisation with downstream consumption, just like flowing water (3).
So, if you want your supply chain materials/products to move towards continuously flowing in real-time alignment with demand (ie. perfect flow) you don't need real-time control. What you do need is adequate processing capacity via S&OP/IBP (and scenario planning which concurrent planning is very quick at), demand-driven, decoupled and sequenced pull replenishment, the appropriate Lean tools and as small a batch size as you can possibly achieve.
The IT you need to operate at scale
The demands upon IT for all of this, far from being highly expensive, 'sophisticated' and complex, are quite simple; here's the decoupled & enterprise-wide pull / Demand Driven MRP softwares that operate through your ERP transaction system to provide all the necessary ROP/ROC functionality including parameter calibration, forecast driven capacity planning/IBP/S&OP, recognition and management of events and many other complex planning challenges.
Evidence
You may be sceptical, can it really be so simple? Here's multiple DDMRP case-studies that show demand-driven, decoupled & sequenced (not scheduled) supply chains deliver desired service levels with a c40% drop in aggregate, average inventory, shorter lead-times and significantly less capacity cost
And you might want to take a lead from academia
To learn more have a look at:
Factory flow is non-linear so don't use master production schedules
Decoupled supply chains: faster, more agile & lower cost
SC Planning: Sequence, don't Schedule
Excellent forecast mix accuracy (ie. 100% - agg. of fc errors / agg. fc) of 80% hides the fact that c80% of your item forecasts (ie. medium to low volume / higher variabilities) are tracking at >40% wrong.
Neither water or supply chains need 'Big Tech' to tell them how to flow