What’s really required is real-time “always on” planning and execution capabilities that eliminate the information lead times between unplanned shifts in consumer demand or supply capability.
The big joke among us mathematicians in today’s competitive landscape is that “We market around AI, recruit around ML, and apply regression when problem solving!”
In reality, regression still makes up a big part of our analytical activities. Further, we still apply quite a mix of mathematical approaches to solve for real world problems in our supply networks including:
Let’s think about what is really happening in our supply network. The ecosystem is rewarded when an end consumer purchases a product or service. Let’s call this time zero or the “moment of truth”. Now let’s travel backward in time from this moment of truth through our supply network - hours prior to purchase, days, weeks, and months.
Yesterday’s systems will certainly enable monthly, weekly, or even daily planning and execution but this is no longer enough. Real-time “always on” planning and execution capabilities that eliminate the information lead times between unplanned shifts in consumer demand or supply capability are required.
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