The Most Boring Problem In Supply Chain — And The Most Important
To achieve extraordinary outcomes from AI and enterprise software, start by doing the “boring work” of data quality management.
This is a post about a boring topic: data management.
But please, stay with me. I know you’d rather read about AI agents, robots, tariffs, or just about anything else other than data — but like your mom getting you to eat veggies as a kid, you gotta put data management on your plate in 2026.
The catalyst for this post was a new study published by IBM last month.
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Is Your Forecast Process Really Adding Value?
Forecast Value Added (FVA) is a metric used to evaluate the effectiveness of forecasting processes by determining which steps, methods, or participants improve — or degrade — forecast accuracy. Organizations use FVA to identify where their forecasting efforts add value and where they might be introducing unnecessary error or bias. This survey explored how supply chain and logistics professionals view FVA today: how familiar they are with it, whether and how they use it, and what benefits or challenges they have experienced when applying it in practice.
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