if u just look on recent years data, and predict your forecast than yeah, u are right f-to-f is much better. However if u follow up your clients movements on data reviews and chase them for proper prediction&forecast than its the most valuable tool that would enable your production/prediction success.
The 2010 was the year of recovery, fight for capacity and customers. The common point for 3 company is that they were able to delivery on time, supply products even to customers with whom theyve made none biz in the past.
Forecasting is not an exact science primarily because the forecaster cannot control what the customer actually does. At best forecasting is a guide. At worst, it is a crutch which can never take the place of good feet on the street in continual contact with customers.
Lastly, a forecast is only as good as the data at the time of the forecast. S*&$#% happens and the next thing you know, you miss the forecast...for better or worse.
Better to put your forecasting efforts into quality customer face-to-face time! The payoff is far better.
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.