We had a coffee manufacturer as a client whose operational challenges centered around maintaining product quality through moisture control, a critical factor impacting yield. The process was inefficient, relying on inconsistent human input for adjusting moisture levels, which varied widely among operators.

This lack of standardization in managing key variables like temperature and pressure resulted in significant product loss due to over drying, ultimately reducing profitability. Such operational inefficiencies, driven by the absence of data-driven processes, drained resources and created a “Bull-Whip Effect” that exacerbated yield losses. If left unchecked, these issues could lead to wasted investments and diminished returns.

For investors, this scenario highlights key risks around scalability, data management, and process optimization. Without automation, inefficiencies can grow with operations, increasing losses. Although IIOT sensors provided valuable data, it wasn’t effectively leveraged, leading to missed opportunities. Reliance on manual expertise over a data-driven approach created uncertainty in forecasting and scaling. This dependence not only impacted yield but also threatened long-term scalability and investor confidence.

However, through precise analytics and targeted interventions, Codenatives transformed this challenge into a lucrative opportunity, resulting in substantial financial gains.