Why Kenyan procurement teams spend hours retyping orders

Kenyan businesses lose countless hours each week as procurement teams struggle to process orders that arrive through WhatsApp messages, scanned documents and handwritten notes rather than formal systems.

The fragmented nature of local purchase orders has created a hidden inefficiency in supply chains across the country, with staff spending significant portions of their workday transcribing data from informal channels into enterprise systems.

"This fragmented process created inefficiencies across entire supply chains, leading to delays, costly mistakes and disconnected systems," observed Alexander Odhiambo, chief executive of Solutech Limited.

The disconnect persists despite many businesses investing in enterprise resource planning systems such as SAP, Odoo and Sage.

 Orders continue to flow through informal channels while expensive software sits waiting for manual input.

For distributors serving supermarkets and retail outlets, a single purchase order might arrive as a photograph on WhatsApp in the morning, a scanned PDF by email at noon and a handwritten note delivered by a driver in the afternoon.

Each format requires a staff member to read, interpret and manually key details into company systems.

The problem reflects how formal and informal business practices coexist in African markets. While head offices may operate sophisticated software, buyers on the ground often rely on whatever communication method proves fastest and most convenient.

Automation tools using artificial intelligence have emerged as one solution to the format chaos.

Such systems can read and extract order details from multiple file types and message formats before transmitting them directly to company databases.

"Today, we have automation tools that are helping organisations to move from manual reactions to intelligent operations," noted Odhiambo.

Odhaimabo says companies deploying such technology report that AI can process orders in seconds with accuracy rates approaching 99 per cent, compared to the hours required for manual transcription.