Richard Beukes

The Setup

Most enterprise software projects start with a 6-month discovery phase, 18 months of development, and a budget that makes your CFO cry. This one started with a Friday evening and a clear spec in my head from years of watching manufacturing operations struggle with disconnected tools.

The Method

I used an AI-assisted council approach — multiple specialised agents working in parallel, each handling a different domain (database models, API routes, UI components, business logic validation). The key wasn't that AI wrote the code. The key was that I'd spent 25 years understanding what the code needed to do. AI was the force multiplier. Domain knowledge was the foundation.

What Got Built

• Production tracking with real-time OEE dashboards
• Quality management — NCR, SCAR, SPC charts, 5S audits
• Maintenance — work orders, PM schedules, spare parts
• HR — training matrices, skills tracking, compliance
• Legal — contract management with PDF generation
• Finance, procurement, warehouse, energy, facilities
• Executive command center with cross-department KPIs

The Lesson for Leadership

You don't need a team of 40 and an 18-month timeline to build enterprise software. You need someone who deeply understands the problem domain, modern tooling that removes boilerplate, and the discipline to ship iteratively. The 48-hour version wasn't perfect — but it was in production, collecting real data, before most projects would have finished their requirements document.

For New IT Staff

Start building things. Don't wait for permission or perfect conditions. The best way to understand enterprise systems is to build one. Use Next.js, Prisma, and TypeScript — they'll get you from zero to production faster than anything else in 2026. And always start with the data model. If your schema is right, the rest follows.

The Problem

I've watched companies across South Africa, Kenya, and Nigeria pour budgets into ERP systems designed in Stuttgart or Redmond. These are good systems — for the markets they were built for. But African manufacturing has a different reality:

• Load-shedding can kill a production run mid-shift. Your software needs to handle ungraceful shutdowns and data recovery
• Multi-currency isn't a nice-to-have — it's daily life when you operate in ZAR, NGN, and KES simultaneously
• Compliance frameworks like POPIA (South Africa), NDPA (Nigeria), and Kenya's DPA have specific requirements that Western ERPs don't natively support
• Internet connectivity at factory sites can be unreliable — satellite-linked, not fibre
• Local tax rules, BBBEE scoring, and regional reporting requirements need native support, not bolt-on consultancy

The Opportunity

African engineers who've stood on factory floors, dealt with generator switchovers, and navigated multi-country compliance are uniquely positioned to build the next generation of manufacturing software. Not by copying SAP, but by designing systems that embrace the constraints rather than fighting them.

What Leadership Should Consider

Before signing your next R110M ERP contract, ask: does this vendor understand that your Kenyan plant runs on backup power 4 hours a day? Do they know that your procurement team needs to switch between three currencies in a single purchase order? Have they tested their system on a 2Mbps satellite link?

The answer is usually no. And the workaround costs more than building something right.

For New IT Staff

Learn the business first. Technology is the easy part. Understanding why a quality inspector on a factory floor in Lekki needs different workflows than one in Johannesburg — that's the knowledge that makes you irreplaceable. Visit the floor. Watch the processes. Then build.

The Data Silo Problem

In a typical manufacturing operation, data lives in at least 5 disconnected systems: the ERP handles finance and procurement, SCADA monitors production lines, a separate quality system tracks NCRs, HR has its own platform, and maintenance logs live in spreadsheets. None of them talk to each other natively.

When the CEO asks "what was our OEE last week across all lines?" — that question touches four systems and takes someone a day to answer manually. That's not a technology problem. It's an architecture problem.

The Integration Approach

• SCADA to Database: OPC-UA connections pull real-time production data from PLCs into structured storage. Every gauge reading, every cycle count, every alarm — captured automatically
• ERP Sync: Read-only connections to SAP or equivalent, pulling master data (materials, BOMs, vendors) without risking write-backs that could corrupt production systems
• Custom Platform as Hub: A purpose-built web platform becomes the single source of truth — aggregating data from SCADA, ERP, quality, maintenance, and HR into unified dashboards
• Automated Triggers: When SPC charts detect out-of-spec conditions, NCRs generate automatically. When maintenance is overdue, work orders create themselves. When contracts expire, legal gets notified 90 days out

For Leadership

The ROI of data integration isn't a new report. It's the decisions that become possible when you can see across departments in real time. It's catching a quality trend before it becomes a customer complaint. It's knowing your true production cost per unit, not the estimate from last quarter's spreadsheet.

For New IT Staff

Learn SQL. Seriously. Every system you'll ever integrate speaks SQL at some level. Understand how to read a database schema, write a JOIN across tables, and build a simple ETL pipeline. Then learn an ORM like Prisma that lets you move fast without writing raw queries for everything. The person who can pull data from three systems and present it in one dashboard will always have a job in manufacturing IT.