You do not need AI — you need a better process

They wanted AI to fix their problem. What they really needed was a better process.

Let me take you back to a project with a small manufacturing company — let's call them "Smith Fabricators." They had a solid business of about 50 employees, rolling out custom metal parts for a variety of industries. What they didn't have was a streamlined process for handling orders and inventory. Every week, their sales manager spent hours manually checking stock levels, tracking orders, and updating spreadsheets.

The Situation: A Need for Efficiency

Smith Fabricators came to me with a clear goal: automate their inventory management using AI. The idea was that AI could predict stock needs, optimize their supply chain, and free up their sales manager to focus on what truly mattered — growing the business.

The Complication: Overestimating AI's Role

Here's where the plot thickens. They were convinced that AI was the silver bullet they needed because they had read countless articles touting AI's magical abilities. But, when I dug deeper, it became clear that their existing processes were not ready for automation, let alone AI. They had no standardized way to track orders, stock levels were updated sporadically, and data entry errors were rampant. An AI system could only amplify these issues, not solve them.

The Resolution: A Better Process First

I proposed a different approach. Instead of jumping straight into AI, we first needed to address the glaring inefficiencies in their existing processes. We started by implementing a basic, custom software solution tailored to their needs. This software automated the mundane tasks of inventory tracking and order processing—business automation—reducing the workload significantly.

It was a straightforward system, built for about $15,000, that integrated with their existing tools and required minimal training. Within three months, we saw tangible results: the sales manager's weekly grind turned into a 20-minute task, errors dropped by 80%, and they could finally predict inventory needs accurately.

The Lesson: Process Over AI

So, what can you take from Smith Fabricators’ story? Don't overestimate AI's role in solving process problems. Start by evaluating your current workflows. Are they optimized? Can they be automated? Often, companies chalk up inefficiencies to a lack of AI when the real culprit is an outdated process.

Before you invest in AI, ensure that your foundational processes are streamlined and capable of handling the insights that AI can provide. You'll avoid the common pitfall of pouring money into tech that can't deliver without the right groundwork.

If you're considering a tech overhaul for your business, remember: you might not need AI — you need a better process.