The drive to automate is relentless. But, unfortunately, it’s bound up in the assumption that automation will automatically result in reduced costs, higher productivity and improved production quality.

With all the benefits on the horizon, how could anything go wrong? Realistically, simply automating to reduce complexity can lead to expensive projects that never deliver a return on investment. Why? Automation is expensive. It includes the purchase of machinery, new tools, downtime, and even new jobs with specialist skills to ensure the project is deployed correctly. Similarly, without achieving the right balance between what ‘can’, ‘should’ and ‘needs’ to be automated can be the difference between success and failure. So, how do you assess what needs to be automated? This article examines three critical components of assessment to determine whether automation is suitable.  

1. Determine if it is feasible; not all process automation results in improved efficiency.

The lure of automation has drawn many operations managers into the downward spiral of immense costs, and artificial intelligence (AI) projects that never come to fruition. The automation strategy for Model 3 is a great example of hyper-automation failure. Elon Musk stated after the project, ‘yes, excessive automation at Telsa was a mistake. To be precise, my mistake. Humans are underrated’. So, how did this happen? The team at Telsa developed an assembly line that was called the most robotics-driven production line in the world. However, during production, the complex network of conveyor belts constantly failed, causing production overtime and ultimately was removed. What are the learnings from this mistake? Importantly, across production lines, there must be a balance between skilled employees and equipment automation. Identifying which processes are right for automation and which are not is vital to avoiding the pitfalls of automation failure.

2. Work out the cost of equipment, tools, labour and downtime.

Not all processes are equally suited and reap the intended rewards of automation. Before devising an automation strategy, utilise four categories to assess if automation is worth the investment:

1. Time and Simplicity: Does the current process take less than 15 minutes or six steps to complete?
2. Frequency: How frequently is the process performed?
3. Repeatability: How repeatable is the process?
4. Human Intervention: How much qualitative analysis and human action is required to deliver the process?

Although complete process automation can tempt even the greatest operationally minded people, knowing the cost of automation versus maintaining a particular process will determine the value of the automation itself. Much of the costs related to automation requires upfront payment for equipment, tools and technology. These upfront payments are costly, especially as the benefits are not attributed until automation is in full effect. Once you’ve analysed fixed cost outlay, you’ll need to factor in current processes. For example, establish the cost of labour, production downtime, and the adoption timeframe. The actual benefits of automation will be acquired when focusing on cost and identifying which systems are dysfunctional. Therefore, improving unplanned shutdowns, processes that add to production costs, bottlenecks or are dangerous activities should be the focus of the automation strategy.  

3. Define clear objectives and measures for the automation

When considering deploying automation in a business, the strategy must consist of clear objectives, workforce impact and measurement. Being explicit with goals can prevent misalignment of expectations across management and plant operators. With objectives in place, there needs to be a consistent measurement of production systems against the automation target. Complete measurement across production systems, instruments and tools will produce vital data that pave the pathway forward. Measuring effort, lag, waste, idle time, issues and costs all tell a story. This story allows for a step-change in performance management. Referring to the objectives and intended outcome provides visibility across which step in the process needs to be corrected and does not meet the defined tolerances. Digitising operations allows for transparency across operations that can serve as a competitive advantage. For example, data transparency can provide visibility to the customers regarding how quickly one can fulfil orders. To enable integrated production systems, you need to ensure that you have the suitable systems to measure production performance. Key indicators will help you prioritise automation projects and build a faster return on investment. A critical system to create interconnection of data is having a powerful MES. MES ensures that businesses can maximise their data capacity and literacy by having clarity over the inordinate amount of data produced. The team at Klugo specialise in MES implementation. Using key fundamentals of vision, outlining deliverables and measurement, our team can ensure end-to-end deployment. Schedule a call with the team today to learn more about MES and how it can assist your automation strategy.  

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