Robots are being used to speed efficiencies and remove some of the administrative tasks that can slow down an engineer. However, with RPA being less common in the engineering sector, it can be met with some suspicion. Expleo’s Rebecca Keenan explains the twin opportunities of RPA in engineering that make sense on both a business and an individual level. Discover her 5 top tips for making RPA stick.
Within customer-facing sectors such as financial services, utilities and retail, process automation is already changing the way that organisations service their customers and workforce. However, in more industrial processes, such as engineering, the growth of Robotic Process Automation (RPA) is still embryonic by comparison.
Not for long. The potential for change in engineering is enormous, with two clear opportunities. Firstly, there are the clerical, back office processes that are common to all industries. For example, HR and finance departments, contact centres, supply chain management and so on: these are areas where RPA has made its name in recent years. Engineering firms can benefit from the same quick wins.
Then, there are more bespoke elements, whether in design or production, to help reduce tedious activity. For example, if a process is highly repetitive and rules based, with only the underlying data changing, there is opportunity to automate. Not only will this speed up these processes, but it will reduce the potential for human error, which can lead to delays further down the line.
Human-in-the-loop automation is the next step, combining the human and digital workforce. For example, a robot could pull information from a CAD system, perform some initial updates, then present the findings back to an engineer on the factory floor. The engineer can make any changes, add data or confirm aspects, then send it back to the robot for finishing.
There is scope too for predictive analytics by bringing in data science and machine learning to increase the power of automation to your organisation. Why not entrust robots to calculate the optimum moment to replace a part of a vehicle or tool, and then order that part to arrive where it’s needed, just in time? The sky is the limit.
Turning the corner
5 top tips for making RPA work in engineering
- Have a vision of what success looks like before you start. Creating a vision and aligning it with your organisations overall strategy and goals will allow you to gain maximum benefits from your process automation initiatives. Outline how RPA will transform your processes and improve business performance across the entire organisation.
- The cultural change is often more challenging than the technical. Preconceptions and personal fears must be addressed openly, with full buy-in and vocal support from the leadership team. A Senior Steering Committee, including the heads of quality, IT, HR, engineering and procurement, will help unite the different entities within the organisation under a common message. Without board level support, it’s rare to see RPA programmes succeed. Education is always key. You have got to bring people on the journey with you. Keeping the robotics team secret just leads to distrust and resentment.
- To turn a pilot into scaled and lasting success, you need to treat RPA as a transformation programme. Don’t think in terms of a single robot in one part of the business, but rather the first robot of hundreds that could drive efficiency in years to come. In that way, you will get further down the track of making the necessary cultural changes in the whole organisation.
- Process optimization prior to automation can make a significant difference to what you can automate and increase the benefits to your organisation. A focused approach to process pipeline creation and prioritisation should be taken.
- Ensure you have metrics in place to track the success of your implementation. You should always measure the performance of your processes before automation. This will help with benefits realisation. It will also be a help if you need to optimise your robot. Processes are continuously made more efficient as feedback and data from the entire digital workforce is captured, consolidated and analysed.