Automation is becoming commonplace around the world and across most industries. The manufacturing sector, for example, is expecting global sales of industrial robots to almost double in volume by 2018. In the home, revenue from the home automation segment is expected to hit over $6 million this year and show an annual growth rate of CAGR 28.19%. Yet, one of the biggest areas for the adoption automation is in the automotive industry.
With the appetite for fully autonomous, self-drive vehicles growing, we are currently staring down the barrel of both automotive and autonomy history. Both personal and public transport will be transformed. Automotive giant Mercedes-Benz previewed its autonomous CityPilot bus in Amsterdam earlier this year, in a move that it claimed would make public transport operate “even more safely, efficiently and comfortably”. The potential future of urban transportation is changing, thrusting automation into at the heart of humanity’s digital evolution.
It may sound flippant, but Mercedes Benz’s claim of increased safety shouldn’t be dismissed. Science fiction films often feature a central computer that is a collective amalgamation of numerous thoughts, but there’s no reason for these computers to continue to only exist in fiction and films. An automated vehicle could be the safest on the road were it to tap into the collective driving experience. Think back to how you yourself drive to destinations of your choice, you go through traffic lights and circumvent roundabouts. It’s all done naturally through a built up knowledge through experience. Now, imagine that the experiences from all of the drivers in the UK are uploaded into one database and used to drive the automated cars of the future. The automated car would be a driver with millions of years’ experience.
This would be the ultimate in collective consciousness big data. Yet, as with big data in all its forms, the valuable information lying beneath needs to be unlocked through effective analytics so that the findings can be processed, extrapolated and used correctly.
This data can be used by city planners across the globe, all of whom are rushing to develop the greatly anticipated ‘smart cities’ built upon automation. For instance, in an effort to address the growing problems of congestion on the roads, Singapore has recently started testing a small fleet of automated Audi taxis to carry passengers around a business park. The driverless cabs are thought to reduce the cost of an average journey by 70 % by removing the need for a driver. Although the cars will initially have drivers ready to take over just in case the technology fails, the plan is to gradually phase out humans by 2019. With the pilot ending in 2020 with a view to rolling out a wider deployment, we don’t have long to wait until automation takes over our lives with similar pilot programmes in the US and Europe are likely to be announced later this year, automation is here to stay.
Driven, in part, by the wider trend for digital transformation, it’s important to look at automation from the entire business perspective and end-to-end process. Organisations 20 years ago would automate a software test on a straightforward algorithm, however now we have a mass of integrated systems, as well as embedded software and engineering, that must be integrated. This makes quality assurance and the testing of these integrated systems far more complex and demands complex automated test strategies.
The only way to ensure a business is working properly is to continuously test the entire business process and to ensure that an upgrade being implemented at one part of the digital ‘chain’ won’t affect digital operations elsewhere.
Whilst it is possible to pool together combined knowledge into actionable digital intelligence that can be used to automate the majority of the quality assurance process, it is important to remember that it takes a human to predict what a human will do. Thus, it is never wise to completely remove humans from the quality assurance process, however we believe at least 30% of transactional activities involving IT will be automated by robots over the next 5-10 years.
It is vital that the automation of a business process is underpinned by a comprehensive end-to-end quality assurance plan that includes an optimum combination of automated static analysis and expert human review. Any and all quality assurance needs to be bought into the automation process from the very beginning of a product or service’s development and continued throughout. Organisations that don’t do this will soon realise it is not enough to just test the new process to see if it will pass or not. The advisory capacity of domain knowledge is crucial to ensuring that automation isn’t simply an automatic route to disaster.