Automation is quickly becoming a major part of businesses across many industries, particularly in manufacturing, where global sales of industrial robots are expected to almost double in volume by 2018, reaching 400,000 units.

However, with the average consumer home becoming increasingly connected with the introduction of smart meters and fridges, revenue from the home automation segment alone is expected to hit over $6 million this year and show an annual growth rate of CAGR 28.19%. A clear indication that ‘robots’ already have a prominent presence and strong influence upon life as we know it.

Growth in autonomous vehicles

The automotive industry is experiencing one of the biggest areas of growth in the automation market, due to the increasing appetite for fully autonomous, self-drive vehicles.

Late last month, it was announced that a new law in California will allow an autonomous public transport shuttle to be tested on public roads without a driver.

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Self-driving cars are already allowed to be tested on California public roads by 15 car manufacturers; technology companies and start-ups, including Alphabet’s Google, Ford, Honda and Tesla. But under current state regulations, vehicles must have a person in the driver’s seat for monitoring, and the car must have brakes and a steering wheel.

This new change in law allows for the first fully-autonomous vehicle without a steering wheel, brakes, accelerator or operator.

A move similar to this by automotive giant Mercedes-Benz, saw the firm preview the potential future of urban transportation by trialling an autonomous CityPilot bus in Amsterdam. It was claimed that innovations such as this would make public transport operate “even more safely, efficiently, and comfortably”.

Safety benefits

This claim of the safety benefits is maybe not as flippant as it first sounds. Science fiction films often feature a central computer that is a collective amalgamation of numerous thoughts. But there is no reason for it to remain fiction.

An automated vehicle could be the safest on the road were it to tap into a collective driving experience. Think of how you yourself drive home from work, go through traffic lights and circumvent roundabouts. It is all done naturally through a built up knowledge from 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.

Generation of valuable data

This data can be used by city planners across the globe who are falling over themselves to develop ‘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 if the technology fails, the plan is to gradually phase the human out in 2019. The pilot ends in 2020 with a view to rolling out a wider deployment after that.

The cars will be fitted with software that will allow commuters to book them, in a similar way to ride-sharing services Uber and Lyft. Similar pilot programmes in the US and Europe are likely to be announced later this year.

Driven, in part, by the wider trend for digital transformation, automation is here to stay. What is important is 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 integrate. This makes quality assurance and testing of such integrated systems far more complex and, therefore, demand complex automated test strategies.

The only way to assure that a business works as it should is to continuously test the entire business process, to ensure that an upgrade being implemented at one part of the digital ‘chain’ won’t affect digital operations elsewhere.

The need for humans

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.

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Because of this, it is never wise to completely remove humans from the quality assurance process – however, software quality firm SQS believes at least 30% of transactional activities involving IT will be automated by robots over the next five to ten years.

The automation of a business process needs to be underpinned by a comprehensive end-to-end quality assurance plan that includes an optimum combination of automated static analysis and expert human review. Any quality assurance needs to be done from the very beginning of a product or service development, and continued throughout.

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.

Sourced from Dik Vos, CEO, SQS