According to the 2016 Australian Innovation System Report, every dollar spent on innovation by Australian businesses returns at least two dollars in earnings. With talk of innovation, digital transformation, and redevelopment of infrastructures infiltrating both the public and private sectors, research and development (R&D) initiatives to foster these future-thinking strategies is an ever-growing consideration. By Benjamin Pring.

This is particularly applicable to Australia, where businesses are able to claim tax offsets for R&D activities undertaken within the country. The policy demonstrates the Australian Government’s commitment to fostering innovation on Australian shores through R&D.

There is a catch, however. Without embracing artificial intelligence (AI) technologies, R&D is rendered pointless. True innovation comes from AI as businesses learn more about their industry and customers, and invest in research that will serve to create real business value.

Since innovation is typically desirable but frequently hard to define, AI should be employed in R&D not simply to improve products and services, but also to expedite business processes, improve sustainability and customer experience, as well as prioritise customer-led efforts.

Why guess when you can know the answer?

The major benefit AI offers R&D departments is the ability to access up-to-date data to justify decisions, which reduces risk and increases the chances of success. The ability to leverage continual insight into businesses, customers and the industry itself is crucial in a world ruled by data. R&D-based innovation without an AI platform could barely be considered R&D, due to the knock-on effects of guessing the key success factors without being positive of the outcome.

Another advantage of AI is the ability to glean valuable insight into customers and industries. In R&D, having access to data and real-time analytics means organisations are able to estimate various metrics such as consumer confidence, which previously was only measureable retrospectively.

The power of prediction will ensure organisations stay ahead of the curve. With a recent PwC survey finding that 83% of companies expect data and analytics will become increasingly important in decision-making over the next five years, businesses should embrace AI and data in order to streamline decision-making in R&D.

Change for the better

Innovation shouldn’t be looked at as a hunt for the next great breakthrough. Instead, businesses should ask how the new digital technology adds the most value. It’s vital that organisations view innovation as a series of small steps, rather than a sprint. With the new technology growing in importance, R&D processes have the potential to be revolutionised through AI across multiple levels:

  • Product innovation: AI platforms may be used to help monitor a fleet of machines as well as recognise which components fail prematurely. This, in turn, would enable businesses to inform the next wave of engineering, technological advancement and field service operations.
  • Process innovation: AI can monitor workflows, recognise any bottlenecks and suggest alternatives.
  • Customer-led innovation: AI can assist with ongoing reviews of how customers are actually using products and services to inform product management and pricing schemes.

By encouraging small discoveries, businesses will be able to change the very basis of competition. With the traditional mentality that a singular breakthrough is best, we’ve seen major players across industries quickly look to neutralise by mimicking the breakthrough in question. With a consistent, long-term approach, businesses will be gifted the advantage of stealth, thus making them nearly impossible to replicate.

Prioritise discovery

While taking a long-term approach has clear benefits for businesses when it comes to R&D, it is important to appreciate the power of discovery. Many businesses recognise that the future is uncertain, and that continuous discovery through a trial-and-error approach will serve businesses more than investment in singularly planned discoveries.

For forward-thinking, successful organisations, this means that a portfolio of initiatives based on discovery should be established in a manner similar to successful venture capitals. A clear lifecycle methodology should be leveraged from inception to the final result, be that success or failure.

But it’s not just venture capital that businesses can turn to for inspiration. Traditional businesses have also been seen to embrace this attitude to discovery, such as car manufacturer Toyota. It has been simultaneously investing in its conventional car models while at the same time working on innovative new driverless cars.

Organisation-wide, innovation should be prized. By embracing a culture of discovery, businesses will be able to demonstrate to all stakeholders, both internal and external, that a ‘business-as-usual’ attitude is not present or expected within the organisation.

Winning the innovation race

A recent Commonwealth Bank report suggested that Australian businesses investing in innovation are the future of our national economy, set to unlock an additional $44bn in value from the regional sector alone. Those that fail to innovate and adapt to changing preferences, expectations and technologies are the ones who’ll be left in the dust while their competitors speed ahead.

Internationally, for example, we’ve seen streaming giant Netflix adapt to its customers and speed up its R&D processes to provide an offering that was previously unavailable, yet in demand by consumers. By leveraging innovation fuelled by AI, companies will able to disrupt their respective industries, much like Netflix, and move quicker to incorporate new learnings. Furthermore, businesses that effectively leverage machine-made insights will quickly develop a roadmap to navigate their ongoing expansions.

With innovation constantly growing in value across industries and fields, R&D into new technologies and processes have never been so vital to success. Data and AI are helping businesses create new growth opportunities by inspiring long-term change, and without them, R&D becomes ineffective.

Benjamin Pring is the Director of the Centre for the Future of Work at Cognizant. He is also the co-author of ‘What To Do When Machines Do Everything’.