Small business owners may find the thought of purchasing new technology daunting. It can often be expensive and difficult to implement. But as the amount of office products continues to grow, investment in technology can, in the long run, often make sense to the bottom line.
Here we focus on three technologies small businesses could use to their benefit. These technologies can deliver more: from 3D printing to AI and virtual reality, we explore how these innovations can make a big difference to a small business.
Until fairly recently, virtual worlds had been the stuff of science fiction. Today, virtual reality is a science fact, ranging from fully immersive and interactive narrative content, to the more linear experience of '360 video'.
The accessibility of VR has seen its use in commerce accelerate rapidly in the last few years. The Jaguar car company, for example, recently launched its new all-electric i-PACE concept entirely through VR. As part of a simultaneous immersive experience for over 250 motoring journalists from around the world, the company enabled discussion and individual exploration of the car, internally and externally, in a way that wouldn't have been possible in the real world.
When used for marketing or promotional work in this way, VR gets strong viewer reactions, says Sol Rogers, Founder and CEO of REWIND, the content production agency that worked alongside Imagination on the virtual car launch. 9 “People connect with the subject matter in a far deeper way than watching it on a TV screen.” The key to VR's success is the way it makes the technology “melt away”, he explains. Where film and television use tricks to absorb the viewer, VR succeeds by being a truly `transportative' medium. The Jaguar motoring journalists, to all intents and purposes, were in that car.
But is VR suitable for smaller firms? Whilst he advises against using it for the sake of it, Rogers notes that as the appetite for content is expanding, so the ability to deliver is becoming easier and cheaper. With prices for specialist `360 video' cameras at around GBP300, companies can afford to experiment, shooting their own content. This, he says, will help them gain an understanding of how VR can help grow their business and whether they want to invest in it.
For those who believe 3D printing is a novelty for schools and science programmes, think again. Alternatively known as additive layer manufacturing (ALM), it is currently being used for the low-volume production of high-specification components in sectors such as aerospace and ultra-high-end automotive, including F1.
By precisely layering materials according to a three-dimensional, computer-aided design, the process stacks layered slices, growing the component from the ground up, as opposed to traditionally machining solid blocks or forming in a mould.
ALM can work with a variety of metals, ceramics and polymers, helping to manufacture a virtually limitless set of customised designs, explains David Wimpenny, Chief Technologist, National Centre for Additive Manufacturing. Its on-demand nature, he adds, aids inventory control, and the process lends itself well to product experimentation. Today, low production volume issues are economically addressed by sheer process flexibility, says Wimpenny. Uptake of ALM to date has been focussed on highly-specialised areas, but it is now gaining traction at a broader level, growing at over 30 per cent per year. Estimates put the global value of the industry at over USD10 billion by 2021. The next generation of printers are already being geared to high volume production, notes Wimpenny. “We expect the productivity of ALM machines to increase a hundred-fold in the next ten years.”
Smaller firms not wishing to purchase equipment may today outsource larger production runs to specialist third party providers. These providers use economies of scale to reduce costs while also ensuring that the latest equipment is used. The sourcing process can even be managed through bidding websites such as 3Diligent.
The availability of such services, notes Wimpenny, enables designers to cost-effectively print, test and revise components, “stimulating their creativity and inventiveness”. He urges potential users to think in terms of entirely new use cases, not to replicate tried and trusted production models.
While we are nowhere near the stage where Artificial Intelligence (AI) makes all human effort redundant, there's a possibility that it will happen one day. The convergence of vast computing power combined with the explosion of Big Data needed to train algorithms means a perfect storm is being created for the rise of AI.
The most basic AI is `robotic process automation'. This can, for example, reconcile invoices, allocating them to the correct ledger. At the cutting edge are technologies such as Google's DeepMind which move into the `neural network' space, and are capable of self-learning to achieve its goals, with minimal or no human intervention.
For most business applications, the long-range forecast for AI is of less relevance than today's narrow, singularly task-focused AI. This can already be feasibly adopted to drive business benefits, says Rob McCargow, Programme Leader - Artificial Intelligence at PwC UK.
AI in common usage - the Google Now and Amazon Alexa `intelligent personal assistants', for example - demonstrates how the technology is undertaking specific learning tasks in the consumer space.
In business, exploitation of `natural language generation' (NLG) algorithms are trending. These can, for example, analyse multiple spreadsheets of quantitative data to produce a written fact-based narrative on the relationships within that data.
This is a practical proposition even for the smaller business, says McCargow. “By removing some of the more administratively burdensome tasks, it liberates staff to focus on more value-adding cognitive, creative and social activities.”
The cost of the technology has tended to limit its adoption. However, the increasing maturity of the algorithms, open source development, and significantly greater capacity for data storage and processing in the cloud, has driven down costs, to the point where its penetration of the SME space is indeed possible.
AI isn't risk-free. The current risks relate mostly to the kind of data usage guidelines laid down in regulations such as the EU General Data Protection Regulation (GDPR). However, the proper curation of data intended for future AI use is vital if, for example, the amplification of often inherent data bias is to be avoided.
A new all-party parliamentary group on AI in the UK is beginning to offer a step in the direction of cross-industry standards, notes McCargow. This is essential because the argument of `collaboration versus competition' will become more prominent as more businesses - including SMEs - seek an AI advantage.