Historically, the role of technology in the organisation has largely been about driving efficiency, but it is now evolving beyond that towards enhancing the capabilities of the workforce by becoming a collaborative partner.
Among the technologies behind this important development are more natural human interfaces, wearable devices and smart machines. The evolution of intelligent technologies and sophisticated interfaces is enabling machines to work alongside and collaborate with humans.
A major benefit of this teamwork approach is that it leverages the unique capabilities of human talent and machines in a way that adds tremendous value to the organisation.
Machines are unmatched when it comes to precision and consistency while humans have the edge in areas such as creativity, contextual understanding and complex communications.
This collaboration trend was identified in the Accenture Technology Vision 2015 report, an annual outlook on global technology trends.
Among its conclusions is that businesses need to recognise technology is more than just a set of tools – rather, it's a partner in a collaborative workforce. A strong motive to adopt this approach is the potential for fast gains in return on investment.
Research firm Gartner predicts that, by 2018, the total cost of ownership for business operations will be 30% lower than today due to the wider use of smart machines and industrialised services. Indeed, this trend is already emerging rapidly across the economy and seeping into everyday life.
For example, there's been much discussion about the development of driverless cars. In the interim many leading car manufacturers have announced models with semi-autonomous driving and navigational capabilities designed to enhance the driver's experience making their journeys safer and easier.
Interfaces enable closer co-operation
A key enabler behind this co-operation lies in the interfaces. Advances in natural language processing (NLP) and speech recognition are making it a lot easier for humans to interact with machines in real time. Speech recognition is becoming more effective thanks to the growing capability of machines to “understand” unstructured conversations.
This is aided by the ability of machines to make instant internet searches and to use contextual clues. At the same time they are becoming more effective at incorporating user feedback to improve their accuracy.
Such is the interest in NLP technologies that the market for this application is expected to grow quickly to reach $10bn by 2018 from $3.7bn in 2013.
Read more about smart machines
Some computer experts are even predicting that voice and image queries will become more prevalent than text-based ones in five years, partly reflecting the growth of more human-like interactions with intelligent software.
This dovetails with the explosive growth in wearable devices as a factor that is forcing organisations to rethink how they manage their workforces. Wearables enable staff to collect and share data more quickly and collaborate more effectively, which in turn enhances productivity.
These devices can collect data via sensors, display it to the user and some can enhance a person's physical capability. The US military provides an interesting insight into one path of evolution for wearables - it is experimenting with so-called exoskeletons or wearable robots, designed to dramatically enhance human physical strength.
Positioning to reap the benefits
To reap the tremendous benefits of enhancing human capital with technology, companies must educate and train their workforces to use it optimally and to be comfortable with it. In a bid to speed up the process, some companies are turning to massive open online courses (Moocs) to provide quality training across the workforce.
Stanford University provides an interesting case study of human and technology collaboration. With the use of machine learning it has halved the amount of effort it expends on giving feedback to students for code submissions on some of its Moocs. Thanks to this innovation, the university can respond to 25% of the course students with almost real-time feedback.
However, they also need to invest in their machines so humans can work with them effectively. MIT researchers showed one way of doing this when they demonstrated industrial robots training by observing the work patterns of individual employees.
For some tasks they can figure out how to do them more efficiently and effectively to reduce errors without having to change a person's work style.
However, such a workforce does pose many questions. These range from how duties should be assigned, governance procedures to inform those decisions, through to the kind of training needed and the degree of specialisation that is required in this blended workforce.
Answering those questions and finding the right balance is no easy task, but companies who manage to redesign their workforces to maximise human and technological potential stand to gain strong long-term competitive advantages.
