Digital business execution is requiring more frequent and complex decision making, continuous problem solving and rapid pattern recognition, all of which require workforce digital dexterity.
In most organisations, however, responsibility for helping employees develop the desire and ability to exploit a wide range of transformative technologies — highlighted in the Gartner Hype Cycle for Digital Workplace, 2017 — does not have to rest with any group or individual.
“Humans will still be at the centre of work, even as intelligent software and machines become our co-workers. CIOs must anticipate how trends in business, society, technology and information will converge to change where, when, why and with whom we work,” says Matt Cain, vice-president and distinguished analyst at Gartner. “CIOs must expand their charter to include workforce digital dexterity.”
The Hype Cycle can help application leaders identity and exploit new and existing technologies that will boost employee engagement and agility for better business outcomes.
Technologies That Will Have a Transformational Impact in the Next Two to Five Years
Augmented data discovery enables business users and citizen data scientists to automatically find, visualize and act on exceptions, clusters and predictions in complex datasets, without having to build models or write algorithms.
Augmented data discovery can reduce time-consuming exploration and the false identification of less relevant insights. Segments, clusters, outliers and relationships are automatically applied to the data, and only the most statistically significant and relevant results are presented to the user in smart visualizations and/or natural-language narrations that are optimised, based on the user’s context.
Application leaders should start with a small list of specific business problems that cannot be solved with business intelligence and analytics platforms, and launch an augmented data discovery pilot to assess the viability of augmented data discovery, prove its value and build trust in it.
Personal analytics is the analysis of contextually relevant data to provide personalised insight, predictions and/or recommendations for the benefit of individual users. Examples include virtual health assistants, financial advice assistants and shopping assistants.
This sector of the virtual assistant market will reach mainstream adoption by 2020. Organisations can benefit from personal analytics by using the data collected to personalize products and services, and to deepen and extend customer relationships, or to assist with planning future services that meet new customer requirements.
Obstacles to the adoption of personal analytics include the challenge of integrating personal ecosystems of sensors and data feeds associated with individual users, as well as the business models required to support product development and marketing.
Technologies That Will Have a Transformational Impact in the Next Five to 10 Years
Conversational user interfaces (CUIs) are a high-level design model in which user and machine interactions primarily occur in the user’s spoken or written natural language. CUIs had huge growth in 2017, with chatbots, messaging platforms and virtual speakers contributing to the boom. The explosion in the availability of conversational platforms is making CUIs an alternative to graphical user interfaces.
“We expect application suite vendors to increasingly implement CUIs in front of business applications, leading to hundreds of different chat interfaces,” says Cain. “Most CUI implementations are not able to respond to complex queries. Increases in capabilities will, at first, largely come from improvements in natural-language understanding and speech recognition.”
Virtual assistants (VAs) help users or organizations with sets of tasks that previously could only be carried out by humans. VAs use artificial intelligence and machine learning to assist users or automate tasks. VAs listen and observe behaviors, build and maintain data models, and predict and recommend actions. They may act for the user, forming a relationship with the user over time. VAs’ importance will grow as society moves into the post-app era in the next five years.
It is unlikely that the VA market will have a single market leader, due to the fragmentation of ecosystems, but the major technology providers — such as Apple with Siri, Google with Google Assistant and Microsoft with Cortana — are likely to remain dominant.
“Businesses that have not begun the process of deploying VAs to interact with customers and employees should start now,” says Cain. “They should look for opportunities to use VAs to make users more productive with business apps and mobile platforms, and carefully measure the impact of VAs on behaviour and performance. Organisations should closely monitor the use of VAs, and be prepared to hand off to human agents to ensure customer satisfaction.”