Making predictions about the course and impact of technology is fraught with difficulties, even a year out. We saw in 2016 that a game concept that was poorly reviewed ended up being downloaded more than 500m times globally and driving significant value to the company that released Pokemon Go, realising some of the hyped potential of VR (Virtual Reality) gaming.
In 1998 the management writer Peter Drucker claimed that “Thirty years from now the big university campuses will be relics. Universities won’t survive.” Twenty years on Universities have survived but they have evolved significantly and the nature of the campus has changed. Peter Drucker’s headline might not have eventuated, but he was right to pick up on evolving technology being disruptive to the way education was delivered.
Sometimes the hype just doesn’t eventuate and sometimes it takes longer for the promises to materialise. Over the last 5 years, the promise and hype of Big Data has dominated IT thinking. The ability to create extremely large data sets that when analysed, can computationally reveal patterns, trends, and associations, especially relating to human behaviour and interactions has evolved and linked with other major trends, IoT (Internet of Things) and Machine Learning.
Machine Learning has taken some massive strides forward in the past few years, enhancing Google’s core search engine algorithm, better recommended products in consumer applications, workforce management in contact centres. But again, we’ve only seen it in a limited range of applications. We expect to see machine learning updates emerge across the board to become an expected component of every form of technology.
We have been hearing about connected fridges, connected cars and connected homes for years now, but the Internet of Things solutions have been slow to come. Partly because of the lack of common platforms and frameworks to connect all these components and partly because of the complexity in managing the data to integrate all but some fairly straight forward solutions. The expectation has been that manufacturing, agribusiness and health would be the major driver for these solutions, but we are also seeing more physical digital integration extending the mobile phone and blurring the boundaries between on-line and physical retail locations. Online brands like Amazon will start having more physical products, like Dash Buttons, and physical retailers will start having more digital features, like store maps and product trials. (Dash buttons are a wifi enabled button that automatically re-orders your favourite products on the push of a button.) We will be “connected” and interact with our physical environment in shops, museums, our cars, work and home forming part of the Internet of Things.
When Automation is combined with Machine Learning we see the potential to move from automating repetitive tasks to machines taking on more complex and subtle job functions. Machines have been handling simple enquiries like account balances, timetable data and tracking solutions for some time, the limitation being the need to set the responses to pre-determined questions. Machine Learning focuses on the development of computer programs that can change when exposed to new data, enabling the machine to tackle more complex tasks and more variable situations.
Recent progress in the Digital world is shifting expectations, removing constraints and creating new opportunities:
- Do you want to “hear the voice” of your customer, real time and without the need for surveys, focus groups and time lags? Social Media and Big Data Analytics enables this.
- Do you want your workforce productive and available wherever they are? Mobile Computing and Internet of Things enables that.
- Do you want improved forecasts and insights and informed decisions? Big Data, Analytics and Insights can support that.
The demand to release new products, new organisational structures and business processes and quickly modify them over time in near real time is creating demand for new ways of working and delivering IT. The tech wave has been building for many ways, but is accelerating. Agile has been broadly implemented but organisations are needing to work faster and faster to meet business and consumer demand so are investing in Continuous Delivery, API Architectures, Dev Ops new ways of governing projects and IT investment in an Agile and Cloud-centric world.
Success in 2017 wont come from the technology alone, it will come from the ability to leverage the technology and drive change into how IT is managed, deployed and the user engaged.