Welcome to 2016 – a year to celebrate some of our favourite quadrennial events: we get to welcome back the leap year, and cheer on Team GB at the Summer Olympics in Rio. And there will be great rejoicing among bean-counters everywhere, as the UN has designated 2016 the International Year of the Pulses.
2016 is also the year for continued government transformation. Over the next year, those within government, as well as those using services, will begin to see and feel the effects of greater investment in the Government Digital Service, further progress with the realisation of ‘Government as a Platform’ and, more broadly, the introduction of the Single Departmental Plan.
On the technology front, though, 2016 won’t be a year of new tech – per se. The stuff people talked about in 2015 will remain the stuff we talk about this year; in particular: the Internet of Things, Big Data, Ambient (machine) Learning and Cyber Security. Where we will see the greatest impact and innovation, though, will be at the intersection of these major waves of technology. So 2016 will be all about confluence. Based on this premise, here are some key things to consider in 2016:
We’ll have more networked devices
We, as consumers and business people, continue to accumulate more devices. Ironically enough, a decade ago, the vision was to combine everything (e.g., Blackberry, Palm Pilot, mobile phone & pager) into a single device. But now there are multiple “single devices” – many mobile options for how we communicate and work. In 2016 this will take the form of cross-category devices: laptops that act like tablets; phones that work like desktops; wearables that perform like smart phones, and so on. It’s no wonder that by 2020 the average person can expect to have seven networked devices.
And it’s not just businesses that are seeing the growth of devices. With greater emphasis on creating David Cameron’s ‘Smarter State’, more and more departments and public sector bodies are exploring ways devices can help transform service delivery.
Because of the cloud, our phones, tablets and wearables have access to a vast amount of processing power and information and as devices get smarter and more connected, so does the government’s ability to do more with fewer resources. The introduction of the ‘Modern Workplaces’ agenda in the 2012 Civil Service Reform Plan has led to a rise in smarter working initiatives in government itself, and civil servants and other public sector workers are beginning to see the benefits.
Across local government, more and more councils are also exploring ways to enable flexible working, not only to improve the working environment for staff, but to reduce the costs of office space, without cutting services. To see how Shropshire Council did this, click here.
Of course, this raises the questions of how we, as individuals, integrate and work best across all of our devices, and how departments and public sector organisations manage and integrate these devices to maintain security and maximise productivity.
These networked devices will “see” and do more
It’s not just that we’ll have more things. As computing power gets faster, cheaper and smaller, the existing features in your things will continue to improve, new features will continue to be added.
For example, wearables will be more powerful with better sensors, monitors, accelerometers and GPS tracking tools to help make our experiences while wearing them more personal and more productive.
And as it becomes easier (i.e. cheaper, faster, smaller) to add more features to our networked devices, it also becomes easier to add more features to previously unconnected things. It is now economically viable, for instance, for laundry services to add sensors to bedsheets to reduce loss and better anticipate when they need to be replaced. Farmers can now monitor livestock with sensors similar to those in our smartwatches that can diagnose disease or help optimise feed, growth and yield.
The real value in connecting these things to a network comes from how these things then communicate and coordinate with each other without human intervention.
All these things will create a lot of data
Of course, the natural by-product of having more networked devices that do more is data. Loads and loads of data. While public servants are used to dealing with vast quantities of data – the data currently managed by central and local government is enough fill all the waters of the Lake District – data growth is set to continue exponentially in 2016.
But it’s not just about the amount of data we produce, but also in the types we produce as well (new sensors, new or newly-networked devices, new social platforms, etc). We’ll also have to manage the speed with which new data is being produced (and therefore processed) and the speed (some say voracity) with which business decision-makers want to turn that data into insight. And we’re not doing a particularly good job of it. Depending on whom you ask, we’re only able to analyse about 0.5% of the data we produce. That percentage goes up a bit if we look at the ability for companies to analyse the data they have – but only up to about 12%.
Much is being done in government to improve this, but there is still a way to go. While the Government as a Platform initiative aims to transform the way data is stored to reduce duplication and eliminate silos, the ability to analyse and interpret that data remains a challenge.
This certainly seems to be recognised by Cabinet Office Minister Matthew Hancock, who in November 2015 announced the establishment of new steering group – led by Sir Nigel Shadbolt – to help departments transform themselves into “intelligent consumers of their own data”. Speaking at the Open Data Institute, the Cabinet Office Minister also announced plans to set up a Data Leaders Network to review the legislation around data-sharing.
Combined with work the Government Digital Service is doing around streamlining processes and transforming the government’s digital infrastructures, 2016 could be the year government sees a raft of changes to the way departments approach data.
For more information on data and the concept of Government as a Platform, click here.
Which brings us to the next prediction for 2016.
The skill gap for turning that data into insight and business process will separate winners from losers
In a recent survey of 72 digital and technology professionals across 45 departments, agencies and arm’s length bodies, the National Audit Office found that while most government organisations have a small group of digital leaders, around 70% have 10 or fewer. Furthermore, the survey revealed that most of these digital leaders have not been in the post long and while a “significant” proportion have private sector experience, many do not have public sector experience.
Recruiting the right talent to help government deliver Government as a Platform and other digital transformation is therefore likely to be a high priority for 2016. Yet the gap between our demand for data (or for insight from data) and the supply of talent that can interpret it isn’t new for 2016. It’s been a high priority among CIOs across sectors for at least the past five years. What’s new for 2016, though, is the impact that early investments in analytics will start to pay off as the use of data becomes a competitive differentiator.
This isn’t just due to the creation of the data scientist role within an organisation, but rather because these individuals have had an opportunity to impact other parts of an organisation helping to turn data sceptics into data evangelists. As data scientists, power BI users, business analysts and other IT professionals have helped to familiarise other business decision-makers with the benefits of data-driven decision-making, the tools used to interpret data have become easier for non-data scientists to use.
These factors, among others, help to create data winners and losers. At the worldwide level, the International Data Corporation have predicted those winners (i.e. leaders) will capture approximately £1.1 trillion more in value from their data and analytics investments over the next few years than the losers (“others”).
The winners will be the ones who create the algorithms that turn that data into insight and process
It isn’t enough, though, for this data to drive business decisions. Even the most sophisticated predictive analytics rely on users within an organisation turning that insight into action. The next logical step (and the next big thing for 2016) is to develop algorithms that allow companies to turn data into autonomous action. Or as senior Gartner researchers describe it “how you do something with data, not just what you do with it.”
Don’t worry, it’s not as scary as it sounds. The machines aren’t rising up. Rather than Terminator, think of algorithms from Netflix used to serve up movie recommendations, or from The Associated Press used to curate information into articles and reports. But the algorithm economy isn’t just about serving up digital content. For example, Rockwell Automation is beginning to tap into Azure Machine Learning to understand how the massive amounts of data being collected can create even more value. The more data Rockwell has, the more they can learn and put together algorithms to predict problems.
Glasgow City Council is aiming to do something similar by creating an open data culture and smart city technology. This has led to more efficient service delivery, as well as using sensors across the city to analyse data and stimulate the creation of apps based on city data. For more information on how Glasgow City Council is doing this, click here.
Machines will better understand how we work
These algorithms aren’t static things, though. As they make their way into more systems, and are programmed to learn more about the data they process, the smarter they become. The better they become at anticipating our needs, as individuals or as organisations. Take Clutter, for instance. This feature in Office 365 utilises machine learning to understand your organisational relationships and prioritise your inbox by importance to you. Microsoft has made the underlying machine learning that enables features like Clutter available to the developer community to create their own machine learning applications to everything from rating one’s Movember moustache to predicting customer churn.
Because of this availability, machine learning applications will take off in 2016 – both in terms of volume and sophistication. Nowhere will that growth be more evident than with the increased importance of virtual personal assistant technology such as Cortana, which will help to curate the many disparate productivity apps we currently use. For instance, machine learning will allow a policymaker to recognise spikes in consumption, or use of a public service and ask “why?”. The right machine learning app would be able to understand contextually who within government would be likely to have the answer and help her find the relevant person to inform. The app would also be able to evaluate known influence models using the context of the particular area, against relevant data sources to try to identify the reason for the spike.
Machines will understand our businesses more
The same technology that will enable virtual personal assistants to curate information for individuals’ productivity in 2016, will also power smarter interactions between organisations. As more data is managed in the cloud, it becomes easier for companies and organisations to securely share information with each other, and turn that information into action/business processes or even policy.
Expect 2016 to be the year we begin to see machine learning applied to massive datasets across organisations. This could be from sectors (e.g. pharmaceuticals and medical research sharing information on human genomic data) or complementary supply chains (e.g., an aeroplane manufacturer applying machine learning in partnership with airlines and parts manufacturers).
Each new networked node creates new vulnerabilities
While we’ll see increased data sharing and automation of the way we make sense of our data across industries, we’ll also see increased vulnerabilities. For each new node we add to the cloud – for each previously non-networked device that gets “smart” or for each bit of shared data across organisations, we exponentially increase the risk to the overall network.
In 2016, expect to see successful companies refining their data security strategy to account for these threats. Within government, the move towards Government as a Platform could help alleviate some of that risk. By creating a unified platform, standardising data and evolving to security standards and threats becomes much easier.
Are you ready for 2016?
However these big trends shake out in 2016, though, the one strand that runs through all of them is data. How prepared are you make the most of your data? Have you thought through all the sources of data your organisation will come in contact with? Do you have the right people and systems in place to take advantage of the algorithm economy and machine learning? Have you thought through the security and vulnerabilities around your data?
A good starting point for answering these questions, and understanding how they all interrelate is through Microsoft’s Data Culture Immersion Series. These customer events are delivered in conjunction with a host of leading Microsoft partners to provide a series of half day and full day sessions specific to your needs.