Public Sector Data & Analytics Roadshow 2017

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In May and June 2016 KPMG, in association with the Public Sector Network (PSN), took the Public Sector Data & Analytics Roadshow to Melbourne, Adelaide, Canberra, Sydney, Perth and Brisbane.

Over 400 leaders working in technology, data analysis, policy and programme development came together to discuss the issues, challenges and opportunities of building a robust and powerful data and analytics programme. Over the events, we saw that participants were keenly aware of how data and analytics could help them respond more effectively to ‘wicked problems’ facing society such as homelessness, long-term unemployment, domestic violence, childhood obesity and environmental management. Richard Burnell, for example, Chief Information Officer with the Department of Fire and Emergency Services in Western Australia, described how advances with data are helping them map bushfire-prone areas and to identify areas of high risk.

Discussion was wide-ranging and in depth. Enthusiasm about the opportunities and benefits was balanced with the need to build trust with citizens and end users of the analysis by protecting the privacy of citizens, securing data from abuse and engaging stakeholders better to show how data and analytics bring value. Sharing data and taking a whole-of-government approach to issues crossing agency and government boundaries was also keenly discussed.

During the roadshow we asked participants to complete a survey to gauge perceptions of the opportunities and challenges their organisation faced in becoming a more open government. Get the report here

The 8 Big Challenges Facing Data and Analytics For The Public Sector

In the public sector, data allows us to adapt and improve public services and enhance our whole way of life, bringing economic growth, wide-ranging social benefits and improvements in how government works.

When organisations embrace analytics as a means to create value, customers tend to be happier— but it’s not smooth sailing. Here are some of the top challenges facing data and analytics in 2017:

Integration

Only with the right infrastructure in place can we hope to interpret and analyse the increasing amounts of complex data available. But that’s only the start of the challenge - many data and analytics tools are operating in isolation. For example, project teams, and tech teams - not to mention the vast opportunities for agencies and departments to share more data and strategies.

Getting out of experiment phase

There’s been a rapid rollout of data and analytics solutions over the past few years, multiple pilot projects have been successful or failed and not continued further beyond that. Most public sector organisations have now found at least one use for data and analytics, but there’s a long way to go before it stops being about testing, and becomes core to any transformation strategy.

Handling large data sets

A whopping 90 percent of data that exists has been created in just the last two years. In 2014 there were 204 million emails every minute. This volume, variety and speed of data is unprecedented. It poses a challenge at every point across the supply chain, from collection to storage to action - and it’s showing no signs of slowing down.

Using the right data

The term big data is ubiquitous - with huge volumes of information flowing. Government data is being leveraged to predict anything from a customer contact to a potential electrical outage. But the relentless focus on the importance of big data is often misleading. Yes, in some situations, you need large amounts of data - but volume doesn’t always matter — having the right data does.

The ripple effect

We’ve seen the impact of drastic changes in the private sector. When end to end strategies are accelerated - it can impact the organisation in ways not always predicted. From an increase in staff anxiety, to a collapse in processes struggling to keep up with results. The challenges will be varied and unpredictable.

Too much focus on data

We can’t finish without highlighting the time spent on data. Projects shouldn’t start with data, they should start with strategic objectives then mapped out to understand how digital capabilities can achieve the strategy. It also makes it a lot easier to integrate into a more traditional culture when you start with highlighting the end goal first and applications second.

Insights into Public Sector Data & Analytics

4 Data Analytics Trends That Will Impact the Public Sector in 2017

Clearly no longer a fad, big data has found a place firmly in many organisations.

For public sector organisations, there are four key areas we’re expecting to be under the spotlight:

1. Data Science Skills

Data and analytics roles will evolve. Traditional programmers will be required to gain data science skills as the requirements of the job expand, and data scientists will find themselves in big demand.

Despite much talk about machine learning moving towards being able to analyse data at a scale humans can’t, a data scientist has become one of the most in-demand, high profile careers in data. Public Sector employers will find themselves in a position where they are competing against high-profile private companies and will have to invest more into their people to upskill, train and retain.

2. Artificial Intelligence and Robotics

According to a Forrester survey, businesses will invest 300% more in artificial intelligence (AI) in 2017 than they did in 2016.

We’re already seeing robotics and automation having a significant impact on the world of manufacturing, cutting human jobs at a rapid rate. Estimates show that anywhere up to 50 percent of jobs that we have today could be lost to automation. In 2017, we’ll start to see this technology used in a variety of industries for a wider set of roles at AI becomes more widespread and affordable. Customer service is one key area in government where we expect to see some user cases from AI and chat-bot technology in 2017.

3. Results and ROI

There’s been a significant shift from big data being a trend, to now firmly part of any organisation. As a result, there will be less talk on how to gather big data and more of a focus on analysing results and proving ROI.

Big enterprises will lead the way with user cases, and we’ll see a focus on closed-loop reporting systems with data being fed back in real time to determine immediate actions.

4. Privacy

Technology is evolving much faster than the legacy. We’ll see public sector organisations put under pressure to evolve their frameworks surrounding data practices faster than ever before.

There will be fails and public outcries. Government systems will have to work collaboratively to create frameworks that protect people’s data without slowing down the pace of change.

Hear for yourself how other public sector organisations are leading the way during Public Sector Data Analytics Roadshow in May 2017. Book your tickets today!

In today’s hyper-connected world, where more data is created every day, businesses and government need to find real value in data
To ensure agencies make the most of their information assets, they must understand what data is available, the rules for its use and protection, and how disparate data sources can be brought together to form an actionable data roadmap
If you’re looking at data five minutes behind, you’re six minutes late
For data analytics to be applied successfully, users must have confidence that the technologies and methods they use to collect, store, and exploit data resources also can be trusted to protect enterprise information
The first step towards establishing a trusted big data analytics environment is to focus on how to prepare a secure foundation for Hadoop
Ultimately, achieving big data security and trusted analytics comes down to fully understanding the data and the systems used to collect, protect and manage it
Without analytics, big data is little more than an enormous collection of individual records—structured and unstructured data removed from their context
To inform agency strategies and enable more timely and better decision-making, government departments need to create a more data-driven culture with pervasive analytics—analytics, automated and ad hoc, that are present throughout all phases of a workflow. This approach allows complex enterprises to leverage big data by forming a deep understanding and connection between their organisations and data assets
Move from the "what" to the "why." - “The more that you can provide the context as you develop your dashboards, the more actionable the information is, the more meaningful it is when you get to reporting
Develop analytics that fit your business model
Understand your information needs
Emphasize imagination and pragmatism
Developing a big data strategy is critical for success
Considering the "Build" vs. "Buy" scenario

What are the questions to ask when thinking about “build vs. buy:” for an enterprise data strategy? Consider the following:

What are the time and budget constraints for this big data requirement?
How secure does the data need to be, as it may vary from project to project?
Is a system needed to powerfully and quickly predict large data sets?
Does this requirement demand a data solution that is adaptable or can it be built-to-scale?
What resources are in place and how can the organization plan and expand its big data team?