With nearly five billion people – and even more things – connected on the internet, data is assuming an increasingly crucial role. Not just for analysis and decision-making. Data is used in new services and goods and for better resource utilisation, as well as to feed into AI technologies that in turn spearhead innovation and research. Flow automation is one of several smart areas of application.
Between 2010 to 2020 the amount of data worldwide increased by 5,000 per cent, from 1.2 trillion to 59 trillion gigabytes. Fast-forward to 2025, and the forecast is that we will not only have got used to a new unit (zettabyte) but will also have further tripled the amount of data in the meantime.
What can we do with data – the latter-day oil?
– "Unlike oil, data can be used over and over again. And it can be developed," according to Per-Olof Sjöberg, RISE’s Business and Innovation Manager.
"For industry and commerce data plays an increasingly important role. And then there are concerns about access to data and data quality. Am I measuring the right things? Am I generating the right data, and how do I process data for the correct conclusions. We at RISE play a role in this context. On the basis of our experience we can be an extremely important partner. We can see what works in one type of industry, and can then pass this on to another one.
Data center for testing and experimenting
Since 2016 RISE has been running a centre in Luleå for tests and experiments in cloud applications, whereby sensor data can be gathered for modelling, simulation and further optimisation. Data processing must be correct and of a high quality in order to be valuable, per-Olof Sjöberg emphasises, adding that processing in this context can be performed with the aid of AI.
– "A huge number of companies are currently working on AI solutions. This approach will be further developed in the public sector and within industry and commerce, and RISE can be of assistance in this context," he says.
There is often uncertainty about who is responsible for data, and how and where to share it, as well as concerning agreed data formats
Sharing a challenge in the public sector
Specifically for the public sector the picture is more complicated. Firstly, data-sharing is made more difficult by the fact that there are 290 municipalities, 21 regions and a number of other authorities, together with the relevant IT departments. And secondly there is a regulatory and skills-related challenge, namely how to share data in the public sector, and the issue of what is permissible.
– "There is often uncertainty about who is responsible for data, and how and where to share it, as well as concerning agreed data formats," says Per-Olof Sjöberg.
Chiefly for small and medium-sized companies the fact that the public sector is a market in its own right with special rules is a headache. The complexity makes it a big leap from test to the actual product launch, and this can bring down a small company.
Public operations are based on a culture of sharing
Review the business models
Patrick Eckemo, senior advisor at the Swedish Agency for Digital Government (DIGG), says companies often underestimate complexity, and need to consider their business model in conjunction with joint development together with public administration.
– "Public operations are based on a culture of sharing. Sharing of solutions lies in the nature of the work. This is frequently not the case with entrepreneurs who would like to sell one and the same solution repeatedly. It’s also becoming more and more common for there to be a call for open source," says Patrick Eckemo.
Companies that assert data ownership based on interactions with people in order to train an AI application move in the opposite direction.
– "They own a product, a methodology and software – not data that comes from the authority and the people.
– "I think you have to want to be part of societal development and part of a sustainable transition – maybe work on open source and instead sell support and development," says Patrick Eckemo.
Major benefits from increased automation
Patrick sees major benefits in increased automation powered with the aid of AI. But the big saving is not really in just using the digitalisation opportunities, but also in changing existing business models, i.e. the way we steer and structure public work. Are we to assume that existing structures are right for the future public administration and digitise them, or are we to have the courage to think differently?
Patrick Eckemo believes that a combined structure that facilitates resource and flow efficiency can considerably simplify the digitisation work thanks to reduced complexity and reduced costs.
Per-Olof Sjöberg at RISE says that in order for individually customised services to be developed, companies and authorities require access to personal data. Services such as precision medicine and individually customised training are based on access to personal data.
– "As regards health and social-care data, it would probably be best if the people themselves owned it. You would then be able to choose to donate your data similarly to the way in which you donate your organs, but you could do it while you are alive and could donate to more than one person," Per-Olof Sjöberg concludes.
- Processing of data using various types of algorithm
- How to apply AI to data
- Train systems using data
- Machine processing
- Measure data, gather data
- Quality-assure data