The Value of Data in the Public Sector

The value of data is becoming harder to ignore, especially since public sector organisations are under increasing pressure to do more with less.

The public sector finds itself at a pivotal moment. Efficiency savings top the agenda in all corners of the public sector, and now digital transformation can radically alter public sector organisations and how they deliver services. At the core of digital success is data.

In a recent whitepaper, Pure Storage, a data expert firm and strategic provider of data services and technologies, considers the value of data in the public sector. Here we discuss the key takeaways. You can download the full paper here.

Without further ado, let’s learn more about data value, data intelligence, and data storage in the public sector and consider significant challenges, such as how public sector organisations can extract data from legacy systems.

What is data?

Data is raw information, including basic numbers or text. In the digital realm, it may include different files, such as images, graphics, or videos. It covers all information gathered for analysis or reference.

Public sector data is information generated and collected by public sector bodies and organisations, such as government departments, local authorities, police forces, the NHS, and schools. Data may include names, addresses, tax codes, national insurance numbers, service use, etc.

Why is data important to the public sector?

There are many reasons why data is important. Firstly, data is knowledge. It plays a critical role in informing strategy and helping with decision-making. Useable data delivered at the right time and in the correct format can prevent problems from snowballing when used effectively.

Data also enables baselines, benchmarks, and goals to be set, which helps an organisation to evaluate performance and make decisions about workflows.

In the public sector, McKinsey & Company states, “Data can simplify the delivery of public services, reduce fraud and human error, and catalyse massive operational efficiencies.” Data is essential for facilitating research, informing policymaking, and improving public service design, delivery and effectiveness.

The Pure Storage whitepaper highlights examples where data has been used successfully in the public sector. For instance, Leiden University Medical Centre uses data to support new healthcare initiatives such as AI-assisted diagnosis and at-home patient monitoring.

Predictive analytics is also hugely valuable to the public sector as it uses data to understand the impact of potential decisions and identify the steps needed to achieve desired outcomes.

Above all, data makes innovation possible.

What is the value of data?

Pure Storage splits data value into three categories:

  1.  Potential value – Turns raw data into connected intelligence and gains the insights needed to deliver real and direct value to citizens. 
  2.  Evolving value – Builds agility, stability and security into data infrastructure to facilitate responsible data exchange and take advantage of new transformation opportunities.
  3.  Future value – Uses data to reduce operating costs, implement policies quicker and improve public services while continually innovating and experimenting to drive a new era of digital growth.

Data enables businesses and public sector organisations to understand customer, public and business needs. By understanding the present, optimal decisions can be made to positively impact outcomes in the future.

It is hard to put a price on data. But research shows a growing gap in terms of productivity and profitability between firms that use data intensively and the rest.

The pandemic enabled us to see data in action. Data was used extensively by governments to inform public health policies. In Germany, for instance, data was used to track ICU beds and manage spikes in hospitalisations.

Why is data value important to the public sector?

Data value, in a business sense, refers to how processed data contributes to the bottom line. Public sector organisations aren’t there to make a profit for shareholders, but they do have to demonstrate that they offer value for money to the taxpayer.  

Presently, there is a lot of siloed data in the public sector, which doesn’t hold much value. But connecting this data and working with it offers enormous potential. It contains the power to increase efficiencies, reduce costs and provide better value to citizens.

How to extract data value from legacy systems

The public sector is in an enviable position when it comes to data because there is so much of it and so much potential. But outdated legacy systems and limited analytical capabilities mean the public sector has struggled to unlock its value.

Overcoming legacy architecture is one of the biggest challenges in the public sector today.

To ensure value is realised, raw data must be extracted and carefully audited before being structured appropriately and migrated into new systems that have the capacity to integrate. Data must be cleaned, enriched, and mapped to new data fields. Cyber security is also a critical task. Extracting data value from legacy systems is complex; it requires expert help from data specialists.

Also, extracting data value goes far beyond migrating data from old systems to new ones. It rests on the government developing a connected data landscape. Digital transformation and extracting data value go hand in hand.

How data can accelerate the digital transformation of public services

All the time that data is stuck in legacy systems, digital transformation and innovation in the public sector are being held back. Yet, data is essential for supporting research and development, which is critical for driving innovation and a new era of digital growth.

Public sector data holds valuable historical context, and combining disparate data from siloed sources offers fantastic potential. This rich depth of data and insights will drive critical decision-making around digital transformation. 

If there is one positive to be found from the pandemic, it is the fact that the public sector and citizens have become more used to working online. It has enabled a glimpse of a future devoid of paper form-filling and unnecessary processes.

Data can help build on the current openness to a digital way of working and improve accessibility ensuring no stakeholders or service users get left behind. Data about needs offers the opportunity for deep knowledge and understanding and can be a force for good in accelerating the digital transformation of public services. 

Data can help organisations evolve, respond to challenges, and make step-changes in the value, efficiency and effectiveness of digital services. 

As services transform, data will be essential to understand situations, respond to needs and anticipate requirements. Using data effectively, public sector organisations can predict, prevent, improve, and deliver better. 

How to remove barriers to data intelligence

According to Pure Storage, 45 per cent of European central government IT leaders said the most significant barrier to digitising citizen services and automating processes was investment in data infrastructure. 

Data intelligence relies on robust data infrastructure. To improve data intelligence, the government must build agility, stability and security into the underlying data infrastructure. Privacy must also be safeguarded to prevent data misuse, and appropriate measures must be taken to avoid security breaches. McKinsey points to the need for a uniform legal framework.

Systems and digital transformation must be more cohesive. Organisational silos are rife in the public sector. There is no connected view of data or consistent logic across data. McKinsey observes that government data is routinely stored in “formats that are hard to process” or in “places where digital access is impossible.” 

All these things impede data intelligence.

Government must review processes to ensure data collection is automated, data pools connected and made available in a way that is easily accessible and useable. Cyber security and cloud data analytics are fundamental foundation stones.

Discussing Government Data Management for the Digital Age, McKinsey sets out five actions to help the government deliver interoperable and connected data in the public sector. These are:

  1. Set out a vision that focuses on clear and tangible use cases
  2. Understand and navigate the relevant data landscape
  3. Offer relevant infrastructure components centrally
  4. Rapidly deliver end-to-end use cases via agile data labs
  5. Establish a central data agency

How to deliver scalable, reliable data storage

Reliable data storage is critical for sustaining data value. It requires the services of a reputable and robust data storage provider.

Cloud-based storage solutions negate the need to store multiple copies of data in different locations to comply with disaster recovery policies.

Taking advantage of the power of the cloud has numerous benefits. Cloud-based storage solutions are scalable and flexible, as you only pay for the storage you need. There is added reliability as cloud solutions provide a distributed architecture and automatic data backups. 

However, more than simply opting for a cloud-based storage solution is required. Research is essential to find a provider that meets public sector organisations’ exacting standards. 

A critical objective is being able to access data quickly. There is no point in securing data if you can’t easily reach it. 

Net Promoter Score (NPS) is the gold standard for measuring customer experience. NPS is a simple measurement of customers’ or users’ experiences with an organisation. Ask for a provider’s NPS score.

And, importantly, how green is the data storage solution? Data centres use astonishingly high levels of energy. Is the data storage business committed to sustainability, and what does it do to minimise its carbon footprint?

Can better use of data help individual public sector organisations to succeed?

Public sector bodies have, historically, generated huge volumes of data but have yet to harness the opportunities it presents effectively. Without intrinsic analysis, data is next to worthless. The power comes from the interpretation of the trends and patterns it reveals.

The first step is to set clear objectives. Once goals are set, data can be segmented to focus on relevant information.

For instance, you may want to compare customer satisfaction ratings by geographical areas filtered by demographics such as age, ethnicity and gender. If clear trends can be identified, then the data can be used to inform decision-making. Over time, the effectiveness of any intervention can be measured and analysed.

Data should lead public policy. A scientific, measured approach will always generate better outcomes and have more significant impacts. If a data-driven culture can be developed, where staff are trained in the importance of accurate data collection, then the results will be even more spectacular.