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Can harnessing data help Local Authorities achieve the digital innovation they desire?

In late 2018 Local Government Minister Rishi Sunak announced the £7.5million fund for digital innovation. This followed the “digital pledge” made by the government and forty-five other co-publishers, which set out a future vision of local services.

The declaration set out aims to:

  • Change the way they [local authorities] invest in technology
  • Share expertise and ensure members of the public receive the best quality digital services from their local council
  • Connect the work of local government digital teams to deliver better local public services
  • Develop common solutions for shared challenges

Local authorities, government departments and partner organisations were then invited to place bids for a share of the funds and consequently adopt this innovative approach – but not all participated. In 2019 the Oxford Internet Institute conducted a nationwide survey across local authorities focusing on data science. It was then discovered that few authorities were exploiting the potential of artificial intelligence (AI), machine learning, predictive analytics etc. to improve service delivery, interactions with citizens as well as the handling, management, and analytics of data.

Fast forward to November 2020, predictive analytics and machine learning alike was still considered to be within the early stages of development and implementation. However, by this point, more local authority bodies had begun to consider the opportunities and value that data and data analytics hold. Whilst this is most certainly a step in the right direction – with many local councils striving to create impact through digital innovation – there are still areas of hesitation, due to the lack of expertise and understanding in the data sector.

 

The challenges Local Authorities face when adopting data-driven solutions

When it comes to adopting new processes within the public sector, there are common factors causing hesitancy. To those with little expertise and understanding, implementing a technological advanced approach can seem treacherous. Factors influencing the lack of adoption within local services reported by the LGA in late 2020 included:

  • Fragmented approaches to data and data quality
  • Availability of time and skilled analysts
  • Lack of corporate understanding of technologies and the value they add
  • The fear of computer-based decision-making, specifically referring to algorithms getting things wrong

Through experience we have seen that although some local authorities are embracing technology and modernising their processes, many are hampered by tight budgets, legacy systems and manual processes due to the limitations of current technology. These can include processes such as data handling, management and governance.

This raises a cause for concern for several reasons:

  • Legacy systems are no longer fit for purpose. Not only are they expensive to run, but they are deemed “outdated”, posing risks for security breaches and are not as agile or scalable as required in modern-day society
  • Data which is manually inputted can easily become duplicated or entered incorrectly, impacting on accuracy, failing to align with and meet or exceed strategic objectives, and detrimentally impacts the effectiveness of local authority operations and frontline services

Data managed, created, and handled this way is often siloed – a key issue within public sector bodies – hampering interoperability, consequently resulting in struggles to harness the true value of all data. These further stifle an organisation’s abilities to make an informed, data-driven decision that will reflect the needs of its citizens. Due to the lack of resources and data functionality, valuable information which could otherwise prove useful in understanding the organisations processes, resources and services is often wasted.

 

This results in ineffective and inaccurate organisational decisions, due to the lack of true interpretations of data – not only inaccurately influencing and impacting budget decisions, but also forecasting and planning too.

 

Why Local Authorities need to focus on Data and Data Analytics

Data collected and stored has grown exponentially. For local authorities this presents a real challenge coupled with a valuable opportunity to exploit. With more data, there is more to be analysed and value to benefit local authorities. Through utilising the organisation’s data (both historical and, through digitally innovative implementations, in real-time) local authorities can take a proactive approach; unlocking insights across the sector and aiding collaboration with other organisations. With the use of machine learning, predictive analysis and artificial intelligence, the possibilities and opportunities that data harnesses are limitless.

In truth, with this kind of technological innovation, local authorities hold the potential to truly transform their frontline services. Holding the potential to improve accuracy and outcomes, or even gain benefits from early intervention through identification of need – ultimately improving the services for the public. The issue is, many local authorities lack the in-house expertise, understanding and knowledge to truly harness the value of data, treating it as an asset.

 

How COVID changed some local authorities’ approach to data

According to the Centre for Data Ethics and Innovation forum (CDEI), local authorities acquired new data which they did not previously have access to from central governments and local service providers during the pandemic. Those few who pro-actively took advantage benefited in a multitude of ways, the following amongst others:

  • Identifying citizens who were most clinically and economically vulnerable
  • Predicting demand and pressures on local service
  • Informed direct public health responses to COVID-19 outbreaks, including local-level.

This was all achieved through improved data analytics and data quality – specifically improving how local authorities deployed existing data and integrating different datasets in new and innovative ways. #

The problem now is that many authorities feel that this momentum will become lost once the global pandemic passes, especially around innovative practises. Whereas emergency measures gave them access to more data and allowed more freedom in approach, it is feared this will come to an end when the measures subside. Local authorities who have been previously unreceptive to change should be willing to look at what was and can be achieved in such a short amount of time, seeing it as a teaser for data’s true potential. Even those who simply learnt the fundamentals and experimented on a small scale have the benefit of being in a better starting position going forward.

 

The impact and benefits of Data and Data Analytics on Local Authority bodies

Where once data was siloed and disconnected, data can now be connected – allowing local authorities to ask questions that can truly improve its services, efficiencies, and current processes. The developments in accessibility of data, open access sharing, and improved data management, creation, and analytics, enable local authorities to effectively analyse increased volumes of data. Improved methods and tools, alongside newly found and shared knowledge and skills, enable effective, precise, and accurate analysis – whether descriptive or predictive – resulting in faster, informed and data-driven decisions which could be targeted where necessary.

There are two types of artificial intelligence that local authorities can benefit from:

  • Machine learning
  • Predictive analytics

Commonly mistaken and interchanged, but very much different.

Machine learning presents local authority organisations with the opportunity to automatically learn and improve from previous experiences. There is often fear with machine learning, as many worry about the inaccuracy of results. However, there are two types of machine learning – supervised and unsupervised.

Supervised machine learning requires an operator. The operator will feed defined patterns, behaviours, and inputs, not only helping the model with accuracy but also helps the machine understand the outcome(s) desired. Unsupervised machine learning focuses on identification of patterns and behaviours independently. This form of machine learning is often used for intelligent profiling, identifying parallels and connections.

Predictive analytics provides organisations the ability to draw upon objective and empirical insights. It can provide insight into resources, identify events and ascertain the effectiveness of tested interventions. Predictive analytics analyses historical and real-time data, locating patterns and behaviours. It automates forecasting with significant accuracy, allowing organisations to trust in this AI and focus on other tasks.

Combined, or singularly, these forms of AI can allow for a better understanding of populations at risk and enable better resource distribution, in turn helping these populations to improve their situation. Identifying factors that make people resilient can ensure that they will not become dependent on services in the future.

 

The specific benefits of Data Analytics and AI

Supports the design, planning and delivery of public services (data sharing focused)

With improved internal data handling, improved delivery of public services can be achieved – especially with the newly focused “open data” approach. Responsible, open, and trustworthy sharing of data – not just internally within departments, but externally with neighbouring authorities and stakeholders – holds opportunities and benefits which have previously gone amiss. This approach can help with the design, planning and deliverables of local authority services; based on data attained internally and externally, identification of greatest demands, service improvements, inefficiencies and lack of resources can be discovered.

However, whilst this is certainly a great benefit there are currently barriers which prevent scaling this as best practice: legal and privacy issues, restrictive data licenses, siloed working and legacy infrastructures and more. Nonetheless, with the government’s national data strategy is now setting out to unlock the power of data within the UK – all whilst remaining ethical, maintaining citizen trust, and putting the needs and values of the public first.

Less time processing, more time analysing

As discussed previously, local authorities typically spend their time manually inputting data – this is an extremely ineffective, likely inaccurate and costly (in all monetary, time and resources) procedure to conduct. Due to the timeliness, local authorities also typically focused on business operations data and sadly neglected other areas.

Through AI data analytics, processes can be automated. This allows local authorities to spend their time more effectively. Relieving them of manually inputting data and instead focusing their time on analysing. This will in turn contribute towards improving the value of the organisation and their services.

Improved visibility

To effectively manage and improve its services, local authorities need to understand exactly what is going on within the organisation – activities, costs, outcomes, strategies, and plans. Following central government fund cuts, for local authorities, every penny counts. AI analytics provides local authority bodies with a birds-eye-view of their organisation. Allowing them to not only see the historic impacts but also real-time impacts too. This can be applied collectively to the whole organisation, or in isolation to specific departments.

For example, understanding how changes to specific or collective services can impact finances today, and whether investment(s) would be detrimental or beneficial in the future. Ultimately, this allows local authorities to accurately align their resources with their visions, plans and values, as opposed to relying on inaccurate estimations as carried out previously.

Anticipate the future

A key benefit that advanced data-analytics presents for local authorities is its ability to anticipate the future of its services. Whether through machine learning or predictive analytics, data analytics and improved data quality, allows organisations to create near accurate “what if” scenarios. This is achieved through creating simulation models. Local authorities can simply take some organisation variables (i.e. KPIs), and establish a “what if” scenario (i.e. “what if we decreased the social care budget by 10%?”. From here the simulation will then express the predicted outcome.

Through this method, local authorities can create a multitude of what if scenarios and plan for unlimited possible outcomes. Meaning that despite what happens today, tomorrow or in the future, they would never be caught off-guard and always have a plan of action and adaptation. Better yet, it allows local authorities to prepare themselves today, for a better more efficient tomorrow.

Real-time understanding

It’s essential for local authority bodies to be able to react efficiently and effectively to external issues. With today’s IT and technological abilities, analytics provides local authorities with the ability to anticipate not just changes but incidents as they happen – this is what is referred to as “real-time understanding”. Through real-time understanding, local authorities and keep up to date with changes in policies, on-going, or even newly presented issues and implement ways in which this can be handled and dealt with. In cases where local authorities did not anticipate said changes or issues, they will be well prepared to make data-driven and informed decisions.

Data analytics holds the ability to truly empower local authority organisations, to not only take control of their operations, but present the opportunities to make accurate, informed and data-driven decisions based on accumulated facts vs. Estimations, and help drive improvements continuously, even despite fund cuts and global pandemic. Data has the potential to help local authorities’ funding work harder for them and help them achieve more.

 

If you’re ready to make this change, your organisation will need to begin with a data strategy. Through an effective data strategy, brought to you by trusted data consultants, your organisation can begin its transition to not only taking an innovative approach, but providing services that promotes trust and puts the values and understanding of its citizens at the forefront of decisions. Contact us today!

 

Related Posts:

Data Analytics within the NHS and why it’s so important. (shapingcloud.com)

Why should a Data Strategy be a Priority for Organisations in 2021? (shapingcloud.com)


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