Within any UK Public Sector organisation, the priority is always the same: to enhance citizen outcomes. But achieving this while being mindful of the strain and pressure being put on employees and budget is not always easy, and many organisations are being pushed to breaking point. To bridge this gap, public bodies are increasingly looking to digitisation to allow them to do more for the people in their care without burning out their current resources. By giving Local Authorities, Housing Bodies, the NHS and many more UK Public Sector organisations the tools to be able to do more and achieve more, meanwhile alleviating the strain on their staff, Intelligent Automation is set to become a central pillar in achieving this.
Here are 8 use cases that explain exactly how Intelligent Automation could do this within your Local Government, Healthcare, Central Government or Blue Light services organisation.
One citizen view and customer service
Thoughtonomy’s Virtual Workforce® also has the power to create a singular citizen view throughout local authorities’ applications. For example, when a person registers a change of address in one department, the Virtual Worker goes through and updates their information in all applications, meaning that when the same person contacts a different public servant in a different department, they will be able to assist them using the most up to date information, rather than having to gather data from the person a second time. Not only does this decrease the amount of time the employee has to spend on the phone; it reduces the number of times the citizen must repeat their information, making for higher user satisfaction.
Increasing productivity and cost efficiency
Human Resources and other ‘back office’ departments undertake large volumes of manual and data intensive tasks; many of which can be executed through Intelligent Automation. For example, constituents’ requests regarding new rubbish bins, furniture collection etc can all be managed by the Virtual Workforce. A Virtual Worker would work within the organisation’s internal requests system and understand the type of request at hand. From thereon, the Virtual Worker can either action the request automatically or forward the enquiry to a human worker. The Virtual Worker’s ability to process requests 24/7 ultimately means that citizen requests can be actioned more quickly, making for a more efficient system and increased citizen satisfaction; as well as free up time for employees previously manually completing these jobs.
ESNEFT – e-referral automation
Previously, ESNEFT’s referral process required staff to work between various legacy systems, printing up to 15 docs, rescanning all of them and condensing into a single page - and then uploading into a clinical system: with 2000 referrals coming through every week, employees were struggling to keep on top of the incoming referrals. Additionally, this was costing the trust a significant sum. Virtual Workers have been deployed to actively monitor incoming eRS referrals from GP patient appointments 24/7. On receiving a referral, the Virtual Worker extracts the reason for referral, referral data and supporting clinical information and merges the information into a single PDF document. Once the data has been combined into a singular format the Virtual Worker is able to update all hospital systems instantaneously and extract critical information, which it passes on to the lead consultant for review and grading. The Trust saved 500+ of staff hours in the first 6 months and the project will save the NHS £220k alone.
EU compliance laws and regulation
A large pharmaceutical compliance body employed many skilled workers to manage the complex and EU aligned validation of new medicines. Their data validation process required staff to work within various legacy systems to complete transactional tasks and identify submissions that were not EU compliant. This made for a time consuming and data intensive task that was sensitive to human error. Using intelligent optical character recognition (iOCR), the Thoughtonomy Virtual Workforce® is able to ensure that submissions from EU member states meet prerequisite guidelines and flag the submission to a human worker if they don’t. The Virtual Worker is then able to work within the company’s legacy system infrastructure to upload and process successful submissions.
Let your citizens help themselves through the construction of online services. Our Virtual Workers provide your citizens with answers they need without using valuable public servant time through the use of Conversational User Interface Chatbots. By employing Natural Language Processing (NLP), Virtual Workers are able to understand the sentiment behind messages and requests they receive via Chatbots, and either issue the correct response or point the client toward an appropriate piece of literature, form, or human worker.
Fraud attempts are prevalent within all aspects of Central Government and with the number of attempts rising, public servants are under increasing pressure to identify fraud patterns and check transactions. Intelligent Automation could be the key to not only saving these employees time, but to crack down on fraud attempts. Virtual Workers can monitor transaction patterns, flagging any that lie outside of what is considered normal or safe activity. They can then put the account on hold and flag suspicious behaviour to an employee. Beyond this, they can also help with the fraud investigation process in the manipulation, ordering and analysis of data using OCR and NLP.
Quick suspect record scanning
It is crucial that police response units are able to gather as much information as possible about the incident they are attending to be able to prepare their response appropriately. This can encompass a thorough search of various databases that can take up valuable time and pull employees off of other jobs. The Virtual Workforce would be able to pick up some of these tasks to ensure speed efficiency. For example, a Virtual Worker can take the name of the suspect in question and search their name across multiple crime databases. The information obtained from this search can inform officers if this person owns a firearms licence; has any previous criminal history; has any history of substance or alcohol abuse; which in turn will allow them to prepare for their response accordingly. Virtual Workers can also scan existing data bases looking for key words to flag to police staff.
Correcting call handler errors
Current crime recording and reporting methods are disparate and have a high data error rate. For example, emergency call handlers are often under pressure to record large volumes of information in a short space of time, while simultaneously providing attentive care to the caller. This inevitably can mean that the quality of data is low - containing spelling mistakes and grammatical issues. This means that a separate team have to be employed to rekey this information for follow up. Moreover, the format that call handlers follow is not the same as the incident filing system kept by the police. This once again means that an employee has to manipulate the data. The Virtual Workforce can be employed to do this job instead. Through Natural Language Processing and iOCR, a Virtual Worker is able to correct spelling mistakes and reformat text to fit into their data reporting system.
If you’d like to speak with a member of the team to get any more information on these use cases and how you can apply them to your organisation, please contact us.