Organisations that have embraced the world of online customer management portals are already benefiting from automation technology, where elements of the process can be implemented 24/7 without the need for any human intervention. For example, a form submission can trigger a workflow that automates stages of the complaints process, drastically reducing the number of tasks requiring human input. This very basic workflow keeps things moving, and instantly reduces the workload of case workers.
As we move through the next decade how can we evolve our customer service? Central to any strategy is the technology that we can deploy that will help lift customer service to a level beyond expectation, and this coupled with harnessing the data collected, should be the standard public bodies aim for in the 2020s.
Automation and beyond: what’s next for complaint management?
You may have heard of terms like Robotic Process Automation (RPA), Machine learning, Natural Language Processing (NLP) and Business Intelligence (BI), but understanding how they can be integrated in to the context of complaint management can go a long way in developing a robust, industry leading solution that provides you with the data to help level-up your organisation.
Robotic Process Automation
Automation of the workplace isn’t new. RPA is looking to do with digital industry what robotics has done so successfully for manufacturing. Like robotics, RPA is highly disruptive. It looks to take manual duties completed by employees on digital platforms and automate them. It can pick up manual, repetitive tasks and perform them twenty times faster than you or I. This becomes massively powerful when you think of it in the context of legacy applications, which rely on physical data input with little to no interfaces to other digital platforms.
Within the context of customer service, automation brings benefits to both organisations and citizens. Processes can be completed faster, providing feedback or communications to customers within an expected time window, leaving old stereotypes of the public sector being slow and laborious behind. On top of this there is a financial element. If things are progressing without the need for human interaction, workers are freed up to perform more value added tasks within the business.
Machine Learning and Natural language Processing
Complaints, up until five or six years ago, used to be relatively simple for organisations to manage. They followed a tried and tested methodology. As social media has become an ever increasing presence in our lives, it has become an extension of the conversations we have in person.
If we remember, RPA automates tasks that we (humans) can carry out. If we can find those complaints on social media, then RPA can. That’s why introducing NLP to the complaints that RPA is identifying can become incredibly powerful for customer service. Complaints are an ideal use case for NLP.
NLP looks to identify multiple complaint types and, as well as this, NLP is looking to harness the emotion and sentiment in which complaints tend to be rich. How does the customer feel? Are they angry? Are they upset? Do they want a simple apology? All of these are valid queries that can help drive automated decision making within a complaints process. This is what NLP seeks to extract and provide.
If RPA has scoured the wider public realm to identify dissatisfaction with service, NLP has automatically read the complaint and figured out what the problem is, then we can use Machine Learning to take the outputs from NLP and provide predictive analysis on the steps that should be taken in order to address the customer’s complaint. Automatically.
The opportunities here for organisations to improve based on feedback they don’t directly receive is enormous. Based on the data at our disposal, we can spot key trends, understand what makes citizens grumble, and make decisions to move forward.
Reporting and Business Intelligence (BI)
We’ve mentioned briefly the ability to harness data, collected from cases and complaints, to improve business operations.
BI brings together data mining, data analysis and data visualisation to give managers and decision makers a comprehensive overview of data. This can be used to make business decisions in a more informed way.
Including BI platforms in your complaint management system helps you visualise areas for focus. By developing dashboards you can visualise where the organisation sits in comparison to KPIs (Key Performance Indicators). This helps measure against goals, targets and SLAs. Using the information for the ‘greater good’ is where real gains can be made; helping guide both operational and strategic decision-making.
The key to a successful complaint management strategy is having a process and a system that lends itself to ease-of-use, accessibility, and timely communications.
Complaints should no longer be used as a yardstick to beat organisations. They are the business tools for improvement and innovation. In turn, this will help build trust with the public they serve.