The onboarding process can be a difficult time for any organisation, says Dan O’Connell.
Whether it is introducing new employees to their co-workers and clients, arranging training, or getting them set up in IT systems, there are a range of challenges that often disrupt workflows and reduce productivity.
It is also a costly period, with the average UK company spending a staggering £1,530 per employee on training, a figure that can place a significant burden on businesses. Nowhere is this burden more evident than in the contact centre industry, where soaring attrition rates have reached their highest point in nearly 15 years. If contact centres are looking to maintain productivity amid high employee turnovers, they will need to find methods of integrating and training new staff at a faster rate and cheaper cost. One solution to this is leveraging AI technology.
Expertise at increased speed
One hurdle a new employee has to overcome is getting up to speed with an organisation’s product or service. This is specifically crucial for contact centres, where success often lies in the ability to answer a customer query with the confidence that comes with a deep understanding of the product. When a customer is calling to solve an issue, an employee’s level of experience is not top of mind for them – they just want their problem solved in sufficient time. By utilising generative AI, organisations have a better chance of closing the knowledge gaps affecting new employees.
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Having a knowledge base that employees can access for quick information, often through a third-party provider, is nothing new for contact centres, and serves as a unified repository of information employees refer to for customer queries. AI can enhance this experience by seamlessly pulling from that knowledge base to generate answers on the fly, as the calls are happening in real time. Rather than being slowed down by having to manually query the knowledge base, dig through documents, or needing to escalate to a supervisor, the AI system can identify keywords in the customer’s interaction, and use this to highlight the relevant resources for the query at hand.
Gaining product knowledge was previously seen as a long-term investment, a skill that employees acquire over time. With the turnover rates as high as they are in the contact centre industry, expertise is needed at a much faster rate. With AI systems, agents can be productive from day one, without the weeks of training and months of ramp time that traditionally hampers the customer’s experience.
Providing real-time support
It is vitally important that onboarded employees not only have acquired the knowledge they need for success, but also have the right support in place. Throwing a new employee into the deep of work without this support can be disastrous, both for the new joiner, and for the company. In contact centres, this support traditionally comes in the form of call monitoring, but with the average agent dealing with over 12,000 calls per year, and workforces split across multiple locations, employees are often left without the assistance of senior staff they need in those early stages.
Where AI can help in this regard is that it can simplify the monitoring process in a way that gives new employees the assurance that their manager has an overview of the call situation and that they can step-in when needed. Customer complaints is something contact centre agents often deal with on a daily basis, but it can be stressful for a new employee adapting to their role. AI technology can identify keywords associated with either a positive or negative sentiment inferred from the call and then highlight the live status to the supervisor through a centralised platform, allowing them to understand where support is needed in just a few seconds.
Rather than being overwhelmed by a manager jumping in with advice in the middle of a call, the use of AI assures the agent that a manager is only intervening at the necessary moment. It also gives new employees the confidence to proceed with calls, knowing that they won’t need to flag a supervisor for assistance because the system will do it for them.
Streamlining the review process
Once a new employee has been embedded into a business, it’s important to check in with regular reviews that evaluate happiness and performance. Traditionally this has been a strenuous process, and if a manager is stretched thin across their responsibilities, employee reviews can take a back seat. Rather than seeing performance reviews as a burden, AI tools can make the process seamless, and provide the structure and data that makes feedback truly beneficial.
The first few weeks and months are crucial for integrating new employees. Identifying the areas that require attention helps an agent understand where they need developing. It is important to understand that every individual has their own strengths and weaknesses. The intuitive nature of AI makes it easier for an agent to understand the areas of work they are finding particularly challenging. By automating many of the strenuous aspects of the review period, the focus can be put towards providing new employees with support that is personalised to them.
With the ongoing agent retention issues, integrating AI tools gives contact centres the confidence to embed new employees into the workflow at speed. While onboarding can traditionally disrupt productivity and bring senior staff to a halt, AI reduces the need for constant supervision and assistance with real-time monitoring systems and generated suggestions. As the contact centre industry braces itself for the challenges ahead, AI provides a support system that allows work to continue uninterrupted and gives new employees support in areas they need it most.
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Dan O’Connell is Chief AI & Strategy Officer at Dialpad.
Amelia Brand is the Editor for HRreview, and host of the HR in Review podcast series. With a Master’s degree in Legal and Political Theory, her particular interests within HR include employment law, DE&I, and wellbeing within the workplace. Prior to working with HRreview, Amelia was Sub-Editor of a magazine, and Editor of the Environmental Justice Project at University College London, writing and overseeing articles into UCL’s weekly newsletter. Her previous academic work has focused on philosophy, politics and law, with a special focus on how artificial intelligence will feature in the future.
- Amelia Brand
- Amelia Brand
- Amelia Brand
- Amelia Brand
