Technology changes impact all facets of a business. For contact centers, this also includes staffing and operations. Digital transformation poses distinct operational challenges for the contact center that go beyond the customer and agent experience; we’ll address two of those challenges here.
While contact centers are increasingly turning to Artificial Intelligence (AI) applications for a variety of reasons, these technologies are not a silver bullet for everything, nor are they a complete solution for a specific problem set. They can, and should, play a role in helping contact centers adapt to digital transformation – in conjunction with existing technologies and processes.
When considering vendors offering AI applications, contact centers should consider how well they interwork and support the systems currently in use, rather than looking to replace them altogether. For now, AI will best serve contact centers as a complementary technology.
Operational Challenge #1: Maintaining Staff
The impact digital transformation has on staffing may not be that obvious, largely because it’s been overshadowed by the pandemic. By now, contact centers and agents have adapted to a work-from-home model, which will remain in place for many contact centers.
Contact centers have been hugely impacted by the Great Resignation, as has the entire service economy. Turnover in call centers has averaged 30% to 40%.
Supporting home-based agents presents many operational challenges for contact center leaders, and compounding that is the way digital transformation is reshaping the customer experience (CX). A key change is the need for seamless omnichannel communication with the growing use of digital channels by customers. If contact centers cannot effectively support this, the agent experience (AX) suffers and, as we’ve seen with the Great Resignation, agents will leave for greener pastures.
In terms of maintaining staffing levels, there are two immediate AI use cases to consider.
The first would be intelligent routing where AI can direct incoming inquiries based on the channel used by the customer. This can be especially effective for existing customers, where analytics can determine channel preferences based on past history. This way, inquiries will get routed to agents with the right skills set – both at scale and in real-time – making their jobs less stressful and more tenable.
A second use case would be self-service automation. The main idea is that better forms of self-service are critical for AX, and all contact center vendors now have AI solutions that go well beyond conventional IVR. Digital transformation is simply raising the bar for what self-service needs to be. The longer agents have to keep dealing with routine queries or repeating steps already covered in IVR, the bigger your staffing issues will become.
Operational Challenge #2: Speed to Competency
Digital transformation enables a remote working environment and allows contact centers to draw from a much larger pool for hiring agents.
While contact centers don’t have the luxury to keep hiring agents as traffic grows, they do need to hire and train them faster than before. This is another by-product of the Great Resignation, where there has been a sudden surge of people exiting the workforce, making the need to replace agents a top priority. As such, the challenge of speed to competency and onboarding new agents is more about maintaining current staff levels rather than adding agents to scale up.
In terms of operations, this means contact centers are playing catchup trying to replenish their depleted ranks rather than staffing up for growth. As noted above, AI applications alone won’t enable contact center leaders to totally catch up, but it has a key role to play, especially to speed up the hiring and training process.
When considering AI vendors, there are two capabilities you should be looking for.
First is the ability to quickly vet candidates for the skills needed, not just for specific agent roles, but also for the basic competencies they’ll need for your industry and customer base. This is especially relevant for global businesses, and how digital transformation removes the borders of geography, allowing contact centers to hire agents with greater proximity to customers on a regional basis. These possibilities are very recent, and while they hold great promise for improving CX, you really need the scale of AI applications to execute on this promise.
Second would be the next step, which is to train and onboard new agents once drawn from this pool of candidates. Machine learning (ML) is of particular importance as you’ll need to profile best practices from your top agents and use that as the template for training new hires. This is how you leverage AI to shorten the learning curve and provide real-time guidance for new agents.
Not only will agent turnover drop when you can onboard them more effectively, but so will the associated costs with staffing.
Guest blog post written by UpstreamWorks. To learn more about this topic and others, visit our events page to check out upcoming events.
