Digital Transformation
Oct 29, 2020

The best agent for the job: Five steps to cloud-enabled, skills-based routing for financial institutions

It's important to use the right tools for the job, they say. The same holds true for employees.

Each of your customers has unique behaviors and needs. And each of your contact center agents has unique skills and capabilities. Pairing your callers with the best agent for the job is key to customer (and employee) satisfaction.

Skills-based routing allows your contact center to assign customer calls to the most suitable – rather than the next available – agent. Cloud is the future of agile, accessible, and resilient operations. And skills-based routing is a widely touted benefit of cloud-based contact centers.

When preparing for cloud-enabled, skills-based routing, financial institutions must take five key steps:

1) Establish the business goal

First and most foundationally, a financial institution must strategically determine and quantify its desired outcome.

For example, the objective might be a percentage increase in customer satisfaction, service efficiencies, or sales revenue. It might be a blend of these – or something else entirely. Whatever the case, the financial institution's senior leadership must drive this decision and endorse the business goal up front.

2) Build a hierarchy of agent skills

Second, the financial institution needs to decide which agent skills will drive the business goal – and then rank their relative importance. This means analytically identifying, or creating from scratch if needed, a hierarchy of agent skills.

These skills may be:

  • Service-driven – for example, dispute resolution or onboarding skills 
  • Product-based – for example, credit card or personal loan skills 
  • Sales-related – for example, past success in upselling or cross-selling certain products and/or services 

3) Analyze agent attributes

Next, the financial institution must analyze:

  • Agent attributes – such as tenure, training, location, and performance 
  • Agent proficiency levels – such as expert, intermediate, or trainee 

Financial institutions must continually monitor and update these skills and attributes. They can use machine learning models to periodically (or frequently) reassign and re-rank agents based on changes to their attributes or proficiency levels and actual outcomes.

4) Develop matching matrices

The financial institution then needs to develop complex matrices to ensure smooth operations. These matrices must match capacity planning, virtual queuing rules, and expansion models to call demand and agent scheduling. This does not happen automatically, and it requires deep industry and process expertise and extensive digital expertise, especially in cloud capabilities. The system will rank customers' behaviors and needs and match them with the most appropriate agent based on agent skills, attributes, and proficiencies; all within the framework of virtual queuing and prescribed wait times in the cloud ecosystem.

5) Fine-tune performance management systems

Finally, financial institutions must create (or revise) performance management systems to reflect this new dynamic and way of working. After all, if an agent only receives certain types of calls (or customers), the system will be inherently biased.

Financial institutions must reexamine base performance pay that is measured against the mean or median and review sales incentives. And they must create mechanisms for agents to be promoted to (or demoted from) different groups, upskilled on new products, and given the time to prove themselves.

As financial institutions seek more personalized and segmented models, they must regularly establish baseline metrics and standards for agent performance. These new performance management systems must also be as transparent as possible for agents and team leaders so that they know what behaviors and outcomes to motivate and reward.

About the author

Max Feil

Max Feil

Head of Customer Support for Consumer Banking

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