I got an invite to a webinar on this topic the other day. The invite had some questions for you to ask yourself about your call center agents and how effective they would be if:
- They could act the way you wanted them to every time
- They didn’t have to have post-its or cheat sheets
- They didn’t need to spend months in training
- They could act like your best agent?
These are the right questions, especially for an organization with a reasonable number of call center agents. Part of the answer lies in being able to implement consistent processes for your agents to follow and deliver a usable system (these were the key elements of the solution being discussed in the webinar). Part of it lies in being able to present the right information to agents as they are working to address customer issues. What’s missing in many call centers, however, is a system that helps them make the right customer treatment decisions.
After all call center agents must decide how to act, how to treat customers.They must act in a way that is legal and complies with company policy. Often the rules implied by regulations and policies must be enforced manually with policy manuals and training. You are reliant on the agent themselves remembering and applying all the rules. Relying on this manual approach makes for errors and inconsistency – many have had the experience of getting an answer they did not like from a call center and then calling back to complain and getting a completely different one. In contrast to this manual approach, embedding the rules in a Decision Management system would allow the system to guarantee compliance and ensure consistency. It could (and should) even define when exceptions can be made and ensure that agents who make exceptions record their rationale.
With this kind of system in place the need to keep cheat sheets handy or put rules on post-it notes goes away – exceptions and changes can be made directly to the rules in the system quickly and effectively. I did some work in a call center that was implementing a Business Rules Management System so it could build this kind of environment and we found many cheat sheets that described how to pull data from various systems and then use that data to make a decision. Once the decision was automated the need for the cheat sheet would go away.
Of course this kind of system also requires far less training. If the system moves from passively supporting decision-making to actively managing it then the user needs far less training in the nitty gritty of policies and other rules. Decision Management systems are also more active, more likely to act appropriately on behalf of the customer or agent, and this often simplifies the user interface (further reducing training). In the previous example, for instance, the agents no longer need to be taught how to extract data from various systems as this is handled under the covers by the decision service that implements the decision.
Finally these kinds of system actually enable all your agents, on their first day, to act the way your best agent would. Capturing best practices and tribal knowledge as business rules is an established approach and a Decision Management system let’s you embed those kinds of rules as well as your policies and regulations. In fact it would let you go further as it supports the embedding of predictive analytics (which have a good track record of out performing human experts) and the management of ongoing test-and-learn experiments to see what works best and should become the new best practice.
So, if you really want to make sure your agents can handle any call, implement some Decision Management systems to help them.
