Our founder and thought leader on the topic, Dimitris Lyras, explored the idea of “muscle memory” and how to use intelligent pathways (an early cousin to AI) to create new muscle memory in a shorter amount of time. Consider when you make up in the middle of the night and have to navigate your way in the complete darkness to get a glass of water. How do you avoid stubbing your foot or tripping over the chair? It is muscle memory. Your mind has created an image of the layout from the bedroom to the kitchen and you follow this map.
Taking this concept and using technology to create the maps in customer conversations is the vision of our company. We have learned a lot in the past 27 years about AI and the best way to leverage it to develop your frontline team members. Let me share some of our most important concepts to drive better performance at the point of contact with your customers.
1. We as humans desire to improve odds. Dimitris explored AI models in an attempt to find better ways to teach concepts where the learner would have a better chance of retaining the material. His research resulted in simulation-based e-learning which takes the results of each simulation and feeds them back into the model to make it easier to learn and retain over time. Dimitris’ objective follows human nature. People want to improve their odds of being successful and examples include preparing for a test, trying out a recipe before trying it on family or friends at a dinner party and training a new employee before letting them go live with a client.
2. People learn by doing. Generally, people learn to master a skill when they can do it with repetition. They also ideally like to learn it in a safe environment where there is no fear or consequence of a negative outcome. This improves their odds of success. How to create that safe environment - for our employees - is the key.
Think about a simulation that an employee would go through to learn the best way to handle a customer escalation about a complex billing issue. Would you want to put a new employee on the phone with a live customer right out of the gate? Or would you prefer that they run through several scenarios or simulations with the computer before they go live?
The repetition will give both your employee and the management team the confidence that the employee will be able to make the right decision in the moment.
3. The foundation of intelligence is planning. The fundamental pillar of intelligence is to make good plans based on experience. Plans turn into decisions. Although most of us rarely think about this in a deliberate way, we lead our lives by making plans. For example, hours before we prepare a meal, we will take out frozen food to thaw in time. One of the reasons this plan is good is because it is born of experience. A few minutes of self-examination will tell us that in all situations, we make plans. Experience, be that our own or that of our peers and elders, helps us make better plans. So then, it makes sense to think about how we build up this capability. And then to examine if it is a particularly human capability by asking if computers can do the same....
4. Computers won't replace humans any time soon. There are headlines every day speculating that humans are on their way out in many business functions. Can computers make plans and decisions like humans, and can they do so in any situation? Plans involve understanding, expectation, reasoning. This, computers cannot do without an immense amount and variety of learning. Because even simple plans for us are demonstrably hugely complex for a computer.
Let’s revisit our analogy of finding one’s way in the dark. As humans we use recollection of past experience. We also rely on tactile memory because we have memories of the feel of things we may run into. Whether we are finding our way to the kitchen, or to the bathroom, we have a fair grasp of the expected proximity of one expected landmark to another. Essentially, we plan our way in the dark from trial and error and spatial experiences.
Likewise, a machine, if it is going to provide relevance, must acquire spatial and enterprise experiences through various situation models that include cause and effect logic. Logic that derives from every generalized discipline needed and which is then applied to each domain. The model can be as broad or as simple according to the scope it serves. But it needs to be well organized into what affects what, and in what context and rich in contextual variations.
Therefore, a computing machine that has already been introduced to the parts of generalized disciplines it needs to know, is then ready for supervised learning on cause and effect. That is, the ability to identify that a certain activity affects another activity inscribed within a plan (or a goal).
That describes what our e-learning simulations have accomplished for the past 27 years. We built the models, trained each model with thousands of client outcomes, and developed simulations for our clients to use to improve the odds of success for their employees.
5. Role play is not the end-all of training. When we were founded, role play was a prevailing training method. As a case in point I can distinctly remember a role play that illustrated how to have a difficult conversation with an employee about lackluster performance. Our management team had low grades in having the courage or mental toughness to discuss performance issues head-on. Role play can have a place in bringing one particular scenario to life where you'll remember it for a long time, but in general role play is not as successful as leveraging simulations to simulate an interaction. There are too many variables including relying on the person you are role playing with to simulate the environment. There is emotion inherent in role play - the fear of making a mistake. Don’t get me wrong - I’m not saying role play is dead - it’s just if you are trying to create a new consistent behavior, technology may be a better partner than a human.
6. Mastery is the objective. For the last 27 years our collective training objective hasn't wavered. We want employees to master their job skills, and in contact centers, master the conversation with the customer. Furthermore we want the employee to be able to anticipate where the conversation is going and influence the direction it takes and the success of the call. AI allows you to have the simulations to master the flow of the conversation. Goal-based scenarios are developed to create or simulate the customer experience so representatives can detect patterns and tailor their conversation accordingly.
With every year we are positioned for AI to help us solve more business problems and at a lower cost. Is AI going to replace all humans? Probably not. But can your company make material improvements leveraging simulation-based e-learning? Absolutely.
If you would like to delve deeper on the subject of AI - we invite you to take a look at some additional resources. Our sister company — Ulysses Systems — has published several newsletters about the evolution and use cases for AI. These musings stem from the research and models produced by our joint founder Dimitris Lyras. Here is the first newsletter if you’d like to take a look. The subsequent articles are also available at that location.
If you have any questions about this article or want to discuss how AI could help level up your contact center, please feel free to reach out to me via my contact information below.
INSERT DINA’S PHOTO from October CS
About Dina Vance
Senior Vice President, Managing Director of North American Operations at Ulysses Learning
In her current capacity with Ulysses Learning, Dina is responsible for the day-to-day operations of the company and also serves as the chief client relationship executive, working with Fortune 100 clients and other progressive organizations to redefine the way customers are cared for. Under her leadership, Ulysses has become well known for its work in transforming customer service, sales and coaching cultures through the development of emotional intelligence or “EQ,” enabling reps to confidently, consistently and expertly handle every call. The company has special expertise in serving the insurance, utilities, and financial services industries.
Before joining Ulysses in 2001, Dina was responsible for the ground-level startup of two contact centers to serve bankers including Fortune 100 clients First Chicago, Harris Bank, American Express and Citibank. This led to her role as call center lead consultant and division manager for an international bank training organization prior to Ulysses. Outside of work Dina is actively involved in local volunteerism and enjoys cooking, gardening and nature walks.
Dina can be reached on LinkedIn or at dvance@ulysseslearning.com; for more details on Ulysses Learning visit www.ulysseslearning.com
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Ulysses Learning was founded in 1995 as a joint venture with Northwestern University’s world renowned Learning Sciences department. Since then, Ulysses’ continued focus on research and development has earned it prestigious awards and recognition and, most importantly, the respect from its clients who rely on Ulysses for innovative performance improvement solutions that change with their rapidly developing and evolving environments.
Contact centers achieve profound business results ahead of schedule with Ulysses Learnings’ artful blend of patented simulation-based e-learning, facilitated exercises, coaching, and technology-driven tools, that redefine the way customers are cared for and transform customer service, sales, and coaching cultures. Ulysses has one of the only training systems proven to build EQ with its proprietary Framework with Freedom© approach, enabling reps to develop skills to empathize with others, build stronger customer bonds, and improve team dynamics with confidence, consistency, and excellence.
Ulysses Learning is a multi-year recipient of the Gold Stevie© Award for the best contact center customer service training.
Begin your contact center transformation now. Phone 800-662-4066 or visit www.ulysseslearning.com to get started.
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