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bots

Five Best Reasons To Use Simulations for Remote Training

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How Simulations Can Ensure Remote Workers Are Job Ready

Well, it’s now August and many of us optimistically thought in March that Covid-19 would be a fading memory. How naive we were. But here we are and every company is trying to figure out what the “long-game” is in regard to changing the way business is done.

Two years ago when I launched Verbal Transactions our small team was able to quickly land some well-known clients who saw the value of using our simulator as a way to augment their existing training programs. One key reason was that it gave them the reassurance that employees would get more “hands-on” practice.

Now with the majority of employees working remotely, tools like ours are even more imperative. Why you ask? Here are the top 5 reasons.

  1. Simulation training has been proven to produce better results compared to instructor-led, video, or eLearning. By giving users the ability to practice in realistic situations exposes them to a more tactile and true-life experience.simulations
  2. Due to the fact employees are not sitting in a classroom or placed in a pod to where they can tap someone on the shoulder to answer quick questions, using our built-in “bot” simulations can be built to allow for users to verbally interact with the simulator to feel they have a guide or mentor to help them along the way
  3. A well-built simulation will allow users to make mistakes with some form of immediate feedback. We all learn from our mistakes. Using simulations to allow you to fail in a safe environment allows you to actually succeed faster.
  4. Because managers can’t physically observe employees doing their job,  using analytics like that built into our ACES software removes any mystery around how well the employee can perform their job. Each behavior you want the simulator to observe can be tied into the scoring and reporting functionality.  No need to watch a video or listen to a recording of the user completing this task, the real-time reporting gives you complete transparency to how well they did.
  5. Most importantly, users appreciate more hands-on practice and feel more confident about how to do their job. Many employees have a variety of anxiety in these uncertain times. Losing their job is one of them. By arming them with tools to ensure you are helping them to learn how to do their job well, ensures, you want them to succeed and to ensure they are well equipped to contribute to helping the company do their best.

 

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Reducing Gladwell’s “10,000 Hours by 90%”

By | bots, call center, contact Center, simulations | No Comments

Deliberate Practice vs. Traditional Training

I’m a big fan of Malcolm Gladwell and I’m sure many of you are familiar with the term “10,000 hours to mastery”. This has since been proven to be taken out of context but he still references it as a guide to how long it takes for someone to master an innate skill. In Frans Johansson’s book, The Click Moment he explains that Deliberate Practice is a more likely predictor of success. Here are the core elements to Deliberate Practice

  1. Set a specific targeted goal or task you want to master
  2. Provide focused intense periods of practice
  3. Receive immediate feedback and self-correct
  4. Prepare to be uncomfortable in order to overcome barriers to success

One of the core reasons our customers use our simulator is that it uses this deliberate practice approach. Many of our customers need to get contact center agents up to speed quickly. Traditionally they are putting them on the front lines before they have had time to really master interacting with customers. By using our simulator, they see how this gives agents realistic practice so they can reduce the time it takes to get to mastery. Like Johannson’s approach, our simulator is a predictor of agent performance — here’s how.

  1. Simulations are built to look and feel just like your scenarios with a specific skill in mine – such as how to change credit card information, how to handle product returns etc.
  2. We recommend building different levels of immersion so that as agents score out of one level they continue to practice one transaction 3-4 times at a minimum
  3. They receive automatic immediate feedback from a built-in bot who guides them through how to handle verbal and on-screen interactions successfully
  4. They are uncomfortable at first due to the fact they have not had any exposure to this. Our conversational interactions are built on best practice responses. Once they become comfortable with each level, they can move on to more complex transactions

No need to use a crystal ball to try to determine who will be successful. Our ACES  automates this process. The intelligence embedded into the system, allows the managers to know right where in the transaction the agent may have gotten off track.

Businesses don’t have the luxury of 10,000 hours of time to help employees get up to speed on their skills. So imagine if you had the ability to help your agents master many of your complex transactions in 5-10 hours vs. 5-10 weeks? You can view some examples on our video page.

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Using Bots Accelerates the Need for Up-Skilling

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Why Bots Have a Long Way to Go to Take Over the World

Like Chicken Little’s cries that the sky is falling, everyone keeps shouting bots are replacing people. Well I am here to tell you they have a long way to go.chicken little

There is some truth that bots are beginning to manage simple transactions like help with resetting a password or authenticating your credentials. But in a recent article published int Silicon Republic, Forrester’s Srividya Sridharan states that bots will only be handling 20% of these basic activities by the end of 2020.

The interactions that bots are not able to handle will require higher-skilled agents. Even though many of us are accustomed to interacting with an intelligent agent, we won’t have the patience for this when we need immediate answers. Agents who can handle the tier two situations, will need to be trained skills such as:

  • Expressing the right level of empathy for the situation
  • Navigating their systems to quickly troubleshoot the issues
  • Learn how to ask good open-ended questions
  • Practice active listening and have the confidence to restate their understanding of the situation
  • Recognize early on when they need to escalate the situation to a higher power

Historically it takes months to get an agent up to this level of proficiency. This is why many of our customers are seeing the value in using or call center simulator ACES™. With the clock ticking on speed to proficiency, companies are looking for ways to get these employees up to speed faster to manage the more complex transactions.

So rather than using AI and bot technology to replace employees, we are using it to help upskill them. By giving employees a realistic immersive experience, we can put them in the hot seat. The built-in bot gives them real-time coaching to help guide them through each scenario. By giving them repeated “deliberate practice” we can get them up to speed in days vs. weeks.

So have no fear, the sky is not falling. We see that AI can be used for good – not evil.good bot

If you want to see an example of ACES in action just click this link.

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How to Accelerate Contact Center KPI Performance

By | bots, call center, contact Center, empathy | No Comments

Reducing agent’s learning curve.

In a recent conversation, I had with a client we discussed why they are using our simulator in their contact center. As a large BPO, their revenue is directly tied to documenting agents are following very detailed KPIs. They asked for me to provide a full list of how our simulator can impact each of these so I thought it would be helpful to share this list with others.

  1. Reduction of AHT, this client wanted to reduce new hire AHT of 12 minutes down to an average of 7
  2. Increase agent confidence which impacts CSAT scores
  3. Improved soft-skills such as expressing empathy, active listening and asking open-ended questions
  4. Improved accuracy of keystrokes and data entry
  5. Reduces the number of times call will be escalated to a manager
  6. Automates measurement of English proficiency

In number six, this was not an intended KPI but as a result of working with a very large technology company, they now use our simulator as a way to ensure outsourced agents are English Proficient. This came up when they enrolled agents at a call center in Vietnam. They were struggling to complete a simulation successfully. Our client thought that the simulator wasn’t working correctly. I assessed that their accents were too strong. The client was somewhat skeptical that this was the case so they placed them into production as voice agents. Shortly after they were in production, customers complained they were not able to understand them. They are now all chat agents. Moving forward all of their simulations now account for and measure their English proficiency with our simulator.

As we have proven many times, if you pro-actively use a tool like our simulator, you can address a lot of the “back office” metrics on the front end and improve the customer experience.

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More Metrics vs. More Completions

By | Adaptive Learning, bots, empathy, simulations | No Comments

Better Training Metrics to Measure Business Impact

I was one of the first people to evangelize the use of Learning Management Systems (LMS) twenty years ago. Now I’m singing a new tune — find a way to measure skill readiness vs. “completions”.

Initially, the LMS systems served a great purpose. But as time went on, companies began adding more and more features to it to help manage various learning activities. I worked with a client who had very robust features for managing classrooms, assessments, catalogs etc. But the bi-product of this was arming trainers with data on the consumption of activities. I could tell you how many people passed an assessment but couldn’t tell you if these same people knew how to really conduct a proper “lock-out tag-out” procedure.

In a recent survey conducted by Donald H Taylor Learning Analytics made the top spot in what the learning

Web analytics concept

the community has a priority interest in 2020. In previous years personalization and adaptive learning held these top spots.

This is great news for Verbal Transactions — as I have been preaching the benefits of more data for the last four years. In our simulator ACES™ (accelerated contact engagement system) we can pinpoint key behaviors that will truly prepare employees for how to do their job well. We are supplying the “system” to measure these behaviors because the standard LMS can’t do this.

For example: In a standard online training program to teach customer service skills, the manager only knows the following:

  1. When the student started and completed the course
  2. What their score on the final assessment or knowledge checks were

In most instances, this course wouldn’t allow the student to complete the course without successfully reaching the passing score.

If you were to build a similar course in ACES™, you would know the following:

  1. When the student started and completed the course
  2. Did they great the customer properly – and how many times it took them to do this according to best practice
  3. Did they properly express the right level of empathy if the customer expressed dissatisfaction?
  4. How well they demonstrated accuracy when keying in information on a screen or recommend proper items to the customer
  5. Did they ask an open-ended question to properly help the customer uncover their needs
  6. Did they paraphrase their understanding of the customer’s requests or needs properly
  7. Were they able to handle the transaction within a reasonable amount of time
  8. Did the offer any cross-selling items at the appropriate time

Anyway, you get the point. With the new digital transformation taking place, organizations can bring this power of more information to them to help trouble-shoot employee performance problems before they impact the customer experience.

If you’d like to see the simulator in action, just click this link.

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Seat Time vs. Skill Readiness

By | Adaptive Learning, bots, simulations | No Comments

How to Get the CEO to Notice

Did you know that only 8% of CEOs see a direct correlation to the money they spend on training and business impact? This is one of the reasons why training is the first thing to get cut from a budget when tightening the purse strings.

Why is this?

I’ve been in the corporate training space for almost 30 years now (yikes!). I was lucky enough to follow the evolution of how technology has impacted the delivery and access to corporate training but I have also seen it become a detriment as well.

When electronic delivery or eLearning was first introduced companies proclaimed “Now you can cost-effectively train employees on hundreds of topics.” This never happened, even though the vendors successfully sold libraries of 100’s of courses to their clients, only a handful were really useful to the organization at any given time.

Once the evolution of LMS’s (learning management systems) came about it was the holy grail of managing and delivering training. At first, this was great. As companies grew comfortable with LMSs they began to turn them into something beyond their original intent.

evolution LMS

Evolution LMS

As this image shows, LMS and digital delivery of training have evolved from one to many to agile. But the fact of the matter is, managers and executives have no solid information to tell them if the employee can actually perform the task the training was intended to teach them.

Technology — that is not necessarily new- AR/VR and simulations have a better approach at measuring skill readiness. In the past, these learning platforms were too cost-prohibitive. The digital demand has driven the costs of these solutions down allowing for increased access. I still see a lot of organizations trying to fit these delivery mechanisms into the same SCORM world but it just doesn’t work.

We need to explore how an organization will benefit from exploring learning solutions that truly measure skill readiness vs. just seat time or completion stats. With the availability of AI/ RPA and big data and predictive analytics, we can build and deliver training that helps employees learn new skills faster and more competently. This translates into a direct tie to business impact.

If you’re at all curious to see an example of AI/predictive analytics and simulation learning visit our video page.Videos

 

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Why Your AI Investment Should Be In Employee Training First

By | bots, contact Center, simulations | No Comments

Did you know that poor customer service is costing corporations $80 Billion a year? Even though our economy is still healthy, I don’t think any company can afford to lose customers.

Every day I read about some new products with “AI” or supposed AI embedded into it. Many of these are bots or customer-facing applications to automate or collect data during a customer journey. But even as you deploy these solutions, if the customer still needs some form of human interaction, your contact center staff will need to have stronger skills to handle the more complex problems.

There is a growing trend and awareness in the corporate training world that has finally recognized that the traditional forms of training either via classroom, online or blended, simply doesn’t fully guarantee your training is effective. It simply allows you to check the box training was giving and maybe an evaluation to tell you if the employee found it enjoyable. So What! I don’t know if they can actually perform their job correctly do you?

Here’s where AI comes into play for training. There are new training applications (Like our ACES) that leverage AI and NLP applications to automate one-on-one coaching and guidance to walk an employee through hands-on tasks. Imagine putting a contact center agent into a variety or real-life scenarios multiple times until they have mastered these situations. The embedded AI tracking their behavior pro-actively addresses any mistakes they may make before they engage with live customers.

Plus using a bot like coach removes the need to use your seasoned staff to coach and assist your new hires. Keeping productive and skilled staff on the phone is a much better use of these resources.

Studies show that using this type of technology can even reduce the amount of time it takes to get that new hire up to speed. If you haven’t heard of the term Adaptive Learning you will. This form of learning allows a learner to learn at their own pace with ongoing feedback to calibrate their skills at just the right time.

If you spent a portion of your AI budget in applications like these, it should actually give you a higher ROI on any money you are spending on monitoring customer experiences. If you can proactively reduce call handling times, assure CSAT scores will be high before your agents are placed into production, I think it’s money well spent.

If you want to see an example of this, just click this link to view some sample videos of our ACES simulation.

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How To Make Your Own Intelligent Agent

By | bots, contact Center, simulations | No Comments

Do you talk to Siri or Alexa like they are a personal friend of yours? Intelligent agents and voice technology has exploded over the last three years. Our appliances, cars and HVAC systems talk to us. Now you can build your own intelligent agent without the need to have programming skills.

Amazon Alexa’s Skills has some great templates. Their Blueprint Skills page provides easy to use templates that cover topics from telling jokes, quiz games, and corporate applications.

Google has DialogFlow which provides templates and tools to incorporate, the built-in functions of your device, like time, location, directions etc. DialogFlow had a longer learning curve for me but I can certainly see the benefits of using this to create your own bots. It will even begin to “learn” how to accept inputs that may not be word for word what it needs to listen for but will begin to accept variations of what you are asking the bot for.

They also offer Actions as an extension of their Google Assistant with some pretty easy to use templates.

There are several new companies forming to provide you with a nice user-friendly tool to build your own bot.

Here are some tips to think about when you are building your bot.

  1. Do you want your bot to have a specific persona
    bot agent

    Facebook bot agent

  2. Who are your target users, do they have a device that works with this platform or can they install an app to interact with the platform you are building your bot for
  3. You need to think about what response you want the bot to provide if the user is giving it an input it doesn’t understand.
  4. Does your bot need to be private or secure
  5. Do you want to collect what someone is saying to the bot

Both Amazon and Google have free options which are a great way to play around with them at no risk. Have fun and test it out, you’d be surprised how easy it can be to build your own intelligent agent.

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How We Conducted An AI BOT Smackdown!

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Yesterday I had the pleasure of being a co-organizer for Chicago AI Days, one of the largest AI events held in the Midwest. During the planning of all of the presenters, panels, and moderators I thought there was one very important panel of experts missing from this event —- the virtual assistant panel!

As the day rolled on, we planned a sneak appearance of Siri, Alex and Google Assist. After I convinced some members of the audience to assist me with the final presentation of the day, I presented to the audience our panel of experts.

One goal of this exercise was to demonstrate that as far as we have come with voice-based technology and AI we have a ways to go.

We began by asking each of the bots some softball questions like “where do babies come from” and “where can I bury a dead body”. Then my assistant had some harder questions to ask like “when was the first bot created”, none of the panelists got the correct answer.

Then we turned the questions over to the audience. When we asked the bots “why are fire engines red” Google Assist was the only one with the correct answer. One final question of the evening to really try to stump the bots was “What is the definition of AI?” Siri did not get the right answer both Alexa and Google Assist did.

Now time for the audience to vote. Votes for Siri — 2% Votes for Google Voice 45% Alexa was the winner with approximately 53% of the votes! As much as I like Alexa I surprise she won.

This exercise also demonstrated why products like our ACES are still extremely necessary in order to leverage the power of speech assisted applications. ACES leverages what Microsoft’s speech recognition does well and calibrates it to produce better results than the out of the box functionality. We all benefit from the hard work that has already gone into these smart assistive technologies but they are not ready to take over the planet or — AI conferences any time soon.

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