By clicking β€œAccept”, you agree to the storing of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts. View our Cookie Policy for more information.
Insights

What We Can Learn from CX to Prepare for AI in EX

January 4, 2024
8 min read
What We Can Learn from CX to Prepare for AI in EX
Case Study Details
No items found.

Watch Video

Read Summary

  • Direct signals (feedback, comments) and indirect signals (digital behavior, journeys) can provide insights into customers and employees. Indirect signals can help predict and improve experiences.
  • Concepts like customer effort scoring have customer experience equivalents like employee effort scoring that can provide insights into productivity.
  • AI and tools like Microsoft Viva can analyze indirect signals from employees to help improve productivity, efficiency, and business outcomes.
  • There is a strong correlation between customer experience (CX) and employee experience (EX). Lessons from CX can be applied to EX.
  • Basic EX metrics like interactions, meetings, and response times could provide insights like CX metrics do. More granular EX data could help employees be more productive and accomplish more.

Read Transcript

We have different types of, we call them like indirect signals and direct signals, right? And like a direct signal might be like a comment or a piece of feedback, an email, some sort of record. An indirect signal would be something like digital behavior, right?

In marketing, that's like someone visiting a page, then scrolling down and going to this other section, the whole journey and what they've been doing there. Each time you get those indirect signals, you adapt, you augment maybe an offer, you start to tweak things on the customer side.

On the employee side, we're pretty good at, I think, actually the direct signal stuff. We have employee engagement surveys. Most organizations have employee satisfaction. They have things like that.

But there's another gap, which is this sort of indirect signals and how do we use those? And more importantly, perhaps, how do we predict things a little bit more?

There's this example that I always think of where you could have, like customer SAT, which everyone knows, right? We have customer SAT, which is a lagging indicator, and then we have something like customer effort scoring, which is a whole set of things, but in the customer experience side is a way to essentially monitor and manage how hard is it for someone to do the thing they want to do. So purchase that product, use your services, etc.

Measuring customer effort scoring is really useful in the customer side of the equation. But on the employee side, while we do, of course, talk about employee satisfaction, employee engagement, and things like that a lot, we often don't talk enough about this concept of employee effort scoring. And so if you would think about it like that, it's the same sort of idea.

We use indirect signals, especially if we think of like Microsoft Viva Insights and other tools that give us all this rich data. There are a lot of things we could do to help people be more productive, right? To be more efficient.

Instead of buying a product or doing something like that at the end of that chain, it's just that they're achieving that business outcome, helping produce that document, or helping in some specific way within the business context itself.

I think where you see this really well is there's these large customers that we've worked with that are 150,000 people or whatever, and they have these making it easier groups. They have groups that measure employee effort scores and are working to streamline things. They're working to optimize things.

Of course, AI and other things are a huge part of that discussion and narrative today. But at the end of the day, it's just having an emphasis and an ownership that we can make employee effort scoring better, we can improve that experience. And that that is a more predictive indicator of productivity than pretty much anything.

Yeah, I think that challenge that you brought up earlier, this idea of, like, what could we learn from CX and how could that adjust it? Those are great examples.

Taking that a step further, another pattern that we've been seeing recently, especially with AI, is that the two biggest things that it drives in employees are productivity and quality improvements. If you're seeing, I think, most MIT Harvard studies that are around 60% on average productivity gain, if you're just using like, ChatGPT 4 or 3.5.

That example set of data is the equivalent of, like, Bing Enterprise chat, right? It's a baseline capability. But if you take something like Microsoft Copilot for Microsoft 365, or Viva or other workloads, it's using the rich data of your organization. It's providing technical skills because it understands thousands of commands within those tools.

There's a lot that it can do that takes that 60% productivity and increases it to, in some of our internal preview work with customers, we're seeing things like 120%, 90% productivity gains. Instead of 20% quality gain on average, which is what we're seeing publicly on those other studies, we're seeing things like, again, 35%, 40% quality gains.

Those kinds of differentiations make an organization more competitive, and they can't be ignored because we all know customer experience, of course, needs to include employee experience, right? There are lots of processes where they kind of just slightly move outside of the customer lens, like the customer experience lens.

Employees and people in your organization have to tackle that, right? There's an escalation, or there's a pattern there.

When that happens, and people have to get involved, being more digitally fit, having more digital skills, being more productive, using AI and other tools to augment their own access to skills and information, those are all things that are going to make a customer experience and then by proxy, the growth of an organization much stronger.

I think there's a really strong correlation between them, but I absolutely echo what you're saying. We really need to think about the data more and intention and be a little bit more directive with that because having it keep the lights on is just not enough anymore.

We need proactive focus. There are basic things, right? There's some simple stuff that we're not tracking, we're not aware of, because we just take for granted that everybody kind of is assessing themselves in a proper way.

But some basic metrics that we would look at on the CX side that we don't on the CX side is like, how many interactions is somebody having a day, and what do those look like from an email voice perspective, even a meetings perspective, like how many meetings are you in?

What are those meetings about? Who's in those meetings? Who shouldn't be in those meetings because they didn't say anything and even contribute in the last three meetings they're in they didn't say anything. Those are the kind of things that are fundamental and basic but could be really interesting. You could then take that a step further.

Depending on inter-department conversations or intradepartment conversations like, how long is it taking people to respond? What does resolution time look like for problems that have come up in these meetings? What's the satisfaction of that actual meeting were there to dos that came out of that meeting that are even being actioned?

Even if I take it down to the fundamental aspect of work that we're in every day, right? I'm in meetings every day and calls every day and chatting every day, like you and everybody else on this call, but are we accomplishing anything? Are they the right ones?

Just those fundamental elements. If we think about what's happening on the CX side and take this stuff into the EX, I think there's a huge potential to unlock, like you said, a ton of productivity and save people a ton of time so they could just do better work.

The things that frustrate people the most, where they get kind of either disappointed or down or don't have fun when they're working, is when they're wasting their time. People want to be productive. I definitely know I do.

I feel great at the end of the day when I feel like I accomplished something, and I feel pretty weak at the end of the day when I felt like I put in a full day's work and I've got nothing to show for it. This is the kind of stuff that should not only be for a manager to help manage an employee, but if we all had access to this stuff, I think it'd be great.

It makes me think of that email that I think I got on Sunday from Microsoft. I don't know if it's a Viva email or whatnot.

Yeah, the Viva Insights one. Yep.

Hey, I spent this many time. Okay, that's cool when I'm looking at that on Sunday, but it's too high level for me to action, so I kind of disregard it.

But if I had more meaty (change this word) stuff, wow, that would really start to build some awareness and then help me make some choices and affect the things that I'm going to be doing, kind of moving forward.

Again, the takeaways here are great, and I don't think we have to reinvent the wheel and figure this out from scratch because they're doing it so well on the CX side.

Need Help With Preparing For AI in EX? Let's Talk
Case Study Details
No items found.

Similar posts

Get our perspectives on the latest developments in technology and business.
You will love the way we work. Together.β„’
Next steps
Have a question, or just say hi. πŸ– Let's talk about your next big project.
Contact us
Popular insights
One of our goals is to help organizations build a better digital workplace experience.
Access knowledge center