Mind the Gap: Closing the Distance Between Service Quality and Perception

If you think you deliver excellent service to your clients, but they think the service is mid at best, guess whose opinion matters most?

And how can professional services leaders work to close that gap before it costs them clients?

Hi, I’m Courtney Baker, and this is AI Knowhow from Knownwell, helping you re-imagine your business in the AI era.

As always, I’m joined by Knownwell CEO, David DeWolf, Chief Product and Technology Officer, Mohan Rao, and NordLite CEO, Pete Buer.

First up, let’s send it over to Mohan and Pete to unpack a recent AI news story that using AI at work can negatively impact your reputation.

First, the Shopify CEO, now this.

There was a bone here, Mohan and Pete.

What are we supposed to do?

Pete Buer is back to keep us honest about the latest AI headlines.

Pete, ready to ruffle some feathers?

Mohan just opened the door to the chicken coop.

Ours Technica just covered a Duke University study that says workers who openly use generative AI are viewed as less competent and even lazy.

Many are hiding their AI to dodge that stigma.

What’s really going on here, Pete?

Well, three things worth knowing coming off of the study.

First, AI shaming apparently is a thing.

The Duke experiment found that coworkers who used AI were rated 14 percent less competent and 19 percent less warm.

It even affected perceptions of teammates who collaborated with the AI users.

They were perceived less competent as well.

Second, the more senior you are, the more self-conscious you are evidently about your AI use.

So, the Duke study found that junior staff using AI, I think it makes them look kind of rookie, whereas senior managers feel that it signals their incompetence.

Third, like attracts like.

So, if you use AI actively, you’re more inclined to fill your team with people who also use AI actively.

And if you don’t use AI, you steer clear of the candidates who show up who do.

So, what do you do with the study findings?

I think as a leader, you have to de-stigmatize AI use and you have to do that very publicly.

It’s part of our home lives, it’s part of our work lives, and we need to be shamelessly making the most of it in both settings.

And so, it’s uniquely the job of leaders in their modeling, in their policy setting, and in their communication to make sure firm culture is positive and accommodating around the use of AI.

One of the best ways to do that is to actually write AI skills, expectations, and use directly into job definitions.

So, be clear about where and how it should be used, and also that there’s an expectation that you should be using the best tools at your disposal to get the job done.

Again, it’s uniquely the work of leaders to cover off this space, and it’s not a difficult thing to do, but it takes deliberate effort, and it makes a little difference in the world.

Such good advice from Pete Buer.

Thank you, Pete.

Thank you, Mohan.

A landmark study from Bain & Co.

found that 80% of firms believe they deliver a superior experience, whereas just 8% of customers report receiving a superior experience.

So how can we close that gap?

I sat down with David and Mohan recently to discuss.

David, Mohan, welcome back.

I want to start today’s conversation with a simple but frustrating truth.

And I think everybody listening is going to be nodding their heads.

Even when teams deliver exceptional results, clients don’t always feel like the service is exceptional.

There’s this stubborn disconnect between what’s delivered and what’s perceived.

And honestly, it feels like this is the basis for any relationship interaction sometimes.

There is a disconnect between those things, but obviously in professional services, this becomes very frustrating.

So let’s unpack why that happens and how leaders can finally close that gap.

Courtney, I think one of the really interesting things is where this concept comes from.

We have spent literally hundreds, over 500 now, conversations with customers in this space.

And over and over again, we hear that firms may measure service quality to some extent, but if you actually look at the research, it is quite clear that actual service quality does not matter when it comes to professional services.

What actually matters is the perception of service quality.

Now, undoubtedly, there is a direct link between perception and reality, but it is not a one-for-one direct link.

It’s actually a fairly indirect link, right?

And so it’s important for us to, number one, acknowledge it.

Number two, figure out how do we measure it, right?

I think a lot of times we’ve measured service quality because we can, whereas perception is really hard to get your hands around, right?

And it’s hard to measure.

It’s hard to track.

It’s hard to drive execution off of.

But we now live in a world where we actually can.

We can interpret signals that are already flowing through our organizations, right?

Communication with clients as an example, in order to get our hands around what is perception.

And the delta between those two things, the perception and the actual service quality, is often related to how something is understood, the feeling behind it, the emotion behind it.

Do I feel, for example, we have found that the biggest driver of service quality perception is responsiveness.

And responsiveness not being just how quickly do I get a response, but how directly is the response addressing what I have surfaced.

That is an emotional feeling.

Do I feel respected?

Do I feel honored?

Do I feel like somebody’s listening?

Somebody has my back, right?

Those types of things really, really matter in professional services.

And it’s time that we start measuring that, tracking that and driving our execution against it, versus just this mere reflection of service quality itself, which is important, but is not the end all be all.

Perception is reality.

David, I feel like we should pause here for a second for people that are new joining us.

You have a lot of experience in this, leading a professional service firm for 16 years or 18?

16.

16 long years, yeah.

They were good.

16 long years.

Do you have a story off the top of your head where you could kind of illustrate this gap?

I mean, I have dozens of stories off of this, right?

And candidly, they cut both ways.

I used to tell our employees, and I would actually tell new clients this as well.

Every time we signed a new contract, had a new client, I would sit down and I would say, listen, in professional services, I can guarantee you that things will go wrong.

What makes a relationship is not whether or not it goes wrong, it’s how it’s handled when it does go wrong, right?

And so to the client, hold us to that bar, right?

Because we want to be proactive and candid and transparent in resolving issues, right?

You should expect that from us and you should have confidence that that’s the way we look at it.

To our employees, we have to live up to that bar.

And why did I say that?

I said it because I had dozens and dozens, hundreds and hundreds of examples where, yeah, I cannot control human behavior and mistakes happen and there will be something that happens.

But everybody understands it’s how you rise to the occasion when it happens, that actually drives the quality of your firm.

What we have to do is now get the operational metrics to match that reality.

I think a lot of firms probably have a similar track track, but don’t measure it that way.

And what I’m saying is it’s now time to take what the best professional services firms do in managing client relationships that way and embed it into our operations so we’re actually measuring it, tracking it, and driving performance off of it.

I feel like that’s a really powerful distinction, what you deliver versus how it’s felt.

And we know professional service firms, you know, it’s built on relationships and relationships.

You know, it’s not just metrics.

Sometimes we can actually over index on metrics so much so that we miss kind of the sentiment, the feelings that are there from the client.

Mohan, is there, what do you see in TAG that’s actually helping us understand that emotional layer at scale?

You know, the nice thing about AI is you can measure the emotional gap between what has been said and what has not been said, right?

So you can measure the emotion and the sentiment, but this is such a complex problem, right?

So it can start way before the service delivery starts.

It can be a misunderstanding in terms of what the clients expect.

It can be a misunderstanding in terms of the service itself.

It can be a misunderstanding in the execution of those services.

It can be something about promising what you can deliver.

There are so many parts to it.

You know, they could also be thinking about, this is like an utility service that I’m getting.

Let’s say you’re some sort of, you provide an utility service.

The customer does not value it except when it’s broken.

Right?

So that is a problem.

Then they could be thinking that, hey, this service costs too much and they’d never appreciate you for it.

It’s a pretty major way to, you know, it’s a pretty major problem in services.

And the way we’ve done it in the past was to make your clients win.

Be there for them whenever they are in distress.

Right?

So whatever it is, you just compensated it.

Good account managers, good delivery managers, good executives did this by essentially bridging it emotionally and being there for your clients.

That’s how we did it.

But none of these scale.

That’s the problem.

Right?

And luckily, with a lot of these communications, now being in natural, whether it’s in Zoom or Teams or in a much more natural language, you can start scoring and you can start measuring the sentiment and starting to compensate.

And ultimately, it is some way of saying the technology helping you so that you can essentially make sure that you’re there for your client at the time of need, but also be able to say when you help them to be able to say, we helped you because these reminders are very important in the entire services journey.

These are some ways that technology can help.

I think it might be helpful to think about the things that you do today in your firm that help you try to get at this.

Obviously, there’s measuring your service quality, but there are things happening in an organization trying to get at the service perception.

It is all of the customer satisfaction scores, it’s surveys that we do with our customers, it’s QBRs.

I mean, there’s a whole host of things that we are trying to do to get at that.

The problem is usually, it’s hard.

Those things are hard and flawed, and you cheer if you get 30% of your customers to respond to something.

You’re like, we knocked that out of the park, and yet none of us would say 30% is anywhere close to a reliable metric on something.

There’s been all sorts of challenges with it, right?

It is the response rates.

It’s also the episodic nature, right?

I always wanted, it drove me nuts, take an NPS score, a CSAT survey that you’re talking about.

You can only survey your clients so often, right?

I want operational data that I can drive execution from.

And that means it needs to be near real time, right?

And so I think it’s hard when you’re surveying your clients once every three months, right?

Even if you really push it and it’s once every six weeks, really doesn’t give you a barometer to be proactive, right?

To be incredibly responsive to things that go wrong.

And so I think that the lack of operational metrics that actually drive behavior is a big part of it.

And you’re describing that very, very well.

It’s not just the responsiveness, though.

It’s the episodic nature of it.

Yeah, exactly.

Yeah.

And you know, with these technologies, what they can help you with the new breed of technologies, that it enhances your self-awareness of the situation, right?

And it provides even some sort of emotional regulation, right?

You know what is happening because as, you know, the scores are getting updated more regularly, daily.

And it allows you to compensate for what may be going on, because it is a difficult business to scale and be able to essentially enhance these softer aspects of client leadership and be able to compensate for that in real time is the key.

You can do it when you had a handful of clients, but it’s very hard to do this when you have a hundred clients and things more or less kind of falls apart, right?

And the only way to do this is to augment it by technology, and it’s possible.

So I would love to get really practical here.

What’s one signal a leader might miss that a machine could catch?

You know, I think you need to think of this in terms of an organizational scale.

It is not just a leader missing.

All the leaders can certainly miss.

It could be something that was said to an account manager at some level that never gets to the leader, right?

So that’s what is hard in a scaling situation where you might have your emotional senses exactly right for great client relationship, but you cannot impart that everywhere in the organization.

And invariably, somebody somewhere is going to miss a whole host of these and that you don’t take the corrective action in time.

Mohan, so I’m just going to tell a story here that just proves that point.

We were talking a few months ago to a chief commercial officer and was sharing me a story that wasn’t even an account manager.

There was somebody in their revenue operations organization who received a question from a client regarding the termination language in a contract.

And the chief commercial officer did not hear about this until over three weeks later because that RevOps individual, great person, knew their job.

They just didn’t have the consulting wherewithal to have the alarm fire and say, this may be a problem.

Now, that’s just a blatant example that I think proves the point that you’re making, that these signals are all over the place.

What technology can do is it can process infinitely more data points than we ever could, right?

And so even as a human being, I can’t sit in all of the conversation, so it can process all of them, right?

But also it can connect those dots.

And sometimes to go to the other extreme, that’s a blatant example.

Courtney, on the other extreme, there are these little data points that are just subtle little hints that something might be a miss, that they start to add up and they layer on each other and land on each other.

And if you can connect the dots, it’s like, you know, something’s going wrong.

It doesn’t feel like, right?

And if you were sitting in the conversation, you would get that feeling, that gut instinct that something’s going wrong.

But technology can go and collect all those data points and connect them in the same way and say, hey, warning sign, 52 times the last week, there’s been a slightly negative pulse that has been communicated to different team members.

Alert, 52 is more than the 26th that happened the week before, right?

Those are the types of things that technology can do because now technology can understand human natural language.

So as I’m thinking through this, maybe the big question is, if your client doesn’t feel the quality, does it really count?

And what are we doing to make sure that our best work is truly experienced by our clients?

Yeah, you know, early on in my career, I had a very voice manager who told me that when you have great people on your team, you know, a star is not a star till they know that they’re a star, right?

So you’ve got to kind of communicate.

So you do good work, and but you also make sure that the client knows that you’re doing good work.

And unfortunately, from time to time, you cannot do the best possible work.

At that point, be very upfront, be very proactive, and just go say what needs to be done to do good work.

Right?

It’s just, it’s this hard work of knowing exactly where the client’s mind is.

Claiming credit when you’re to claim credit and tackling problems head on, I think is the key here, right?

And how do you scale it is the bigger question that we’ve discussed in the episode.

David, what do you think?

Yeah, I think that’s right.

And I would add to that, that there’s different ways to quote, feel that service quality, right?

So a lot of research has shown that impact, right?

Actual impact at the bottom line of a business is the best way to drive retention.

Unfortunately, for professional services, it’s very difficult to take credit for and to be able to measure that impact.

But if you can prove that impact, and it’s something that you can take credit for, it can be powerful.

And regardless of what the customer actually feels, I think you’re going to have a long lasting relationship because you’re driving bottom line results for your client.

Now, hopefully you can do it in a way that feels good as well.

And most firms that drive impact actually do deliver on that.

But I think that’s really…

But I also think the softer your service is, the more you’re providing advice, the more you’re providing consulting deliverables, those types of things, making the client feel like somebody is in their corner, right?

Somebody has their best interest in mind.

Those types of things really, really matter.

And so how do you do that in this day of technology is the question.

And I think there are platforms that can surface these signals and can provide them to you, but there are also platforms that can help direct you and advise you on, here’s what you should do about it, right?

And I think that’s the cutting edge of this technology, is the ability to surface the signals and infinitely read more data than we otherwise could, but also to be able to figure out how do we coach ourselves up and do, here’s the next best action, this is what I should do, here’s the recommendation that we have to be able to proactively kind of build that bridge with the client and pull them close to you.

Well, and ultimately, at the end of the day, what we want, you know, we want professional service firms to be able to lead from intelligence and data and not from gut instinct, which is where we’re left many of the times.

David, Mohan, thank you as always.

Thank you.

Pete Buer and I just had a webinar on establishing an AI powered client management system.

You may recall a few episodes back when we previewed the webinar.

Well, it happened and it was great.

Just to prove it, here’s a short clip from the webinar where Pete paints a picture of what exactly an AI powered client management operating system looks like.

You can get the full recording at knownwell.com/operatingsystem.

I’m going to start high with a quote from our friend Socrates, or if you watch the same movies that I do, Socrates.

The beginning of wisdom is the definition of terms.

It’s not exactly known, but it’s believed that what he meant by that is that you can’t have an intelligent conversation, whether it be about philosophy or client management in the modern era, if you aren’t clear from the start about the central concepts involved.

So, what is this thing, this client management operating system?

The short answer is it’s an interconnected set of capabilities, think tools and processes and data and frameworks, that come together effortlessly to drive effective service and commercial operations.

Now, recognizing that’s a pretty high level definition, fairly academic, probably doesn’t meet the Socrates bar for the true beginning of wisdom.

So I’m going to offer another example of an operating system that we’re all familiar with.

You know it as Apple’s IOS system.

I know it as the PBPOS system, which is to say the Pete Buer Procrastination Operating System.

Let me share with you how it works.

So this is Tuesday, starting in the upper left, 7 a.m.

I’m dressed for the day, checking Google calendar on my iPad in the bedroom before I come downstairs.

And I notice magically no meetings scheduled until late in the afternoon.

Inspired, I click on Slack to see if Courtney or David have blown up the channel.

And lo and behold, all is quiet on the Knownwell front.

Siri checks weather for me, mid 70s, sunny with a light breeze.

7 15 now, I’m making my way downstairs.

I’ve got my phone, open up the Tea Time app, make a reservation at Viking Springs Golf Course down the road for 8 30.

Check my Jeep app to see that there’s gas in the car and warm up the driver’s seat.

It’s been a little cold lately.

7 30, place an order for Starbucks.

Pick up bacon and Gruyere egg bites if you know the one with the venti ice coffee, no cream, no sugar.

And on my way to Starbucks, I place a call to my friend, Will Sherlin, the voice of Knownwell, and convince him to play hooky with me on the golf course that day.

So we’re all using this form of an operating system, which is again, an interconnected set of capabilities, in this case, software applications, hardware data, right?

Combining effortlessly to give me an absolutely terrific Tuesday, despite the horrible golf.

Okay.

Before I can go on, Pete, I have to know what the movie reference was.

You don’t know Bill and Ted’s Excellent Adventure?

I can’t say that I’ve ever seen that one.

So maybe we have to put it on the list here.

Keanu Reeves had his best.

Yeah.

So I’m beginning to understand, I think, what you mean here.

So two big insights for me is, first, we all have something that is running what we’re doing, even if we’re not aware of it.

Really this application of the operating system concept, seeing all these different apps that are running on this core operating system.

And I know we’re going to get in to that more.

And the more I think about it, some operating systems that I’ve seen, more mature, and some are kind of a hot mess.

But I think everybody out there has some kind of operating system, whether they realize it or not.

Over and over again, you know, when I ask companies to talk about, hey, tell me about what’s your management system?

What’s that look like?

You know, I’ve heard things like, it’s duct taped together, but they’re also really proud of it, even though it’s not, they would say it’s duct taped together, because it is kind of hard, because again, it’s working on the business, really getting that operating system together.

So let’s close out the section with a view of what the 301 level of client management operating system looks like.

Now powered at the center by AI, we’ve crawled and we’ve walked, and now we run.

So bottom left, now we’re green, so that must be good.

And I’ll do a, that was then, this is now with our prior view, where we had limited transaction data before.

Now AI can hoover up and integrate all of that transaction data, along with all the other forms of data at our disposal, especially and most importantly, given the human powered business model, the natural information flows between ourselves and the customer.

Where we had and still have that messy disconnected tech stack, AI lets us circumvent it.

And by the way, helps us maybe even sidestep that multi-million dollar data integration project that we’ve been putting off for years now.

Where we had spotty data on different aspects of each customer relationship before, we can now create a comprehensive and easily digested single view.

Where insight used to be held mostly in the head of our experts.

Now everyone on the team has access to an expert level view.

And where we were making decisions based on gut instinct.

Now we have real insight, outcomes informed recommendations.

I won’t belabor the story more because we’ve been working our way around this circle at three levels of the system for some time now.

But not only does AI bring a new level of game in decision making, it also makes each of the other three elements of the operating system better.

So on the right hand side, real time tracking of progress against goals and objectives, identification of soft spots, automated recommendations for closing gaps.

It’s watching and thinking for you about where you stand and what you should do in your goaling system.

At the bottom, on your roles and responsibilities, insights and recommendations automatically customized to the user persona, the role, the responsibility of whoever needs access to the system.

And similarly over on the left hand side, on your meeting cadence, insights and recommendations tailored for every meeting you run across your operating system.

And there are dozens of them, and it’s effortlessly able to customize for every single one of them.

We’ll see in the next segment how this comes together when we share a view of AI in the wild in use.

And I’m looking forward to getting to the opportunity to go from what the concept looks like to what it looks like in use.

Pete, thank you.

That’s really helpful and quite a journey.

I am mindful for everybody watching.

Maybe their CEO was listening when the Shopify CEO recently said, don’t ask me for a hire until you can prove that you can’t do it with AI.

And it’s kind of daunting in a way.

You’re like, how do I do this?

And I think there’s so many things here that you’ve already kind of shown.

Hey, you actually can from the very operating system really power it with AI.

So I love that we’re about to get in some tangible example.

So if you’re out there and your CEO has given you that challenge, hopefully some of the things we’re about to talk about and have been talking about will really help here.

Thanks as always for listening and watching.

Don’t forget to give us a five-star rating on your podcast player of choice.

And listen, we’d really appreciate it if you can leave us a review and share this episode on social media.

At the end of every episode, we like to ask one of our AI friends to weigh in on the topic at hand.

So hey, perplexity, this episode, we’re talking about closing the gap between service quality and service quality perception.

So what do you think?

Closing the gap between service quality and how customers perceive it is all about making sure what you deliver actually matches what you promise and what customers expect.

Getting regular feedback and being honest in your communication helps you spot where things don’t line up and fix them fast.

And now, you’re in the know.

Thanks as always for listening.

We’ll see you next week with more AI applications, discussions and experts.