EP3: How Enterprise Organisations Are Scaling Human-Centric Innovation

00:00:00: Welcome to the Zoom Amir podcast, where we will explore how technology and human connection are transforming the way

00:00:06: we work.

00:00:08: In today's episode were joined by two incredible voices in the world of customer experience and digital transformation Michelle Booth And Andy Kingston.

00:00:17: They'll be diving into what it really takes

00:00:19: To create

00:00:20: connections and collaborative ways Of working powered by AI How Transformation is

00:00:25: much more than just deploying new

00:00:27: technology.

00:00:28: So, without further ado let's hand over to Michelle and Andy.

00:00:32: Thanks for joining us today.

00:00:34: I'm Michelle Booth CX AI lead from a mere region at Zoom And i am delighted to be joined by Andy Kingston Head of Consumer Channels Transformation.

00:00:44: Andy & I actually worked together in the past on some early adoption of AI in financial services so it is great.

00:00:52: And since then, Andy's worked across some very complex enterprise organisations so has a wealth of experience in scaling human-centric innovation.

00:01:02: Today we're going to get into what it takes to create a more connected and collaborative way of working aided by AI... ...and what that change in adoption looks like for customers, for organisations or employees And I'm really looking forward to getting Andy's view on the value of AI and where he sees it making the biggest impact in customer and employee experience.

00:01:26: So welcome, Andy!

00:01:27: Something that we've both seen in customers who invests in this technology is almost a hope that the transformation will just happen.

00:01:36: here's the shiny tech you know wears the results.

00:01:39: What's the difference that you've seen in simply deploying technology and actually changing how experience works for customers, colleagues on a wider operation?

00:01:49: It is great question.

00:01:51: That word hope always springs eternal into this field.

00:01:56: but I think there are probably three core elements.

00:01:59: so one when thinking about technology and transformation we often bring architects in or bring technologists who deeply ingrained in the back end systems, in a working of how an organization's data flows from system to system.

00:02:16: And that is great starting point and know what they are possible because I think we've all been on the end being told dream about technology can do for us but reality restrictions of how your organisation systems processes and data is architected it is big one right?

00:02:36: So there was this But there's probably a step before that, but I think a lot of people miss.

00:02:43: And certainly I've seen whether you're gonna have to flick onto LinkedIn and see people talking about how they wanna do this or want to do that?

00:02:50: They almost get a bit like the Magpie effect because it gets obsessed by the shiny technology side Before really being super clear on what is am trying to solve Is an opportunity.

00:03:02: I'm trying grab where once we connect with more customers challenge or a problem I'm trying to overcome, and that might be lengthy handling time of customer interactions.

00:03:14: It might be levels of automation and containment not at the right level.

00:03:19: it could be as simple as customers are satisfied Or maybe just like the level complexity A colleague serving their customer has to deal with And actually rebuilding all our systems and processes is hugely costly and unrealistic.

00:03:36: So, therefore the AI or that technology can do some of that for you.

00:03:40: I think one like nailing down what is it your trying to do?

00:03:44: That's a key step before you get into what kind of technology they're doing and getting in to the whole architecture bit.

00:03:51: And then another thing.

00:03:52: there was third step which is people who are roles like me sometimes have to over ourselves.

00:03:59: We don't always know best and I think like Gunn talked from my colleagues about what they're seeing, what their experiencing.

00:04:07: And go and ask them the questions about if you had technology that could do whatever it is your trying to achieve?

00:04:14: Would that help?

00:04:15: because most often or not though give you the home truth They'll actually tell ya another year like That Is The Real Problem.

00:04:21: Or Actually You Should Have The Wrong Thing.

00:04:23: You Should Be Trying To Fix This Bit.

00:04:25: For Us I think we tend to do in a desire to spend the capital with being blessed with.

00:04:32: We're trying to go so quick that we forget about really important step and would bring frontline colleagues in way too late, almost when you want them to prove or justify their all the work they've gone on say yeah this is just make a massive difference.

00:04:45: then we get reviewed per se whenever I said okay it's not great!

00:04:49: So there are definitely those three steps.

00:04:50: i think.

00:04:51: be really clear what your'e tryna do?

00:04:53: Then how is even possible within environment working and then get colleagues who are serving customers in very early on to tell you the kind of what's an all side of it.

00:05:08: What would this really do?

00:05:11: And a benefit for that is, design much more impactful things with greater propensity to land more positively first time around but also realistic about your outputs.

00:05:24: And you are when it comes to kind of justifying that capital expenditure, whether your can return investment or all the metrics.

00:05:32: You want a track for success?

00:05:34: You're actually tracking the right ones.

00:05:36: That's some of the challenges I've seen in the past is we do all great work but then we track the wrong things at the end and can't work out those being good on their phone up!

00:05:45: Then we ended up revisiting them.

00:05:48: so yeah three simple steps for me that the first and a third sometimes are slightly put in the shadow of the second one which is always big and shiny.

00:05:59: Tech team, can you deliver this for me?

00:06:00: It's

00:06:01: not.

00:06:01: it's not a geek project as it is like.

00:06:03: let's ground it in realism and look at the actual problems we've got today And I'll be working with people to know best and I guess collaboratively delivering will drive the adoption.

00:06:15: then I'm interested then when you do strip back the fundamentals of good service, so generally not change.

00:06:21: You know customers still want things to be quick clear easy.

00:06:27: what's really changing with technology is our ability to personalise service and make sure that we do it in a way thats relevant Not creepy but helpful.

00:06:37: How do you see technology helping organisations strike that balance between a simplistic service and the more personalised context aware experience?

00:06:48: This is like multi-layered, right.

00:06:49: You're absolutely right about.

00:06:51: let's not make it creepy.

00:06:52: Let's not scare customers.

00:06:55: but I think there are fine lines between scaring and delighting.

00:06:59: And he's not just about data.

00:07:02: It's how its presented move from the thing that you're engaging the customer about to the things like delights.

00:07:12: So, I've said way too many times in my career customers don't wake up at morning and want a callers or wants chat with us.

00:07:22: most of time they wanna get on their lives.

00:07:24: we are certainly in service sector.

00:07:26: We ask kind-of not that important really until things go wrong And then they wanna talk.

00:07:34: So I think the first bit is you've got to put your technology and if you're going use technology, and colleague.

00:07:41: To get through the points quickly.

00:07:44: time Is there?

00:07:46: The deal breaker here can you resolve the customer's inquiry quickly on with absolute confidence?

00:07:52: so like almost earn their rights to then Get onto another topic or in a right to try and go and delight the customer?

00:08:01: And then the technology under data is the really important thing.

00:08:07: But I think it's not just about, The data prompts or their potential needs that you've identified.

00:08:14: It's also how we position and with context to what customers may be told in your initial inquiry.

00:08:21: Now as an inbound service provider If you're thinking of outbound Or embedded like digital Most customers are of Faye with self-serving, app based interactions now.

00:08:36: So using data slightly differently technology to proactively engage there I think is a really interesting opportunity and the number of considerations.

00:08:47: so one if you want to interject in a customer journey or custom interaction digitally it must add value.

00:08:54: If your interjecting then customers going well.

00:08:56: i could have done that myself like commercially.

00:08:59: its not adding no value to business but actually degrading the service, experience.

00:09:04: So you must have value.

00:09:05: and then secondly how do you interject?

00:09:08: And who interjects?

00:09:10: whether it's technology-led or whether its colleague led.

00:09:13: I'm making sure your absolutely transparent about why.

00:09:16: Why are you actually trying to engage with that customer?

00:09:21: That sounds like a really obvious thing.

00:09:23: but again It is something we miss all of time.

00:09:26: We don't tell customers what we're engaging in our position at the start.

00:09:31: So, the customer was trying to second guess probably still wrapped up with trying to do whatever they were trying to Do.

00:09:37: so I think there's a flow to A lot of this around using The technology but doing it through the lens Of what's the value add To the customer.

00:09:47: and if you've got a colleague involved?

00:09:49: The value add to the colleague?

00:09:51: Probably the key bit is Like, when do you start?

00:09:55: At what point are your confidence to go back?

00:09:57: so that is creepy.

00:10:00: I've also seen organisations try and get down into a segment of one in their data like really hyper-personalised...I'm not sure how you need it!

00:10:12: You don't have to go to the depth and mine out those amazing diamonds in your data to engage with customers.

00:10:21: I think you can desire to get there, and you could desire to have the most impactful nudges in data points that an organization has ever seen.

00:10:32: But you can just provide solid data-driven prompts... ...that a colleague can be trained to use their skill to interact with.

00:10:40: And i think thats where we see our biggest impact right now is Yes!

00:10:45: In the future We all want amazing Data Driven interactions That make our lags Better as consumers and the organizations want that, because you can argue.

00:10:56: You get your positive jobs of better revenue and cheaper costs to serve but in the interim just providing good data to colleagues real-time saying have this conversation then train a colleague on the conversation not on the process Because technology could do.

00:11:15: it's the conversation where value really comes.

00:11:19: I think that is an opportunity where we are now.

00:11:22: And I think that sets us up for the future, whether data is richer or more segment of one way with really worked out how to leverage a huge data like organization sits on because that will just better emphasize what the colleague needs do which would be complex technically difficult stuff.

00:11:43: technology can't go but stepping stone is colleagues and good data at the right time.

00:11:49: You know, I air a phrase a lot which is we need to use technology in the way that helps humans be more human.

00:11:56: And it's exactly what you're describing there – almost getting the blend of.

00:12:01: We've got insight and data.

00:12:04: It doesn't necessarily mean today we should rely fully on the technology to deliver that.

00:12:08: Let us actually work with experts let give them information have better conversations, until we get the basics absolutely right with AI.

00:12:18: That's the space you see most value from them.

00:12:21: or are you seeing where were moving into Andy?

00:12:23: I don't think it is necessarily just the basics... ...I think its society to trust technology and trust in AI.. ..I think that still a whole different podcast talking about trusting AI which weren't going through today.

00:12:36: but there an element of how much do we trust Within organisations, we're training ourselves to a certain level but not do it all.

00:12:45: To put our thinking and how are builds on the framework or basis that AI gives us?

00:12:52: I think that's a skill in itself which is good for evolving further.

00:12:57: Absolutely!

00:12:58: And at the more advanced end where we see AI identify... quite critical things in conversations such as fraud or risk, are even vulnerability and then take action off the back of that sometimes independently.

00:13:14: And some times with human oversight.

00:13:17: how would you suggest organizations think about designing?

00:13:21: That kind of blend when humans judgment is so important.

00:13:25: but the automation is there to support on keeping an element of trust I guess and a character at the

00:13:32: centre.

00:13:33: If you take back to almost the first point we made, which is a choosy use case.

00:13:37: See if used fraud for example, fraud and financial services are great examples of this.

00:13:43: often there art not always science but they're out of colleagues.

00:13:48: helping customers understand whether an interaction is fraud or not is being able to consume multiple different data points.

00:13:58: Learn from repetition, learn from the warning signs that the customer doesn't see.

00:14:04: often they've become a victim of fraud because it's something new and never experienced.

00:14:10: so its almost a naivety to it.

00:14:12: And this does not mean customers have done anything wrong.

00:14:14: It just means They don't know how to look for that to be a warning sign whereas a colleague has seen over again as their learning through repetition through repeatedly serving customers in similar scenarios.

00:14:27: But to do that, the colleague often has to consume huge amounts of information.

00:14:31: they have to work out quickly with the customer which bits are valid and which nots.

00:14:37: And thats where the more complex AI can come.

00:14:40: because you could train your models.

00:14:44: so think about it.

00:14:45: You could break down different aspects or fraud If you use that as an example, the different types of fraud and different types to scams.

00:14:52: And break down what other core areas call things a colleague is considering?

00:14:57: What data are they pulling from different

00:14:58: systems?".

00:14:59: This could be double-digit numbers of systems they're pulling information from while talking to your customer.

00:15:06: So how do you put into AI models in the background to build a propensity score or start to decide... ...what are chances?

00:15:15: this is fraudulent or not?

00:15:18: I think it's an element definitely we can consider and he didn't have to be fraud.

00:15:22: It could be multiple use case, but then the second thing that would encourage anybody who is thinking about considering what happens with a role of their colleague?

00:15:30: Because you could argue in less emotive examples of fraud.

00:15:36: if there technology can do that does they just need to relay the answer to the customer?

00:15:41: possibly?

00:15:42: But If That Was The Case Across All Things We Wouldn't Go And See GPs Anymore Would We Because we just all rely on what chat GPT or any of the other language models told us about what their ailments are.

00:15:54: But, We still go and see a GP.

00:15:56: so why is that?

00:15:57: Well it's human connection It's the reassurance they have.

00:16:01: I interpreted this well.

00:16:03: Do i know in my scenario with these things going On Is This Definitely Right?

00:16:09: And A Lot Of My Experiences In Financial Services You See This A Lot.

00:16:13: even when you and I worked together around digitization in the early adoption of technology, we would often see that customers... You could give them all information on your public website.

00:16:26: Pandemic was a great example about bounce-back loans or payment holidays and their approach to furlough and everything else.

00:16:33: We put all our information out there And it'd be written by best content writers who've got an organization And it'd be really simple and easy to understand, but you still have customers calling you saying can I just check what this means for me?

00:16:47: It's less of a reflection on the content.

00:16:50: But more of a reaction from customer confidence.

00:16:53: in that scenario financial services and banking... Oh i'm not quite sure!

00:16:59: Just want human touch to reassure me.

00:17:03: so You could build great complex handling AI tooling that can build propensity models and guide colleagues for what is the next best conversation to say.

00:17:19: Absolutely, we should all be aiming for that because ultimately speeds up service cuts down at length of interaction.

00:17:27: And also you could argue For anybody who's running a customer service team You could argue it reduces their time To get new colleagues trained.

00:17:38: But he does pose another question, which is so what's the role of a colleague then?

00:17:42: And for any of us have been to see a GP recently.

00:17:46: The role of the GP has changed slightly.

00:17:49: they are exploring much broader lifestyle with you than whatever it is your de-ailment.

00:17:56: You've gone to see them about this.

00:17:57: They're exploring other things that happening there.

00:18:00: seeing in society With you do use on face we go well.

00:18:04: how was that linked to the bad toe I've got?

00:18:05: Or, you know they're looking for longer term lifestyle symptoms that may need your help to address because what they need to learn now can all be sourced on the net.

00:18:17: Whatever whatever you've got is wrongly off-toped.

00:18:19: They can type it in a family and so then no longer have to retain that information... ...they needs just understand bigger picture.

00:18:25: And I think That type of learning's really transferable across all industries.

00:18:30: So you could do the ultra complex with digital With AI technology But the role of a human has to change with it and some organizations will go down their roots off.

00:18:41: I don't need a human anymore, i'm going use this as cosplay.

00:18:43: im gonna dramatically reduce my cost base.

00:18:47: Can our society ready for that?

00:18:49: For organizations...I think is really interesting question.

00:18:52: Some organizations would stay very traditional And use little bit technology.

00:18:57: Really put colleague at heart of interaction.

00:19:01: Try build relationship depth relationships trust And then there'll be a spectrum in between, but organisations will choose where their colleague sits and the customer lifecycle.

00:19:11: I'm interested particularly on that piece because i think if you went back five probably ten years technology generally AI more than buzzword today was all about cost to serve benefits like how do we drive down the cost of serving customers or your user base?

00:19:30: What you're talking about there, Andy is very different in terms of where people are deriving value.

00:19:35: And I think a lot of people listening to this will be feeling the pressure that there's a pressure to use technology and deliver value from it.

00:19:45: Are you seeing how values being derived from technology and AI more broadly?

00:19:54: It

00:19:55: still features, whether it's core.

00:19:57: Whether contact sensors are seen as cost centers?

00:20:01: I don't know...I think those who are more forward focused on the art of The Possible Are thinking about this differently than its a cosplay.

00:20:13: They're seeing that actually the future is about experience.

00:20:18: That's their area to win-on and if you get your experience right you can achieve, I referenced it earlier.

00:20:24: they have positive jobs.

00:20:25: You can see more customers choosing you, more customers buying all of your products or services and if you get the blend right where they trust their reassured They know that they've got support when they need It And Your digital tooling That they can self-serve from is robust.

00:20:43: Okay i always say that Customers don't wake up in the morning and love to ring the council Because they do not feel like another choice because sometimes we inadvertently tell them in our communications to them.

00:20:55: We send him an email that has absolutely no call for action, but the way it's written and the customer perceives they have to ring up and check or... ...we do it because we build digital journeys that self-serve that doesn't give them reassurance of what they've tried to do was happened.

00:21:10: So those fundamentals with development of AI and maturity of AI haven't gone away.

00:21:17: Those fundamentals are probably greater than ever before And they probably all play to an element of cost as they have, but the also play much more.

00:21:27: I think it's an element experience and speed.

00:21:29: Also plays through it and having human contact available.

00:21:34: so we'd agree by that.

00:21:35: human contacts will become for more complex cases.

00:21:40: four areas are really high emotion on their day-to-day transactional or more and more becomes handled by technology.

00:21:48: I certainly don't think it's a cosplay.

00:21:51: Cost to serve is the primary currency anymore, i think experience measured in lots of different ways and you know thing we definitely shouldn't be scared off with the technologies...I've got have a brand new suite of metrics!

00:22:07: You just gotta work out how.

00:22:08: either do your metrics translate from the old-fashioned way of serving a customer?

00:22:12: Hasn't the customer gotten their answer they wanted or that are needed can measure them.

00:22:17: at the same

00:22:19: time I think hearing about working with the experts who understand a customer, designing where AI sits and that's the strategy is crucial.

00:22:29: And then as you say measuring Changers and innovation with AI is very much around, I guess the experience differentiator that you create into your brand.

00:22:41: A lot of people listening today will have got a lot out of this talk.

00:22:44: so i just want to say thank you for sharing your insights!

00:22:48: And i look forward too speaking not only about AI but also more of our experts' talks on this subject in future podcasts.

00:22:57: So Thank You Andy really appreciate it.

00:23:00: Thank you for listening to the Scaling Human-Centric Innovation podcast with Michelle Booth and Addy Kingston.

00:23:06: We hope that you enjoyed this discussion, and hear more conversations with leaders shaping the future of work

00:23:11: and experience!

00:23:12: Make sure to listen to The Rest Of The Zoom Amir Podcast series where Connection meets innovation.