#25 Faster Chatbot Adoption with The Automation Guys

In this episode of the Process and Automation Podcast, Arno and Sascha will share tips for faster adoption of chatbot technology. Hello and welcome to another episode of the Process and Automation Podcast with the Automation Guys. Jaanu, what are we covering today in our episode?

Thanks, Sascha. So today we're going to look at a couple of tips we've compiled to really accelerate the adoption of chatbot technology within your organization. Of course, you know, there's a lot of hype out there with, you know, with regards to chatbots, AI-driven virtual assistants, And all of these are really focused around, you know, to drive better outcomes for digital engagement. And this is for large organizations, very small organizations. So this kind of whole new customer-centric way to interact with clients and partners and suppliers is really gaining a lot of momentum. And I think, you know, chatbots is key to really enable us to move forward with that way of thinking. You know, we want to have these virtual assistants that can enable this customer interaction to be very fast and to drive outcomes that's very quickly. And of course, you know, all of this is driven by AI Cognitive Services that allows us to, to, to build really intelligent sort of interactions with our customers. So, so really, again, what we want to do is, is sort of just present the tips for, for faster adoption for this chatbot technology within your business.

Oh, great.

So that's the first point we want to, we kind of want to look at is we want to, so when you do this within your business, you really want to clarify the purpose of the chatbots prior to adopting it. And you should have a really, really strong business case for this, and there should be a strategic purpose behind it, behind your adoption. And you need to have a very, very good implementation strategy, and you have to have really good business goals prior to adopting chatbots. And I think that that's a key driver to the success of this initiative. So really want to look at 4 elements here. So the first of all, You want to look at the purpose, and this is kind of like a blueprint for rolling out chatbots. You know, what is this purpose for bringing in this conversational sort of digital conversational agent with inside your business? And what's the kind of the skills needed, you know, for this digital worker or this digital bot to be able to interact with your customers. And the next sort of element of this is really what is the job that this actual chatbot needs to perform and the experience we need to install with inside this bot. Also, the third thing is we need to look at the content. So, you know, what's the objective? What's the content that this will serve? What's the information it will provide? And also the fourth point is the interaction. How will this actually interact with end users that's at the other side of this digital channel, right?

Absolutely, yeah. So I think so the next good point we can jump into is how we define sort of the key strategy and the metrics and how we can measure success. I think this is a key part. With any kind of project, with any project you're kicking off. So chatbot is not very, very different to that. So part of the development, the deployment strategy in companies should be a well-defined set of metrics to measure that project success. So everyone needs to, need to understand where, where are we going to. Otherwise you don't really know where, where, if you have reached your, your desired outcome. So yeah, some of these key, key metrics you could look at are sort of the percentage of the reduction in resolution time when using these chatbots. So when it comes to sort of customer service, for example, the percentage of the reduction in manual effort. So before, you know, you had to maybe do a lot of work in Excel, copy and pasting, so if, and responding to incoming requests by email and that kind of stuff. So how does this look like after implementing the chatbots? Percentage of incidents resolved end-to-end through chatbots. I think that's a very powerful one to achieve. So as you probably have read as well in the news, or maybe have heard in our previous episodes, so some companies achieved 80% efficiencies or improvement in the end-to-end process. So it's something really to aim for. It's a great measure of success here. And if you get that number very high, the end-to-end resolution through chatbots, then another measure is really the user experience and the satisfaction. Because any new technologies you bring in, it all sounds nice and fancy, but if the users are not really keen on using that technology, it's literally worthless. And yeah, so that's a very important factor here to look at and to listen really to the feedback you might get as well by implementing these new technologies. Then I think another final really important measure here. So there are other measures obviously as well, but we think this is important. The percentage of users leveraging these chatbots as their primary channel of communication. So if you plug these chatbots, for example, in MS Teams or Slack for internal-facing scenarios and your employees are picking this up to do self-services with HR and all sorts of other areas, If this then becomes sort of your primary channel of communication, wow, this is, this is incredible. So yeah, so here, here are a few measures we think are important. Yeah, so the list can, can probably go on and on.

Yeah, and I think the next sort of, I guess, tip is to start simple, but choose things that's got a very high impact. You know, they always compare a chatbot to a very young new employee that's keen to learn fast and accelerate. And, you know, you need to mimic that. You need to see a chatbot as something that on day one you can start with something very simple. And as you then kind of grow the knowledge of that bot and be a bit more specialized, then you can also train it to field increasingly complex tasks. So you might have on day one a chatbot that automates very simple repetitive tasks such as HR FAQs. And of course, you know, that, that's a very simple initial use case for it, but then you can grow the, the use case to do more complicated HR tasks. Now, previous episodes of this podcast, we have talked about use cases specifically in HR for chatbots, and then numerous. And I think the message here is that if you just start simple, you choose the ones with a very high impact, you prove the technology work, and then from there on, you know, you can scale that out and incorporate more use cases more functional sort of areas that chatbot can, can engage with employees with and effectively kind of grow that into something quite large, but grow it on the fact that it is successful, it's very effective, it ensures that there's high degree of engagement, high degree of satisfaction, employee satisfaction, and, you know, and scale that out across your organization. So I think, you know, kind of starting small is kind of a big part of this, right, to test it out and prove it works.

Yeah, absolutely. So I think, yeah, again, like with many, any other new technologies, you don't want to pick sort of, yeah, with big, big goals in mind, but you don't want to pick sort of the most complex process and area you want to change and improve on. So enterprises need to really look initially maybe for what we call a minimum viable product, an MVP, so that that can reduce, yeah, just the manual intervention by automating the bulk of this repetitive and tedious task. So, and yeah, as normal, prior to launch at scale, it is really useful to do this POC or pilot to demonstrate usability and the impact internally. It was just a small use case. Arno mentioned a few earlier and we talked about the HR services, holiday requests, those kind of things are very easy, impactful because they are addressing nearly all, basically every employee in the business. But it does, so you can test that really, really nice here and then Yeah, during that pilot project, the chatbot can be observed, the conversations can be refined because, yeah, so you have to sort of, yeah, just structure the conversational flow a little bit and then you need to see how the AI is dealing with all that kind of stuff. So all that, that, that needs to be defined so it's all right in the context. And then once they, once it's working, the productivity and sort of the efficiency criteria are met, sort of success criteria you also discussed before the chatbot can be, can be, yeah, then widespread into the organization, can be announced to everyone and, yeah, launched really everywhere, maybe in other, other regions of the company, in other departments. Yeah, and then the successful implementation of the pilot will then be the basis to progress further and to really maximize that, that, that the value of a chatbot technology.

Yeah, that's very important. I think once you get that first successful implementation under your belt, or, you know, of that initial pilot, you know, that will really pave the way, and that will also be a very logical progression, you know, to extract maximum business value, you know, for or from this chatbot initiative. And I think You know, brings us to the next point. You know, you have to think big and you have to do that from the beginning. And, you know, and I think when you're trying to achieve this, that the highest level of productivity using chatbots, you know, it's important to identify sort of all of those processes and roles and customer touchpoints, for example, that can be automated. And to plan all of those future deployments in stages. You know, it's always better to adopt a phased approach and to automate, you know, processes using chatbots in different departments and spanning kind of different roles and different processes. And, you know, I think, you know, what you need to guard yourself is against this, I guess, this notion that exists with inside the enterprise that's got this inertia to change. What that means is that it doesn't want to change direction. It's down this track. You might try and bring new technology in, but because of this kind of organizational inertia, it doesn't want to change. So you want to guard yourself against that. That's one of the pitfalls you need to recognize. When you deploy this, and that can really be avoided by using a sort of a two-pronged approach, in my opinion. So, you know, the first one is a sort of a top-down approach to drive this chatbot adoption from the kind of, from the business leadership. So it trickles down into the business units. And another approach is where you start from the bottom up, where you approach, I guess, that sort of the business users and make them evangelists of the benefits of chatbots, so they can drive adoption among senior employees. So that kind of goes up the chain. But I think that the technology is really progressive. I always say, you know, that the art of the possible is extremely wide, and there's no reason why you should think big, although you can start small, you can still have those kind of like those big plans for this and those big initiatives already planned.

Yeah, and with all the excitement of this new technology out there, and if internally the team gets excited about this technology, it's also worthwhile to think about developing in-house skills on this chatbot technology and on that specific platform. I think that's sort of key if you're kicking off. Sure, you can kick off maybe with some implementation partners, but as soon as you're sort of out of MVP stage, I guess you want to have that capability in-house. And Yeah, so that's very, very important. Otherwise, it's not really worthwhile to really think about a long-term solution. And so yeah, that's the first thing. So you need to really upskill to your— you need to upskill your team and allocate the right time, give them the time to learn these new things. And Yeah, so that's, that's, that's, that's, that's very important so that it can then be included in the project teams and do the tweaks during initial testing and during the pilots, and as well being a— as well an evangelist here and there within the business if they have these skills. So yeah, so one, one important thing to consider here is to ensure you're able to, to to have that learning available from day one. So, but most of these vendors out there, they provide really good academies for that kind of stuff. And yeah, I think as we mentioned before, setting these metrics to measure the chatbot performance and impact. So those things are really important to to be done by the team who's looking after the chatbot solution. And yeah, I think, and evaluate more and more of these training tools to create really the focused sessions your IT and the subject matter experts really need. Otherwise, yeah, you do your MVP, the implementation partner might leave because you don't have any sort of expensive or extensive budgets for the implementation partner. And then you're suddenly thinking about your training requirements I think that's a bit too late. So to be really successful and to support this fast adoption of chatbot technology, that's also a very important point.

Yeah, sure, very, very good tip. And I guess if you already got RPA deployed within your organization and perhaps you've got an RPA center of excellence, You know, it's a very good springboard to actually leverage to get chatbots embedded with inside your organization as well, because, you know, a lot of the Center of Excellence lessons learned and the Center of Excellence sort of practices extends to chatbots as well, you know, from an RPA perspective. And, you know, I think you should really, if you do have an RPA center of excellence, you should really try and kind of align those two together. And again, you know, a center of excellence will help you to prioritize the processes that has got a very big potential for this conversational automation and also to, you know, to ensure that they are deployed in a in a way that's got a high degree of quality, compliance standards are met, for example, and it also is deployed in a way that allows for coordinated communication with all of the various stakeholders that's involved with inside these projects. So again, I think if you're in a good position where you have got a RPA center of excellence, because of course, you know, that's a good framework to govern the rollout of these automation projects. You know, try and use those best practices of your center of excellence and, you know, try and use those best practices for rolling out your chatbot projects.

Yeah, very good indeed. So the next important part is all about change management. The introduction of new technology can have different impacts within the organization. Some people are, some employees are really hyped and they are very happy that robots are taking over. So this is what lots of people feel, but others are, yeah, definitely maybe not so happy. They don't understand that. So, so although businesses are really, really now focusing on this idea of a virtual assistant or a chatbot, so some, yeah, some, some concerns are there that it might reduce headcount and costs, or definitely headcount. So I think reducing cost is not necessarily a concern, but reducing the headcount is. And Yeah, I think it is important to emphasize when we implement chatbots, that is all about the overall customer experience and the values we give our customers and internally actually and externally productivity goes up. So that should be sort of the main focus and not— it's nothing against humans, so that we reality in future looks like, yeah, so that the companies of the future looks like we have processes where we combine people, AI, and bots. I think that's what's already happening more and more, and we have to sort of understand that and maybe accept that. But with proper change management, it is very crucial from the start really to get people on board and to avoid that resistance of any initiative we might start. Because if As soon as you just put this in, you just tell everyone you have to use it, people will not use it. You will see this in your metrics. There's no user adoption. People will write a lot of bad messages on internal chats. And then all that investment, all the time you spend on it, maybe because some areas of the company thought it's a good idea, that's, yeah, so that investment is going to sort of nowhere. Yeah, as I mentioned, they are very, very important to make that clear. It is helping people during their job so they have more time to get on valuable activities, more meaningful activities, and because we can automate more end-to-end and they are really working on the meaningful stuff. Yeah, so that's a very important part in any kind of digital transformation project to not Yeah, leave your employees behind.

Yeah. Well, you know, like they say, these virtual enterprise assistants are support to human interaction, not a replacement for it. And I think that that's really true. I think that, you know, if you have got proper internal communication on what the chatbots are there to do and that it's an assistance and ensure that message is very clear to employees. You know, employees will be on board with this, the positive sort of nature of the adoption of these conversational automation sort of initiatives you're running and the benefits to themselves. You know, it's going to make their day job easier. It's going to sort of free them up so that they can focus on more productive work throughout the day. And it kind of brings us to, to kind of the next point in, you know, this top tips to, to bring chatbots into, or to drive adoption for chatbots into your business, is it's really to, to give a chatbot a personality, right? Because, you know, if you give a bot a personality, it really helps a user to connect with it on a on an emotional level. And, you know, so we have to have these personality attributes that's kind of like assigned to these bots to complement the user's personality that will interact with it. And also the user's needs and the way they interact with the bots needs to be reflected in the interaction styles and of the services these bots offers. And, you know, I think that, you know, we talk about human behavior, and I think that if you look at the usage and usability and the usefulness of these virtual assistants, it really directly impacts the user's ability to achieve their life goals. And, you know, and it can be a really good primary motivator for the user to use these chatbot services, especially if there's something of value that's on offer. And, you know, if the bot's personality is favorable and people like interacting with it, then they will use it, right? If I think that the conventional bots that we used to see prior to, I would say, the intelligent bot we see these days, people used to interact with it, they didn't like it because they know it was a bot. And they know it was useless because it couldn't kind of provide them the information they need. But these days, because it's sort of very intuitive, it's AI-driven, it's, you know, you can make it very friendly, you can give it a recognizable name, it provides the outcomes that the users want, and people pay attention to it, that it is this personal assistant. It's not like this old, you know, the Microsoft like Microsoft Clip that used to pop up in the old days on Windows and it says, you know, I see you want to write a letter, can I help? No, you know, that's just pre-programmed stuff and it's like, just go away. Whereas with this, you know, you can actually give it a personality. A lot of people actually give all of their bots, specifically in HR and finance, names and it sort of just gives authenticity. And, you know, I think the ability for a virtual assistant to respond authentically is actually very important. And, you know, I think that you must use this to your advantage to, you know, to kind of like drive that adoption and to make people engage with it, right?

Yeah, indeed. Yeah, it's if they have a nice name and have maybe even a a nice image on the chat window, doesn't look too technical, then it works quite well. Maybe that's not nothing what IT really cares about. IT probably cares about other stuff when implementing this new technology. So very often with these platforms these days, they are low-code driven, so sometimes You could kick off as a stakeholder in the business, you kick off a project potentially without IT because you don't need in a traditional sense developers anymore. So we talked about this, this whole low-code movement in all different areas of intelligent automation. So this really helps to get the journey started and to get to result very fast. But, but that, that shouldn't mean that we are not speaking to IT anymore, because at the end of the day, if something doesn't work, they, they will definitely be involved because the system needs to be supported. And very likely these chatbot technologies, they are not standalone like a low-code web application or so. So chatbots are only good when, when they connect to internal systems a lot. And for that, Obviously, we need to install it properly. It needs to have proper governance around it. What can be done with this chatbot technology? Everyone needs to know about where it's integrating. Obviously, security is a big concern when it comes to chatbots. So it's very important to foster that collaboration between IT and not just IT, as well as other subject matter experts within the company. And yeah, only, only Yeah, if we work really in a team, have this internal collaboration working, then it will be a successful go-live later on as well. Yeah, so it will be supported and everyone will be happy.

Yeah, no, I absolutely agree with that. And I think, you know, the kind of the main takeaways from the session is really that these virtual assistants are increasingly important role in customer engagement. And, you know, more and more businesses out there are exploring the use of this technology to increase employee satisfaction. And like you said earlier, Sasha, you know, we are seeing an explosive growth in the popularity with up to 80% of companies out there already using virtual assistants or planning to implement it, you know, in the next kind of year or two. And, you know, despite all of this popularity, there are aspects to consider when you implement conversational technology using chatbots, you know. And training a virtual assistant is not really different to training a human employee. You just need that time and investment, and, you know, you, you need to invest that into the initiative to ensure that you get those outcomes you want. And you need to start with a very clear strategy and set up that key metrics like we touched on earlier to evaluate the success of your initiatives. And you need to mobilize the right people, you need to mobilize IT, the subject matter experts, and all of these people needs to engage to build this minimal viable product and to start learning, this learning experience to demonstrate that usability of chatbots, you know, even if the impact is initially at small scale, you know, you could scale that up. And from there on, you know, you could further expand this initiative across the organization. And, you know, you need to ensure that you communicate and embrace the benefits of what these virtual assessments can bring to your business. And of course, like we said, don't forget give each of your chatbots personality, right?

Absolutely. Yeah, then it will be a success. And if you like sort of the sound of chatbots and you're thinking about this, hopefully these tips to get a fast adoption of chatbot technology were helpful. Hopefully you can take one or two points from this podcast episode today. And yeah, if you'd like to learn more about chatbot technology and need a helping hand, reach out to myself or Arno. So we will obviously put all the information again, as always, into the show notes. And yeah, I think it's an exciting technology. And yeah, I definitely— we encourage you to have a look at chatbots. And we're looking forward to all your feedback and all your questions you might have. Visit our website theautomationguys.net to leave your feedback and submit your suggestions, or post on LinkedIn, that kind of stuff. We are everywhere on all the social channels. And yeah, we're looking forward to all your comments. Unfortunately, that's it again with this episode of the Process and Automation Podcast. If you like this episode, please give us a 5-star rating and don't forget to subscribe to this podcast so you don't miss any upcoming episode. We hope you will tune in next time, and until then, let's automate it! [MUSIC] [MUSIC]