[00:00:00] Hello. And welcome back to another episode of the process in automation podcast was the automation guys as always with me here is Arno. Hello Arno hey Sasha. So. Today, um, we have talked about, uh, automation over the last 30, 40 episodes. And, um, yeah, let’s, let’s go into this topic, um, again, uh, do Roundup on, on what we have covered so far.

[00:00:43] What do you think about that? Yeah, that sounds great. I think we’ve, we’ve spoken a lot about, uh, a lot of the different disciplines of the automation, uh, specifically around hyper automation and intelligent automation. Um, you know, we’ve covered, uh, [00:01:00] a great degree of topics. Um, and of course, you know, we’ve, we’ve gone into a lot of use cases as well.

[00:01:06] Which, uh, has been well-received by our listeners. Um, and thank you for all the feedback you guys have given us, given us some ideas for, um, sort of future podcasts as well. People do tend to like use cases because I think it’s a, it’s a great, great way to, um, I guess, uh, the art of the possible in, in a sort of a practical sense, um, with an example, Of course, you know, throughout these couple of months, a lot about RPA, of course, there’s still a big buzz on the RPA space.

[00:01:41] Sasha, as you know, you see a lot of things coming through. Um, you know, now that things are sort of post pandemic is starting to open up. Um, you know, and people are sort of getting back into project mode. They are certainly sort of reaching out to us and, you know, starting to. Um, you know, look at [00:02:00] more RPA initiatives that, that potentially can, can safeguard them in the future against some of the disruptions we’ve seen.

[00:02:09] No, thank you. Um, uh, RPA is, is one of the, you know, one of the big topics we have, um, discussed, um, uh, and alongside that RPA. Yeah. Comes to this topic, low code, isn’t it. So building applications with, um, with the speed of light. So basically drag and drop coming up was there was, was innovative ideas and put them into solutions very quickly, uh, in, in days, weeks rather than months.

[00:02:36] So that’s th that was a big, big topic we discussed as well. And. Um, we see, uh, Bexley daily, um, all these oldest projects coming up currently it’s RPA it’s workflow, um, it’s, um, user interfaces, um, getting sort of a way from, from Excel spreadsheets and emails, building even tiny business applications to solve sort of [00:03:00] tiny department or problems by that.

[00:03:02] That is really, um, as well. One of the big topics which came up and probably something we will see more and more. Yeah, a lot of use cases, of course, for low code. I think low code has truly found its place now. Um, it’s very mainstream. Um, you know, the people we talk to, um, you know, a couple of years ago, they wouldn’t know what low code is, but you know, now when you have conversations, people get it, they understand it is a way to develop software using drag and drop type capabilities.

[00:03:35] What was talk about the Lego blocks? Other people say it’s, it’s like the flat back version of software, but it is true, you know, it’s, it’s, it’s components you buy, um, and you put it together and depending on the vendor and what type of components you require for your type of application, you want to put together.

[00:03:56] Obviously different vendors offers different capabilities. [00:04:00] Um, you know, I th I think there’s not a lot of difference between the sort of the mainstream vendors, like you said, it’s actually, I think with, with low code, uh, especially low code workflow automation, very easy to create these productivity apps solving a very small problem or enterprise wide problems.

[00:04:19] Um, of course, combined with the RPA really, really compelling offerings. For people out there that wants to start with automation, very easy to get started, dip your toe in it. There’s a lot of sort of free trials you can download just to get started, you know, and I guess the message is, um, you know, challenge yourself.

[00:04:40] It is, uh, uh, what we call sort of, uh, innovation technologies, you know, take a problem. Um, uh, you know, any business problem, you know, finding a workflow tool or RPA tool or inquire with other myself, Sasha, uh, we can always give you some guidance and, you know, solve your first [00:05:00] problem. And, you know, from there on you, you will see that the kind of the speed of execution and how quickly you can start to automate these processes and add value to that to you.

[00:05:14] Yeah. And of course, you know, we’ve got, um, AI chatbots. That was quite a big thing that we’ve discussed in many episodes, you know, very, I would say, uh, a very, uh, sort of. Uh, progressive technology now. Absolutely. Um, yeah, AI is progressing, um, and that’s, that’s probably why, why becomes more attractive because chat bots we had for awhile.

[00:05:44] Um, but now, um, enhanced. Chat bot capabilities was, was, was AI conversational AI at as quality as well. Um, so that’s, that’s something which came up from just recently and, um, and it seems to become more and more attractive [00:06:00] Microsoft at the big acquisition as well into the, the, uh, AI, um, about, um, speech, that kind of stuff.

[00:06:07] Um, so there, there is probably far more to come, uh, in the next couple of years. And it’s just, just very nice to, to add a few more channels, um, into, into your business process. Now you can, um, use your WhatsApp, you Ms. Teams, slack, Facebook messenger, all sorts of communication mediums and in channels to actually.

[00:06:32] Intacct was the process. So we basically run the process just, just on a, on a, on a chat window. And this, this is something really new. Um, probably was a younger generation actually. Date date date, probably not a year to really want to do processes differently going forward and, um, something, um, everyone who is customer facing has to look at.

[00:06:54] And, um, but we discussed the other use cases, right? So lots of external internal, uh, [00:07:00] use cases we’ve covered like 40, 50 different ones. And then several episodes, you know, huge, huge pool of opportunities. Yeah. Now I think between AI driven chat bots, Low code workflow in RPA. It’s so easy to put a really meaningful and full solution together.

[00:07:21] So for example, you might have a complaints management workflow that in the back office, you want to string together, the process. How do you deal with a complaint? You might have a bit of RPA in the background that wants to interact and link that complaints process with perhaps a third party system. So that’s the glue between your work.

[00:07:41] And your back in system and it’s then very easy just to log in, uh, AI driven chat bot in the front. So you can have a solution just for that particular scenario, probably ready in a couple of days. Bye. Bye. You’ve got a channel in the front where somebody can engage a AI driven chat bot [00:08:00] that chat bot obviously understands names.

[00:08:03] Of the person that is actually logging the complaint for example, or it could be a suggestion, you know, it could be anything, but in this instance, the AI chat bot would be able to then route that case to the back office. That’s that a transition is seamless, have something in the back office and get a task, pick up the pace and, um, be able to, uh, deal with that very quickly.

[00:08:27] Now if you, if you look at us sort of a traditional way of doing that, or they’re having somebody take a, uh, a phone call or somebody sending an email to a generic inbox, you’re going to have all sorts of garbage arriving up inbox, or you’re going to have a very expensive resource having to, um, sort of a man, a telephone.

[00:08:45] Um, and there’s gonna be a lot of sort of manual emails being sent this organized process, something like this, very easy to string together days. And you’ve got your first automation. Just with those three components, how you can really string [00:09:00] together a sort of a meaningful automation and it doesn’t stop with complaints.

[00:09:04] You know, we talk to them, use cases for HR. You know, a lot of companies has already got an HR processes. Maybe it’s a employee leave requests. Um, it could be expense claims. So there might be already some internal forms and processes, um, that exist. Maybe there’s a SAS system, a cloud-based system. It’s so easy to then actually, uh, you know, elevate the type of functionality that, that those systems though, they’re just preexisting assets, give you by providing, uh, an extra additional channel, uh, via chat.

[00:09:41] Because again, the chat bot, you could train it, plug it into your, um, back in systems. Um, you know, chatbots, for example, they’re very good. They explore your object models and your data structures and the back machine learning modules understand your data structures of the data. Um, so it’s [00:10:00] really easy for you to understand if, if, if the intent is to locally leave requests, you, for example, load the employee record to see how many available.

[00:10:09] If they. And like you say, Sasha, you could surface this through episodes of a web interface. It could be WhatsApp teams, slack. There’s just so many, so many, um, potentials to, to, um, almost bring those existing functionalities that you’ve got forward. Um, you know, we touched on HR, but think about finance.

[00:10:33] Yeah.

[00:10:36] Exactly. Um, you know, and I think if, if there’s, uh, a shared inbox somewhere or there’s a spreadsheet floating around that gets emailed across, um, you know, to different people, you know, we’re plugging in, I would say these, these really three strong, uh, automation technologies. Um, you know, it, it, that the [00:11:00] possibilities is, is, is, is, is, is, is really endless, you know, and, and the sort of efficiencies you can gain.

[00:11:06] Um, and I guess once you get started with it, that’s been when, um, you know, you could explore further and, and, uh, we talked a bit about process mining, you know, then you go out and look for other opportunities, maybe things you’ve never discovered that that doesn’t exist, but, you know, there is a problem.

[00:11:26] Yeah, absolutely. So process mining is a big topic as well. Um, and, um, Yeah, I guess. So one very big problem was there was automation in general before going into process mining. Um, I think a very big program is, um, finding these opportunities within the business. So this is what we have, um, many discussions.

[00:11:48] Um, so maybe we identify the first one, um, really nice, um, candidate for automation, low-hanging fruit, um, um, sort of that kind of stuff. Um, And [00:12:00] then we do the project very often was businesses and everyone is happy, but then sometimes sort of initiative slow down a little bit. And, um, the mistake very often, um, we together was businesses maybe had in the past, we didn’t have, we didn’t look for out for a huge amount of sort of opportunities within the business.

[00:12:19] So it is, um, it is really. Critical for huge success. Um, um, or good success was in, was in the business. Um, for automation. When, when you find out I’m like 10, 12, 20, 30 different different opportunities, you have an idea. Well, where, where you should, um, what you should address next after you have done, maybe your first initial MVP with something and everyone is happy, but then you have to keep up the momentum.

[00:12:47] You need to have this bigger picture. And, um, and process mining and, uh, some, some other, um, process discovery technologies could, could be really [00:13:00] helpful there to, to uncover, um, uh, what you should address next, because sometimes you concentrate on the nice and sexy things you want to tackle, or the really big one big problems.

[00:13:13] They, there may be good projects and its own, but very often. There may be not, um, the best one to take over next and turn process mining might bring up, um, problems, um, by identifying all sorts of, um, uh, sort of, um, time stems in systems. Um, um, ideally, and it was in the whole end to end process. You’re identifying all the steps someone is taking, or the whole department is taking over time and then comes up with some was.

[00:13:45] Was was an, uh, an answer of maybe inefficiencies here, problems there. And, um, maybe it is just an organizational problem or maybe it becomes very obvious that it’s, um, it is a [00:14:00] problem we need to solve was, um, was automation was a chat bot was workflow, uh, or combination of all of it. Um, our process mining can be very varied.

[00:14:12] Yeah. We always say it’s using your existing digital footprint to understand how processes really run. And I think that’s, that’s really important because there’s so much data out there and they, you know, the digital footprint might be very large that it’s very hard to comprehend. Exactly. You know, what is running smooth?

[00:14:39] What is running? Not so smooth. Yeah. You know where those, those actual problems are, that, like you said, Sasha, that you need to uncover. And, you know, this is almost that ultimate way to point process mining tool at this digital footprint and, you know, uncover those problems and, and really [00:15:00] give you the opportunity to really drill into the ones that’s really problematic.

[00:15:05] And to, to address those and to then make really. Technology decisions too, to say, okay, perhaps we need to automate a process here. Perhaps we need RPA bot process there. Um, you know, this particular issue will be fixed by plugging in a bit of, uh, AI. Um, and I think process mining is a really, really good catalyst for unearthing these, these opportunities.

[00:15:33] Um, of course, like you said, a lot of people start with, especially when they’re new to automation, they, they might start with some of the obvious, um, automation challenges, um, you know, with inside departments, you know, some of the operational processes, finance processes, I think process mining just gives you that ability to, to really go very granular and, and really understand, um, you know, some of those underlying.

[00:16:00] [00:16:00] Process problems a lot better. That would be otherwise really, really hard to uncover buyer by analyst, for example. And so, you know, some we’ve covered process mining quite a lot. It’s very important topic. And, um, you know, one of those topics will, we’ll have a lot more episodes now, a lot more discussions.

[00:16:23] Um, you know, and we, we actually think at ADA is a really, really fundamental, um, you know, part of hype automation that, that gives hype automation, um, you know, really sustainability in terms of your business, because you can always uncover more problems. You can always look to, to further streamline things.

[00:16:45] Um, and you know, once you’re in that zone, It’s it’s it’s it’s really then when, when the sort of the true benefits, um, you know, automation speak big, become transformational, and it is very often, um, it’s not [00:17:00] necessarily a procedure process, um, sort of flow problems. Sometimes it could also identify. Uh, within that process, a specific supplier, a specific product, a specific, uh, invoice or whatever, just Molly, the, the, the, the item, which is going through the process, um, is actually that problem.

[00:17:23] Um, so which, um, for example, someone is approving an invoice, um, which is sort of not, not sort of, um, um, in, in the. Sort of metrics and the more normal thresholds. Um, so non process mining can even uncover that. So at the specific step in the process, um, the process is running fine. So we getting from approval to, um, to, to the next step fast, or from, from first approval, second approval.

[00:17:48] This is all super efficient and really good. But then, um, was what’s going through the process is also analyzed by process mining. Um, and then you can identify maybe, or this [00:18:00] supplier or this kind of supply in these countries, actually, not very good for the business because it’s breaking rules here and there.

[00:18:07] Um, so it’s, and then you can, in real time, if we’d run through the process, identify, okay, well, we need to add. And, um, similar like him was, was, uh, was chatbots. Um, if something sort of comes in, you need to then connect it to lots of systems. And this is what process mining can allow you as well as a business.

[00:18:26] So while it goes through the process, you can drill down, um, any way through all the data and. Where are the inefficiencies capacity, uh, problems. And, um, and you can immediately kick off an automation to maybe correct a specific thing, not to fire a person if a specific situation happens. So you can immediately, um, Yeah, react otherwise, um, three months later, you’re going through your reports and think, oh, ah, that happened, uh, we should have spotted that one.

[00:18:57] And this is also what process mining is doing in [00:19:00] real time. So really going through every little process step and the actual item, which is going through the process. Yeah. Um, yeah, I mean, it could be as simple as that, there’s not a purchase order attached to the invoice and people just naturally assume that they will.

[00:19:18] Um, you know, because there’s not a purchase order, then they need to chase somebody else to actually retrospectively raise a purchase order whereby ideally fix, fix the process at the start. So no invoice submissions on this, there’s a PO touch, very simple example. But I think that, you know, within it cited the finance department, it is such a, uh, a small thing that.

[00:19:46] Go unnoticed and people are just trained to deal with it and manage by exception. Whereas process mining is something that it could literally tell somebody, well, it’s this process taking very long time. Why is it taking a long time? Okay. Let’s drill into that [00:20:00] part of the process. Like it is, there’s a huge lead time from an invoice being accepted to an actual invoice being paid.

[00:20:07] Well, why is that? Because there’s a usually time with where there’s a hand off to somebody else to actually. Uh, chase for a beer and then raised a beer then were relative to the purchase requisition. So it is sort of a cascading effect. That, um, you know, this sometimes, uh, unearths and like you said, Sasha, it’s, it could, it could be, if, you know, if you have a multinational company that let’s say this works well, for instance, in Germany, but it doesn’t work well in Italy.

[00:20:35] Well, it works well in Italy, but now not while in Germany, but it’s the same as what’s going on. Uh, standardization that you, um, thought was brought in and it was working. So technically the processes should sort of, um, you know, behave the same and have the same sort of process timed. Uh, if they don’t, then you can understand [00:21:00] what the reason is for.

[00:21:02] Exactly. Today’s a really good case study, um, sort of by done by Uber. So Uber is using process mining, uh, heavily to, to identify just for customer service. Um, so usually process mining comes out of very often, or it sits more in the financial, um, uh, departments, uh, accounts payable processes, but we are, Uber is using it for.

[00:21:26] Looking globally, how their customer services are running and they obviously see, okay, here in the U S we have those kinds of touch points to solve a problem. And then certainly if you, if you branch out into different regions because of, um, um, so from, from my understanding, um, so Uber, when they grow, they grow very quickly in a specific region.

[00:21:48] I make a decision, okay, we going into this region and then we grow and, um, was everything. What comes with it? It grows maybe. Not as efficient as maybe some other [00:22:00] thought. So then to just overlay what actually the real picture is globally. Um, yeah, you used an process mining to then see. Okay. Um, so we are so far off in these regions, um, from, from maybe a global standard and impressive, impressive nursing thing.

[00:22:19] Probably impossible to get to that place. If you were to deploy. Sort of sort of normal, traditional, um, business analytics to apply it. So, so that stuff’s all data driven. Um, it analyzes your digital footprint. And like I say, it’s worth giving process mining a lot of ad time. Um, like we did in our plus episodes.

[00:22:43] So the check it out, if you new to it, um, it is certainly something. Like I said it, which is very valuable to, um, to your automation initiatives and, um, you know, give it that sustainability, you know, that, that kind of project [00:23:00] pipeline you need to, to, to, to really get to that, those transformational effects, I guess, lots of enterprise, a lots of companies really agree.

[00:23:09] Um, so just justice we thinking in these other benefits. Um, so this is why it’s aloneness is one of the big players in the market. And I just received a. Sort of a billion, billion dollars investment, um, just last month, which is a fantastic news and clearly shows is, um, is a huge demand. Um, not just now because these, those kinds of investments are sort of looking to the future massively.

[00:23:36] Um, so, so then there will be huge demand and every company will probably look at it at some point and come up with, um, yeah, I guess even every, every small to medium company. You want something to, or to just analyze whatever you do. I may recommend you should do things here. You should do things there to improve.

[00:23:58] And ideally was [00:24:00] AI on automated. How brilliant would that be? Yeah, we also talked a lot about integration and, um, you know, the need for integrations with legacy systems integration between systems. Avoidance of data silos. So, so there’s a lot of work being done at the minute by various vendors, um, vendors we work with really create easy to configure data hubs and, you know, easily integrated data hubs that gives a single source of truth or your automation initiatives.

[00:24:37] Uh, very important of course, um, because. When you create new automations, you don’t necessarily want to create new data silos. It’s very important to, to have these single source of truths, uh, whether it’s a customer record employee record, um, you know, financial records, um, orders, or, you know, all of these records where, [00:25:00] um, you know, having, uh, a single data point or a single data object.

[00:25:06] Four for four, these records are really important. Um, you know, not just for, um, maintenance of data, but also for all of these automation technologies that we speak about in our podcast, um, to be able to connect to. So, you know, so they can consume, consume that data and, you know, all of them actually looks at it.

[00:25:31] Uh, you know, data across the business who that data can then be, um, also opened up for, for reporting and analytics insight. Um, it can be combined with an analytics that’s produced by your automation, uh, software worthless software, RPA software, and so really a very, very, uh, important component as well that we, uh, touched on.

[00:25:59] Mm, [00:26:00] some of my episodes, um, and you know, undoubtedly, you know, a lot of work will still go on, um, you know, in, in, um, in this year. And also I think Nessie in the future, like I said, I see a lot of vendors are spending a lot of time, um, you know, to, to create these, these enterprise, uh, data lakes for all, for their products.

[00:26:24] So, so, so it’s, uh, it’s a very convenient. A place to, to bring a lot of data sources together. Yeah. Was everything what’s happening these days. Um, Zoe have hundreds of cloud applications, um, even in small companies. Um, but yeah, in the bigger ones you have, you’ll say it wasn’t a cloud. You have your work day service now.

[00:26:48] So all these, these big enterprise services as well are sitting in the cloud as a SAS offering and, uh, And do you have yours? So your work flow systems nowadays, they customers [00:27:00] are opting in for deploying things into the cloud, but these systems are not sort of complete systems to cover an end to end process.

[00:27:07] And that’s, that’s this situation we are in. Many years ago, we always say, okay, you need to buy this platform. And then we deploy everything on site. Everything needs to go into this platform, but this is, um, that, that one maybe was an interesting idea a while back, but re so far from reality, um, because we have hundreds of applications internally, already in many, many companies and we definitely have even more applications out there.

[00:27:34] A really good SAS offering small. Solutions to tackle problems, HR solutions, which are in the cloud, um, and, um, payroll solutions, which are in the cloud. And then they all part of the overall process. Uh, some elements are on-site, some elements are manual. And to just connect that too, because we will never bring everything into one system.

[00:27:58] So this is all Tapia. [00:28:00] So we only have the choice to, to, to come up with some really powerful to bring all that data and orchestrate all that data and all these different silos, um, to make one overall nice flowing process. Um, it could be. W when we, when we talk about the workflow side, obviously we have maybe a nice, um, uh, um, um, workflow system, uh, local system is, um, uh, on top of it.

[00:28:27] And then we will have lots of lists, little, little arms, and grabbing all that data, um, to, to make that overall process. But without integration was out API connectivity, um, and in a secure. Way. So like really enterprise grade security to speak to all these different systems from, from onsite to, from on-premise to cloud and back and forth.

[00:28:53] So yeah, you can’t, you can’t build a modern system and, um, Yeah, this is where we are, [00:29:00] was that, and this way integration, um, becomes a topic for, again, not just large enterprises is really starting for, for small businesses as well. They have their zero finance software. They have their Bumble HR, um, HR system.

[00:29:15] They have their, um, uh, documents may be in G cloud. So, so these problems are not just problems for enterprises. We talk obviously learned lots of big company use cases. But that, that is a, is a really, really important. And when we look at the full end to end automation capabilities. Yeah. And I think, you know, a, a data hub for, for your business where you could, um, have a data service or provision a data service really.

[00:29:52] If, if you approach that from the start in the right way, um, you, [00:30:00] you could service so, so many consumers of it, um, including people that would potentially layer, uh, workflow solutions on top of that. So, so if you get it right. Um, you know, you could, you could really, um, sort of open up the flood gate for four automations because you, you know, that you’ve got to, uh, rarely, um, you know, a, sort of a single source of truth of your, of your business data and, you know, providing it’s secure.

[00:30:32] Um, it’s descriptive. Um, you know, other teams can then can then look at that, consume that and built and workflow systems on top of that without really worrying about, um, the sort of implementation and, um, you know, w w where all of that data is persisted. As long as it’s, it can be consumed. It’s really easy to, you know, to plug in the, these, these automation.

[00:30:58] Um, and like [00:31:00] I said, uh, reporting as well. So business insights, analytics, um, you know, once you have that sort of a data hub up and running, uh, to a degree, and you know, if you are a small business, it might be a smaller scale. And if you’re enterprise great business or enterprise sized business might be a larger scale, but the point is, you know, it is a place where you could make data available for people.

[00:31:27] And, and really sort of liberate that data so people can, can create these reports and create these automations and, and mine that data, and then start to draw that those insights and intelligence out of it. Um, so they can make better decisions. They can automate their processes. They can then understand where the gaps are, where perhaps RPI needs to be plugged in.

[00:31:48] Um, so it’s a really important.

[00:31:53] That was it’s process mining. Isn’t it? He on there potentially. Um, so if you, if you look at them [00:32:00] as maybe, maybe a bit of the same data, but, um, if, if you combine that as well as, uh, was AI analytics, um, can be very, very interesting. Um, so. Predict potentially, um, specific outcomes. So we’re process mining is looking at the currently what’s happening real time.

[00:32:19] Um, so it was, was maybe analytics. If you have all that historical data and you do a few other things was analytics, you then can build predictive data models. Uh, and, um, yeah, really fantastic. Things can not be here. Can come, can, can happen. Um, you know, Every time when the sun is shining, um, your trains will be delayed because of.

[00:32:43] The doors have a sense of problem, which only kicks off off the 35 degrees. And if you collect all that data and then use proper analytics, maybe it was AI. Um, so USAA as a train manufacturer that you can then sort of predict, um, and maybe find, [00:33:00] um, uh, or need to adjust your maintenance schedules and specific times of the year to just, um, uh, figure it out.

[00:33:08] Yeah, or to just prevent, um, uh, um, disruption in service. So, so all this this can be done was, was, was, was the area of analytics, um, can go really, really complicated on that one. Yeah. So I guess the question is, um, for some of our newer listeners, that’s new to automation, where do you start? Where do you start with all of this?

[00:33:34] What’s the first thing you would do? Yeah, I gotta see what, um, you know, just to look at, um, your current situation, um, what’s, what’s happening in your business and then define sort of where you want to be. I think that’s, um, uh, and that, that sort of determined some what needs to happen in all these different areas.

[00:33:59] So, [00:34:00] So, what will you need to identify your pain point? So this is the, this is the big thing. Um, so otherwise you wouldn’t change things. You wouldn’t, uh, have a business case if you don’t know where, where actually the pain is. Um, so that there’s, there’s definitely some analysis to be done. Uh, initially, um, that could be done was all sorts of methods.

[00:34:22] Isn’t it? So it could be technology, it could be interviewing people, um, Yeah, and many, many other topics areas we covered can be covered as well in our podcasts. Um, any other, any other ideas? Yes, I think we covered, um, you know, process discovery. We, we covered that in depth. That was a really, really good, um, episode where we really looked at, um, you know, how do you help?

[00:34:52] How do you actually start talking to people and understand what pain points are we highlighted a few techniques there [00:35:00] for, for mapping our processes? Um, I think, you know, A lot of people go one of two ways. Um, the first route is really just start small, identify really small problem and apply Loco technology.

[00:35:18] And this includes workflow and RPA potentially chat bot to solve that, just to sort of test the water, um, how it works, technology wise. How a delivery of a low-code project looks like, um, and really to get buy in from stakeholders to, to, to, to, to really see it is not very hard to do these things. Um, in my opinion, the hardest part is really just to sit around a table and understand, you know, what are our top 10 problems, top 10?

[00:35:51] You know, what is the three that we desperately need to solve? I think once you, at that point, The remaining part of it is really [00:36:00] quite simple because all it is is in the question of just mapping those processes out. Um, it might be that you start with one, um, get the buy-in from all the stakeholders, ensure you get the buy-in from it and sit down, understand the vision, um, and, and automate it, you know, get a minimal viable solution out as soon as possible, making a difference as soon as possible and build that.

[00:36:25] And do so in a collaborative way, you know, always keep those stakeholders as end-users of the processes. Engaged, always ensure that what you’re doing is, is making their lives easier, not harder, try and reduce work on people, don’t create more work, um, and try and target those processes that really consumes people’s time.

[00:36:49] It could be really as simple as. A shared inbox where stuff arrives and you just want to take that stuff and put it in the right places for people so [00:37:00] that they can pick that up and do their day jobs. I mean, that in itself is such a, a good place in my opinion, to start with, with RPA, for example, when you go around and you just ask people.

[00:37:10] Show me your shared inboxes, you know, and there’s 50 of them. I’m like, well, there’s an obvious place to start. Um, let’s train a robot, let’s train a robot to read those emails and actually use a bit of sentiment analysis to understand what this is. And even if it’s just as simple as forwarding that email on to the correct place, you know, that, that, that in itself is a very, very small implementation, but it’s a step.

[00:37:39] Once it arrives at a place. Maybe there is an opportunity then to consume that email and create a lot of workflow, whereas a task for somebody when I click on and they look at it and you give them the information they need to make, make a decision, or if there’s opportunity to look at it and auto approve it because it’s below [00:38:00] the threshold limit of a hundred pounds or something.

[00:38:05] Whereby, you know, you can train a robot to, to make that decision, take the volumes that the low value, high volume transactions out of your business and grow from there. You know, start looking at other opportunities, stop looking at your channels. Right. What if we plug that chat bot in here, employee doesn’t have to send an email to HR to ask them about the leave policy or some contractual policy.

[00:38:34] A bot can feel that no, no many. There are many of those sometimes we think, okay, we need to really concentrate on the, on this big problems. Should I, um,

[00:38:48] You have seen, we worked on really big projects, which had lots of business support stakeholders and fixing a problem. But when you look in this organization sure. They, they may be, there was the [00:39:00] view. Okay. We will look at further automation later on. But if you, if you, if you enable lots of departments to actually get almost that stuff for themselves.

[00:39:09] So this is why local is so important. Um, uh, instead of just doing this complex automation and programming, um, so yeah, to, to help. These departments, these two to address this huge amount of smaller problems. Um, and to, to really get them, get them, get them going. Uh, what’s the right it and governance around it, but there’s this.

[00:39:33] Yeah, this is what we talked about a lot. And, um, But then really get them going, um, and tackle all these 80% of small, um, problems, um, instead of just getting through the 20%. And, um, I think that’s, that’s, that’s why, um, was all these things we have available at the moment. Um, what’s such a, it’s such a great time for everyone to look at it and get started.

[00:40:00] [00:40:00] Yeah. And I think, um, although the, the topic of automation is quite broad. Um, if you, um, if you unpack it slightly, a lot of the, the, the things we do to automate these processes are not very difficult. It, it is, it is literally if you automate a process, it is dragging boxes onto a design canvas, connecting it up with decision points.

[00:40:29] It is quite natural for people to understand that, especially when they understand their processes. I think that’s what that’s, in my opinion, what makes low code? So AP link, because, you know, it’s, it’s easy to represent your process. It’s easy to model. What your, your data should look like whether or not each invoice or transaction could be, uh, uh, uh, you know, a, um, uh, a purchase requisition.

[00:40:59] It could be [00:41:00] a transaction number from a bank statement that needs to be allocated in a financial system. Well, apply it to the financial system. What a bit of that, that looks like it’s, it’s so easy in these, these low-code systems to model that. And of course, to create the user interfaces, really modern looking user interfaces without writing code.

[00:41:21] I think for me that that’s one of the great benefits and then of course publish it. So it’s accessible on mobile so people can actually look at this when they on route. So they are connected to their processes. And again, you know, it doesn’t have to be a very complicated thing. You know, a lot of the use cases we looked at in, in the podcast, you know, our standard things like onboarding, offboarding, you know, these types of things where surprisingly, when you, when you speak to, um, people, um, these types of sort of, um, you know, kind of mainstream [00:42:00] standard process are still quite manual.

[00:42:03] Um, so, so these are some of the, some of the great places in your business to start automation and to start looking at that sort of low-code automation, RPA, and, and you know, how, how that could, um, be used to, to really rapidly, um, automate these processes and, uh, you know, make these problems go away. Um, a lot faster, like you said, in the beginning of this episode, you know, like lightning, lightning, fast compared to traditional high code development where everything is written from scratch.

[00:42:39] Using using high code methodologies and, and, and, and, you know, the, the old traditional ways of doing things. Um, so we’re an exciting, um, sort of time where, uh, you know, it certainly a lot of the things we do, um, uh, as a business, uh, we certainly look at really complicated stuff and, [00:43:00] and to this day, it’s, it’s really quite surprising how, how mature these platforms are at actually.

[00:43:06] Um, being able to cope with really, really sophisticated, um, enterprise type implementations, but also how quick it is to create something very small and make sense. Yeah, we, we had to recently in intake of new gradients and, um, and, um, they couldn’t believe it how quickly to can actually build a proper, um, enterprise ready.

[00:43:29] Fully working application. Um, so they, they, they, where you just use to sort of the normal stuff, um, building, building web apps, um, sort of, you know, sort of hand, um, uh, Yeah, you have to code everything. Um, so it was the frameworks, that kind of stuff. And now jumping on a proper workflow platform, um, low code, low workflow platform.

[00:43:55] They, they just learn it so quickly. And get [00:44:00] results, uh, and then just week two weeks impressive results. So, um, so yeah, it’s, it’s fantastic to see w when it works, um, uh, everyone is happy and everyone is really keen on finding other problems in the business. Uh, come up was really quick ideas, prototype things was these local platforms.

[00:44:22] So that’s, uh, that’s, that’s also fantastic, Jim. Um, and we should talk more about not necessarily building applications. Um, we can use, um, uh, also the, the, the, um, using low code for, for innovation and just ideation. Um, it’s, it’s also very powerful. Yeah. I had an interesting quote where somebody said, once you see this stuff, it’s really hard to unsee it.

[00:44:47] Oh yeah, that’s good. It is. It’s something that’s stuck with me. And, um, it’s, you know, it’s, it’s something really that, um, If you’re new to locate a it worth, checking it out, [00:45:00] you know, get in touch with myself and Sasha more than happy to give you guys a demo. Uh, obviously more than happy to, to, um, give you some, some ideas on, um, on a particular problem and how these, um, the technology and the hyper automation space would help you to solve that problem, how long it would take.

[00:45:19] You’ll be very surprised with the timescales, especially if you use to sort of a longer timescales when it comes to traditional it development, it’s definitely something worth checking out. I know there’s a lot of talk in the market about it, but, uh, you know, challenge yourself a challenge. Um, you know, between Sasha, myself, we’ve got a, a really, really long history with, with, with low code.

[00:45:44] Um, you know, we’ve, we’ve delivered a lot of these projects and, you know, we can certainly give you a, a really, really good, um, initial start just to get you out the starting blocks, uh, with automation and sort of just to demystify things. What you going to [00:46:00] do, perhaps where you are on your journey? What, what, what a potential good next step would be?

[00:46:04] How big you should go. What the sort of team makeup should look like. What’s the culture you’re aiming for in your project delivery. Um, and really just, you know, all of the peripheral things that that would make, uh, your automation journey, very successful. Yeah, this is why we have created this, um, this checklist, um, for, for every one of our listeners, um, 50, um, um, sort of tips to really get started with the intelligent automation, um, journey.

[00:46:34] So you can always go to, um, the automation guys.net, send us a message there. So just send us like automation as a, as a sort of a key word. Just send that message to us. And then we will share, share that checklist with. Um, so, and then you have sort of everything to get to get really started on, on that was success.

[00:46:58] Great. Thank you. Sasha. [00:47:00] Been really good discussing that again. Um, I hope our listeners enjoyed that. Um, and, uh, I don’t know if there’s anything else that you want to add. No, so that’s, uh, yeah, that was a good, good session. Good Roundup on, on what we have covered so far and what we very likely will continue to cover.

[00:47:18] Um, so as I mentioned earlier, um, so we are very happy for feedback and suggestions. Send them send them through on all the automation guys.net website or on our social channels. And we will, um, oh, join our clubhouse session. Uh, we have every week on Tuesdays at four. And, um, yeah. And then we will, um, discuss that more with you.

[00:47:44] As always thank you very much for joining him,

[00:47:50] unfortunately, that’s it. Again, was this episode of the process in automation podcast. If you liked this episode, please give us a five-star rating and don’t forget to [00:48:00] subscribe to this podcast. So you don’t miss any upcoming episode. We hope you will tune in next time. And until. Let’s automate it.