Session Information:

Establishing a Center of Excellence (CoE) for your RPA Initiative?

For those starting their RPA journey, this session focuses on how to set up a CoE program to govern and scale your automation initiative.  Learn some of the tips, potential challenges, and lessons learned from Finastra.  

During the session, you will learn methods to: 

• Identify the right structure for your organization
• Organize and upskill the team
• Establish your intake / assessment process
• Lessons Learned / Keys to Success 

Session Transcript:

Global consultants at Deloitte predict that at some point in 2023 rpa will reach near universal adoption and by 2024 organizations will lower operational costs by 30 percent by combining realigned processes with RPA along with a range of hyper automation tools and yet many of us haven't begun our rpa journey or we're only just getting started and of course with covid that has added additional impact for us it's been a bit of a double-edged sword limited funding but pressure to go faster and of course a key part of a successful automation program is a robust center of excellence.

I'm Wendy Sherrock I lead the operational effectiveness team at Finestra, which also includes the intelligent automation coe and I'm Lena Webster I'm the program manager for Finestra's RPA initiative and Wendy and I are going to be speaking to you about our experience in setting up the RPA center of excellence.

We'll be talking about the governance the standards what we found worked and what perhaps didn't work so well so I will now pass it over to wendy thank you lena great i'll start off with a quick overview of Finestra and who we are and then and then go into the to the rest of the of the content that we've prepared for you today Finestra was formed in 2017 by a combination of mysis and dnh and we build software solutions for financial institution institutions.

We have deep expertise with an unrivaled range of pre-integrated solutions spanning retail banking transaction banking lending and treasury and capital markets with a global footprint and a broad set of financial solutions finaster has 1.9 billion in revenues about 10 000 employees 8 600 customers including 90 of the top 100 banks globally and just to give you a a feel for the scope and the scale of the organization you'll see some some of our key statistics and i'll just call out the one in the center here just to give you give you an example of our impact in our reach finaster originates about 70 billion in u.s. mortgages annually alone.

Exactly, that gives you a sense of who we are let me share with you now our journey our rpa journey one of the first things we did was we we defined what our mission and our vision is and i'm sure this is quite similar as some some of yours and feel free to share that in the chat as well um but we we came up with a very simple mission and vision to analyze digitize and remove waste to drive productivity and scalability across the organization and of course we want to do that by maximizing the value-added work taking out all the the waste and the non-value added and quite frankly the frustrating tasks that that employees have to deal with day in and day out and one of the things that you'll need to do is educate people on what rpa is believe it or not we had some some people that were googling what RPA stood for in some of our early meetings.

Which quickly helped us to understand that we need to educate people on on not only what rpa is but what it isn't as well so this is one of our our first you know slides that we created to help share that with with other employees.

I'm sure you have something similar or if you don't we we highly recommend that um of course we're looking at from an rpa standpoint those processes that are manual and highly repetitive and those that need to really take advantage of structured data so these are some of the things to educate people on in terms of benefits of course you know cost savings and financial benefits and productivity those those are all the top ones that we all go after but there are many other benefits for your rpa program as well and what we've done here is tried to highlight some of those ancillary benefits.

You know customer experience risk and compliance there are many opportunities to to drive those improvements and the benefits to the organization would love to hear at what we're missing what what else you might be tracking in your organization if you've got your rpa program up and running so that that's just to set the stage a bit and let me share our journey.

Which has been quite an interesting one um given all the recent events but we did start our journey back in february of 2019 we did an initial assessment and proof of concept i'm sure for those of you that are are well um well ahead on on your journey started in a similar way but we came up with a kind of a list of of those first few processes that we wanted to automate and proved out the business case essentially from there once.

We knew that we were moving ahead we had to identify the tool that we would use as well as our system integrator or si for us it was blue prism and ubiquity and then we got started we were very excited um you know it's kind of like getting a flywheel started and we had the flywheel starting to crank we were building out those processes and then covet happened.

I like to call it the cobia car crash and i'm sure many of you felt different types of impacts depending on where you were in your journey we uh collaborate with another company and and for them they actually it it went faster they had to go faster but they were also much further ahead for us it happened right in the middle of our phase one launch we were just we actually just had launched our first um our first process and boom so like many companies.

We had to to kind of hold on spending on critical spending and reassess and re-evaluate the good news is that we're now in a place where we've done another business case we are getting restarted on our journey um but we do expect some some construction along the way so hopefully that gives you a sense and i'm sure you we all have interesting stories of uh how our road maps have been impacted by all the all the events that are that are happening um and of course as as we went down that journey part of part of the effort that we really spent and we build out a whole playbook around this is you know what what is our center of excellence and how do we structure.

It so I'm pleased to hand it over to Lena to educate you a little bit more on how we went about that thank you Wendy um within within our center of excellence we decided that we should structure it and i would suggest that anyone else do this as well in accordance with our organization to set and align with our organization's culture and structure so here on the screen in front of us we can see we've got the centralized center of excellence and on the other side of the coin we've got the fully federated center of excellence.

I'll talk through each one of these to begin with a centralized coe is right in the middle of the organization all the activity surrounding the rpa initiative takes place from that center the centralized coe is responsible for setting up the governance for setting these standards including coding standards for your automations also in sharing knowledge and objects across the organization and and delivery sits with that central coe as well.

If we move to the federated analysis structure this is where the lines of business and the functions will actually take on the role of finding the rpa opportunities and thereby building the rpa pipeline all the other work is then conducted by the center of excellence if we move again to the federated delivery structure this is where the rest of the organization will not only conduct their own assessments but prioritize them as well so one of the risks of having a centralized coe is that the center of excellence actually can become a bottleneck to releasing the automations depending upon their workload.

Finally in the fully federated structure this is where the lines of business and the functions within your organization are completely empowered to not only find those opportunities but to deliver the automations themselves build and release the digital workers for the center of excellence they retain the responsibility of ensuring knowledge sharing building the capability within the organization and obviously the governance so for us it would be very interested to hear some of the different options.

That you've taken in terms of structuring your coe at Finestra, we started with the centralized approach but we also knew that we would have to at some point evolve to the federated structure and the reason for this is in the beginning we wanted to make sure that we established a strong center where we would have the governance the standards but also within our organization we were experiencing a bit of rpa's sprawl and by that i mean that there were different areas of the organization that were using different tools experimenting with automation but not sharing that knowledge having a centralized coe.

We felt would bring all of that structure and knowledge into our enterprise solution ensuring that we got the most benefit out of the automation tool that we were using as well as making sure that we would be able to establish a robotic operating model which could then be used consistently by the whole organization also in the beginning of your journey education and messaging is very important and we wanted the coe to have that consistent messaging across the organization now the reason we knew that we would have to eventually move to the federated structure is that Finestra is an organization.

That has different lines of businesses it's very entrepreneurial and we knew that there was a risk that the center of excellence could become a bottleneck for the rest of the organization being creative getting the real value that we want them to have from the automation solution so with the federated version the lines of business will get that benefit faster you extend the knowledge and you extend the capability across the organization.

We also wanted to have the correct roles within the center of excellence so on the screen we have the different roles that we chose to be part of that group the head of rpa is wendy who i'm presenting with today a very important role is the discovery manager the discovery manager is responsible for liaising with the different areas of the business reviewing all of the business processes and finding the real rpa opportunities that will give a good return on investment the discovery manager builds the pipeline that then gets fed into the delivery team the delivery manager which is myself is responsible for that uh building of the automations.

The training of the digital workers if you will ensuring that the priorities are met and that we deliver on time now any project really requires that you bring the people the hearts and minds of the organization need to come with you to achieve that we put changed management right in the middle of the center of excellence the change managers are there to help us reduce some of the rpa anxiety that we at least found within our organization when you first introduced the idea of automation it helped to establish a mindset.

Where people can embrace automation rather than fearing that advancement we actually went to the point where we knew that we would have to have well-defined roles in responsibilities to get that coe factory moving properly so we did do role descriptions and we hired the right people into those roles now the center of excellence can be as effective as you wish it can have the right structure but it does not operate at least does not operate effectively in a vacuum so it operates in a universe so what we have is the coe ecosystem and we've called out the different functions and areas of the organization that we believe are absolutely essential to a successful rpa program.

So i'll call out just a few of these the first one i'd like to call out is human resources so along the lines of having change management right at the center of our work when you introduce automation you do impact on the roles that people are performing the tasks that they're doing every day even if you are removing the manual tasks they really don't like you're still having an impact and that can cause people to have some anxiety also.

If you want to truly have an integrated human and digital workforce HR needs to be involved as you might have job descriptions for example where part of the job is performed by a human and part of the job is performed by a digital worker we also found that having finance in our corner was especially helpful now rpa you can of course have quantitative benefits assigned to it but a lot of the benefits in rpa are softer benefits that many can find difficult to quantify or to monetize so having finance involved means that we had a a function that can help us determine.

What really is the return on investment to help us set the standards and the measures for our success and the last one i want to mention is security we found uh and i think this is true for every rpa initiative we had to rewrite some of our security processes we had to introduce new user profiles new ways of setting up the digital workers there are policies in every organization that makes sense for a human workforce but perhaps don't work.

When the workforce is digital an example here i'll call out is multi-factor authentication or mfa at Finestra this is conducted by a text message that is sent to a staff member's mobile phone they then take that code from the text message plug it into the screen and then they're allowed access to a particular system digital workers don't have mobile phones so sending them a text message is not necessary so we did have to rewrite a number of security policies in order to suit this new world now a center of excellence working within that universe has three main things to do and there is a quote from a book called the light in the heart.

That I think sums that up particularly well so don't just change transform so in this sense we are able to control the mindset and the understanding of what rpa is we found that there were numerous misconceptions about what rpa is including that some people thought they were actual physical entities in the office that would be able to bring people a cup of tea when they came into our reception area unfortunately that's not what they are this is software purely and we need to make sure that we educate individuals and we transform the way they think about automation.

That we reduce the potential anxiety and we get them to see the benefit the next one don't just relate advocate takes this a step further so we don't want individuals who are just necessarily thinking that this is a new technology being introduced but it's not really for them you want to find some real champions who will take hold of the automations understand that they can provide solutions that meet their functional goals and will help the discovery manager understand where the opportunities are finally don't just promise but prove.

So you've spoken to your leaders you've had your business case and now you have to actually show that you are getting the return on investment that you expected now you can and you should in my opinion write some reporting into your automations based on the key um and the key success factors that you've determined and then you will have right in front of you on a piece of paper.

The proof that the benefit is there and you're getting that expected value an important point as well is to make sure that you cultivate the capability across the organization that you really build the talent around the automation so some key parts of this is that you must have those technical skills you must have a technical architect who is able to ensure that you've got a sound platform.

That is efficient that is optimized and will support your scaling goals obviously you need to have the developers to create those automations but business analysis skills are another key item for your success that is finding the right opportunities building the pipeline so that you get your factory of rpa working from the pipeline to development to bringing the people and the mindsets along the way to make your rpa initiative a success.

We also found that it's incredibly helpful to learn from others so we have paired up with another organization much further ahead in the journey than we are but we've been able to learn a tremendous amount from their experience and we can encourage you to go out and share with other people who are doing this you are certainly welcome to contact myself and wendy and we'd be happy to discuss it with you finally in summary.

This is what i like to call the coe flower and it essentially sums up what the coe is doing for the organization so they are setting the vision and the mission they are also defining the robotic operating model helping with the change management to get the adoption through the organization to set the automation mindset they are understanding the value ensuring that there is a key way of measuring your success and reporting back on that they are setting the standards not just for the culture but literally coding standards they are there to encourage faster delivery.

That could be in sharing scripts that could be in ensuring a prioritized list is available and finally making sure you have your rpa opportunities ready to go building that pipeline understanding where automations can really add the value there are some processes where automation doesn't necessarily make sense i'm going to pass over to wendy.

Who's going to tell you a little bit more about that yes and it it is all about finding those opportunities and and once again as i said earlier you will have to educate the organization to help find those opportunities and there are you know regardless of your industry there are four categories of tasks that best fit rpa so i always like to start here to help kind of get people socialized around what what is a good fit for rpa first of all updating information.

I'm sure like us many of you have some type of process to update addresses in your you know clean up addresses in your system so that's one example migrating information from one system to another especially where you have what we call swivel chair updates where you have to take information from one system and re-key it into another system urgent tasks for example if you have a data data breach much better to have a digital worker that's responding to that in in instantaneous um an instantaneous manner versus waiting on a human to notice that that's happening and from a similar perspective system monitoring if a system goes down you'll you know it would benefit greatly to have a digital worker who can instantaneously respond to that as well.

So those are those are kind of the four high-level categories in terms of the identifying those opportunities and ensuring it has the right characteristics um this is this is kind of a good list to start from and it does need to be rule-based you do want the right kind of volume we've we've had quite a few people who they find opportunities for automation but it's something that's only updated once a month and that's just not not enough time um you do want it to be prone if it's prone to human error that's a good candidate for rpa um and and it does need to be a stable process so we we have a few that have also come forward but they're still in the process of of um making a lot of changes and that would be kind of hard to manage from an rpa standpoint.

You want to get get to the point where the process is more stable and i'm sure many of you have said this yourselves that we don't want to automate a bad process and that that's kind of a part of that that puzzle and i'll i'll speak a little bit more to that um in a couple of slides but hopefully this this gives you know we use the slide to help educate others and in the organization on what is a good fit and then we connect that to our request form and our our discovery uh questionnaire which you see here so first on the on the left hand side you'll notice we've got a process request form and we you know we tell people up front it's it's not a quick it it's relatively short but it will take about 10 to 15 minutes to complete because we want to gather some of that information to make sure that that we have enough to prioritize now for those that aren't sure.

What is a good candidate we have links to more information uh we have a gamer yammer channel where we have videos published and other articles and other resources that help people understand what rpa is we you know we have had people actually googling what that means so we wanted to try to provide that and we also set up a a an email that people can use to reach out to us as well and i would encourage any of you who would like to stay connected um you know we're still learning would love to to work with you and learn with you as well on the right hand side you'll see that the deeper dive discovery questionnaire where once again.

We are probing in we're asking about the volumes um we're trying to get to how many systems are actually being touched the um the amount of time that that we're looking at because that will all feed into our business case so that's the kind of information we gather and and the way that we ensure that that when we're prioritizing we have all the right data to make those key decisions so like i said earlier you know we don't want to automate a bad process so how how do we figure out whether or not um that's the case we do have a a process framework at Finestra and when we have an opportunity we start with the framework to to understand.

How the process is working today and we do kind of an initial higher level assessment more of a business optimization opportunity assessment and from there we can kind of qualify whether or not it's even ready to consider for rpa or do we need to initiate some business optimization activities um it could even be just ensuring that we have the process documented but again I'm sure many of you have said that like I said before we don't want to automate a bad process.

So once it is ready for for rpa then we do that deeper dive assessment and make sure that that with the discovery we have all the information we need um do an initial level of prioritization and get sign off to proceed we build that deploy our digital workforce and then of course make sure that we all we feed any of those changes back into our process framework.

So that's how we kind of pull all those pieces together we want to wrap up by sharing some of the common challenges that we've experienced and then we'll share some of our lessons learned as well we wanted to narrow to a few key key challenges first of all and we hear this a lot in the industry too there's always a challenge in in uh demonstrating the roi and the value and so to address that we first of all look kind of across the organization.

We look at multiple work streams and ensure that we are defining key measures of success up front and the other thing we do is is work very closely with our our finance business partners so in the in the universe that Lena shared earlier you know that is part of our ecosystem and the finance business partner is just a key key um stakeholder to to work very closely with along those lines funding and chargebacks and or making you know deciding how you're going to do that that's that was that still is a challenge that we're working through.

We've got a model we're testing now but what you want to do again is work with your finance business partner and test whether a value sharing model might work or do you want to charge back the cost of the of the bots and the center of excellence um or do you just manage that you know within the coe so those those decisions need to be made depending on the your company and and how you're structured but it that finance business partner will help you and then finally kind of goes back to the first one um as well as educating people on what rpa is and isn't but those misaligned expectations ensuring people do understand clearly what rpa does but also what it's not capable of and and defining those measures of success.

I know that sounds like a common theme and it it definitely is for us so this is a good opportunity now to kind of summarize the many of the lessons learned that we've gathered along the way Lena which two would you call out so i would call out one that I alluded to earlier which is um you need to start defining your setup your support and change protocols early so this is the liaison with the security team setting up your new profiles also ensuring that you agree how the rpa is going to be supported once it's in operation the other one that i would like to call out is it's extremely important to have a very good partnership between the technical team and the business smes the people actually writing the automations or training the robots really have to get into the minds of those business owners and understand to a very low level uh how the process is run how it can be optimized and the best way to automate.

It those are my two Wendy wonderful and the two that i would call out first of all when it comes to developing your coe model Lena said this earlier but I think it's worth reiterating that you want to factor in the the culture of the organization your organization structure and really kind of think through the the different types of models that lender presented everything from central fully central to to fully federated the other one that i that i wanted to mention and i'll i'll kind of land on this because to me this this one is such a critical one and that is that my best advice to you is don't go it alone you know for us we found um robiquity to help us along the way.

You know we it was important to find those experts because we we were all new to this and rubiquity has been super helpful they they are pragmatic they're not afraid to roll up their sleeves and and kind of get in into the you know into the details with you um but most importantly they teach you to fish i i encourage you to find that partner that that makes sense for you um and do reach out to us as well at rpa at finastro.com.

We would love to both collaborate and learn from from what you've learned as well so i would encourage you to add any uh lessons learned advice um that you that you've had in the chat as well as any questions and uh and we're happy to to address those as well so we are still at the beginning of our our journey but we hope that hearing some of the approach that we've taken so far the challenges as well as the lessons learned helps you in your journey.

Thank you.