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Intelligent Automation that is making big changes in the office

You’ve probably heard a lot of mention recently about Robotic Process Automation (RPA) and Artificial Intelligence (AI) in your business, or amongst your professional network online. Perhaps you have a few questions about how this is going to impact you and your work life, and you feel it could threaten your job. On the other hand you may be keen to get involved to futureproof your career, but feel it could be a bit too technical for you.

To put your mind at ease, firstly this definitely is a tool that you can leverage in your career. Also, it is a lot easier than you think to get involved with RPA and AI. A lot of it is not the complex and scientific development of mathematical matrices and neural networks that you’ve read about online or seen on TV. To use these technologies, you and your team can start getting involved in right now.

The reality is Automation and AI is the future and it’s here to stay so let’s help you swim with the tide!

Let’s look at the hottest, fastest growing technology in the digital transformation space and that is RPA, robotic process automation. Where did it come from? Why is it gained so much traction? Where are these trends heading? How is this going to impact your work in your job and how you can use it to enhance your work life?

Digital transformation is essentially how businesses adopt a handful of different technologies to modernize how their business runs to modernise their old processes, applications and approaches that they use to service their customers. Many in this space see RPA as the backbone of Digital Transformation which can be used to accelerate these trends that we’ve been seeing working in the background for the last decade or so.

This new era is what they call the “fourth industrial revolution”, so once you get a handle on what automation is and how this can be used in your company, then you can start getting involved in automation activities and projects to future proof your business and career.

what is RPA?

Simply put RPA is low code software that can be programmed to follow a simple process and then repeat that process over and over again. If you’ve ever created or used a macro in Excel, you record a few steps, you can add logic for “IF THEN” decisions, press play and then you can see that process run in a loop until it’s completed the list of work that you’ve set it.

If you’re an Excel VBA macro whiz you can actually go into the underlying code and build complex processes from scratch, pulling data from websites and different applications. RPA is a similar concept, and not just tied to Excel or Microsoft office applications, you literally can program RPA to get data from or enter data into any combination of desktop applications, web applications, website pages, web forms, APIs etc.

Think of RPA as an automated person that rather than a piece of software, as it actually uses the user interface just like you and I would to clicks on buttons and links, or type into forms, as if it’s using the keyboard! An analogy I’ve heard about what RPA potentially can do for you, would be to imagine if you had to a new apprentice (with no experience of your industry) that you could train to do a specific task over and over again. You could just hand them all your simple tasks over to them all the tedious repetitive tasks and they will just get on with it. Such things like copying and pasting data from one system to the next, entering data into an application from a spreadsheet or a web form, or even taking information from say an invoice and update your financial spreadsheet.

They don’t have to know anything about your industry and can just get on with the work straight away. Then you can just spend your time focusing on more complex intuitive tasks, the more interesting parts of your job you enjoy.

This is just a glimpse of the power of robotic process automation, as RPA can do much more. If you can map out each step of a process and logically define each decision point (i.e. it’s a logical decision that doesn’t require human judgment), then it could pretty much automated.

Where did process automation actually come from?

RPA was created by Blue Prism a software company back in 2003, and they launched their first product called “Automate”. The underlining functionalities of RPA are like macros, screen scraping and recording – which have been around since the 90s – was finally packaged into a user-friendly platform. There were two reasons that drove the need for this software; firstly businesses that had been outsourcing, especially overseas, to keep their costs down were looking new ways to save costs due to the rise in labour costs. Secondly, companies themselves were becoming overly data hungry – demanding more from IT in line with the rising demand of the customers wanting faster services, more ways to purchase things, and better customer service and experience. There’s only so much that IT departments can in this new fast paced world.

RPA became a much faster solution to solve technical issues, as technical roadblocks, integrations and data fluidity could be solved in a matter of months or weeks, rather than the years it can take to implement IT overhauls and upgrades. And with it’s comparatively lower costs, RPA arguably became the backbone of digital transformation to modernize businesses who had slow clunky ancient applications and processes.

Very quickly business processes could become faster and smoother to reduce queues, reduce errors and save time on mind-numbing manually-intensive tasks, so that staff could spend more quality time on customer service, human to human interaction and creative activities.

Though RPA has come a long way, there’s still much more to go. The growth of RPA and AI is exponential. In the graph you can see that $1.1 billion was the RPA market back in 2020, and is predicted to be worth 2.4 billion in 2022. AI is even more massive at 1.2 trillion in 2020. Obviously the US is leading the race and followed by the UK, Japan and Germany but countries change all the time and clearly China is really making waves in the AI space.

The top RPA players

The top players right now are UiPath, Blue Prism and Automation Anywhere. They pretty much have similar underlying code. From my experience UiPath is my favourite followed by Blue Prism. A lot happened in 2020, UiPath had its IPO in the states and US investors look to bid for Blue Prism.

As an RPA developer UiPath was always been my favourite so I was absolutely thrilled when Guy Kirkwood, the then-chief evangelist of UiPath gave my book a five star rating and said it was “highly recommended for anyone in the in the automation space”, and he even went on to write the foreword to the published version.

Three trends

1 Citizen Development

Automation software companies are making it really simple to develop your own automation robots so that basically anyone can intuitively develop one, similar to how we can all use Excel

2 Intelligent Automation (RPA + AI)

The second is that Artificial Intelligence is becoming closely integrated with RPA platforms. Either AI is being built into the RPA platforms or RPA vendors are creating ecosystems in order to seamlessly ‘Plug and Play’ a plethora of AI Capabilities into an automated process. E.g. If your automation needs to ingest a scanned image and pass the data from the image to the RPA ‘Bot’, you can literally drag and drop optical counter recognition functionally into the workflow.

Vendors that build ecosystems can scale much faster than having to build AI capabilities into their platforms. They can focus on RPA and leave the AI to the AI companies and experts.

It is said that RPA can only automate about 20% processes in a business because RPA doesn’t think, so AI in process automation is of growing importance, so that you can scan a pdf document or categorise emails in a mailbox, engage with clients (and staff) with a chatbot.

3 AI in Applications

The third trend is that automated workflows and AI capabilities are now being built into applications like enterprise resource planning (ERP) applications and customer relationship management (CRM) software. In fact most enterprise software that you’re using now will see newer versions with Intelligent Automation built in.

How will RPA and Intelligent Automation affect our day-to-day work-life?

Soon you will be able to leverage these technologies to look like a superstar by smashing your targets, delivering better customer experience, and experience better user experience so that you can work more efficiently.

There is a big myth that Robots will take over all our jobs. Job loss is by far the biggest fear when introducing any new technology and intelligent automation is no different. No one wants to feel like their job is at risk, I felt this first-hand when multiple articles said how analyst roles (which are highly logical, and data driven) would be the most at risk of being automated.

Obviously that didn’t happen but in some organizations it’s been hidden and developed in dark corners, which just elevates staff suspicions. This technology should be celebrated due to how much pain and frustration and the laborious effort this will alleviate from so many people’s work lives, freeing them to do more interesting, creative, problem-solving, and human-to-human interaction activities.

Looking past the scaremongering, we’ve seen time and time again how new technologies actually created new jobs. Look at the personal computer, the internet, mobile phones. All of them created whole new industries, new jobs and new ways of working. I’m not niave to the fact that some jobs will be replaced or parts of jobs, but smart companies are investing in their staff, upskilling them on how to use automation to do their jobs better. Automation typically opens new avenues to meet customer needs, ambitious professionals are upskilling in technologies which are making waves so that they keep relevant and future-proof their careers. We’ve taught thousands of professionals in over 100 countries to upskill to get involved in automation or to advance their automation careers.

A good phrase to leave you with is that “Automation should take the ‘robot’ out of the human” so that we can spend more time on the actual job. Our brains work best doing creative, interactive, problem-solving tasks, not repetitive mind-numbing tasks – which are prone to human error.

A side note, I’ve written many articles about how real value of a business is its staff. The worst thing I’ve seen is when a business removed staff only to hire new staff some months later. This was a massive brain-drain, as they lost process and domain knowledge, they lost staff who had relationship with teams and clients, and had to re-trained new staff that had less expertise.

The key message here is to keep discovering the power of new AI technologies and how you can use them in your role, in your team and at your business. Soon we will be in a world where there are very few menial tasks as we will be equipped with “virtual assistance” that can compile information from multiple application, fill in forms, read/scan long documents for you, to get you the information we need. We will no longer need to do repetitive copy-and-pasting, form fill.

Covid in 2020 did accelerate a lot of the trends, and in my book “Business @ the Speed of Bots” I wrote in 2019 that “Business was going to change more in the next 5 years than it did in the last 20” …I didn’t at the time realise how right I was!

Like and subscribe to my YouTube channel Tony IA (Intelligent Automation, Simplified) for videos created to simplify intelligent automation for business leaders and professionals who are new to automation to level-up your knowledge. Become empowered on how you optimise your business and discover new technologies, in a lean and accelerate way. You can also learn more from my book, Business @ the Speed of Bots: The AEIO YOU method HOW TO IMPLEMENT ROBOTIC PROCESS AUTOMATION THAT SCALES. Get ready for the new digital transformation age for more information. The foreword is written by Guy Kirkwood, who is the Chief Evangelist at UiPath, and a very well-known advocate of RPA with over 20 years of experience in outsourcing.

The common pitfalls awaits your Automation team …and how to avoid them

Whether you’re looking to train up your automation team from internal staff or whether you’re looking to hire some external experts I want to make you aware of 14 common pitfalls that I and my network have noticed new automation teams making time and time again. These issues can manifest at project level when you start to get going at automating

Lack of senior business leader buy-in

The number one thing every automation team should make sure they have is senior stakeholder backing. If your senior stakeholders believe in the technology and believe in the benefits of your program and projects, you can move forward at pace without getting too stuck and any blockers can be quickly removed.

Lack of IT ownership and understanding

It’s vital for IT to be bought in as well. They will need to take ownership on the part they will need to play if you want to roll out automation company-wide, giving you support on infrastructure and the IT side of things, so that you can focus on automating business processes. IT will need to understand what RPA is and that robotic process automation is very different to IT software development. RPA is more akin to digital workers rather than software development

Missing or unavailable data

You’re inevitably going to come up against a lot of missing data and unavailable data when you try to analyse your businesses processes, and when analysing your teams and the business as a whole. You need good data to show you where the best automation projects are and to estimate how much value you can deliver back to the business.

You may need to do a little leg work to measure the current state of processes and activities, and if you’re lucky you may be able to extract data from applications and databases to find the data that you need in order to determine which projects are worthwhile. Sometimes (well more often than not) data just isn’t available, but you at least need a consistent measuring approach so that one project/opportunity can be compared to another.

Staff’s resistance to change

Staff buy-in (the end users of the automation, or those who will work alongside automation) is vital. If staff are engaged in the various automation activities and understand the benefits that you are going to bring to them, their team, their business this will accelerate progress and roll out. Otherwise you’re going to have them feeling a bit resistant to any changes you’re trying to implement on them, that they haven’t been a part of.

Digital transformation should be co-creation between the tech experts and the business experts. When staff are involved, and it’s their change they will gain the understand that you’re there to deliver solutions to help them achieve their goals and their targets faster and exceed them. Together you can solve the problems and inefficiencies causing them to have to work late nights, be overloaded with work, and together your solutions will be fit for purpose, actually benefit them and they will be happy to use!

Loss of traction

Loss of traction is a big pitfall when you’re running an automation program and is a sign you’ve bitten off more than you can chew. Perhaps you’ve start too big, it took too long to develop and now you’ve hit a brick wall.

A better approach, especially when you’re team is new, is to build up momentum slowly and progressively starting with smaller simpler automation projects which gets people excited, get business teams brought in and then you can keep scaling up by building bigger, more complex and exciting projects. Starting small and building fast also gets you automation team to get your deliver processes perfected.

Practice the steps slowly then you’ll be tapdancing to work in no time

Unclear roles and responsibilities

If no one knows what anyone else in the delivery process is doing then you’re just going nowhere fast. Throughout the deliver process everyone involved needs to know what their role is. Everyone in the implementation process needs to understand what’s expected of them and what to expect of other people so written down roles and responsibilities and have everyone agree, leaves nothing up for interpretation later down the line.

You can use what’s called a RACI chart to help clarify what people need to do. For each action or activity define:

R = who is responsible for the action. I.e. who actually does the work

A = who should be accountable if the work isn’t done, is subpar or is delayed

C = who can the person doing the work consult to get expertise on a subject

I = who should someone Inform when the activity is done …or has issues

Each of the 4 architypes above can have multiple people apart from Responsible. There needs to only be one person who take responsibility for issues

No clear governance model

A governance model are the steps that determine when something is done, what good looks like and what to do when things go wrong. Without clear governance process (coupled with clear roles and responsibilities), you and your team will find themselves wasting a LOT of time chasing people, going around in circles and being batted from left to right trying to work out what to do and who to go to.

To avoid these headaches, make sure you have all your key stakeholders agreed on the governance model and if something slips you know how to escalate that to get it fixed

Who to speak to (Who deals with servers? Who are the application owners? Who deals with username/password creation?)
How is it done (what is the process? Multiple people/activities involved?)
What is the criteria (? What requirements for this request? What does ‘good’ look like?)
When will they deliver it by (Is there a timeframe? How long some a testing environment take to set up?)

Lack of process clarity

You effectively become a process expert yourself when you analyse a process thoroughly. If not, how will you be able to translate the business problem into a technical solution, in enough detail for the developer to build?

In automation, a Process definition document (PDD) is used to define clearly and unambiguously what the process, from your discussion with the subject matter expert(s) or process owner(s). When you understand exactly what the process looks like and what the improved solution looks like, then the developer should have everything in the PDD that they need.

Process documentation differ from what workers do in reality

It’s not advisable to rely on just the work instructions of a process or training manual because that’s probably been sitting there for years collecting dust and it’s not up to date. Most likely the team has found better ways of doing it, or they’ve need to change the process due to the systems being updated or the applications have been upgraded.

Process documentation is a great starting point but make sure you’re speaking with the team on what they do now, how it can be better and then co-design the solution.

Automation behaves differently in live environment to how it worked during testing

OK so your developer tested the automation, you thoroughly tested it again during user acceptance testing (UAT) and it worked perfectly ..but then when you launched it, your automation broke down, generated lots of exceptions or didn’t work as expected.

This it’s uncommon as development and testing environments can be slightly different to the real thing, even the data you used in testing might be slightly different, or the version of the application might be a newer version in the live environment.

As you can’t be 100% sure what will happen when you’ve launched your automation it’s important to have a “hypercare” phase, sometimes it’s called “warranty period” or “post go live support”. This allows your team to babysit your newly launched robot until you and the business are happy to let it go on it’s own

Lack of time and commitment from process owners and users

When you agreed upfront with team managers how much time and commitment you will likely need your process owners to dedicate to working with you on a project, it can ensure your project isn’t delayed by unavailable subject matter experts (SMEs), or your tempted to continue on a process which isn’t fully defined.

Automation delivery requires full understanding of the process that you’re automating in detail, and you can document that clearly and unambiguously. This is why the number one pitfall (and number one solution for success) is senior buy-in. Senior stakeholders can unlock the doors and make time for that person to commit time with you. Automation design and delivery is not a one-and-done thing, it’s a process which needs several sessions for defining, designing, and testing the solution. With a committed process expert, you have a better chance of getting it right first time.

Poor stakeholder awareness and understanding of technologies

With automation, your stakeholders are the business, they’re IT, they’re HR and Change management. All these teams will need to get to understand what this technology is, where they fit in and how it can benefit them. And from an informed position, they will have feedback on how this technology should be used.

Automation can’t be built in the dark corner of the business and be successfully rolled out, because once it’s launched, it just might not get used, or your program could be blocked and never see the light of day.

To get alignment and buy-in company-wide, run some awareness sessions, some one-to-ones, or/and host ‘lunch and learns’ to educate teams on what this technology is and how powerful it can be to help them in their day-to-day jobs, and progress the business as a whole.

Unrealistic expectation

Sometimes automation and technologies in general can be a little oversold, or at least misunderstood, so people may have the wrong understanding of what it can do and how fast it can do it. Automation is a powerful tool, it can take just a matter of few weeks to get set up and it is typically a lot lower cost option to software development in many cases, but it’s not a silver bullet.

Automating business processes does take sufficient upfront investment of time and commitment from staff to get solutions implemented, so it’s good practice to be clear on how long it’s most likely to take (E.g., up to 2hours a week spread over 6-8 weeks, or 3x 2hour workshops) and use a cost-benefits calculator to estimate the potential value the solution can deliver.

Choosing the wrong process

I wanted to leave this to last, as this is probably the number one pitfall that your team needs to stay away from. Choosing the wrong process is one of the most common reasons for automation failings and why projects stall. When a team works on a process that isn’t suitable for the technologies that they have, it’s too big, or if it’s too complex, it can stall the entire program as stakeholders loose faith.

Many experienced automation teams use complexity calculators to estimate how difficult a process would be to automate, and they use suitability checklists to filter out processes that aren’t suitable for different type of RPA and AI solutions.

Automation Experts Are in High Demand

Business leaders are finding it difficult to hire an automation expert for as the already huge shortage of experts in this space is only being worsened by the growing demand in the need for experts. The solution may be closer than you think – you can scale up your in-house automation programs by training and empowering your own staff.

Is training my own staff risky?

As a leader you may feel that relying on your existing staff to automate your processes is a risky approach, the common misconceptions are:

What if my team can’t deliver robust solutions?
What if the delivery is too slow?
What if a bot is built wrong, goes rouge and takes over?

Whilst these are all valid concerns, nothing compares to building hands on expertise and knowledge within your team and to overcome staff shortages. Hiring a small team of experts is expensive process, and large external teams require considerable on-boarding to get acquainted with stakeholders and business processes and culture. Empowering your staff to do it themselves in a repeatable and controlled way is only advantageous for your company, it can be much faster, and keep budget spend down. Lean IA has reduced implementing automation into 22 repeatable steps, so you can execute automation yourself like a pro.

Once you have a method for upskilling and empowering existing staff, you’ll be able to scale this methodology out to other teams and build your own network of automation hubs, or squads (small automation team), to deliver projects faster, all controlled by you centrally. RPA will have a huge impact on business.

It works. Companies such as Deloitte have implemented RPA software to scale up to the equivalent of the manual work of hundreds of people. In their third annual robotics survey Deloitte asked organisations to complete a survey on their RPA use, they received responses from over 400 companies with the combined value of over £1,500 billion which shows growing awareness of robotics.

Le Chair the author of a recently published Forrester report entitled, “the RPA Market Has Reached a Defining Moment,” said, the “emerging mix of RPAs, API development, and — especially — intelligent automation will challenge IT decision makers”.

What is the really holding us back?

The big problem isn’t the technology, its cultural restraints. It’s getting over common pitfalls and challenges. For businesses to grow they need to excel their processes and speed up their solutions which can only be done by building their automation teams. The solo band of a hybrid developer analyst expert will not be able to compete against an upskilled in-house team, this is why training your staff will be a huge benefit.

Frequently asked questions on training existing staff with minimal automation expertise

It’s too powerful to leave unchecked and up to staff, we would have no control.

This is where the industry is headed. Automation software itself is fast progressing towards “citizen developers”, where RPA software is so simple and straight forward that it’s intuitive. UiPath conducted a survey in 2021 that found 40% of employers increased their investment in automation. Just like how excel became something everyone could learn to use effectively in a short timeframe. It is possible for staff to become developers within a matter of weeks, and with the right controls their skills advanced as they move from simple to more complex processes to automate. It’s the same for delivery, brand-new automation delivery teams can effectively run projects following a step-by-step process.

The learning curve is slow for newbies

Yes, it can be. Newbies may make the same mistakes repeatedly, but the majority of these mistakes are due to a handful of missteps which can be broken down to 3 root causes. Even experts can make these mistakes if one of these 3 things are missing:

A repeatable execution process,
Uniform team training
A standardise toolkit

In reality not everything can be outsourced, staff need to be trained. Constructing a training framework with a controllable execution process which would allow you to uniformly train your team in under a month, with the use of a toolkit of templates and analysis tools for creating a robust intelligent automation strategy could help you speed up the process.

We have a 22-step process for enabling even newbies to execute like pros, here is a link to our eLearning portal which gives a complete upskill in the full automation lifecycle.

Will we save time and money by speeding up our delivery?

A slow delivery could end up wasting time and result in the need for experts to start again from scratch. It always takes a bit of time to get started with anything new, this is why having an expert on-site can really give your team a jumpstart and boost confidence. The number one thing that gets in the way of progress is not technology, is corporate culture and buy-in. Your existing staff will already have relationships with teams, know the processes, applications, and business processes. If you empower them with IA knowledge, they will turn into automation superheroes. The wider you cast knowledge of intelligent automation throughout your business the faster you can actually progress. The clearer your governance and roles and responsibilities are, the less wasted time going round in circles, chasing stakeholders and correcting mistakes by having to re-do work. Delivery becomes faster.

It’s a hard sell to get SLT to buy-in to an automation program led by an inexperienced team

This will change once you’ve onboarded staff by fast-tracked training. You can do this by acquiring a standardised toolkit with automation best practices built in, and by using tailored a repeatable execution process. Start with a small process to run through your governance model to demonstrate that you have complete control over automation activities. If you can actually deliver with a controlled repeatable process, you will be able to scale much faster than relying on a team of external experts. With these lower costs to scale (vs hiring larger external teams to scale) your team will be nimbler and boast much high Returns on investment. Larger external teams will eat into returns faster.

Is there a high risk for frequent mistakes and detrimental errors?

There may be a high risk for frequent mistakes and detrimental errors, technical debt and that no one in the team can QC check each other. A large majority of businesses have started doing this on their own but granted this gets them into hot water. What’s missing from new teams, and what separates them from professionals is just a handful of tools:

A repeatable framework (for running projects)
A clear governance model (so all team members knew their roles and responsibilities)
Quality checkpoints
Standardised templates (simple form filling to ensure correct data was captured)

What are the most common pitfalls at project level?

Whether you decided to train your existing staff, or hire external experts to do so, it’s advisable to look out for these pitfalls:

A lack of senior business leader buy-in
A lack of IT ownership and understanding
Missing or unavailable data
Staff’s resistance to change

We have discussed the most common issues found by introducing IA and following our 22 steps will help provide all of the solutions, it really is as simple as that.

New to RPA? Avoid These Top 5 RPA Mistakes

All across the country and from our network in other countries too, we’re observing businesses and teams new to RPA and automation making these same mistakes. Let’s dive straight in to see how these can be easily avoided

1) Lack of senior or business leader buy-in / RPA Strategy

Getting senior buy-in is the only way to get a successful RPA programme moving. During stakeholder engagements it’s vital to get top-down enthusiasm and demonstrate how RPA can enable their senior management teams to be more efficient and cost effective.

If senior management are fully on-board, they can remove blockers, deploy the right personnel to assist the RPA team to attend workshops, identify opportunities, and they can invest their limited funds in more RPA initiatives. If senior leaders believe in the technology, they will be more likely to redirect funds away from ‘tried-and-tested’ methods, such as recruitment or outsourcing, and start investing in this new and seemingly untested (in their area at least) technology.

2) Choosing the wrong process

Time and time again I’ve heard of companies or consulted with companies who were in the midst of trying to automate a complex, low-volume, highly volatile process as one of their first processes. Sometimes the process even requires several forms of AI.

This is a clear sign of “shiny object syndrome” (SOS), the propensity to chase something because it’s new and shiny and everyone else is doing it.

Or perhaps a case of “The one who shouts loudest” gets their process automated. At this point the RPA sponsor or senior needs to step in. New things can have great value, but there must be a logical approach to utilitising such a powerful tool.

Choosing the wrong process to start with is guaranteed to stall an automation programme. Stakeholders will lose interest, the RPA team will get disheartened, and the RPA sponsor will be wondering whether she will ever get a return on the investment and may consider pulling the plug on the whole thing. Such a toxic perception of this tool will swiftly destroy what you are trying to achieve. If you suspect you have started with the wrong process, this realization may mark the last chance you have to hire an experienced RPA analyst or success manager to turn things around and get the process back on track.

If you have just hired an expert and have yet to choose your process, it would be wise to listen to the expert to avoid choosing badly.

3) Lack of time/commitment from SME

Though buy-in from senior leadership gets things moving, the second hurdle is getting the managers and the team themselves excited and keen to get involved. This is potentially the hardest sell, as many may be totally content with the old way of doing things. Some may not feel comfortable with change in general, and the rest may quietly fear that this new technology could change their job or replace them.

Once team managers and SMEs are on board, the right expectations need to be set with them so they understand how much time the RPA team requires from them in order to design the right solution, to the necessary detail. If expectations are not clear upfront, staff and managers may grow frustrated with intermittent disruptions to business as usual. It’s important that they understand how the discovery and implementation process works, and the RPA team needs to clearly layout their method, and explain that it’s not a one-and-done event, but a staged process.

4) Poor stakeholder education and communications

Doing RPA in a dark corner of the office leads to staff thinking the worst. Openness and visibility is best; take them on the journey with you. At a minimum, an easy way to stay visible is to create a newsletter and an online portal with information on the technology, the process and a discussion forum for questions and concerns.

In addition to the visibility provided by open-door policy and regular lunch-and-learns or periodic workshops, the Centre of Excellence should stay in communication with staff. Popping up and disrupting teams for a few days, then disappearing without results can be very irritating. Stakeholders in a few organizations I’ve worked with have expressed their frustrations about previous RPA teams who attempted to implement but were shut down or moved on to a different team without any explanation. Understandably when I came to launch the RPA properly I was initially meet by reservations and reluctance. Even if your RPA team needs to close down an initiative, its courtesy to inform the team as to why, so that the relationship ends on good terms and they are welcoming the next time you circle back.

5) Not streamlining process first

There are two schools of thought in RPA. Roll out automation fast leaving the processes as it is because it will immediately impact the bottom line. Or optimize a process first with lean thinking so that the process is redesigned to be streamlined and is designed for a robot instead of a human. At Lean IA, you can surely guess which one we prefer. Garbage in, garbage out.

Optimising a process can provide a much faster payback period as costs may be lower because the process may be designed to be simpler. Imagine a process where the human goes back and forth to pull data from one application into another. This workflow is long winded as the human has limited memory, whereas the process could be redesigned for the robot to take all the information from the whole page, then paste it into the other page in one go, thus eliminating the old back-and-forth way.

Developer working on code late at night, view from the back

The 5 key mistakes of Automation & AI

…that are causing teams 99 problems to digitally transform

“Transformation is a process, not an event” – John Kotter

If you’ve been involved with change management you most likely would have heard these words – which are from the world-renowned change management and business thought-leader John Kotter, and he’s written several books on the subject such as his New York best seller “Our Iceberg is melting”. The essence of his message and approach to change still runs true in this new digital age

—–RISE OF THE MACHINES ——

With the tech trends of the last few years suddenly accelerated by recent global events – it will become increasingly difficult to direct teams and strategize as the world becomes more digitally reliant, without technological awareness steering the ship.

As technology begins to infiltrate every industry, market sector and every job, CIOs, as a Mckinsey article put it, need to “move from being a functional to a strategic business leader”. If a company does not have a CIO, the non-techie business leaders (no matter the industry) need to become more tech-savvy to navigate in the new technology age to leverage cutting-edge tech and create value.

There are common traps that business leaders who are new to automation technology fall prey to. These surprisingly common pitfalls and mistakes end up causing an array of consequential problems and challenges down the line – so I’d like to address this at the root from which most or all problems and pitfalls stem from

—————– Digital workers, not software ——————

But firstly, robotic process automation (RPA) is functionally quite different to traditional software changes – RPA is strongly business led (mainly by the COO and the operations team). The reason lies in the history of RPA which was designed to put power in the hands of the business and alleviate pressure for the IT department. RPA allowed the business (with expert guidance and support) to implement solutions and navigate technical roadblocks of old legacy systems faster, in a couple weeks or months, rather than waiting on cumbersome technical changes which could take years.

The other difference is that RPA is used in a very new way to other software, because effectively RPA ‘robots’ are virtual workers who do specific menial tasks – repetitive and mundane processes like copy-and-pasting customer data from one system to the next, or processing invoices.

SO, WHAT ACTUALLY IS RPA —————–

RPA is a software platform, alike a virtual worker, that can mimic any menial and repetitive tasks your staff do on their computer, as long as the process has a logic workflow, with rules-based decisions and it doesn’t require human intuition.

So no matter what type of business or industry you are in, if you have staff doing repetitive tasks, this is a waste of their time and intellect, and waste of your money – as an RPA virtual worker, costs one tenth the cost of a full time employee, doesn’t take breaks and can work 24/7,365

Intelligent automation (IA) combines automation tools like RPA with Artificial Intelligence to further enhance the scope of what your virtual workers can do, be that; reading emails, extracting information from scanned invoices or forms, or even replying to customers via a chatbot

This suite of powerful technologies can save vast amounts of time on menial tasks and unlock six, seven or even eight figure financial savings annually from your business, whilst also increasing speed, throughput, accuracy of service and improving compliance and customer and employee satisfaction.

Many business leaders in industries not yet on the forefront of automation do not feel that this is right for their business and this is fair to think this, as vendors have focused mainly on Finance, Manufacturing and Insurance industries. However currently about 50% of businesses have started to use RPA, though it is forecasted that by 2025 97% of all businesses will be taking advantage of this modern technology.

Further exploration on how businesses can get started with automation is covered in another article, however I’d like to draw your attention to one data point:

“50% of all investments in RPA (and AI) fail”

This is a concerning reality I have been investigating for several years now, as almost all businesses in a few short years will be utilizing automation and AI, but only 50% of their projects will succeed – so let’s take a look at common reasons for this

1. Lack of senior business leader tech-awareness

Where senior leadership teams are not fully aware of or can’t articulate what process automation is, it can be difficult for these innovative leaders to get their peers or seniors bought in. Furthermore, it becomes even more of a challenge to fit this into the corporate strategy and develop a roadmap for rolling this out enterprise wide

Leadership teams that have a good and aligned understand of how robotic process automation and artificial intelligence (aka intelligent automation) should be used to transform the business and build centre of excellence teams to govern this will led in their market. Most businesses know that they need automation, AI, a chatbot and other buzz words to modernise, but not every leader truly understands how to leverage these in practice

2. Matching wrong technology to use case

“Easy when you know how”

Choosing the wrong process for RPA or AI is by far the most common mistake we see businesses make in every industry, and it becomes an expensive PROBLEM, both in money, time and patience. Furthermore, it can result in projects being shut down, and then reopened a year later under new management. There’s also the cost of hiring external consultants to fix the issues and help teams unlearn bad habits – as well as re-gaining commitment from frustrated stakeholders

Identifying automation suitable processes is really quite straightforward when you have a tried and tested method for identifying, assessing and implementing processes. Having a data-backed approach and mechanism is a logical challenge against certain politics and influences and ‘teams who shouts the loudest’. It’s a challenge I’ve come up against many times however by using business data and a scientific approach, it was much easier to persuade stakeholders on the best course of action

3. Poor stakeholder education and communications

“Your most valuable assets – your staff”

Implementing process automation to save hours and days of menial tasks from your employees working lives may sounds good financially, but actually can sound very daunting to employees, as it can stinks of replacement and redundancy. Poor (or lack of) communication from the business is the reason for what is by far the biggest cause of RPA and AI project failure and delays – staff resistance to change

Staff need to be empowered with the know-how and the understanding that technology as always is here to augment our work so we are more productive. Teams need to be shown that the benefits of automation means less late nights trying to meet deadline, better job satisfaction due to doing more creative and human-to-human work instead of tedious, repetitive, mind-numbing tasks.

Granted, it would be naïve to believe that no staff member will become redundant or lose their jobs. As an analyst for many years, I have repeatedly heard that analyst roles were most likely to go as they were highly logic and methodical– perfect for automation

However, for societies and businesses to advance, old jobs (just like old business models) that no longer work will need to be modified/evolve to those that do. And having a training plan for employees serves everyone two fold.

1 – employees are upskilled and trained to do their job in a new way or do newly created jobs, or staff are re-deployed into different teams that are growing

2 – employees leave companies and enter the marketplace newly skilled to be repositioned into a faster growing industry

4. Lack of time and commitment from SMEs

“Making automation a corporate priority”

Stakeholders of RPA projects generally have unrealistic expectations as they believe implementing automation is a lot faster and simpler – but unless they’ve been made aware, they wouldn’t know what actually goes into automating a process.

Process owners and subject matter experts are who automation teams interact with the most to identify the problems, design, build and test the solutions. As they play such a central role it’s imperative that they and especially their managers understand at a high level the general process for delivering automation, as the project will literally live or die with them. They hold the knowledge of the process, the have the access to the process data.

What I’ve witnessed and heard from peers is that team managers (either un-informed or resistant to change) will dedicate an hour or two of one or two SMEs initially but then re-deploy them back into Business-as-usual work and have limited availability and put it as low priority going forward – again RPA is a fairly new concept and stakeholders must be shown that these changes is a process, not an event

5. Not streamlining process first

“Garbage in, garbage out”

There seem to be two schools of thought in RPA. Roll out automation quickly, leaving the processes as it is. This immediately positively impacts the bottom line with financial savings. However, re-engineering a process to optimise it first doesn’t speed up a bad system (which could put immense strain on bottleneck or result in an unstable robot), but provides a better return on investment and gives you a more robust bot due to a simpler process

Lean thinking is a great combination to RPA and AI, as many companies are starting to form Lean teams in tandem with their RPA team.

These 5 key mistakes cause hundreds of problems and can be boiled down to these 3

Businesses failed to transform their automation plan because:

1. They didn’t know how to get started and couldn’t build momentum

2. They had technology skills gaps throughout their core and stakeholder teams

3. They didn’t have a clear plan which showed how automation would be rolled out or how help achieve various corporate objectives

Problem 1: Can’t start, No momentum:

Why couldn’t teams get started? Because they didn’t create a repeatable formula

Why didn’t create a repeatable formula? Because they didn’t have a tried and tested framework to use

Problem 2: Technology Skills gaps:

Why did these companies have skills gaps? Because they didn’t educate their core delivery team and stakeholder teams uniformly.

Why didn’t they educate their team? Because they didn’t have a comprehensive training plan

Problem 3: No Plan, Can’t scale.

Why didn’t they have a clear enterprise plan for RPA? Because they didn’t have an automation strategy

Why didn’t they have a strategy? Because they didn’t have a scientific approach to build a data-backed automation strategy

We believe that in this new age, business leaders who empower their workforce to augment themselves and keep discovering new technology will achieve full digital transformation. Our training package is developing automation professionals to solve their team’s root causes and overcome common problems.

HR: Working alongside your digital workforce

Did you know, implementing process automation is a lot closer to onboarding new staff than deploying an IT systems upgrade?

Tasks for on-boarding a robot/digital worker:

· Setting up user IDs and credentials

· Assigning the correct access and authority levels

· ‘Training’ on the process and business rules

· Assigning a manager for each automated process

· Telling robots whom to notify of any issues

· Monitoring performance and escalating concerns

“By 2025 97% of businesses will be using robotic process automation (RPA)”

With the majority of businesses on-boarding new digital workers in just a few short years, how staff should work alongside ‘robots’ may become the number one question for HR and management. IT and operations teams have been the main focus for assisting with the adoption of automation, but, as mentioned in our book Business @ the Speed of Bots, HR has been neglected …but should this now be the focus?

Staff, no matter if they have a technical or non-technical role will feel nervous with the thought of having digital colleagues. However, HR needs to work closely with the Automation Centre of Excellence (CoE) team to ease anxieties felt company-wide and be a key player in showing staff how to embrace digital transformation for their own benefit, creating a culture shift.

If you’re not too familiar with RPA, it’s a powerful and versatile tool to automate monotonous and repetitive tasks, so that staff teams can become more productive by spending more time working on value-added tasks. But have you ever wondered why 50% of RPA and AI projects fail, and why less than 5% of businesses succeeded to scale this capability?

– one theory suggested that building the technology isn’t the issue, the struggle lies in educating the business on new technology so that they can effectively lead this initiative, instead of resisting it

RPA presents many new challenges for HR:

· Helping to source the right experts to develop teams in house

· Addressing concerns of employees who view RPA as scary robots, rather than enablement tools

· A new method of automating monotonous tasks vs the old way of outsourcing these overseas

· Creating and revising job descriptions and providing new training

· Restructuring progression paths as new positions and new business services are created as a result of automation.

Developing in-house vs outsourcing automation?

Up until now, businesses have turned to vendors for guidance, however, RPA and AI software vendors specialise in how to build automation and design architecture, however, it is the consultancies that specialise in working with clients to get value from it. Maybe what is missing is a transfer of knowledge to empower staff teams to support the roll-out of the technology.

For example, an accountant wouldn’t ask their preferred spreadsheet provider how to get the most out of the technology. With the correct guidance and understanding from a spreadsheet expert, the accountant would be best placed to answer that question themself

Scary robots or powerful enablement tools?

If you’ve not seen that powerful film Hidden Figures, it’s about ‘the Computers’ (a team of female mathematicians that worked at NASA to manually do research, analysis and testing). When they had recently discovered that Nasa had bought the IBM 7090, the character Dorothy Vaughan said:

“Oh, it’ll run eventually, and when it does, we have to know how to program it.”

This quote really stood out for me as it seems quite apt for this new digital age. Developing and empowering staff to better understand how to use and work with these new technologies is key for a business to transform.

A study mentioned in Business Wire showed that 70% of businesses believe RPA allows employees to have more human interaction. Keeping employees engaged, productive and happy at work is to succeed at digital transformation. The study also mentioned how 60% said RPA helps people focus on more meaningful, strategic tasks. Yet another survey carried out by TechnoJobs shows that 43% of those questioned expected that over the next 24 months, they expect automation to have the greatest impact on customer service and order-processing functions

Managing teams augmented with the Automation.

Just like when working with colleagues, staff teams need to understand how to communicate with digital workers, and managers will need to know how to manage their digital workforce.

Staff will need to know:

o How work should be assigned to robots or passed on to robots to complete a process

o When robots have finished the tasks or whether the robots completed the work correctly or not

o How to track performance of robots and who the robots should report issues and errors too

o What new targets need to be set for teams, now that they are faster, more productive and are outperforming their previous targets

New roles that intelligent automation (IA) will create.

Automation will inevitably change the structure and responsibilities of all of our roles, be that if you’re working in an operations team or even if you work in the automation team itself. High volume, monotonous and repetitive tasks will be handed over to digital workers and most likely replaced with newer more intellectual, and subjective tasks. Be that more human-to-human tasks, like problem-solving, research and analysis, or customer service tasks.

New automation-related jobs or responsibilities will inevitably emerge such as roles that monitor digital co-worker performance, assess new opportunities for process improvement, or even migrating existing Analysts, Project Managers, or technical staff into the businesses core RPA/Automation team

“Digital transformation is human at heart “

These are the words of a sticker that I have on my laptop, and it’s a truth that I’m reminded of every time I sit at my desk. Automation isn’t an IT or Change team thing, it’s an anyone thing – It’s business-led, supported by IT, guided by the Centre of Excellence, but the solutions are designed (and owned) by the staff teams

One of the most sobering statistics that I’ve seen in most recent years regarding technology trends was in a McKinsey Global Institute report, which estimated that by 2030, automation will drive 75 to 375 million people to reskill and even change occupation. To look at this another way, the RPA job market will be flooded with ‘new blood’ looking to get into the RPA/automation field. This massive influx of inexperienced RPA staff could push the RPA failure rate above its current 50% mark.

It might be worthwhile to keep your existing staff who have the experience and knowledge of your clients and processes, along with existing relationships with your staff and train them in RPA delivery. With a little help from expert boutique consultancies to mentor and guide your in-house team to execute RPA projects successfully, your company can quickly become self-reliant and quite possibly more successful than fully outsourcing your Centre of Excellence indefinitely.

Where to go from here? Apply ‘AEIO YOU’ to your business:

· Awareness should start at the top, and so should alignment. Digital transformation works best in organisations where seniors stakeholders are all bought in and aligned on how best to use the technology

· Businesses that educate and empower their staff in identifying the right use cases for the array of intelligent automation technologies are able to find opportunities quickly and scale faster

· A business that has a logical, data-backed method will identify high ROI opportunities and by involving staff in the ideation stage will make it easier for staff to work alongside robots once they are launched

· Businesses should build automation solutions on a lean and optimised process, using the best practices of their chosen providers, where that’s RPA, intelligent automation or a new form of AI

· Measuring results is vital, RPA projects should yield financial and non-financial results that benefit staff (and of course the business and the customers). Perhaps there was enhanced staff satisfaction from fewer late nights, a morale boost from a high Net Promoter Score due to faster service and fewer errors, or less management pressure as a result of achieving ambitious objectives.

· A company that has an organised automation team and clear control and oversight of the digital workforce will ensure benefits are maintained

· And a company that continually uncovered newer technologies to enhance their existing automated solutions, and upskills their staff, will inevitably achieve full digital transformation

What is Intelligent Automation (IA)?

Digital transformation in the workplace is being hailed as the fourth industrial revolution, and changing how business add value,. So embracing it now could be the key to success for your business. You may have heard key terms such as Intelligent Automation (IA), Artificial Intelligence (AI), and Robotic Process Automation (RPA) which is the backbone of digital transformation, but if you are unsure of how they could impact your career, do not worry these concepts are not as complex as they sound, and we will break them down into simpler terms for your understanding. With change comes uncertainty, and a natural fear of job loss, but at the same time there is also ample opportunity in leveraging IA and RPA to enhance and develop your career. It’s a lot easier than you think, read on to learn more.

What is Robotic Process Automation (RPA)

In simple terms, RPA is low-code software that can be programmed to record a simple process and then can repeat that process over and over again. RPA is the number one, fastest growing technology in the digital transformation space. If used correctly it can be implemented to save time and money.

How can RPA be put into practice?

Simple, for example if you use a macro on excel, you can record a few steps of the process you follow and then press play to see that same process run in a loop until it’s completed the list of items you’ve set. You can even edit the underlying code or build the process from scratch; the RPA process is pretty much this but faster and more sophisticated. As long as the steps are logical, and do not require intuition or judgement, RPA can be used on any combination of desktop applications, web applications and websites, the options are limitless.

RPA is more similar to an automated person than a piece of software as it uses the user interface just like you and I would, by clicking on things like buttons and links, and typing as if it was using the keyboard. It’s almost like training a new hire to conduct specific repetitive tasks such as:

· Copy and pasting data from one system to the next.

· Entering data into an application from a spreadsheet.

· Updating financial information from an invoice.

These are just some examples of what can be done with Robotic Process Automation. It’s almost like outsourcing simpler tasks to a virtual assistant that will save you time and allow you to focus on more complex tasks which require your input and decision making, the more creative work.

Where did RPA come from?

The concept of RPA (the use of macros, screen-scrapping and recording) has been around since the 90’s, however a software company called Blue Prism launched a more user-friendly product called “Automate” in 2003.

When talking about Blue Prism shaping IA today, the SVP of Blue Prism Danny Major has said, “Intelligent automation is fundamentally changing how businesses reimagine ways of working with a unified workforce, digital first, people enriched. We’re ready to assist business leaders by bringing our understanding of intelligent automation tools and giving them the capabilities and insight they need to help it become the foundational operating system in the enterprise.”

This is when RPA began to gain popularity, it came about for two reasons:

· When overseas labour costs were rising, and businesses needed to reduce costs.

· Companies became overly data hungry and demanded more tech to keep up with rising customer demands for faster services, more ways to purchase things, and improved customer service and experiences.

In reality it was difficult for tech departments to keep up with the demands, this is when RPA become a faster solution to solve technical issues in a matter of months or even weeks.

Process automation can be seen as the backbone of digital transformation to modern businesses with slow process and clunky ancient applications, or make even fairly modern business operate a lot faster and smoother by:

· Reducing queues

· Reducing errors

· Save time on simple tasks so staff can spend more time on customer service

· A better understanding of what was going on in the backend of the business

· Achieving a better work life balance and a better user experience

How can you outline an RPA process?

If you can draw out each step of a process and a simple guide on how each decision can be made (without human input) then this process could be automated by a robot. A simple example would be:

1. Click on Google Chrome icon

2. Type Yahoo Finance web address

3. Type stock name on excel (APPL)

4. Then you can create decision:

a. If price is down – click buy

b. If price up – click sell

5. Close down Google Chrome

Will bots replace us and take our jobs?

No one wants to feel like their job may be at risk, but with the development of new technology there will always understandably be a fear of job loss. Those who do not fully understand RPA and AI may also feel this way, but if you examine the possible implementations of this technology, you will quickly come to realise that it should be celebrated and not feared. The aim of PRA is to reduce the amount of time spent on mundane, repetitive tasks to free up time for more intellectually stimulating and satisfying work, leading to a more purposeful role, ‘Automation should take the robot out of the human’.

Despite the scare mongering online, AI is miles away from being smart enough to replace humans and new technologies tend to create more jobs (look at personal computers, internet, mobile phones). They create new industries, new jobs, or new ways of working. It is an evolution, and there will of course be jobs that are replaced, but smart companies are upskilling staff on how to use automation to do more. We often see the loss of knowledge and skillsets when staff leave the company, and new staff have to be trained to replace them, but some of this may now be automated. Automation typically opens new avenues to meet customer needs and allows us to focus more on interesting and creative work. The real value of a business is and always will be in its staff.

How can I learn more about RPA?

Automation and AI has helped to significantly improve our lives over the past few years in ways you might not even realise, from saving us time to narrowing down the number of choices we have to suit our personal characteristics. The algorithms used for Siri, Alexa, and Uber are all based on AI, and even the algorithm on Netflix which suggests recommendations of what to watch next, that saves us hours of time scrolling to find something we’d like to watch. There are many ways you can use PRA and IA to improve your business too, and it’s not as difficult as you may think.

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