The 7 things successful automation teams do to scale

By 2030, automation will drive 75 to 375 million people to reskill and even
change occupation – do you agree it’s time to upskill your workforce?

By 2025 97% of business will have started using Automation

By 2030, automation will drive 75 to 375 million people to reskill and even change occupation – do you agree it’s time to upskill your workforce on how to adapt and adopt these new technologies?

Over the last 5+ years we’ve communicated regularly with our international Automation and AI network, we’ve also observed, interviewed, worked with, worked for, shaped, trained, learnt from and researched teams globally in Europe, US, India, Hong Kong, China and the UK

We’ve extensively researched the automation industry and seen it evolve from when Robotic Process Automation (RPA) was brand new in the mainstream in 2017, to how it has become intelligent automation. Our research has been focused on two metrics that have remained unchanged all this time, globally! We asked:

Why do 50% of all RPA and AI projects fail?

What were they doing right, what was everyone else (even big companies and large automation teams) doing wrong? We started to see patterns, repeating cause-and-effect situations and coming from a Lean-Six Sigma world, the instinct was to understand the root-cause.

Why do less than 5% of businesses succeed at scaling automation?

We discovered that each automation team or business had their unique (and sometimes not-so-unique) issues and problems, but they all tended to stem from an array of similar challenges that they had all come up against (see the Top 7 challenges RPA teams will face). After reviews and tracing we identified that most of these challenges could be traced back to a handful of mistakes that had been made and in turn we were finally able to boil these down to just THREE root causes (see the 5 key mistakes of automation and AI).

These 3 reasons seemed to be the cause of all the issues and problems that was causing all these Automation teams to not get value and fail at scaling their automation!


By understanding these root causes and mistakes, we were able to notice the patterns of what successful teams were doing and time and time again saw SEVEN themes in successful teams, and saw a lack of these 7 things in struggling teams.

Here are the 7 things that successful automation teams do to roll out automation at speed and at scale which we put into the acroymn: A. E. I. O. Y. O. U. and the AEIO YOU methodology which we have explained in our book Business @ the Speed of Bots (the AEIO YOU method)

The AEIO YOU methodology

Based on the 7 things successful automation teams do, AEIO YOU is a unique blend of Lean Thinking, Change Management, Intelligent Automation best practices to maximise ROI.

This 7-stage process (and its 36 repeatable steps) can be used to adopt and roll out new cutting-edge technologies across an entire business, to improve Automation project success (current industry success rate is 50%). This methodology ‘changes how we change’ with technology so that the entire company is involved and comes along the digital transformation journey, vs having change ‘enforced’ on them


this is the Awareness and alignment stage, where a company becomes aware of the new technology from a senior level and learn about how this capability fits into the overall strategy. However, an important step sometimes missed in organisations is to also make staff teams aware of the technology, how it will help them personally as well as has the business will be strengthened.

This is also the stage which aligns the different key business areas to agree on how to use this technology, how this new capability will be governed (in a centre of excellence) and where this CoE will sit (e.g. in operations, IT or perhaps in the business change department.


Once a Automation roadmap and operating model has been established for the RPA CoE team, the staff should be educated in the new ways of working. This is your core RPA/Automation team, Automation Champions and staff who will be helping with the automation. They should also be educated in their part in the CoE, what is expected of them, how to use tools and techniques

Coupled with this, is the provision of standardised tools from the CoE to empower core CoE staff and stakeholders to be part of the digital transformation. This will ensure that your teams produce successful results in their automation projects repeatedly


This is the application of tools and training to identify and accurately assess opportunities. This is also where your teams follow strict guidelines to design (ideate) the right solutions


This stage in the implicating of the optimised solution, be that RPA, intelligent automation or a lean intelligent automation


This is a way to measure return on investment or yield and prove the benefits were realised as predicted


This stage focused on the support side. As your virtual workforce grows you will need to re-organise and develop your support team with role profiles and procedures which were needs when your bot factory was small, so that you can better oversee your bots.


This final stage is a reflection of the first and second stages, where you become discover of new technology, upskill your team to match the new technology, and upgrade your automated processes which AI

Tony writes for the Digital Transformation network, educating businesses in using new cutting-edge technologies.

To learn more about using Process automation and other technologies, check out the AEIO YOU® Portal, a one-stop centre of excellence enablement platform for getting value from RPA and IA – speak to your local AEIO YOU® partner to learn more

Robot doing repeatable tasks with a lot of folders and magnifier. Robotic process automation, service robots profit, automated processing concept. Pinkish coral bluevector isolated illustration

RPA’s biggest myth is also our biggest concern

“Bots will take all our jobs.”

Job loss is by far the biggest fear in companies to date. Understandably no one wants to feel like their job is at risk; I had even read in the news how analysts were the most at risk as their roles were highly logical and data driven. As an analyst myself this was a delight to hear. When your RPA team start going into different departments to find automation opportunities fear of job loss is the biggest challenge they will face. It’s a very sensitive topic which needs to be handled carefully, otherwise it can stifle any momentum you were hoping to build.

Change management is vital to ensure the right messages are communicated but businesses need to be thinking about how their staff (their most value assets) can be upskilled and look at redesigning career roles and paths to align with digital transformation.

Bots should be seen as enablers to a workforce not substitutes because human workforce’s experience and intellect is too valuable to lose. In many circumstances RPA has seen an increase in jobs as teams become more productive and cause companies to grow. New technologies always give rise to new types of jobs. Bots can remove the burden of tasks from the workforce, but this gives businesses the opportunity to upskill their staff – by attending specialist courses. I once heard the phrase that ‘RPA should take the robot out of the human’ so that the human can do more interesting and creative work.

There’s a lot of scaremongering about a Terminator-style uprising where Ai becomes as smart as, if not smarter than humans and takes over. There was even a recent debate (August 2019) where Jack Ma and Elon Musk debated the benefits or threats of Ai becoming smarter than humans.

Whatever the theories about what Ai could achieve, what we know now is that Ai is miles away from being smart enough to replace humans. Yes in March 2018, an Ai system was able to read handwriting faster and more accurately that humans could, and for other specific tasks (like playing chess or Go), Ai can out performance humans. Ai can even understand natural language, it can learn, and it can recognize images, but it still is a fair way from replicating human intuition and reasoning and having general intelligence.

Many leaders in technology believe we are already effectively Cyborgs, fully dependent on our technology. Your mobile phone is pretty much a prosthesis as many of us could not exist without it for more than a few waking hours. However, technology has always been an enabler, now allowing us to move through life at lightning speed compared to 30 years ago.

Intelligent automation and Ai bots are no different. They are virtual assistants and digital workers that improve staff productivity and enhance their careers. These intelligent bots are owned by their team (not by IT) to do the lower straightforward work, leaving the higher-level thinking to us humans. Bots are there to enhance our efficiency and effectiveness, not replace it.

However, as business leaders, an important stat you need to be aware of is that when companies introduce RPA about 65% of staff feel their roles are in danger. Like a cancer this can be harmful to your organization as fears spread to two thirds of your staff. If your company is serious about its digital transformation, it’s imperative that you engage with HR and address emotional resistance so what your most valuable assets feel valued.

Granted, RPA will remove the need for a many jobs and reduce the size of teams, as it allows individuals to become more productive. Where a job had required ten people to manage the volume of work, augmented with RPA, it would now only require 7.

So, the big ethical question is, what happens to the other 3?

This seemed to be the most sensitive and generally most avoided question in the media, though of late I’ve seen it become more talked about as technology advances and automation becomes more ubiquitous. Understandably every business has a natural attrition rate, due to performance, retirement or people moving on to other careers. However, businesses should have a plan for how to redeploy their top resource if possible.

  • Can they be re-deployed to another team that would otherwise need to hire external staff?
  • Will the company itself expand its workforce in the near future, and thus does it make more sense to keep these staff who already know the business, customers and processes?
  • Can we upskill them so they can move into a more technical role to support the new digital workforce?

As a responsible RPA leader, now is the time to start engaging with HR to review the re-structuring of employee progression paths in line with these new automation capabilities. This not only will mitigate fears of change and job loss spreading through your organization, but will also keep knowledge in-house

Perhaps a new way to answer this question could be; where a job had required ten people to manage the volume of work, augmented with RPA, the same team of 10 can now do the job of 14 in your ever-expanding business. Re-deploy, upskill, grow

You can learn more about implementing RPA (Robotic Process Automation) and intelligent automation at The virtual consultant. Online support 24/7

You can read about Lean IA’s trademarked AEIO YOU method in their new book Business @ the Speed of Bots, Succeeding In The New Age Of Digital Transformation


Overcoming the 5 key mistakes and 3 root causes of Automation and 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 of 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, as I hope to show you today


With the tech trends of the last few years suddenly accelerated by recent global events –  it is becoming 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 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 – firstly because 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.


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 customer via a chatbot

This suit 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 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 or 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 team 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 logic 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 – 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 b 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 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:
1- Why couldn’t teams get started?

Because they didn’t create a repeatable formula

2- Why didn’t create a repeatable formula?

Because they didn’t have a tried and tested framework to use

Problem 2: Technology Skills gaps:
1- Why did these companies have skills gaps?

Because they didn’t educate their core delivery team and stakeholder teams uniformly.

2- Why didn’t they educate their team?

Because they didn’t have a comprehensive training plan

Problem 3: No Plan, Can’t scale.
1- Why didn’t they have a clear enterprise plan for RPA?

Because they didn’t have an automation strategy

2- 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 helping businesses solve these root causes and overcome common problems.

You can contact LeanIA to request a seat on their webinar series “Leaner, Faster, Agile” to discover what you’ve been missing out on.


Are you an Early adopter?

This adoption curve (a.k.a. the Rogers’ bell curve) shows the general distribution of when people and businesses start to adopt a new technology. Change and the unknown is scary to humans, and so when something is brand new, be that a new technology or a new way of doing something, understandably very few people or businesses want to be the first to trial it.

The Innovators are the brave first few. They are probably those in the inner circle, or close enough to the new technology to appreciate it. They may be more educated in the new concept that then rest of the people. Generally, they are pioneering-risk takers with a passion for exploration

The Early Adopters are courageous and daring with a great eye for spotting the beginning of a winning trend. They are keen to stay on the cutting edge so they know when a new approach is starting to gain traction and they can capitalize on the potential upswing.

The Early Majority is pretty much everyone else who can really benefit from the new idea, the rest of the target market. They still can get an advantage over the remaining 50% of the population who have yet to discover it

The Late Majority are slow behemoth organizations that only move because their institutional investors are peering intently over their shoulder. By this time, they feel more at risk not to be involved, as they may get left behind, or may already be behind. Or perhaps they are smaller companies with not enough resources to research market changes and may have only caught wind of the new technology from observing a competitor.

The Laggards are frankly the are the old-fashioned, stuck-in-their-ways companies, who refuse to move, they believe their old way will prevail. Think Blockbuster.

If you’ve never even heard the phrase RPA or Robotic Process Automation, you’re way behind many of your competitors.

It’s a sobering thought – especially if you’re in manufacturing, banking, insurance, healthcare or utilities (these were RPA’s earliest adopters). You’re even further behind if your company has lots of manually intensive processes, with a business model that is no longer scalable. Tell-tale signs are high attrition rates, highly frustrated employees, poor customer service, or large backlogs of back-office work which may be why you’re hemorrhaging clients and money.

However, if your company has started investing in RPA technology to automate your processes, this is great news! Your company can see the massive potential of getting a competitive advantage. As of this publication (2019) you’re probably at the latter end of the Early Majority phase. If you’re also leveraging Artificial intelligence (such as Intelligent Character Recognition, Machine Learning or Intelligent Chatbots), then you’re certainly in the Early Adopter camp, as your competitors will probably give it another 6–18 months to make this step.

Now it’s time to scale your automation and create a Centre of Excellence team

You can learn more about implementing RPA (Robotic Process Automation) and intelligent automation at The virtual consultant

You can read about Lean IA’s trademarked AEIO YOU method in their new book Business @ the Speed of Bots, How to implement RPA that scales


How to quickly identify your RPA team’s strengths and weaknesses

When you’re in the mists of ‘doing automation’ it is sometimes hard to find the time to take a speak back and understand what is and isn’t working in your RPA delivery. Make projects have stalled, staff aren’t as engaged anymore, or key stakeholders are looking elsewhere to invest their budget to save time and money, like in outsourcing.

I can’t now remember which business psychology book I had read this, however an important point it made was that you can’t perform whilst you’re in a learning phase and you can’t learn when you’re in a performing stage. This is why in our AEIO YOU methodology, reflection is a keep step in RPA delivery.

You can’t perform whilst you’re in a learning phase, and you can’t learn when you’re in performing stage

I’ve seen many teams that have processes and frameworks set up and keep running and hitting a brick wall, repeating this action each time, hoping the wall may eventually break (though you may run out of money due to minimal results before that happens).

So, here are a handful of questions to ask your self, your business and your team at each stage of the AEIO YOU method to help you identify where you may have potential areas of improvement in your RPA team and implementation process, which may encourage finding a new method that fits your situation

A: Aware & Align

Are YOU Aware?

It’s vitally important to win hearts and minds by being visible and taking key stakeholders along with you through the transformation journey.

  1. Can you and your RPA team clearly articulate in a sentence or two what RPA and intelligent automation is?
  2. Do senior managers in Operations, IT and HR understand how RPA and intelligent automation can impact and benefit their teams and departments?
  3. Do directors and C-levels understand how RPA and intelligent automation can fit into the organisation’s strategy? And do they have congruent realistic expectations?
  4. Do team leaders and staff members understand how RPA and intelligent automation can enhance their performance, productivity and job satisfaction?
  5. Do your RPA and Intelligent Automation Centre of Excellence and Operational Excellence teams understand the various myths and challenges as mentioned, and are they aware of how to avoid common pitfalls?

Otherwise can you combine several RPA hubs or centralise resources, tools, and knowledge so you can learn and improve faster?

  1. Are all RPA opportunities identified, assessed, and measured in the same way?
  2. Do all developers and support engineers work to the same coding standards?
  3. Do you have a standard tool kit, including checkpoint criteria and templates for each stage of automation lifecycle?

E: Educate & Empower 

Are they educated?

Test whether your Centre of Excellence (CoE) team has educated your entire staff:

  1. Can key stakeholders and staff involved in RPA projects clearly explain what RPA is, and what the benefits are at a business, department, and individual level?
  2. Have you connected with HR to educate them on the emotional impact of digital transformation with regards to new career paths and incentive structures?
  3. Has everyone in the teams you’ve targeted for automation attended at least one lunch & learn session or workshop?
  4. Do teams understand what the eight types of waste are?
  5. Do team managers understand what metrics must/should be collected to assess a process’s performance and suitability for RPA?
  6. Does your CoE have its own intranet portal with information, shareable material, and a forum for requests and questions?

Do they feel empowered?

Verify that your CoE is providing the tools, templates, guidance, and training need to accelerate your digital transformation strategy:

  1. Has each team interested in RPA been given an automation catalogue template and guidance?
  2. Is the CoE having regular communication with teams who are pursuing RPA to ensure they are using the right tools, and using them in the right way?
  3. Has the CoE received any positive feedback or interest from staff keen to learn more about the technology or take on more responsibility to assist in identifying and assessing opportunities?
  4. Has HR communicated that the CoE may provide new roles in the near future?

 I: Inspect & Ideate

Inspect: Have you identified and prioritised opportunities?

Review these questions below to confirm that your team has prioritized your automation candidates in a logical way:

  1. Have you measured your processes by effort (AHT x volume) and potential saving?
  2. Do you know which handful of processes make up 80% of all your team’s effort?
  3. Have you reviewed your top processes in detail to understand their complexity?
  4. Have you plotted your top processes by Effort, Benefit, and Ease of Implementation on the Complexity quadrant?
  5. Have you provided the leadership team with a visualization of the makeup the department’s processes so that they can strategically prioritise which processes to automate first?

Ideate: Have your solutions involved all the right people?

It’s important to include those stakeholders that may cause or be affected by the existing problem and may be impacted by the solution when implemented:

  1. Have you involved key stakeholders from the team(s) that are upstream from your process, who feed information into your target team?
  2. Have you involved key stakeholders from the team(s) that are downstream from the process, who receive information from your team?
  3. Do all the root causes identified by the workshop group relate to all the problems being experienced in the target team?
  4. Have you first considered lean process re-engineering?
  5. Did you have a technical expert present in your solution design workshop?
  6. Did you have full participation with everyone’s opinions being heard and respected?

O: Optimise 

Are your processes lean?

Before moving to the automating stage, look back and see how much waste you’ve removed from the process and see if you now have a lean process to automate.

Remember that the purpose of Lean Six Sigma is to meet the customer’s expectations as fast as possible, and in RPA and intelligent automation, Lean Six Sigma can greatly increase the ROI of your initiatives. See how well you can answer these questions:

  1. Have you identified all eight wastes in your target process and team?
  2. Have you mapped out your target team or process in a SIPOC?
  3. Have you identified non-value-added areas using a VSM?
  4. Is your CoE’s physical and digital work environment organized using the 5 S method and ready to scale?
  5. Have you run a root cause workshop and used the 5 whys to discover what the potential root causes are for the inefficiencies in your target team?
  6. How much waste have you eliminated in the proposed future state model, even before you automate?

Y: Yield 

Are you getting value?

The big question clients, stakeholders, and senior leadership will ask is, are they getting value from this digital workforce? Look at these questions to make sure your team can answer this:

  1. Was performance of the processes measured accurately before they were automated?
  2. Do you have visibility of your bots’ performance, via logs and a dashboard?
  3. Do your internal/external clients have visibility on how their bots are performing?
  4. Are you regularly tracking the bots’ and CoE’s performance metrics that answer the right questions?
  5. Have you found ways to quantify qualitative data? (cost of errors/re-work, using Net Promoter Scores etc)
  6. Have your robot performance indicators helped teams discover potential ways to improve on the most common systems and business exceptions?

O: Organise & Oversee 

Are you in control?

Go through these questions to confirm whether your Support team have all their bots under control and the team has a scalable structure.

  1. Do you have someone carrying out each role shown in the Support CoE structure (even if some of your team are wearing several hats)?
  2. Do you have a transition manager who is a separate person to the developer and support engineer?
  3. Do both the Development and Support teams use the same agreed coding standards, best practices, criteria, and knowledge base?
  4. Do you regularly provide process owners with bot health and performance reports and discuss seasonal or future volume increases?
  5. Do you have a prioritization mechanism and triage process for handling requests and defects?
  6. Are you continuously looking to optimise your CoE through the same lens as when inspecting a BAU team? (automate repetitive tasks, using self-service portal for clients and process owners).

U: Uncover, Upgrade & Upskill 

Have you identified ways to enhance your bots to gain more benefits?

Keep circling back to the beginning of the AEIO YOU lifecycle to stay aware of new emerging technology and education.

  1. Is your team aware of the plethora of different types of AI capabilities on the market? (e.g. chatbots, ICR/OCR)
  2. Have you meet with different AI vendors and watched demos of what their products are capable of doing for your business?
  3. Have you run any POCs with vendors to demonstrate first-hand how much value their ‘bots’ can add to your CoE team?
  4. How serious (or nervous) is your business at implementing AI into their business processes?

Want to get a clearer understanding of your RPA/CoE teams stregnths and weaknesses, take our straightforward multiple choice test and receive a free report that scores each sections and breaks down your results with useful actions you can use today to improve


You can learn more about implementing RPA (Robotic Process Automation) and intelligent automation at Lean IA Consulting

You can read about these tips and tools used in their AEIO YOU method in their new book Business @ the Speed of Bots, How to implement RPA that scales

Automation vector illustration. Flat tiny machine line work person concept. Robot machinery equipment to control modern and futuristic arm process. Manufacture revolution strategy to minimize employee

RPA FAQs and some TLAs

What does RPA stand for and what does it do?

Robotic Process Automation. This is low or no-code software that automates business processes by mimicking a human’s clicks and keystrokes on a computer screen.

RPA works for almost any monotonous task your teams do on their computers, for example, it can copy and paste data from one application to another.

What is a PDD and an SDD?

PDD stands for Process Definition Document, this is the most important document in RPA because it is used by the business analyst to transfer the business’s problem into a technical solution that the RPA developer can understand

The developer uses the PDD to create the SDD (solution design document), which is a more technical document which provides guidance to the architecture of the bot

What is an L4 keystroke document?

L4 stands for Level 4, which comes from Six Sigma is arguably the lowest most detailed process map, whereas L0 would be a very high-level map of the process

In RPA a level 4 map shows the clicks and keystrokes a user would make to perform a task or process, each step in this map would be numbered and would be accompanied with a keystroke document which would further describe each step and provide a screenshot highlighting the button clicked or text box typed into

What is a POC?

POC stands for Proof of Concept, where a business would test the capability of a new tool or software to see if it worked in the way they want to use it. However, businesses generally prefer to call this POV or Proof of value so that they can measure how much value the new tool provides at a small scale

A POC/POV is generally done before a large scale purchase is made, as is used to get buy-in from stakeholders

What is a CoE?

CoE stands for Centre of Excellence (similar to Operational Excellence), this team or function is responsible for sustaining high quality and consistency in the delivery of a new capability.

This is done by having central place which provides tools, techniques, templates, training and frameworks to ensure that all across the business everyone is implementing and assessing RPA in the same way for example

What is an Automation Catalogue?

This is a list of all the manual processes in an organisation that has gone through an assessment to see how suitable it is for RPA and what expected benefit can be gained from this using RPA

Analysts may want to put another layer of assessment to see what other benefits can be gained using other methods aside from RPA, e.g. outsourcing, Lean process re-engineering, intelligent automation or AI

What is an EAR?

EAR stands for Enterprise automation roadmap. Once the list of processes in the automation catalogue has been thoroughly assessed, they can be prioritised and put into waves, and presented on a roadmap to show how the full RPA rollout will be accomplished, and when

What is Lean Six Sigma?

This is a combination of Lean thinking (making things efficient), and Six Sigma (making things well/high quality).

Understandable Lean Six Sigma is a powerful combination with RPA and intelligent automation as automating a lean process can provide much higher ROIs as you get “more bang for your buck”

Some other acronyms from the intelligent automation world

AEIO YOU: A method for successfully implementing intelligent automation into an organisation

IA: Intelligent Automation

RPA: robotic process automation

FTE: Full-time employee

AI: Artificial intelligence

GUI: Graphical User Interface

SME: subject matter expert

PDD: Process Definition Document

SDD: Solution Design Document

SLA: Service Level Agreements

API: Application Programming Interface

ICR: intelligent character recognition

COE: Centre of Excellence

CBA: Cost benefits Analysis

RCA: Root cause Analysis

A case: a unit of work that flows through a process, e.g. an individual customer request

PMO: Project/programme management office/officer

UAT: User Acceptance Testing

POC: Proof of Concept

POV: Proof of Value

EAR: Enterprise Automation Roadmap

MPV: Maximum Potential Value

TPV: Target Potential Value

AHT: Average handling time

SIPOC: Supply, Input, Process, Output, Customer

COO: Chief operations officer

TT: Takt time

GDPR: (General Data Protection Regulation)

CASS: (Protection of Client Assets and Money)

ML: machine learning

OCR: Optical character recognition

BPO: Business process outsourcing

BPM: Business process management (or Mapping)

VM: Virtual Machine

VDI: Virtual desktop interface

You can learn more about implementing RPA (Robotic Process Automation) and intelligent automation at Your virtual consultant

You can read about these tools used in the AEIO YOU method in their new book Business @ the Speed of Bots, How to implement RPA that scales


The 36 steps the AEIO YOU method

The underlying approach of the AEIO YOU method is to ensure you’re applying Robotic Process Automation (RPA) and intelligent automation to lean (aka streamlined and optimized) business processes. Using lean thinking you can achieve a much higher ROI from your new technology than if you were to have just automated bad processes.

Remember the old adage, ‘GIGO’ (Garbage in, garbage out)

Follow these steps to bring your RPA Centre of Excellence (CoE) team to a maturity level to proudly call it an Automation Factory. Then start again from step 1, but this time with a newer technology

Here are our 36 steps of the AEIO YOU method:


1. Understand the Technology

2. Know the myths, Challenges and the Benefits

2b. Know the common mistakes and pitfalls

3. Understand the market

4. Choose the right solution provider

5. Be an evangelist

6. Run a Pilot (POV rather than POC)

7. Start building your Centre of Excellence


8. Bring in the Experts

9. Involve staff so they welcome the change

10. Keep hold of your most valuable assets

11. Upskill to build capabilities inhouse


12. Zoom out. Create an Enterprise Automation Roadmap

13. Zoom in: Define and Measure the problem

14. Filter on what’s suitable

15. Focus on the top 20% (80:20 rule)

16. Build a complexity map: Cost vs Benefits vs Financial savings

17. Prioritise: Go for some quick wins first

18. Zoom in further: Business Analysis 101 (Data and requirements gathering)

19. Root cause analysis


20. Solution design

21. Lean thinking

22. Business Case: detailed cost-benefits analysis

23. Define the process

24. Design the solution

25. Build the solution using best practices

26. Prepare the data for testing

27. UAT

28. Hand over to support team

29. Launch

30. Reflect

31. Repeat and scale


32. Realise the benefits


33. Maintain the benefits

34. Manage the changes


35. Circle back for continuous improvement

36. Discover newer technologies

You can learn more about implementing RPA (Robotic Process Automation) and intelligent automation at Your virtual consultant

You can read about Lean IA’s trademarked AEIO YOU method in their new book Business @ the Speed of Bots, How to implement RPA that scales


3 Ways Intelligent Automation Can Help Grow Your Business

AI and robots are already being used to great advantage by businesses no bigger than yours.

You can stop trying to imagine the future of A.I. because, believe it or not, the future is here. While robots aren’t yet walking our dogs or doing our grocery shopping, A.I. certainly is a growing presence in the business world. The growth in this industry is astounding.

In fact, most of the top 100 artificial intelligence startups are based in the US. This means that the trends for intelligent automation are becoming increasingly visible. But what is intelligent automation?

It is specially designed software that detects products or objects in images, pulls data from documents or manipulates information. These software robots have been trained to complete tasks that have a “human” quality. They can adapt and learn the more they work.

Now that you know what it is, let’s talk about three ways intelligent automation can help your business:

1. Increase productivity

Imagine a 25-percent increase in staff productivity. That’s what a restaurant in labor-short Singapore expected when they implemented their new “flying waiters.” These drones are designed to deliver plates to diners while the employees perform other tasks.

This is just one example of the opportunities to increase your employees’ productivity using RPA, or robotic process automation. Using these software robots, your basic business computing can be done efficiently, freeing up your employees for the non-repetitive and more creative tasks.

While you are imagining the many ways you can increase your business’s productivity, don’t forget about the common human errors you can avoid.

Related: AI Is Taking the Art Out of Sales

2. Reduce common human errors

As more businesses turn to automation in an effort to relieve their human workers of repetitive tasks, they are also avoiding many common human errors, making these businesses much more efficient.

Software robots can learn and adapt far more efficiently than most human workers. In chatbot programs, for example, this feature is especially helpful for standard customer service needs.

The chatbots continuously gather information as they are used, and they use that information to help your customers.

With the increasing availability of intelligent automation, what return can you expect to see on your investment?

3. Improve your ROI

Now that you have implemented software robots for tasks that you no longer need employees to do, imagine the possibilities for the return on your investment.

You hire fewer employees and pay less in salaries, wages, training, and benefits.You invest in the automated software and equipment and outsource your maintenance.

With increased productivity and reduced human errors, your average costs for the same work will be much less, which can exponentially increase your return. What business owner wouldn’t want that?

Read the source article on Entrepreneur


Why AI means the end of ‘pure’ RPA

Interview with Process Excellence Network

PEX Network:

What is your working definition of ‘intelligent automation’?

Antony Walker:

RPA is dumb computer software doing manual tasks. Intelligent automation is combining things like RPA or BPM tools with some sort of artificial intelligence, so that it doesn’t just move data through a process, but it can interpret and understand data. Unstructured data is where RPA falls short, whereas AI can fill this gap. And 80 to 90 per cent of processes have unstructured data

PEX Network:

What problems can intelligent automation be brought in to fix?

Antony Walker:

RPA, AI and intelligent automation is seen in the media as something that could replace people as many businesses have been focusing on FTE savings, however it should be used to augment what people do; taking the tedious boring tasks so that people can focus on more intellectual, creative parts of their life. And it allows businesses and their staff to discover new revenue streams that were once unviable to reach, so that their business can in fact expand.

PEX Network:

What sort of organizations are looking into RPA and intelligent automation, and why are they doing it now?

Antony Walker:

Early adopters of this technology have been finance, insurance, utilities, healthcare and law firms. The manufacturing industry have used physical automation for decades and are also looking at automation on the software side as well. The biggest benefit are for industries that have a lot of paperwork and repetitive tasks, so you can imagine areas like legal, tax and accounting departments having a big appetite for this. Processes that are repetitive and logic-based can be automated, so this is why RPA has benefited them greatly.

Over the next year, there’s going to be a lot more focus on AI. In 18 months to two years, I don’t see there being any pure RPA initiatives, everything is going to have that intelligence built in. This is because IA is really starting to mature now.

PEX Network:

That is quite a statement. What do you think is driving all this?

Antony Walker:

There have been a lot of advancements in AI. There are a lot of use cases and quick wins for teams to implement AI and benefit from it straight away. And as mentioned previously only 10 to 20 per cent of processes use structured data. Many business leaders and analysts I’ve spoken to have become frustrated in their previous pure-RPA projects that weren’t providing the ROIs they had expected. That’s why lean IA hits this problem twice. Lean means you use fewer ‘robots’ to get more savings by optimising your processes first, and IA means you can target more processes and move away from just pure-RPA.

PEX Network:

How will these changes affect the big legacy banks and financial institutions?

Antony Walker:

Two big stories that have been in the finance technology world for a while now are robo-advisors and cryptocurrency. Independent financial advisors will start to feel squeezed out. They are being challenged by these AI capabilities advising people on how to best invest their money, so IFAs are having to adapt and focus more heavily on the human, customer relationship side. Then we have cryptocurrency which threatens to decentralize the monetary system.

One thing I have seen in the utilities industry are start-up companies in the energy sector that have popped up with very low overheads due to having minimal infrastructure, and are able to greatly undercut and move faster than the big corporations. This is definitely something legacy banks may fear happening to them.

Any industry that has a lot of paperwork, manual processes, large workforces and unnecessarily complicated or dated processes in their back office operations will feel the pinch as they start haemorrhaging money and customers. In asset management the baby boomers still prefer using paper forms, I’ve been working on a project where we used intelligent cognitive-recognition software to scan information from a paper form and then put this directly into the database, which saved staff having to read the document and manually typing the information into the database manually a thousand times. Do note that we are now at a time where computers can read handwriting more accurately than humans.

These are just a few of the things behind the scenes that AI and intelligent automation are having an impact on.

PEX Network:

If this technology really is maturing and becoming more ubiquitous, what’s going to be the big difference that we’ll notice?

Antony Walker:

How we interact with the banks and insurance will be a big one. Natural Language Processing is going to advance a lot more, and is where I am personally starting to focus. Website chat bots will become a lot smoother and smarter; they will understand what we’re after, and understand what our profile looks like; they have our data, so they will be able to really customize what their recommendations are to our specific needs.

In insurance situations like a car accident when we use our phones to make a claim, they will be able to read and respond to our moods, understand the images in photos we send them, know where we are and remember our history to tailor their advice

In summary, customization, speed and accuracy of service through more convenient avenues are how we’ll notice these technology advancements over the next few years.

Read the book, Business at the speed of bots