If you are dreaming of your Automation team moving from delivering small automations to find big transformational processes to automate, or if your backlog of automation projects is drying up then this article is exactly for you!
You’re not alone, a lot of teams are out their struggling to find automation opportunities, unsure where to look, spending a lot of time looking in the wrong place, wondering if there are any opportunities left. If you’re like most businesses struggling to scale up their automation program, then there are 100s of potential automation opportunities waiting to be discovered by your team.
Today you will learn about the most powerful tool that automation experts use to find the best opportunities that are both easiest and fastest to build. This tool will also help your Automation team avoid the most common mistakes that stall automation program. You’ll ensure you don’t choose processes automation suitable or are so big and complex that they never get finished, causing stakeholders finally lose interest.
I’ll also show you how to prioritize projects in a way which makes it easier to roll out smoothly with minimal hiccups and can massively boost your momentum. I do cover this in my blue book of secrets “Business @ the speed of Bots” (which has been highly recommended by one of the top executives at UiPath, probably the largest automation software company), but let’s get you started so you can start using this tomorrow
How do you Prioritize opportunities?
I have a question, what metrics do you use to prioritise automation opportunities? I’ve worked with a few new automation teams that use a process’s time saved to prioritise which process to automation. It makes sense to spend time on the projects which will make the largest savings, right? However, this doesn’t look at the big picture and can miss some vital points that can trip them up later down the line.
I want you and your team to take these two steps further. We are going to use three dimensions to find the highest value opportunities, where we look at comparing Time Saved (effectively direct financial benefit), to the Ease of development and implementation, and the Intangible Benefits (which may have an indirect financial benefit). In fact, many teams seem to forget to consider intangible benefits in their cost-benefit analysis. These are things like reducing human error, improving compliance, or generating revenue in new ways.
When you use look at Time Savings, you miss how difficult a process is, it could save a lot but requires expensive AI technologies which could generate a net-loss because the solution is too expensive to run. On the other hand, you may discard a process because it doesn’t save significant time but the reduction in human error could have a massive positive impact on the business.
What is an Automation Opportunities Map?
A bubble chart of your businesses opportunities is a powerful visual which paints a clear picture to your senior leadership team where all the potential savings are hiding. The three dimensions of the map is the x-axis (the ease of implementation), the y-axis (the intangible benefits), and the size of the bubble (the financial benefit from time saved). This diagram has four quadrants for the types of opportunities that exist in your business:
The big quick wins (top right):
These are your high value projects; they would save a lot of intangible benefits and would be very easy of implementation. Typically, they also save significant time for staff too
Quick wins:
They will deliver a slightly smaller benefits but they’re still very quick and easy to implement. These can commonly be even easier to implement that the Big Quick wins, because they are more straight forward processes, and so are easier to support as well.
Long terms:
They have large financial and intangible benefits; however they are a lot more complex so will take a longer time to implement, and probably shouldn’t be at the top of your priority list.
Must Dos:
These are low benefit, high complexity but as they are suitable and potentially, they are automation-suitable processes that are necessary for your company to operation effectively (e.g., legal or compliance processes), you eventually must do them.
The great thing about this map, is that you can select the department or team you want to focus on and can zoom in to see all the process opportunities in that team.
How do you create your Enterprise Automation Roadmap?
You opportunities map is useful aid for senior leadership to prioritise which departments and teams, and the processes within them, that they want to automate first. You can design the road map to progress in a logical manner, starting with easier, high value-high return projects so that momentum can be built steadiness so you can scale successfully.
As your roadmap dictates that move to more complex processes, these projects will move you from using purely Robotic Process Automation (RPA) tools, to incorporating a variety of AI capabilities, like Chat bots, Machine learning, Optical character recognition (OCR) software.
The roadmap is another great visual to show how much savings will be delivered from various projects and when the senior leadership team can expect to see this manifest. With the Opportunities Map and Roadmap, you will be able to clearly show business leaders exactly how projects will help move the dial on achieving their corporate objectives (e.g., doing projects A, B and C will improving staff morale, automating projects A, D, E and F will reduce errors by 30%).
1D – Measure the Effort (Total time that can be saved)
Firstly you want your team to measure how much staff effort each process takes each month. Simply calculate the time each process takes multiplied by the volume of work that process has.
E.g. (2mins per case) x (200 cases a month) = 400 minutes of potential savings
This will give you an indication of roughly how much potential time can be saved when that process is automated. Of course the process may not be automated end-to-end, so you may want to estimate the Automation percentage of each process. As you learn more about the details of the process, you will be able to calculate a more accurate Automation %.
As a side not, most likely time savings may not actually reach the bottom line as financial savings because in most cases time saved for staff is deployed so that staff can focus on more value-adding tasks. Or it saves on hiring cost as existing staff can be more productive.
2D – Measure Process Complexity (Ease of implementation)
Measuring complexity is a vital part of finding opportunities. Once you found processes which take up a lot of time, you need to confirm they are automation suitable. Then you want to understand how easy a process will be to build and then to implement due to many other factors. This will give you visibility of the costs of creating these solutions.
Cost of development, costs of support of maintenance and the cost of the technologies requires for these solutions. If a process is complex to build, that it will most likely be complex to support. The more complex a process, the high these costs.
In addition to development complexity is team readiness. If the process experts are unavailable or the applications are undergoing changes then this will add to how difficult the project will be to implement.
3D – Measure Intangible Benefits
By definition, intangible benefits can be hard to quantify but they’re not impossible. Some of these benefits can indirectly attribute to financial savings for example removing errors is an intangible benefit, but there’s also a cost to the error itself and there’s a cost to time taken to fix the mistake. Even when it comes to becoming compliance, the financial savings is the cost avoidance of not paying fines.
Look at the projects you are and will be delivering, what intangible benefits are you saving that you have not accounted for? You could be selling your automation team short
Automation Analyser for individuals and teams
You can build an Opportunities map in excel, however if you have a team of several analysts gathering data from different business areas, you can use Lean IA’s Automation Analyser to compile all the data centrally, auto-analyse all processes to identify automation suitable opportunities. This immediately creates a Pareto chart to show you where most of the staff’s effort is going. You can also see a bubble chart at a department level and can zoom in to see opportunities at the process level.
With these visual aids produced from data your team can gathered centrally with a click of a button your team have all the insights they need to plan how best to roll-out automation company wide. Essentially you will be able to provide leadership team will a slot machine with different levers to achieve whichever objectives they have, and it will spit out the list of projects that are needed
If you want to learn more about lean Intelligent Automation in your office, subscribe to my YouTube channel Tony IA (Intelligent Automation, Simplified) for videos created weekly, 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.
2 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
3 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.
4 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!
5 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
6 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
7 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?)
8 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.
9 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.
10 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
11 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.
12 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.
13 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.
14 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.
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.
5 things you NEED TO KNOW about RPA (Robotic Process Automation)
Robotic Process Automation has been around for a while now, but there’s still a lot of misconception about what it actually is. Maybe you’ve heard different conflicting opinions and thoughts online about how it could impact you and how it can be used.
I want to highlight FIVE things that you need to know about RPA, its benefits and why you personally should get involved in automation. I also want you to be able to spot a process which eventually is going to get automated and give you a peak at popular RPA development platforms, so that you can see how easy it is to build automated “Bots”.
I’ve been a Lead Automation Expert for many, many years now, focusing on using “Lean thinking” with Intelligent Automation, working in many industries at some of the largest companies, tier one consultancies and also some small and medium enterprises. When I first heard about RPA was in 2017, when I was working as a Process Improvement Analyst (using lean six sigma to improve business processes). My boss had approached me to take lead on using “robotic automation” to improve processes and make savings. I honestly thought that he was about to roll out a physical robot from the storage cupboard behind him!
What is RPA?
To be clear, Robotic Process Automation is software robotics similar to an excel macro. RPA is low- or no-code where you can record the process you want to automate, or you can build the automated process from scratch by drag-and-dropping actions onto a process flow. RPA is able to scrape data from website pages or web-tables, or directly from databases using APIs. It can add data into an excel or fill in webforms or into desktop applications.
This highly versatile application can work with any application desktop, web app or website as it uses the User Interface just like you and I would. It can press buttons and links, tick boxes, select from dropdown menus and type into any text field as if it were using a mouse and keyboard.
It is an amazing technology but it’s not actually a silver bullet. There’s a lot of things that RPA can’t do and that’s why it businesses are coupling RPA with AI capabilities. Pure RPA can still automate potentially hundreds of your business’s processes right now, but RPA is limited by the fact that it can only use standardised input and can only make logical decisions. I.e. RPA can’t do anything which is which would require human judgment and intuition.
More and more RPA is overlapping with Artificial Intelligence (AI), as vendors add AI capabilities into their software so that the scope of what RPA can do for your business keeps increasing. Gartner had estimated that RPA on it’s own would be able to eliminate 20% of repetitive tasks. When I was interviewed for Process Excellence Network in 2019, I shared how this trend would eventually bring an end to pure RPA.
With the emergence of Intelligent Automation (RPA + AI), if say you wanted to read data off a pdf or respond to a chat, or use information collected by a chatbot to better serve a customer, you can now literally drag that capability into your RPA bots workflow.
The Optical Character recognition (OCR) software is able to read the PDF document (whether that be text or handwriting). A Natural Language Progressing (NLP) integrated tool could understand the customers intention from the question entered into a chatbot/webchat, and then trigger an automated process to take over and carry out the required action or retrieve requested information.
What are the benefits of automation?
Robotic process automation on it’s own is great at manually intensive tasks, that are tedious and repetitive, and require a lot of combined staff effort to manage the workload. RPA is especially good for those repetitive tasks that have seasonal volume.
Do you have areas in your business where staff are constantly working late?
These teams could leverage automation to save them time on odd-jobs and partially automate processes here and there to free up more of their time to hit their targets and deadlines faster.
Do you have KPIs showing high amounts of human error in certain teams?
Automating processes prone for error can effectively reduce errors to near zero. Even if the whole end-to-end process can’t be automated, augmenting staff can ensure they retrieve/input/use accurate information or data validation can be automated.
Do you have long physical queues or customers on hold for long period of time? Perhaps your staff are taking a long time to respond to clients.
Intelligent automation has grown very popular in the customer service division. Customer service advisors use multiple applications to assist enquiries and also have a lot of form filling and updating customer data so automation can be used to streamline a lot of these processes
With seasonal spikes, instead of going through the whole process of finding and hiring new teams and having to train them up, your existing staff can leverage automation technology to be more productive.
Are you outsourcing certain processes that could be automated?
You could potentially develop a Bot once and all you need to pay after that is server costs, the software licenses and maybe a little maintenance to keep it running and up to date
The by-product of these cost savings, improved efficiencies, and error reductions, is the enhancement of customer experience. The service that you deliver to customers will be more accurate, faster and more convenient that from your competitors that don’t use automation effectively.
Giving automation technology to your staff can also improve staff morale as it can be like giving everyone in your team a virtual assistant to exceed targets and gain a better work-life balance with fewer late nights and more time spend on interesting, creative, human to human interaction and customer facing tasks.
How do I spot an RPA use case?
There are about eight things you want to look for when identifying a process which is suitable for automation:
1. RPA needs standardized input. Its able to use pre-determined information like options in drop down menus or selectors. RPA on its own can’t understand free text
2. RPA can’t do a process that requires human intuition, RPA cannot think, it can’t make any judgment calls. It pretty much can just ‘copy’ a task if you show it the steps
3. RPA needs rules. It can only make a decision if its rules based, and the outcomes are pre-determined. You must be able to program the logic that the Bot needs to make to choice the right option.
a. For example: IF price goes up press “BUY”, ELSE IF price goes down press “SELL”
4. RPA works best when the process is repetitive and manually intensive. You want to find processes which repeat over and over again like updating details for a long list of customers
5. RPA is best for those high volume processes like adding 100 customer details every day into a CRM application. This isn’t a necessity, but it does mean that you will deliver a significant amount of savings for your development effort.
6. The process needs to be stable you if your RPA is to last. RPA using the User Interface (clicking on buttons, types in text boxes). If the process keeps changing the Bot will keep crashing and will constantly require new development so that it can navigate the new application or webpage layouts.
7. Make sure there’s no pending changes on the process or applications. Related to the previous point, it’s not a good idea to have your team working on automating a process that is due to change in under 6 months’ time, or the applications are due to be upgraded. This could require having to rebuild the automation before the end users ever had a change to properly benefit from it. Changes are inevitable, but timing is everything.
8. Obviously, the process for automation must be fully computer-based. However, it certain steps require someone to pick up a phone or print something then it could be possible to automate with a “human in the loop”, where you automate the first part of the process, the bot notifies the person to do a physical task, then that person triggers the automation to finish that process.
a. It is possible to integrate RPA (software robotics) with physical robotics, for example, an automated payment process triggers a physical robot to pick the stock in a warehouse
How can I build an Automated process?
The RPA studio is where developers design the automated steps for the Bot to follow. There are two main types; drag and drop where you can just drag an activity like an action or decision point into a process map (you would see this set up on Blue Prism or UiPath software).
The other way is displayed as line-by-line code, where you drag the activity and all steps show are lines of code in a page, instead of shapes (see the images for a better understanding). This is typicaly found with Automation Anywhere and IBM’s software, however recently there is an option to depict the process steps with shapes.
[img]
To build a robot there are just a handful of steps you need to follow to create a building an automation:
IDENTIFY PAGE ELEMENTS: you have to spy different objects on a screen or a page of a website or an application and all this is it just helps the rpa robot to recognize different elements on a page so this is a button this is a link this is the name field
DRAG ACTIVITIES/ACTIONS: you can drag in different activities into the process map like an action to open excel, open chrome or type a web address
DRAG DECISION POINTS: you can drag in a decision so that could be:
IF price had gone up press “BUY”
ELSE IF price has gone down press “SELL”
ADD LOOPS: this loops through the process for a predefined number of iterations. For example you could have a data table in excel. The bot counts the rows and loops through the table row by row inputting data from excel into a web form
PRESS PLAY: Once the process is finished you can press play (or define the trigger to start the process) and you will see the robot moving through the process step by step
That’s it! Pretty easy right?
RPA Vendors are quickly moving towards a world of “Citizen Development” as they develop their platforms to become so intuitive, anyone could build automated processes.
How is RPA using/integrating with Artificial Intelligence?
RPA on its own can probably only automate about 20 percent of processes (still you’re looking at hundreds of processes), but then what about a rest?
This is where you need different types of AI to plug into your automated process so that it can extend its capability. RPA platforms are making it really easy to do in two ways. Either they’re embedding AI into their platform or they’re building massive ecosystems where it’s very easy to integrate with different AI applications.
Let’s take a look at a few:
OCR (optical character recognition) is a type of AI that can read data from an image. So if you had a pdf or a scanned image or maybe even just a photo, Optical character recognition (or perhaps Intelligent Character Recognition) can turn data from an image into structured information that the RPA Bot can use. You could get a scanned invoice or PDF and with OCR capabilities your automation can input invoice data directing into your excel spreadsheet or your finance application. Intelligent character recognition (the smarter version of OCR) cans understand things like handwriting, varying fonts and even spelling mistakes.
Another very popular AI in the office is the chatbots. You can have a web chat where customers are asking the same questions like “what’s my balance?” or “who’s my account manager?”. Maybe customers wants to do similar activities like “I want to purchase flights to cyprus in january” or “Book a hotel” or “book a car”. A chatbot using natural language processing (NLP) to understand the intent of a question can trigger an automated process to go into the customer’s account and find who the account manager is, or look at their balance. If it were a holiday making site, the automation could book a holiday/flight/car using the requirements the customer specified.
NLP, however, is not limited to chatbots. It can understand free text, so could read an email or text in a comments box. For example, NLP capability can read the content of an email and use this to categorise and organise a mailbox, which in turn could trigger different automated processes for each type of email. Intelligent automation has endless possibilities.
Machine learning and this is probably what most people think is “AI”. You essentially feed a computer with a load of data, and it finds different patterns and correlations, so that when you ask it a relevant question it can calculate the answer which has the highest probability of being correct.
This has been useful in healthcare. The computer is given the details and symptoms of patients that have a specific disease, and the details of people that don’t have that illness. By calculating the similarities and dissimilarities between the people in the two groups, when the machine is given the details of a new person, the machine can calculate the probability that this new person as the disease or not.
Sales and Marketing can use machine learning in a different way. If you have hundreds or thousands of customers that you want to sell something to but you don’t fully understand their buying habits or preferences. By feeding customer data and purchase histories to the machine, it can calculate patterns can make the best recommendations of new products to customers that have a high probability of buying.
Now that you have an awareness of how Robotic process automation is being used in the office and how Artificial intelligent is supercharging what RPA can do, start looking at processes in your business that can be automated today
If you want to learn more about Intelligent Automation in your office, subscribe to my YouTube channel Tony IA (Intelligent Automation, Simplified) for videos created weekly, 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.
6 ways your business is wasting TIME, MONEY AND RESOURCES in every Process and Team
You may already be aware that your team or business isn’t running as efficiently as you would have liked. Maybe it’s the long customer queues, long the hold times or there’s high error rates that are difficult to stomach. Perhaps it’s the slow turnaround time for sales to be process or it’s the constantly low staff morale that has tipped your off that something is very wrong.
If you are aware that things could be a lot better, are you struggling to find where the problem is or how to solve it?
Let’s look at six places to look for inefficiencies in your business and teams. Using this method in team workshops will help you to uncover a whole list of underlying causes of business problems, that could be solved quickly with intelligent automation technologies.
The method I want to share is a lean thinking technique call the Ishikawa or the Cause-and-Effect diagram. It also looks like a fish bone so called a fish bone diagram too.
The head of the fish bone this is the Effect, this is the problem or pain that you’re experiencing. Then the fish bones are the 6 areas where you will find the causes to the main problem. This powerful tool can be used in workshops to help the team focus when brainstorming around the whiteboard.
The goal is to get ideas on the whiteboard using post-it notes then you can group these ideas of possible causes into themes. Then you will have Each theme could potentially be a project or a clue to finding the root cause of your problem.
Measurement
This looks at whether you’re actually measuring staff/business performance correctly and accurately, or are you measuring performance at all? Sometimes just measuring something can immediately uncover the problem. In lean thinking and process improvement, a common phrase is “if you’re not measuring something you can’t improve it”.
So you first point of call is to check IF and HOW you are measuring key performance indicators (KPIs). Measuring accurately may show that the problem is not as bad as it seems, or it only looks bad to you because you’re just measuring it wrong.
In the automation world, new automation delivery teams may just look at the time saved to calculate the benefit and value they are delivering; however they may be delivering significant intangible value (cost avoidance, compliance, staff morale and error improvements). They are missing the full picture. If this is your team, are these KPIs not being measured because your team hasn’t thought to do so, is it too difficult to measure or the data needed to measure it unavailable?
Another reason that inaccurate/incomplete measurement might be an issue is because teams lack the right resources or skills in-house to know how to measure these KPIs.
Material
Materials is do with whether your teams have the right resources to do the task effectively. Does the team feel they don’t have the right skills and need further education on a new process or application, or potentially the company when through a recent brain drain and people who were skilled in that department have now left.
Method
This is looking at the process design itself. Is it an awkward process which is unnecessarily bureaucratic, or old and inefficient? As applications and technologies advance, processes also need to be revised as an old process might not be fit for purpose anymore.
Just by redesigning and streamlining a process, and removing redundant steps can make massive improvements to a process, and that’s even before it’s been automated.
I remember when I was an analyst, a team I was working with were carrying out a which required they print off the document and file it away into a cupboard. Quickly we discovered that these documents were never used again, not even for audit purposes. It was an old process when documents where physically signed. The process had never been fully updated, even after all documents (which were now signed with e-signatures) were all stored on the computer.
Mother Nature
This looks at the environment that staff work in. This could be a physical environment like their workspace or a virtual environment. Is comfortable? Are things in the right places?
A productivity study found that a team’s productivity can drop by four percent for every degree above 27 degrees Celsius. The virtual environment can have just as big an impact, if files are in messy unorganised folders with no logical location or naming convention.
Mother nature can be wider than just physical or virtual environments, but it’s also covers changes in economic or social environments. For example a market crash, COVID, or legal/political changes can reduce efficiencies and make processes more clunky. In Europe, the GDPR compliance mandate slowed a lot of processes down and required that processes were sped back up through process re-design and automation.
Manpower (Preferably People-Power)
This can lead to people to pointing fingers at different teams but it can expose the different politics and frictions between which is useful because most times friction and politics and disagreements between teams is just the misunderstanding between how different teams operate and the environments that they work in. This can highlight who else your team can speak to, to uncover more about this problem or pain.
Digital business transformation is People, Process and Technology, in that order. ‘People’ is normally the Number One problem in transforming your business. This friction and resistance is misunderstandings and misalignments, but this is exactly what Intelligent Automation can do for your business. It can be used to remove silos to align teams and to uncover these misunderstandings for more efficient future
Machine
Not to be confused with materials. Materials are resources, something you use to make or provide something. Machines are the equipment that we use to produce the product. Some businesses are inefficient purely because their staff are using legacy computers and applications which are clunky, slow and terribly un-user friendly.
Robotic Process Automation is a powerful tool to solve these technical blockers in a matter of weeks or months, which would take the IT teams years to develop fixes.
Once you’re workshop attendees have populated the board with all their reasons for what is wrong with these 6 topics, gathered metrics and KPIs (if available) for each issue raised, so that you have an indication of how serious each issue is and then you can start to prioritise them for Intelligent Automation projects.
Subscribe to my YouTube channel Tony IA (Intelligent Automation, Simplified) where I create videos every week 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 was the then-Chief Evangelist at UiPath, and a very well-known advocate of RPA with over 20 years of experience in outsourcing.
Pareto Chart – Automate 80% OF SAVINGS with just 20% of activities!
Pareto Chart – Automate 80% OF SAVINGS with just 20% of activities!
The most insightful ratio that you might not have heard is called the Pareto ratio, Pareto’s law or the 80:20 rule. Essentially, your teams are spending 80% of their time on a mere 20% of business processes. About 20% of your customers make up roughly eighty percent of your profits, and eighty percent of your results are from twenty percent of the efforts you put in.
A Pareto chart coupled with an Opportunities map (see link at the end to get more info on this), will help you to build huge momentum and massively accelerate your rollout plans. But..
What is Pareto’s law?
In “Lean” intelligent automation, you can use this 80:20 rule to find the best automation opportunities in your business for your Automation team to focus on. I want to show you how to create and use a simple Pareto Chart to identify a shortlist of processes that will deliver the most savings, so that you move away from small tactical processes and deliver large transformational automation.
You can create a Pareto chart in five simple steps:
1. Measure the effort for all processes
2. Calculate the percentage of the total effort of each individual process
3. Put processes in order of most effort
4. Calculate the accumulative effort of each process
5. Find that 80% mark
Create a data capture table
In an excel table as shown below, you need several columns for your team to populate as they build a list of processes. In workshops as your automation analysts go team by team, they will be able to gather high level process data from several teams in a matter of days.
I really like this process because it’s by far the fastest (and cheapest – if you were looking at process mining) way to scan hundreds of processes and teams in a matter of weeks.
You will need:
· Process names (and the department and team name if you are compiling data from across your business)
· Average handling time (how long each process will take to complete a single iteration)
For example, How long do staff take on average to complete the registration process for a single customer
· Volume of work (how many times per month do staff do each process)
For example teams may complete 100s of customer registrations each day, which could amount to hundreds or thousands of customer registration on average each month
NB: Average monthly volume is preferred as a daily average (using a month’s worth of data) could be unreliable due to seasonal peaks and troughs throughout the year. Whereas a yearly average could take too long to gather that amount of data.
Step1 – Calculate the Effort
Depending on the size of your automation team, and also the relationships you’ve built with business teams, you can have multiple analysts working is different teams simultaneously to speed things up.
What I have done before on occasions when I was the single analyst on the team and had good relationships with teams and had their support, was to book short sessions to explain how to complete this data capture table and do a few examples, then have the team themselves go through this themselves. This allowed me to cover a LOT of ground meeting with multiple teams in a week and collating data for 100s of data in a few short weeks.
Another point to add, is it helps teams complete the tables you provide them if it is partially complete. If you’re lucky, your business may have a lot of process data in documentation or extractable from applications logs, or in Management Information (MI). Your team can fill in the data they can find, and encourage business teams to sense check, revise and complete the data table for their processes.
For an Automation standpoint, you can other process details for accessing automation suitability of each process ( cover this in other articles), but to demonstrate this Pareto chart your team as a minimum need to collect Process Name, Average Handling time and Work volume.
The Effort of a process is simply multiplying the Average handling time with the Volume of work. E.g., if a process takes 2mins and is run 100 times a month the staff effort is 200 minutes a month
Step2 – Calculate the Effort%
With Efforts of all processes calculated (for your business or for your department, depending on your scope of your program) you total up the effort for all processes together. This on its own can show you how much time your entire business or department are working on all activities that you’ve identified. If there is a significant difference between the amount of staff and total process effort, this will indicate that there are still a lot of processes and activities that you’ve missed.
The Effort percentage for each process is then calculated by (Process Effort)/(Total Process Effort)
If all processes make up 5000 minutes a month and your process is 200min a month, that process’s Effort % = 200/5000 = 4%
Step3 – Put Effort in descending order
With Effort% calculated for all processes from all teams in your table, put processes in order of Effort%, so the process with the most effort at the top.
Step4 – Accumulate Effort %
Create a new column for Accumulates Effort %. When you’ve ordered the processes, add the process effort % of the first process in this column. Then add the 2nd process’s Effort %, then add the 3rd process’s effort to the Accumulated total, and so on.
As you continue adding each process’s Effort % to the Accumulated total this to continue towards 100%, when all have been added up. You can see how this works on the most righthand column.
Step5 – Find the 80% mark
With your long list of processes organised with the most effortful process at the top, all you need to do now is to find the 80% mark and skim the best processes off the top.
However, the Pareto chart is a powerful visual to show senior leadership where you want to focus and how big of impact your ventures will be.
Excel on latest versions has a Pareto version, where the histogram bars is the effort for each process, and the line curve is the accumulated % of each process.
You can find the 80% mark on your Pareto chart and highlight the processes you wish to automate.
Automation Analyser tool
As mentioned earlier, as your analysts work with each target team, there are other data points that they can collect to assess whether a process is suitable for automation, and how suitable. Also, I mentioned how an Automation Opportunities Map coupled with a Pareto Chart can accelerate your automation program. LeanIA’s analysis tool has this all in one, were your whole team can drop data gathered from different teams into a central location to be analysed for assessing and identifying not only the best opportunities for your team to focus on, but suggests a priority order for your team to focus on the right projects first, allowing you to build momentum as your roll out automation without stalling your program.
There’s lots more this application can do, as you have a Opportunity bubble chart at the department/Team level, and when you chose your target team, you can dive deeper to look at a bubble chart of opportunities just for that team. These visuals and tables can easily be copied for presenting to your leadership team
Subscribe to my YouTube channel Tony IA (Intelligent Automation, Simplified) for videos created weekly, 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.