Posts tagged: Centre of Excellence

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?

”Empowered teams transform businesses”

If you’re a business leader, the COO or transformation director keen to bring intelligent automation into your business this is exciting news – but it’s important to note that “resistance to change” and “choosing poor use cases”, being the two most common reasons for why 50% of RPA and AI projects fail. This all boils down to a lack of education amongst analyst and consultant teams new to automation as well as technology knowledge gaps throughout the stakeholders who are impacts by it
There are tonnes of training programmes for how to build an automation software robot, and how to develop chatbots and programme AI solutions – but there is a lack of strategy, analysis and project delivery training in this automation and AI space
This type of training is one of the 3 things that we’re focused on providing our clients – we want to show you that -even if you’re late to the automation party, you can still get ahead of the game

“Automation is an anyone thing”

Robotic Process Automation aka RPA was specifically designed to elevate the pressures from the IT department from the demands of the tech-hungry companies. This demand was driven by customers wanting faster, more accurate, and more accessible, 24/7 omni-channel services. RPA gave business operations teams the power to control their destinies so to speak and build solutions to solve technical roadblocks caused by legacy systems, in a matter of weeks, instead of waiting for months or years for software upgrades.
By being a business led technology, in many instances it is the COO and operations directors who determine how it is used. Besides, they know the processes better than any technician or analyst and know how to get the most value out of their resources. There is a great need for the senior leadership team to have awareness and solid understanding of new technologies, benefits and use cases to navigate teams through the new digital world – upskilling needs to start from the top
Automation and AI requires investment in both training and technology so that the whole workforce is empowered, however many companies only train a handful of people in the core automation team

The empowered workforce approach

RPA market grew over 63% last year: an article in Tech Crunch a leading technology publication in mid 2019 saw an explosion on interest in robotic process automation. In fact by 2025, 97% of all businesses would have invested somewhat in RPA – we can safely say this technology will great impact all industries and business models over the next 5 years – as well as change the competitive dynamics in each market sector

70% biz believe RPA allows employees more human interaction: this recent study by business wire showed that “keeping employees engages and happy” led to successful digital transformation of businesses (take a look back at our “can’t get started, no momentum” webinar to get an overview of the RPA benefits

Even UiPath one of the world’s largest RPA vendors expressing the need to “keep employees at the core of RPA efforts”

McKinsey Global Institute report estimated that by 2030, automation will drive 75 to 375 million people to reskill and even change occupation. So on that final point, do we agree it’s time to upskill you staff? – and build a tech-savvy workforce?

If you’ve looked for training how to use cutting-edge technologies, most likely you’ve struggled to find the right training plans for your team – well let me explain why this is:

About 90% of all RPA trainers provide development and architecture training, the other 10% also do some basic analyst training to provide information for the developer, but you’ll probably be hard pressed to final a provider of training focus around the application and strategic delivery

This is also echo’d in other technologies, such as cloud and AI training – like Azure, Google cloud platform (GCP) and Amazon’s AWS – where all training focuses mainly on development and technical architect

We totally appreciate the importance of developer training however we would suggest that this lack of non-technology training for teams cause be 1 of the root causes for why 50% projects fail, and 98% can’t scale

 “ 50% projects fail, and 98% can’t scale” 

Teams are able to build the technology but teams struggle to manage projects and execute strategic plans for enterprise wide roll out – and by teaching 5000 students to help teams worldwide, helping firms and consultancies to set up and manage teams to both build and support automated solutions I’ve had the unique opportunity to peer behind the curtain and identify the roots to these grave statistics

Furthermore, by coaching and managing newly formed teams of analysts in RPA, I can see how an imminent flood of new analysts, consultants, programme and project managers in the market, with minimal tech experience will further reduce the success rate of RPA and AI projects.

Here are our 4 recommended steps for you, if you see the value that investing in teams to be more tech-savvy will bring to transforming your company:

STEP 1: AWARENESS – have a communications plan with a consistent message

1. Awareness training for your senior leadership team
2. Awareness training for Stakeholder teams (namely HR and IT)
3. Awareness training for staff

Core stakeholder teams such as IT and HR should be the first to know about these new changes so your business is physically, technically and emotionally prepared for the new changes

STEP 2: GET INVOLVED – provide Digital Transformation training for teams to get involved

1. Training the core team on the technology and how to implement it
2. Training staff on how they can contribute so they and their teams can benefit from the technology (this is augmentation not replacement)
3. Run regular workshops and lunch ‘n’ learns for staff to learn more, develop themselves and prepare for the new digital age

STEP 3: TOOLKITS – provide training on how to use tools and templates to implement automation

1. Training for tools for each role in the implementation process (portfolio manager, analyst, automation champion, other stakeholders etc)

STEP 4: AUTOMATION & AI ECOSYSTEM – train on a suite of new technologies

1. Training on various automation and AI technologies,
2. Learn the most common technologies such as:
   1. Process Mining and Process Discovery
   2. NLP (natural language processing) and chatbots
   3. Machine Learning and Deep Learning
   4. Computer Vision and ICR (intelligent character recognition)
3. Discover and learn new technologies that match the use cases in your business such as swarm intelligence, sentiment analysis, Datalakes etc.

So in summary, in order for a smooth and wide-spreading automation roll-out we encourage Centre of Excellence teams bring the whole company along on their digital transformation journey by; Building Awareness, Starting from the top down, training both the core team and stakeholders.

When starting your RPA and intelligent automation journey your team will inevitably come across some or most likely all of these challenges – let’s discuss how to overcome them, and potentially minimise the chance of them arising

Missing or unavailable data

When it comes to running successful RPA programmes, data is key. You want to measure whether the opportunities you’re exploring are worthwhile, and you also want to prove that benefits from the change have been realised.

Missing or inaccurate data gives a false view on the potential savings or return on investment of your automation incentives. You want to measure the weekly volumes and average handling times for each process as accurately as possible, so you can calculate the amount of FTE (full-time employees) effort these processes use, which will allow you to start prioritizing your opportunities.

It’s best to collect sample data and observe the process to sense-check the metrics. Some teams don’t collect data like weekly volumes or AHT (average handling times), and sometimes it’s difficult to extract data from the system. Also, unless you’re in manufacturing, it’s generally frowned upon to walk around with a stopwatch to time staff on how long their processes take to complete. To get a rough idea of AHT your team may have no other alternative but to ask several subject matter experts (SMEs) for their gut feel, however, recording the screen as staff carry out the process would be better

Staff’s resistance to change

One of the biggest challenges is resistance from staff who may be directly affected by the change. If they can’t see how it benefits them, why should they be interested? If they feel their job could be at risk, why would they want to cooperate? A good communications plan can mitigate the resistance, and conveying opportunities to upskill or re-deploy staff alleviates fears of being replaced and shows staff they are valued.

Getting buy-in should be first on the agenda and maintained continuously. You can keep staff involved with regular lunch-and-learns or periodic workshops that makes staff aware of the technology and shows them how to get involved. Keeping the door of your Centre of Excellence open and continuing to communicate with staff can relieve many tensions about introducing automation technology.

Loss of traction

It’s great if you have made a start by rolling out some POCs but perhaps things have gone cold and stakeholders have lost interest. If you’ve lost traction it could be because you’ve made the same mistake that countless other businesses make: you’ve tried to solve a really big problem or your team have chosen a very complicated process. These opportunities take far too long to deliver. When starting up, you need to deliver some quick wins regularly, mixed with some good-sized opportunities to get the momentum going. I’ll show you how to choose the right mix of processes to start with and how to prioritise the rest

No clear governance

If there are no checkpoints or no gated process, and roles and responsibilities have not clearly been defined, then no one is accountable for each step of the progress. Your project is at risk of going around in circles or halting all together. Having clear, written governance that is agreed by all parties upfront, and with senior sign off, is the only way to avoid this pitfall.

Not only do you need to know who is responsible for each part of the implementation process, there needs to be an agreed turnaround time for each step. Assemble questions such as ‘How long should it take to get robot access to applications, or for the Process Definition Document (PDD) or Solution Design Document (SDD) to be signed off?’ and ‘How long will it take for the bot to be handed over from the developer to the support team?’ Also consider that at each checkpoint or gate you need clear acceptance criteria.

Process clarity

The PDD is the most important document in this whole process. This is what translates a business problem, into a technical solution. RPA business analysts must manage the relationship between the SME & developer, so that the developer creates a bot that does what the business wants.

Its important that the process steps are well documented at a detailed level, showing the clicks and keystrokes the robot should make. The developer will most likely be unfamiliar with the process so there must be no gaps or jumps between one step and the next.

This document must include everything the developer needs to effectively become an immediate expert of the process. The developer needs to know:

• Where the bot takes the information from
• How it will receive it and in what format (e.g., what is the folder location, website address or email address, and will it have a specific subject title? Will the file be in xlsx or pdf format?)
• The precise format of the data (e.g,. what type of data is in each field, what is the file naming conventions are, and other data integrity information).
• What the bot must do with the information
• Where or to whom to send it.
• What time(s) the process needs to run, what days, and if there are any service level agreements (SLAs). This may determine whether multiple bots might be needed to process all cases in time to meet the deadline.

We take a closer look at the PDD document structure in the book Business @ the Speed of Bots

Documentation can differ from reality.

This links to the previous point. A major faux pas of your RPA team would be to rely on work instructions and other process documentation to design the automated process. What’s written down tends to be quite different to what actually happens. There are 2 simple reasons for this:

1.     Work instructions are usually written by the experts who know the process inside out. This is susceptible to ‘the curse of knowledge’, which means assumptive leaps may exist between steps, and the author may automatically believe this to be obvious.

2.     The team or individuals might have found potentially better way(s) to do the process after the instructions were written. In lean thinking, the best way should be the standard, so maybe it’s time for the team to find out which team member is the most efficient and use that person’s knowledge to update the formal process documents.

To avoid this pitfall, it’s always recommended to walk through the process with the SME. Shadow the person to observe how the process is executed in practice, so that your RPA analyst can fill in any gaps identified in the documentation.

Test vs. Live (Production) Environments

More often than people want to admit, bots can act differently in the live environments than they did during testing. There are several reasons for this but mainly it’s due to the application versions in the test environment being slightly older to that in the live environment.

Even if you have the most updated version in test, the bot may still act unexpectedly for unknown reasons, hence why a two-week, live test period is advised (or longer if the process is a high-risk, high-impact process such as one involving finances). During the test period the developer and support team can watch the bot closely and immediately fix any bugs.

We’ll look again at testing the process in both the test and live (or production) environments later on, but ensuring the test platforms have the most up-to-date versions to match the live environment as close as possible can minimize risks.

#rpasuccess #digitaltransformation #rpaimplementation #artificialintelligence

You can learn more about implementing RPA (Robotic Process Automation) and intelligent automation at Leania.co. On-demand Consulting

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