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What does the future hold of Manufacturing?

Skills shortages, demand forecasting and inventory management are still some of the toughest challenges in manufacturing today. But can a digital workforce help solve some of these pains?

Skill shortage

81% of leaders in manufacturing surveyed in a report by Crowe (a leading audit, tax, advisory and risk firm), said they had difficulty recruiting skilled staff, due to various issues. The main being a struggle to find the right skills, though Brexit would have a significant impact too

The skilled workforce, mostly baby-boomers are aging and retiring, though they are hardly being replaced by new graduates how are tending toward more cutting-edge technologies. I, myself opted to move into fintech and automation instead of perusing a potential engineering career in Formula One or Aerospace

Deloitte estimated a job shortage of about 2.4 million in manufacturing by 2028 in the US alone, that’s a $2.5trillion impact.

Can intelligent automation provide a solution for finding the right skillset more effectively, can this technology work with works and physical robots to help manufacturers do more with less?

Skills shortage: finding a needle in a haystack:

Training and knowledge retention are some of the key solutions to solving this issue, as well as attracting skilled labour and graduates in the first place. And though Robotic process automation can’t assist with manual tasks to make up for the shortage in skills workers, Intelligent automation (RPA and AI) can help manufacturing businesses find the right skillset or right apprentice who will be a great addition to their team.

CV filtering is not new, and there are some very good CV analysis software out there which should be considered if you have the budget. However, a cheaper and effective way is combining RPA and Natural Language AI to check for such things as keywords, phrases, calculate years of experience, to identify your top 10% most suitable applicants and can even part-automate the initial interview setup, on-boarding or rejection processes

This can be a fairly quick set up– saving your hiring team hours of time scanning CVs and responding to job seekers. AntWorks has an interesting cognitive machine reading solution which is quite straight forward to customise and train, and can work in tandem with your RPA provider of choice

Skills shortage: augmenting existing staff:

Augmenting existing staff with RPA and AI can considerably improve productivity, accuracy and compliance, and by automating your back-office processes, RPA can collection and share data amongst legacy systems that had previous not communicate well with each other.

More data on digital processes leads to better reporting and in the world of lean manufacturing, better insights for re-engineering processes

Robotic process automation (RPA) is an extremely versatile software platform which allows businesses to quickly build automated processes by mimicking the clicks and keystrokes of staff for specific processes and tasks. It can only work on digitised processes that do not require any human intuitive, as an RPA robot can only make logic-based decisions. RPA is most suitable for high volume, repetitive tasks

HR, Finance and Accounting are some of the common areas for automating processes. Here are a few of the processes that can be automated:

The best place to start is to understand how worthwhile adopting RPA would be by calculating how much potential savings exists in your business right now.

What is the total effort in manhours for manual processes like the ones mentioned above?

A simple calculation of (volume of each process) x (average handling time of each process). You may uncover six, seven or even eight figures of untapped finance savings if these processes where automated

Find an automation consultant to help you determine the complexity, timeframe and cost for implementing these automations, to determine the payback period and ROI

If the business case stacks up, it’s time to start thinking about this strategically. Look for expert advice to stand up a Centre of Excellence team to successfully deliver automation company-wide

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

Isometric smart industrial factory. Automated production line, automation industry and factories engineer workers. Industrial manufacturing teamwork innovation technology vector illustration

Automating supply chains and logistics

Did you know, T&L businesses have more untapped automation value than most other businesses?

Supply chain: “A supply chain is a network between a company and its suppliers to produce and distribute a specific product to the final buyer” [1]

Logistics: “the overall process of managing how resources are acquired, stored, and transported to their final destination” [2]

McKinsey Global Institute estimates that the transportation-and-warehousing industry has the third-highest automation potential of any sector [3]. Out of the top 10 challenges of Logistics Fleetroot has suggested, there are 8 that Robotic Process Automation (RPA) and Intelligent Automation (IA) can immediately address, with low start-up costs and fast ROI (potentially seeing financial savings and non-financial benefits in-year)

  1. Reducing transportation costs
  2. Improving Business Processes
  3. Enhancing Customer Service
  4. Improving Supply Chain Visibility
  5. Supply Chain Finance
  6. workforce Shortage
  7. Government Regulations
  8. Technology Advancements

Let’s look at the 3 key themes here where RPA could be applied to ease a lot of the pain being experienced in your industry now and are likely to continue in the near future

1. Reducing transportation costs

Fleetroot estimates that 30-50% of logistics expenses are transportation, this is a considerably large problem that was made much worse in 2020, however this also means that there are significant savings that can be gain through automation in this area.

Working for a Utilities company many years ago, we used a customised Fleet management system that calculated the most cost-efficient routes for each of the hundreds of national driver to make each day, this system recalculated in real-time and update drivers of their schedule. In the continuous improvement team, we analysed details down to the amount of equipment held in each van and the type of fuel drivers were using to find opportunities for further cost savings.

However, one key thing seemed to be missing for both our analysis team and the management system, access to the full data picture. Many of the legacy systems did not speak to each other, so it was difficult for our team to gain access to the data we needed, and it seemed to me that the fleet management also had the same handicap

With the introduction of RPA, systems can exchange data, automated processes can better monitor back-office activities and data is much easier to retrieve. With better data analysis leaders are able to identify different behaviours and bottlenecks leading to re-engineering processes so that they are more efficient, more user friendly and can encourage more positive behavioural shifts.

2. Visibility, transparency

Looking back at my time at Lockheed Martin, one of the world’s largest systems integrators, it is apparent that Robotics, automation, and AI have been in logistics for a very long time. However in the dawn of Robotic process automation and intelligent automation, automation can be extended passed just physical robotics, and process automation is now more versatile and easier to implement.

Even today, there are logistics companies that rely on huge, intricate spreadsheets to manually manage costs and other data. 47% of supply chain executives still rely on Excel, with almost 70% of companies using Excel for supply chain management

In additional, data throughout the supply chain is typically fragmented so there is no single source of truth, allowing more innovative and wide-spreading companies to overtake a large piece of that space.

Through RPA, collecting and sharing data and information through automated processes will give leaders more visibility and control on what is going on under the hood and thus reduces risk. This means better forecasting of demand, reducing lead times, reducing the silos internally from department to department as well as externally between supplier and customer.

3. Labour shortage, customer service and process efficiency

We are all feeling the sting of 2020 due to the China-US trade wars, Brexit, and Covid-19, which will inevitably continue to hurt business throughout 2021

As we see huge shifts in the economy and key industries from the ‘old-way’, Governance and regulations has become turbulent. Our businesses will need to quickly adapt, re-adapt and build in these new business and compliance rules into their processes

Augmenting staff may be the best way forward as they can become more efficient, accurate and productive. Even if on the surface some business processes may not yield significant financial benefits, if automating them can maintain compliance then there is a cost avoidance saving.

In addition, by providing your staff with digital assistance, monotonous and repetitive takes can be handed over to your ‘digital workforce’ allowing your staff to focus on more value-adding tasks like customer service, or research and analysis to continuously improve your services, potentially find new services to offer, which previously weren’t possible or viable options

So what actually is Robotic Process Automation, and how is it used?

Robotic process automation (RPA) is an extremely versatile software platform which allows businesses to quickly build automated processes by mimicking the clicks and keystrokes of staff for specific processes and tasks. It can only work on digitised processes that do not require any human intuitive, as an RPA robot can only make logic-based decisions. RPA is most suitable for high volume, repetitive tasks

Here are just a few ‘Quick win’ logistics processes that are suitable for automation [5]:

  1. Scheduling and Tracking
  2. Order and Inventory Tracking
  3. Invoicing and Credit Collections
  4. Supply and Demand Planning
  5. Purchase Order Management
  6. Freight Management
  7. Returns and Refunds

Get started now – as “the future is already here”

If you can appreciate the urgency for getting familiar with RPA and IA, the first step is to educate your organisation, from the top down so that senior leaders are aware of and understand how to use intelligent automation (robotic automation and Artificial intelligence) to get tangible value.

But a step frequently missed is to also educate from the bottom up. Change will only work well when everyone is on board as anyone in RPA has learnt. The teams have access to the data and understand the processes, and will who will support the implementation process and will eventually own the automated solutions, not the IT or Automation team. “Emwpowered teams transform businesses”.

Find your Proof of Concept process – discover your quick wins, those easy to automate, back office processes that can deliver significant savings this year. Use a methodology like AEIO YOU® to use your business data to fish them out, and start building momentum

Automate strategically. Gone is (well should be) the time for tactical automation. Automating processes here and there wastes time, is less cost efficient and slows progression (see our webinar Proactive vs Passive).

Time really is of the essence and we just don’t have time for it anymore, as “The future is already here – it’s just not evenly distributed.” – William Gibson

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

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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

A:

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.

E:

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

I:

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

O:

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

Y:

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

O:

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.

U:

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

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4 Steps to building a Tech-Savvy workforce

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.