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Is Low-Code Automation Really That Simple?
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There is a clear mismatch between the work undertaken by humans and their actual capabilities. The fact that digital workers are more suited to undertake that work instead is driving the adoption of intelligent automation.
It’s easy to see why. Digital workers can work 24/7/365, completing monotonous, repetitive tasks, with no errors. They are usually 10-20 times faster than their human colleagues. They can work across all industries, with almost all IT systems, via APIs, and can be integrated with cutting edge machine learning technology.
The trend towards the adoption of digital workers and automation software is set to continue into the future, according to a wealth of predictions:
So the question is not whether intelligent automation will be used, but how best it can be deployed to its greatest advantage. As we have seen over many years of working with organizations in different industries, the greatest benefits derived from intelligent automation are realized when companies are ambitious in their plans for transformation.
However, most companies start with simple task automation, prioritized by business value. It’s a pragmatic strategy that delivers benefits, and normally gives a lot of hours back to business, but is often simply making existing processes work faster.
As a next step we see the introduction of process excellence, lean practices and a focus on sub-processes in a department. As with task automation, the main focus is to eliminate repetitive and mundane tasks, rather than achieve transformation.
Following process excellence, companies start looking at cross-department end-to-end processes, and automating as much as possible in each one. At this stage companies introduce more intelligence to the digital workforce, whether that’s intelligent document processing, or automated decision making.
The fourth stage is transformation, where digital workers are part of workforce strategic planning, and they are leveraged as a differentiating factor to creating new offerings and capabilities.
Organizations move through these stages at different speeds. Some organizations focus for years on task automation only, while others begin their journey at the transformation level from the beginning.
In time, organizations find that they get closer to having automated end-to-end processes, sometimes without even having that as their target.
The gamechanger in all of this is a shift in organizations’ mindsets and approach to intelligent automation. When they have a vision that around 30% of the work in their organization will be done by digital workers, they also have to develop a new approach to automation. Visionary leaders approach intelligent automation as transformation projects, not just in the way work is done, but how they do business.
Imagining the future of work means planning how to manage an existing workforce. Some roles will disappear and some new roles will be created. There will be shortage of skills in many professions, so how will you become an attractive employer to attract the best people? How should you re-skill your existing staff? How can you use the talent you have in the best possible way and get the organization ready to face the future?
In a shared service center, for example, it is very likely that many tasks and processes can be automated. One bank that automated its onboarding process was able to redeploy 75% of their onboarding team to more valuable work, for example.
In product development, which requires a great deal of innovation and creativity, there is a much bigger need for human workers. Healthcare is strongly human interaction centric, which means the proportions will be very different. The goal of automation is to free up doctors’ and nurses’ time to be able to focus and dedicate more time to what they are there for, which is to treat their patients.
Compare that to manufacturing, where the focus is on mass-production, resilience, efficiency and data. Here digital workers can be incorporated to meet cost cutting goals, while freeing up employees’ time to be innovative and focus on creating new business opportunities.
Having considered the human element and where digital workers could be used, it’s important to analyze end-to-end processes such as order–to-cash, procure-to-pay, customer acquisition, or sales lead-to-closing.
It’s then possible to design intelligent automation for straight through processing with the support of process excellence specialists and automation architects working together with an automation first mind-set. This way of working takes more time to do the analysis and process re-design, but does give much higher benefits.
Outside-in, or zero-based design, is a methodology that has proved to be efficient for companies and organisations looking for transformation and radical change. This starts with imagining what the optimal end goal will be. What’s the result you are aiming to deliver? What’s the customer experience you are looking to provide? By beginning with this kind of goal and working backwards, it becomes clearer how to use intelligent automation to get to the optimum results.
The next stage is to think about data and what is needed to complete the different steps of the customer journey or process. Where do you find the data and where is it created?
An intelligent automation platform and methodology brings together all of the elements that can transform a business. At Blue Prism, we’re making work smarter and more productive, so people are free to do great things.
Designed to strengthen the enterprise, Blue Prism’s intelligent enterprise automation platform connects both the human and digital workforce with systems, cognitive tools, applications and technologies, including AI, machine learning, OCR, and the Blue Prism Digital Exchange, an ecosystem of ready-made automations available to business users at the click of a button.
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