End-to-end intelligent automation is not just a matter of better, ‘smarter’ automation, it also provides a platform for organisations to adapt in the face of business disruption. The past few years have shown that operational challenges have intensified, fuelling the pressure on driving productivity and reducing costs. The pressure is currently staggering more than ever with the tremendous increase in energy prices.
That makes Intelligent Process Automation a leading force in today’s competitive market and a key factor to innovation, a sustainable, future proof business strategy and a way to reduce costs.
Intelligent automation initiatives are characterised as highly inclusive efforts across a business process. But how do you prepare for success with such automation initiatives? And secondly, how do you put it to practice and gain long term success by scaling automation across the whole organization?
In this blogpost, we’ll zoom in on how to prepare for your Intelligent Automation (IA) journey with actionable guidelines, and a special focus on value discovery and how Model8.ai can help in this by leveraging process insights with Process Mining.
The share of companies adopting automation technologies is steadily climbing, according to a McKinsey Global Survey on the topic. Yet few of these companies have achieved automation’s full potential: although most respondents say it’s possible to automate at least one-quarter of their organizations’ tasks over the next five years, less than 20 percent say their organizations have already scaled automation technologies across multiple parts of the business.
We believe scaling automation starts with incremental innovation (take a look at a recent blogpost by our Humain.ai —Digital Evolution, Accelerated. colleague Toon). Yet even at a granular level, process improvement should be connected to over-arching business objectives, such as cost reduction, increases in efficiency, and digital transformation. Doing so will justify the effort and demonstrate explicit, tangible results.
Therefore, make sure to start with the bigger picture in mind to maximize ROI on the long term; it is important you think strategically about automation from the beginning.
Below foundations will help you prepare for your IA journey by:
With so many existing and emerging technologies available at their fingertips, organizations need to have a vision and strategy for intelligent automation to succeed. Reflect on:
Answering these questions will help you to develop and nurture a vision for your Intelligent Automation Journey, based on the organisational strategy and goals supporting long-term success. It is not about the technology itself, it is about people (your employees, your suppliers, your customers, your partners,…). Technology platforms act pure as enablers to augment the human capabilities. So with a strong vision, you are able to empower the people to embed and scale technology across the organization (forget these silos). In the end, it will help you build a unified workforce of people and automation — each handling the processes most suited to their capabilities.
Build a strong business case for automation and clearly state the purpose, and how people and automation will work together. Make sure to link the business case(s) to your vision by indicating how automation will drive strategic objectives.
Next to that, we advise organizations to build a capacity within their business specifically for automation, to ensure that automation projects can scale effectively. This capacity, typically called a Centre of Excellence (CoE), is a central group dedicated to automation that provides leadership, best practices, and support for all improvement initiatives. Again this is not focused on one technology. Build a CoE that is governing, managing, and supporting different technologies or platforms able to optimize, improve and automate business processes. Think end-to-end and capture the full scope of automation. It is fundamental to empower people and use their ideas, this will make them more engaged, drive continuous process improvement and facilitates their buy-in.
Discovering specific processes that are good candidates for improvement is vital to the eventual ROI — but how can we do this? And can technology help with this?
A well-known methodology is to map out the current as-is situation through manual value discovery. This methodology mainly relies on interviewing SME’s and business process owners, explaining the different steps they take and how a process is performed.
Although the knowledge of those who execute and own the processes is integral to any continuous process improvement initiative — by solely relying on manual discovery, you run the risk of missing insights, not capturing the bigger picture, or getting subjective results.
That is why Model8.ai stands by a complementary, hybrid approach: by adding Process Mining to manual discovery, we provide visibility that generates insights, leading to powerful improvements: a wide and robust foundation for a process optimization and automation roadmap.
Using process mining, one of our key technologies, we provide an objective, data-driven approach to process improvement. It is a continuous, step-by-step methodology to discover, enhance and monitor your business processes.
Process mining makes the value discovery process more objective and complete, and prevents insights being missed or overlooked during manual discovery.
By now you have some good guidelines on how to get started with Intelligent Automation, and how Process mining solves several major challenges in value discovery: It brings speed, analytical power, and fact-based accuracy to the problem of process fragmentation, inefficiency, and lost value in business operations.
Process mining brings speed, analytical power, and fact-based accuracy to the problem of process fragmentation, inefficiency, and lost value in business operations
But a diagnosis is not a cure. Therefore, Model8.ai helps with the right approach and expertise to transform insights into lasting change.
Jonas Maeyens is the Managing Partner & Process Insights Lead at Model8.ai and part of RoboRana Group
