Scaling Intelligent Automation Is Like Feeding A Panda

Enterprises are adapting Intelligent Automation increasingly as the integration of IA (Intelligent Automation) has led to a boost in productivity and reduced costs across a wide range of internal and external processes. Now, you can not only enhance and upgrade the processes such as Invoice processing, customer relationship management, inventory control, onboarding, and many more with Automation, but you can also scale Intelligent Automation successfully.

Many organizations have embraced intelligent Automation as they evolved their ways of working and restructured their operations to suit the new way. As a result of the pandemic-driven changes, there is a significant shift to digital and remote operations. Simple process automation is being outperformed as natural language processing, computer vision, machine learning, cognitive Automation, and analytics have made Intelligent Automation (IA) an exceptional solution. Integrating IA augments employee productivity and customer- experience, executing the processes faster, better, and cost-effectively. All the while, they are resolving some previously unsolvable pain points and relieving employees from the burden of performing error-prone, tedious tasks.

The challenge of scaling up

In the quest towards a comprehensive adoption of Intelligent Automation, the significant pain points that enterprises experience is the challenge of scaling up. While the initial response may be to fret about the inadequate skilled resources available to implement this technology throughout the organization, the reality is entirely different. It is more about how the resources are managed and implemented. Let us look at the usual challenges that enterprises face while scaling Automation:

• No clarity in Intelligent Automation vision and strategy
• Absence of leadership buy-in
• Improper alignment between technology and business stakeholders
• Knowledge is isolated.
• Not able to clearly measure and understand the ROI (Return on Investment) or rather the true value.

For instance, when using RPA (Robotic Process Automation), you can see the visible value (ROI) is cost reduction. But what about other factors which can further augment the entire process? Risk mitigation, cost avoidance, and soaring customer and employee experiences? Once you consider these factors, you will find tangible results.

Thus, we recommend a strong strategy, a rational operating model, a democratic approach, and complexity management to scale Intelligent Automation up successfully. 

Develop a clear strategy

At the start, it is crucial to define the goals and objectives of the IA initiative and align them with the overall business strategy. Vice versa, the organizational structure, too, has to be aligned with the IA strategy and culture to support the IA capabilities seamlessly. The organization must have a vision of what they want to accomplish. Since Automation brings about considerable and immediate impacts to the entire organization, the organization should have plans ready for overcoming the possible challenges which may come up and address them in the pilot stage itself. 

Some relevant questions to ask at this stage are:

1. Access the business processes that exist and possible re-engineering scopes.
2. What are the missing links in the process?
3. Are the employees, processes, and technologies up for it?

The organization can develop a structure that will support the IA strategy. It can include a well-defined engagement model, a change management program, and a training and communication plan to support and prepare the employees to work seamlessly with Intelligent Automation or with their digital co-workers or digital assistants.

Design a model supporting continuous improvement

Process Discovery:

First, the organization must figure out and identify the processes and interactions within itself that can be automated. Process discovery is a valuable program for identifying the processes which can be addressed with Automation. Once installed on the users’ computers, this IA program records their clicks, interface, and process steps as the employees do their regular work. Machine learning application present in it analyses the data. Once it creates a list of observed processes, the program presents the potential areas for Automation. It ranks them by the benefits and analyses the criteria of the number of people performing the process or the process length.

The program also presents a detailed process analysis where it portrays each process in flowcharts showing the various variants. Thus, process discovery technology can effectively accelerate intelligent automation implementation and increase the number of use cases.

Process Mining:

Process mining solutions access the details from the logs of the ERP systems of an organization and can furnish the details of each process execution. Both process discovery and process mining solutions combined can yield noticeable results.

Data discovery:

Data discovery solutions can scan enormous amounts of data and discover the hidden arrangements and deep insights which secretly drive business challenges. It also considers the information present with the companies’ external sources such as demographics, economy, weather, etc.

When well-defined, the tools and processes for monitoring and measuring value will augment and enhance the processes. Many times, organizations consider tech-related endeavours to be stand-alone attempts. But when scaling intelligent Automation, the value will maximize mainly when the process is a continuous improvement initiative.

Democratize the endeavour

Organizations can democratize the Intelligent automation scaling approach by involving internal and external stakeholders to work and learn side-by-side. From using low/no-code platforms to building solutions, citizen developers can bridge the gap between automation solutions and business processes as their practical process knowledge and intuition combined with the right tools can aid in scaling up intelligent Automation. Their automation efforts and ideas in certain areas can make the entire process much more cost-effective.

 Complexity management

Even though an organization has identified the opportunities to apply Intelligent Automation and has achieved remarkable results from the pilot project, it may need help to derive its full potential as they have yet to implement IA across its teams and geographies. When we address Automation to the processes in an agile manner, allowing multiple teams to work on various parts of the process simultaneously, we can see the value of IA enfolding. As the suite of automation benefits enlarges, many processes with similar elements can be up for reusability, accelerating delivery and cost-effectiveness.

Scale intelligent Automation up

As organizations shift towards digital transformation, rethinking and redesigning specific processes are inevitable while implementing intelligent Automation. The introduction is the simple part of the process; scaling it up to its real potential is the ultimatum. 

1. A clear strategy and operating model are crucial.
2. Initiating with the well-defined processes first, optimizing them with IA
3. Finding out the possible interlinks which be augmented with IA.
4. Increase stakeholder ownership and resources to implement IA via no/low-code platforms.

Take Away

Are you looking to automate your processes? In your automation journey, though there is no “one-size-fits-all” policy, the key is to focus on impactful use cases and start on the journey that considers your organization’s strengths. Then we at Saxon can help you with your journey and scale Intelligent Automation up to your full potential.Get in touch to have tailored solutions for your processes.