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Solving the Intelligent Automation dilemma: A comprehensive guide to scale

Solving the Intelligent Automation dilemma A comprehensive guide to scale-Saxon AI

Enterprises are increasingly adopting Intelligent Automation to boost productivity, reduce costs and optimize their processes. Now, you can not only enhance and upgrade processes such as invoice processing, customer relationship management, inventory control, onboarding, and many more with automation, but you can also successfully scale Intelligent Automation at a low cost. 

Many organizations have embraced intelligent automation as they evolved their working methods 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, and Artificial Intelligence coupled with business process management (BPM) and robotic process automation (RPA) have made Intelligent Automation (IA) an exceptional solution. Integrating IA augments employee productivity and customer experience, executing the processes faster, better, and cost-effectively. 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

Scaling intelligent automation poses significant challenges for organizations. While many may initially worry about the lack of skilled resources, the reality lies in effective management and implementation. Let us explore the common challenges faced when scaling automation:

Lack of clarity in Intelligent Automation vision and strategy:

Organizations must define clear goals and objectives for their IA initiatives and align them with the overall business strategy. This includes evaluating existing processes, identifying areas for re-engineering, and ensuring employees, processes, and technologies are ready for automation.

Absence of leadership buy-in: 

Leadership support and commitment are vital for scaling intelligent automation. Leaders need to understand the value proposition and potential benefits of IA, and actively champion its adoption throughout the organization.

Improper alignment between technology and business stakeholders: 

Successful scaling requires close collaboration between technology and business stakeholders. This alignment ensures that automation efforts are aligned with business objectives and deliver tangible value.

Knowledge isolation: 

Effective scaling necessitates sharing knowledge and best practices across the organization. Siloed information can hinder progress and limit the potential of intelligent automation. Encouraging collaboration and knowledge sharing is essential for success.

Incomplete measurement of ROI:

 Not being able to measure and understand the ROI (Return on Investment) or rather, the true value of Intelligent Automation is another challenge. While cost reduction is a visible benefit of Robotic Process Automation (RPA), organizations must consider other factors that contribute to the overall value. These include risk mitigation, cost avoidance, improved customer experiences, and increased employee satisfaction. By measuring and understanding the true ROI, organizations can realize the full potential of IA.

 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 your organization’s overall business strategy. Vice versa, the organizational structure 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.    Assess the existing business processes and identify possible re-engineering opportunities. 

2.    Determine the missing links in your processes.

3.    Evaluate the readiness of your employees, processes, and technologies for Intelligent Automation? 

Align your organizational structure to support the IA strategy and foster a culture that embraces automation. Develop a well-defined engagement model, change management program, and training and communication plan to ensure employees are prepared and capable of working seamlessly with IA.

Design a model supporting continuous improvement

To identify the processes suitable for scaling intelligent automation at a low cost, you can utilize process discovery, process mining, and data discovery techniques.

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 that 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 analyze enormous amounts of data and discover the hidden patterns and deep insights which secretly drive business challenges. External data sources, such as demographics and economic factors, can also contribute to identifying automation opportunities.

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

Democratize the endeavor 

Active involvement of internal and external stakeholders can democratize the scaling approach of Intelligent Automation and keep costs low. You can leverage low-code/no-code platforms to empower citizen developers who possess practical process knowledge. Their insights, combined with the right tools, bridge the gap between automation solutions and business processes, resulting in cost-effective scaling.

 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, that too keeping the costs low. 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 

As organizations shift towards digital transformation, rethinking and redesigning specific processes are inevitable while implementing intelligent Automation. Introducing it 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 interdependencies and areas that can be augmented with IA. 

4.    Increase stakeholder ownership and allocate resources to implement IA via no/low-code platforms. 

Take Away 

Focus on impactful use cases that leverage your organization’s strengths when embarking on your automation journey. Scaling intelligent automation successfully and keeping the costs low requires careful planning, clear strategies, and active engagement from leadership and employees. By embracing IA and implementing the recommended approaches, you can unlock the full potential of automation for your organization’s growth and digital transformation.

Ready to automate your processes and scale intelligent automation cost-effectively? Contact us at Saxon for tailored solutions that drive efficiency and empower your organization.

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