Progressive manufacturers are automating thousands of hours, onboarding dozens of digital workers, and expanding intelligent automation rapidly beyond core RPA. These organizations have broken the century-old “this is how we’ve always done it” industry mold and embraced the new reality of digital leverage. Even more impressive, these organizations have established hyperautomation momentum in relatively short order executing a regular rollout cadence of technology while maintaining a backlog of projects.
With the understanding that it is a question of when, not if, hyperautomation will be adopted by manufacturers, how do some organizations achieve momentum so quickly while others remain in various stages of limbo?
In this article, we will reveal how lean six sigma and hyperautomation can converge and complement one another to create digital lean momentum when the proper balance of governance and culture are prioritized.
Manufacturing Lean Six Sigma and continuous improvement teams are tasked with moving organizations forward by driving efficiency and eliminating waste. Their core activities are seeing problems, fixing and solving those problems, learning, and sharing the learning to continuously improve.1 Intelligent automation (or hyperautomation) is a combination of artificial intelligence (AI) and robotic process automation (RPA), where AI enables insight-driven analytics, decision-making, and personnel management, and RPA automates processes and reduces human participation in them. IA, via Ashling Partners application, reduces waste via three areas of focus–efficiency, effectiveness, and experience.
There is no doubt that these tools go hand in hand, but HOW?
Lean Supporting IA
First, let us look at how lean compliments hyperautomation through the lens of common obstacles of IA integration.
In a recent 2021 State of Automation2 survey conducted by Ashling Partners, change management and awareness/education were recognized as top challenges in scaling automation programs. Often overlooked and undervalued, the discussion around digital transformation is critical.
These programs, quite literally, are changing the future of work for those in Finance, Supply Chain, HR, Engineering, Quality, etc. “It’s not that people are being replaced by hyperautomation, it’s that the skills they need are changing.”3 Change management is a foundational element of CI/Lean that should be utilized to both plan for IA transformation through education and communication as well as carry out a deeper conversation. WHY is automation a priority for the company? HOW can you get involved? WHAT automation means for your job and the company as a whole? Utilize their cross-functional abilities to bring your organization to the middle drawing out ideas from subject-matter experts and filling your automation funnel.
The reality is, hyperautomation is not only bringing about a competitive advantage for business and profitability, but also ushers in significant quality of life improvements to its workforce. An RPA leader recently shared they were most proud of creating improved communications and ease of work for their supply chain team through process automation. Their employee engagement continues to accelerate as they are effectively “taking the robot out of the human”.
Building further on this application, it would be advantageous for organizations to leverage CI/Lean teams for process mapping on the front end of automations. As Bill Gates accurately stated, “The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency.” Leverage existing CI/Lean teams to map end-to-end processes as they have the experience of engaging horizontally and vertically within your enterprise.
IA Accelerating Lean
We can acknowledge lean as a proven method for identifying problems, finding their root cause, and developing solutions. How can we use hyperautomation to magnify lean processes?
Bain finds that while traditional lean typically produces a 15% reduction to key operations costs, digital lean adds a 100% improvement on top of that, for a 30% cost reduction.4 Utilization of advanced analytics, machine learning, document understanding, and process mapping can assist continuous improvement teams to make higher-quality decisions.
Data collection and analytics are a large part of lean projects. It is common practice for lean/CI teams to pour through piles of paper and data sets in the interest of trend analysis. IA can reduce the cost and cycle time while quickly finding patterns in complex systems and data that traditional analytics might miss resulting in faster time to market to internal customers.
For example, machine learning (ML) uses statistical modeling and algorithms to learn and improve the accuracy and confidence of a decision without programming. Leveraging machine learning, the industry 4.0 themes turn to the prediction of demand rather than forecasting: prevention of downtime rather than reacting to it.
The Convergence of Digital Lean
Here is the takeaway, intelligent automation is in acceleration mode. 82% of respondents stated that their organization’s automation budgets would be increasing in 2021; in fact, 18% of those budgets would be increasing more than 50%.2 Speed and proper execution of IA is the competitive differentiator to maximize production, minimize waste, and enhance operational efficiency.
Leveraging existing CI/Lean teams with IA adoption is only a question of structure. Their relentless culture of process improvement should be reason enough, but they can also bring scalability and sustainability to your program.
For more information on leveraging your existing CI/Lean team or accelerating your hyperautomation strategy utilizing a holistic approach, contact Ashling Partners here.