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Continuous Improvement: Important then, Fundamental now


If organisational leaders are going to harness CI for strategic business transformation, they’ll need to understand it — and not just in the current context. Delving into its historical relevance and evolution over the years can truly help today’s organisations appreciate the driving force of change that CI can be.

The pioneers of continuous improvement

Some of the earliest attempts at optimising industrial efficiency can be traced back to the Industrial Revolution itself. In the late 19th century, Frederick Taylor was the first man to scientifically analyse work and devise the most efficient method of completing tasks. Taylor’s recommendation of using of written documentation for every part of a worker’s job has echoes in quality standards used even today (ISO 9000 series.) During the same time, Frank Gilbreth emerged as an efficiency expert whose time and motion studies revealed that the key to improving work efficiency was reducing unnecessary motions and led to more research into the field of ergonomics.

Trailblazers of quality in the modern world

In the early 20th century, Henry Ford led the revolution in manufacturing with pioneering mass-production techniques that are still celebrated today. Other visionaries, such as Walter Shewhart, W. Edwards Deming, Kaoru Ishikawa, and Joseph Juran, made significant contributions to quality management by introducing concepts like Quality Circles, Statistical Process Control, Root Cause Analysis, and Quality Improvement. The emergence of the Toyota Production System (TPS) marked a pivotal moment with its relentless pursuit of the highest quality, lowest costs, and shortest lead times, introducing principles like Waste Removal, Kaizen (Continuous Improvement), Just-in-Time, and standard work. The pursuit of process improvement has captivated scientists, scholars, and researchers for decades.

‘The Machine That Changed the World’

Around 1990, Jim Womack decoded the Toyota Way and introduced the concept of Lean Manufacturing in his influential book, ‘The Machine That Changed the World.’ Simultaneously, Six Sigma emerged at Motorola, utilising statistics and the scientific approach to reduce variation and enhance quality. It was around then that the term ‘continuous improvement’ not only entered the business vernacular, but firmly cemented its place as a strategy in its own right.

Towards the end of the 20th century, CI methodologies and Lean principles spread to service industries such as banking and insurance, resulting in improved customer service and cost reduction. This shift also influenced product and software development, where practices such as Kanban were used to accelerate process lead times. As companies continued to leverage CI to maximise their advantage, it paved the way for mass digital transformations powered by technologies such as Robotic Process Automation (RPA), machine learning, and Artificial Intelligence (AI).

Today, a multitude of methodologies coexist, including Lean, Total Quality Management (TQM), Business Process Management (BPM), Business Process Reengineering, Agile, Theory of Constraints (TOC), Lean Six Sigma, AI, Machine Learning, ISO standards, and other digital approaches.

But if the history of CI tells us one thing, it’s that strategic use of data has always been at the crux of driving transformation, enhancing efficiency, and maximising return on investments.

The renewed importance of CI in the era of automation and AI

We’ve just established that CI is not a revolutionary concept. So why should businesses still consider it, especially amid recent breakthroughs in generative AI and machine learning? Isn’t innovation about adopting the new? Yes, but CI and new transformative technologies are not conflicting entities. In fact, continuous improvement is less of a tool in this context and more of an approach or philosophy that, when realised, allows organisations to harness the capabilities of new tools and technologies more effectively. In other words, CI has gained renewed importance in the era of automation and AI as it creates an environment where any new change can not only safely and sustainably play out, but its impact can be quantified too.

At first glance, CI might not feel as cutting-edge as AI, edge computing, robotics, or automation, making it challenging for operational excellence leaders to engage with CEOs and demonstrate the value of CI. But this is where they need to put on their Continuous Improvement leader hat and articulate to leadership teams that no matter how the business world evolves, it is imperative that processes continue to be improved by identifying and removing waste, as it is the only way to sustain growth, outperform competition, and continue to remain relevant to customers.

CI is not ‘still’ fundamental but ‘especially fundamental’ for businesses today

Adoption of new technologies is imperative for businesses today. However, rushing into implementations without doing the required legwork can undermine the credibility of new investments and diminish the likelihood of achieving the desired ROI.

Large-scale, transformative projects such as those that involve AI, robotics, or other cutting-edge technologies usually require large budgets and take time to roll out and deploy. This can turn into a waiting game for business leaders especially if their processes are outside the scope of the transformation. But with the appropriate CI skills, leaders can guide their teams to take a proactive approach to improving processes and removing waste which delivers results sooner. When individual team members can see their work translate into impact, it feels more meaningful, which further strengthens the continuous improvement mindset across the organisation.

CI skills along with access to comprehensive, standardised, and dynamic datasets allows leaders to identify and quantify opportunities, design effective processes, and pinpoint scalable automation solutions capable of addressing system-wide issues, which translates into significant macro-level benefits for their organization. CI tools such as Enlighten track every aspect of an operation, providing data that includes volumes, hours, backlogs, waste, value-add, costs, and FTEs for each activity, process, linked process, and client. This data-led approach expedites the discovery process, enabling leaders to swiftly identify quick wins and set the ball rolling on automation opportunities.

Not only do CI tools excel at using data and scientific approaches to provide visibility and help businesses solve complex issues, but as a methodology, it can also result in a cultural transformation. By design, CI includes people in the process of change and fosters a culture of continuous learning, which is invaluable in a rapidly evolving technological landscape.

In our next article we will debate whether CI is an art or science and answer the all-important question of how to bridge the gap between understanding CI and implementing it.

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