Q 743. Digital Lean is considered as the next big thing for improving process efficiency. Explain the concept of Digital Lean and also provide examples where this has been implemented.

 

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Digital lean simply put is a very potent combination of timeless lean principles and constantly evolving digital tech. to decrease waste and variation in processes.

 

Digital lean technologies comprise of IOT, AI/ML Models, APS software, Custom web development & Mobile Apps, Big DATA & Analytics etc.

 

As per Bain & Company, while traditional lean manufacturing has delivered substantial value, the integration of digital factory transformation has the potential to double the reduction in cost through lean activities.

 

As per Deloitte, Digital Lean has replaced predictive maintenance with preventive maintenance. Machine learning Algorithms predict machine downtime and auto-schedules maintenance work orders which helps to reduce both maintenance expenses and unplanned and planned downtimes.

 

In some of the big manufacturing companies, the factory managers have started allocating work orders to different production lines to improve schedule adherence by creating real life schedule adherence simulations through digital twin of a factory.

             

Online retail companies use predictive analytics to optimize inventory levels on the basis of real time demand thus reducing issues of over & under stocking.

 

In Health care industry, analytics is leveraged to streamline patient intake process which reduces wait time and improves patient experience

 

Smart meters and IOT sensors installed on equipment helps to measure and optimize energy usage.

 

To sum it up, Digital lean amplifies the impact of lean and the broader digitalization efforts.

The concept of Digital Lean combines the core principles of lean Manufacturing which are waste reduction, CI and customer centric processes with digital tools like IoT, AI, and digital twins. This gives more precise, real time data collection and analysis, providing better decision making and more agile operations.

Few of the key benefits of Digital lean are enhanced visibility, predictive maintenance, improved quality control, and increased flexibility.

In enhanced visibility tools provide real time insights into operations helping in easy identification of inefficiencies and helps address inefficiencies.

Under predictive maintenance AI and ML are used which can predict equipment failures beforehand and in turn reduces downtime and maintenance cost.

For improved quality control advanced analytics help in monitoring and improving product and services quality by detecting early defects in the process.

With increased flexibility digital lean helps in more adaptable and responsive processes which can adjust to changes in demand or supply chain disruptions.

For e.g. in consumer electronics siemens have applied digital twins to simulate and optimize manufacturing processes, helping to better resource utilization and faster time to market for new products.

For e.g. Toyota has integrated IoT and AI into their lean manufacturing processes to enhance production efficiency and reduce waste.

Digital lean has transformed how industries operate by making process smarter, more efficient and adaptable.

Lean is a process of continuous improvement techniques and activities used in manufacturing or service. “Digital Lean” is an advanced approach towards process improvement by combining the principles of Lean and Digital transformation technologies.

The traditional Lean process focuses on eliminating waste, improving efficiency and optimizing workflows whereas Digital Lean will integrate all Digital tools such as Artificial Intelligence, Robotic process automation, Internet of Things and advanced analytics of Lean to enhance the process. If the organizations would leverage digital technologies, then they can gain real time insights, improved decision-making, more agile and efficient operational environment.

Key concepts of Digital Lean would be identifying value streams, creating flow, utilizing a pull system, and eliminating waste through data-driven insights. 

·       Value stream - Map out the entire process to eliminate non-value-adding activities.

·       Creating flow – Ensure smooth and uninterrupted workflow.

·       Pull system - Produce only what is needed and reduce the inventory waste.

·       Eliminating waste – Streamline the processes and identify the waste which can be eliminated through data driven insights.

 

How Digital tools can enhance Lean when it is applied to these concepts –

·       RPA Automation – When automation is deployed it reduces the manual intervention and errors conducted by human.

·       Real-Time Data (IoT, Sensors, Digital Twins) – this will provide instant feedback and give real time update on the performance for process optimization.

·       Advanced Analytics & AI – AI will enable predictive maintenance and decision-making.

·       AI-driven Process Mining – AI driven process mining identifies any bottlenecks and inefficiencies dynamically.

 

Some of the examples of Digital Lean implementations –

Bosch and Siemens, the two leading manufacturers in home appliances and industrial equipment faced challenges in minimizing machine downtime and optimizing production workflows. Their manual inspections would lead to delays in detecting the defects and maintenance needs. These organizations felt the need to deploy IoT sensors and Digital twins. This helped them to continuously monitor the performance and detect any signs of wear and tear. The machines were now able to generate real time data which was used to create digital twins to simulate operations and predict failures if any.

AI algorithms were implemented to analyze sensor data and predict if a machine would require maintenance. This would prevent any unexpected breakdowns.

RPA was deployed for the quality checks to ensure seamless workflow and reduce human errors.

The above digital tools resulted in -

ü  15-20% increase in machine uptime, leading to higher production efficiency.

ü  25-30% reduction in maintenance cost due to predictive analytics.

ü  12-15% improvement in quality control by reducing defective products and rework.

 

Another example is of Meta (Facebook) a renowned social media platform. Meta receives billions of user-generated contents which gets posted daily across Facebook, Instagram, and WhatsApp. The content moderation team needs to manually review the content and tag the violations, which was time-consuming and prone to errors.

Meta developed AI models like DeepText and RoBERTa to automatically analyze the text, images, and videos uploaded on their site to detect policy violations such as bullying, hate speech, misinformation, violence, child exploitation etc.

This had reduced the need for human content moderators to manually review the content every time it was flagged. Reviewers would now focus more on the complex cases. Incase if AI incorrectly flags the content, then the human reviewers would provide feedback back to AI. This ensures that the system is continuously learning and improves the accuracy of identifying violating content.

By deploying automation, Meta was able to reduce manual moderation workload by almost 70 - 80%. Almost 90% of hate speech and harmful content was now removed automatically before the users would report it.

 

Hence Digital Lean can help multiple industries such as manufacturing, healthcare, finance, logistics, or telecom etc. to achieve remarkable gains in productivity, fraudulent activities, cost savings, and process efficiency.

Digital Lean is the application of lean principles in a digital ecosystem so as to minimize waste, improve the efficiency and in the process enhance the value delivered.

This is based on applying lean thinking and leveraging digital technologies

 

Key Benefits of Digital Lean (which are self-explanatory)

1. Waste Reduction 
2. Improved efficiency/productivity
3. Helps in data-driven decision making 
4. Helps in better communication and strong collaboration
5. Helps in continuous improvement 

 

Let us see how these benefits get reflected with few of the below examples

 

Example1 :   

An IT service provider wanted to address one of its insurance customer's problem. The Customer had a quarterly release for one of its key product's features (it was about having Policy and Claims Administration management systems for Individuals and Corporates)    

 

In a competitive market, the customer felt that it would be difficult to stay with its competitors if every release happens in a quarterly period. So it wanted to improve its time-to-market. This is where the IT Service provider(hereby, referred to as 'SP') applied the 'Digital Lean' approach. The customer organization, even though stated that the work was done through agile Way of Working(WoW) but it was more of a waterfall approach. 

 

Steps taken to address this problem:

a. The SP organization team provided(formed) a cross-functional agile team (along with an agile coach) whose job was to streamline the existing process such that the team is in a position to release the key product's features in every two weeks and also work upon the designated features that were to be developed newly, in an iterative and incremental approach

 

b. The agile Coach and the team identified the issues in the existing ecosystem with the help of an AS-IS flow of the IT delivery process. It also took cognisance of the value flow happened within the portfolio (of the key product). The agile coach spent considerable amount of time in his understanding of the current ecosystem and helped the agile team by sharing his profound knowledge to it. 

 

c. The team identified some area of improvements. 
   i. First with the expertise of the coach, it redefined the value stream for the key product as

there were some waste process steps involved. 

ii. Then it started to improve its continuous integration process which ensured that the code developed by team members were integrated into the codebase routinely thereby preventing code conflicts

iii. The team improved upon its Built-In-Quality - automation of unit testing (jUnit tool), automation of functional testing (Selenium)
d. Implementing DevOps - CI/CD pipeline properly - Automating completely Continuous Integration and Continuous Delivery processes - which means once the code is put into the Source repository (codebase for the key product), the Continuous integration server (here, 'Jenkins' was used) triggered the build automatically which ensured the code was tested(unit & functional) and deployed automatically in pre-prod environment (Automation happened till the Continuous Delivery part of the CICD pipeline). Then post a managerial approval it was deployed to Prod environment. 

 

The result of this whole exercise was that from a quarterly release the team was able to move to 2-weeks, a drastic improvement    

 

Example 2:

An IT service providing company helped one of its Banking customers who wanted to leverage AI (which it was using for handling its customer needs & internal operations) for improving its IT delivery. The cycle time for an end-to-end requirement was taking 16 days. With the usage of AI tools in each of the phases of Software Development Life Cycle (SDLC), the cycle time got drastically reduced to 4 days.. 

 

How did that happen?
a. The team had requirements done using JIRA AI - Atlassian Intelligence 
b. The team used Figma AI for System design
c. The team used Copilot for Code Development (Build)
d. The team used Selenium AI for Functional(System) testing

 

The learning curve involved has just kept them in the newer cycle time(4 days).The AI journey has just begun for them and is expected to see more improvement (in cycle time) in the future days!!

 

Example 3:

One of the retailers used DevSecOps as part of its Digital Lean Process, for improving its Delivery time cycle. It applied agile Way of Working as the SDLC for its flagship product and then used a AS-IS process for its delivery cycle and observed that it is spending considerable time in Non-functional testing requirements (Such as Security testing, performance testing) during the later stage of product development through lot of manual efforts and with plenty of rework effort, primarily due to security defects. So the retailer, leveraged DevSecOps which ensured that Security was put into every phase of the SDLC through automation. This resolved defects seeping into the product and also in the process virtually eliminated the rework effort spent for fixing defects based on security and thus improving(reducing) its delivery cycle time 

 

Other Industry Common Examples 

1. For early detection of disease, AI - IBM Watson Health is used - it helps in reducing human errors, provides patient services as well.

 

2. A patient got a high Blood Pressure and was hospitalized. His family was worried and he was there in the hospital for few days and his family members took care of him. Now all were staying in the hospital even though there was an attender (from the hospital) to take care of the patient as per doctor's advise.  The family had gone through undue pressure and also had to spend considerable amount of cost for their stay in the hospital room (room accomodation cost).  The patient was worried about all of this. This is where he thought of wearable device 

 

Wearable devices ensure that your health conditions to be monitored. Having a wearable device ( a IoT based device) can solve these kind of issues. With the device, monitoring can be done as the patient wears it. That would ensure that he/she can wear the device (move out from hospital, in the process) and do his/her routine affairs. The device would keep on providing constant data about the health condition of the patient.

 

The result was that the patient got discharged as his monitoring started to happen routinely through the device and he was discharged from the hospital before his scheduled date (he was kept for monitoring purpose only primarily for several days) and his family also left the hospital along with him and no further accommodation cost!!  

 

Conclusion:

This is the era of Industry 4.0 in which Digital Lean is a key aspect.  Digital lean provides the powerful capabilities of technologies with a lean approach, thereby helping organizations to achieve enhanced (superior) productivity, flexibility, adaptability, smart and well-connected systems, quick real-time decision-making. The examples shown above, elucidated some of these benefits 

 

 

Lean principles emphasis on cost reduction, focus on waste elimination, and customer demands drive processes. It provides a data-driven approach to decision-making and tracking root causes and hence can be applied to any domain. Lean often surfaces hidden issues and emphasizes on continuous improvement.

 

In the recent years, advancement in robotics, materials, and artificial intelligence are all building the future of manufacturing. Industry 4.0 and physical technologies define speed, waste reduction, and customer demands processes with digital nomenclature.

 

Hence, digital technologies and lean principles are intersecting in what is commonly termed "Digital Lean" which can be a powerful combination of timeless lean principles and constantly evolving digital technologies to decrease waste and variability in processes.

 

Digital Lean, also known as Lean 2.0 can be defined as the augmentation of traditional lean activities with technologies such as IoT, AI, digital twins, and more to increase factory visibility, productivity and agility.

 

For example.

In traditional lean, manufacturers adopt preventive maintenance as part of TPM initiatives, where maintenance teams schedule maintenance activities before equipment failure occurs. Hence the effectiveness often dependent on the experience of the maintenance team.

 

In digital lean, predictive maintenance replaces preventive maintenance. Machine Learning (ML) algorithms predict downtime of machines before they occur and automatically schedule maintenance work orders. This data driven approach helps factories reduce both maintenance costs and unplanned/planned downtimes (Deloitte).

 

Let's understand how digital lean can improve traditional lean waste (TIMWOOD) reduction

 

Transportation:

• Traditional Lean reduces the nonlinear processes scattered across the shop floor-that require transportation of materials from distant storage to the point of use.
• Digital can quantify the amount of transportation time required per product or process, enabling the identification of opportunities to better streamline and organize the shop floor. 

Inventory

• Traditional Lean methods allow products to be manufactured only in the quantity needed and at time required. Instability across the value stream is often absorbed in additional inventory.
• Digital Lean can enhance operations with real-time visibility of the work-in-progress inventory throughout the production process to identify unexpected inventory buildup.

Motion

• Traditional Lean processes address additional movements that don't add any value to the product and contribute to longer production times. For example, poor design of production lines and cells increase unnecessary motion for operators to complete value-added tasks.
• Digital Lean, through analyzing performance data or using augmented and virtual reality simulations, can better inform the design of layouts and equipment to optimize worker movement.

Waiting Time

• Traditional Lean approaches help mitigate waiting time in unbalanced operations, bottlenecks, downtime, and poor production planning where employees, materials, and assets are not adding value.
• Digital Lean reduces waiting through dynamic rerouting of operations based on updates on the real-time status of assets, quick identification of bottlenecks, and multiple simulations of optimized scenarios.

Overproduction

• Traditional Lean mitigates the overproduction caused by the asynchronization between demand and supply, including delayed demand signals and rigid processes constraints.
• Digital Lean can provide real-time visibility into the value stream to proactively adjust capacity, avoiding the building of goods that are not required.

Overprocessing

• Traditional Lean can help avoid processing not required by the customer that is performed across the value stream, such as over-inspection or unnecessary high tolerances.
• Digital Lean connects and integrates the life cycle of a product (and the value stream) through a digital twin: a continuous thread of data mirrors development, production, and use that stretches from the initials design through the lifetime of the product. 

Defects 

• Traditional Lean can help reduce defects by establishing standards in the way assets are maintained, processes are defined, and products are designed. Defects across the value stream, causing rework or scrap.
• Digital Lean helps identify the precise asset, process step, or product feature that is causing defects and reducing first-pass yield.

Industry Example of Digital Lean Implementation

In the pharmaceutical industry reveals that the current industry average for OEE is slightly above 35%, indicating ineffective resource utilization. Additionally, and efficiency gap between effectively digitized and average pharmaceutical factories, with digital facilities boasting 1.75 times higher OEE that indicates up to 60% throughput with no capital investment.

 

Availability: Pharmaceutical manufacturers leveraging digital technologies exhibit an availability score of 67%, underscoring the positive impact of Industry 4.0 solutions on their lean activities. These companies make informed decisions that directly address the primary OEE loss factors within the pharmaceutical industry. Here is the breakdown of availability wastes:

 

• Planned Losses: In Pharma 4.0 factories, the planned loss of 22% of staffed time indicates a substantial reduction in changeover time.
• Unplanned Losses: In digital factories, unplanned losses, accounting for 11% of staffed time, signify an extended equipment lifespan.

Performance: The performance score for Pharma 4.0 companies stands at approximately 93%, underscoring that digitization serves as a remedy for mitigating speed losses and minimizing micro-stops.

 

Quality: The quality score for digital pharmaceutical factories is approximately 98%, signifying heightened productivity and a reduced likelihood of receiving warning letters and OTIF penalties in comparison to traditional factories.

 

In conclusion, the digital lean is the future of manufacturing industries and beyond.

 

Digital Lean: The Smarter Way to Improve Your Processes

1. What’s Digital Lean?

Think of Digital Lean as a high-tech upgrade to your traditional Lean processes. It takes everything that makes Lean great, like continuous improvement and focusing on what truly matters and adds the power of the latest technology. Imagine combining the efficiency of Lean with the speed of AI, real-time data, and automation. That’s Digital Lean helping you work faster, smarter, and more effectively. It’s like upgrading your business from a bicycle to a high-speed car. You’re still moving in the right direction, but now you’re doing it with a lot more power and precision.

 

Key Features of Digital Lean:

Automation: Imagine never having to do those boring, repetitive tasks again. With digital tools, routine work gets automated, freeing up your team’s time to focus on the fun, problem-solving stuff that makes a real impact.

 

Real-Time Data Analytics: Picture having a dashboard that tells you exactly what’s happening in your business—live. With tools like IoT and AI, you can monitor things in real-time, make quick adjustments, and stay ahead of any issues before they become problems.

 

Process Mapping & Visualization: You know how easy it is to get lost without a map? Well, Digital Lean gives you that map. With digital dashboards and process mapping tools, you can “see” your operations. You’ll immediately spot what’s working and what’s not, allowing you to fix inefficiencies fast.

 

Collaboration Tools: Whether your team is in the same room or scattered worldwide, digital platforms make teamwork a breeze. Share information, make decisions faster, and get everyone on the same page—no matter where they are.

 

2. The Magic Happens When Lean Meets Digital Technologies:

Real-Time Monitoring & Predictive Analytics: With IoT, you can track everything from machines to inventory, live. Predict maintenance needs, avoid downtime, and optimize your schedule so everything runs smoothly.

 

AI & Machine Learning for Process Optimization: Machine learning digs into your past data, uncovers inefficiencies, and suggests ways to improve. It’s like having a personal advisor analyzing your operations and giving you smart, real-time advice.

 

Cloud-Based Collaboration & Data Sharing: Thanks to cloud-based tools, your teams can work together seamlessly, no matter the distance. Digital Lean eliminates delays, breaks down silos, and gets everyone working as one.

 

Digital Twin Technology: This one’s pretty cool. Digital twins create virtual versions of your physical systems. You can test ideas, simulate different scenarios, and spot potential issues—all without affecting your real-world operations. It’s like trying out a new business strategy in a video game before using it for real.

 

3. Digital Lean in Action:

Toyota: Toyota is known for Lean, and now they’re pushing the envelope with digital tech. With AI and real-time data, they optimize maintenance, track inventory, and reduce waste. Their machines are connected through IoT, so they can spot issues before they even happen.

 

GE Aviation: GE uses Digital Lean with digital twins to improve their production line. These virtual models allow them to spot inefficiencies, streamline processes, and cut waste—all in real-time.

 

Siemens: Siemens is using digital tools to monitor their production lines, identifying inefficiencies or defects right away. With automation and real-time insights, they’re constantly improving.

 

P&G: Procter & Gamble is taking digital Lean to the next level with IoT and AI to manage their supply chain. By fine-tuning production schedules and minimizing waste, they’re making smarter decisions with tech.

 

Amazon: Amazon is a perfect example of Digital Lean, especially with their fulfillment centers. Robotics, machine learning, and data analytics help them streamline everything from inventory management to customer orders.

 

The Benefits of Digital Lean

Faster Decision-Making: With all that real-time data, you can spot inefficiencies quickly and make decisions on the fly. It speeds everything up.

 

Better Customer Experience: By cutting delays and improving operations, businesses can provide faster, more reliable service to customers. Happy customers, happy business!

 

Cost Reduction: Digital Lean reduces waste, lowers unnecessary costs, and makes better use of resources, which means lower expenses in the long run.

 

More Flexibility and Agility: With automation and real-time insights, Digital Lean helps businesses stay flexible and adjust to unexpected changes—whether it’s a surge in demand or a sudden shift in market conditions. You can stay agile and keep everything running smoothly.

 

The Bottom Line

Digital Lean isn’t just a buzzword—it’s the future of how businesses improve. By combining Lean principles with powerful tools like IoT, AI, and cloud computing, you can make your operations faster, smarter, and more cost-efficient. Big names like Toyota, GE, Siemens, and Amazon are already leading the way, showing just how powerful this approach can be. If they can do it, so can you!

Interesting examples and use cases quoted for use of Digital Lean by the respondents. Dieylani LO has provided the best answer to this question. Well done!