In today’s hyper-competitive and rapidly evolving industrial landscape, manufacturers face relentless pressure to increase operational efficiency, eliminate waste, and drive continuous innovation. Lean manufacturing principles remain the cornerstone of operational excellence, but with the advent of Industry 4.0, these principles are undergoing a transformative evolution.

The ODI (SA) 20 Keys system, rooted in Iwao Kobayashi’s influential Japanese workplace improvement framework, offers a structured pathway to lean excellence through 20 interconnected focus areas. These range from foundational practices, such as workplace organisation and quality assurance, to advanced domains, including production scheduling and technology adoption. Traditionally, the 20 Keys system aligns closely with lean principles, emphasising waste elimination, employee empowerment, and process optimisation.

However, the rise of Artificial Intelligence (AI) technologies, encompassing machine learning, computer vision, reinforcement learning, and predictive analytics, now offers unprecedented capabilities to enhance each key. AI can enable

• smarter decision-making,

• anticipate disruptions,

• optimise resource allocation, and

• automate routine monitoring,

thereby supercharging lean transformations.

This blog explores how AI technologies integrate with and elevate the ODI (SA) 20Keys framework, with a particular focus on practical applications within South African industry contexts. Drawing on extensive analyses and real-world case studies, we highlight AI’s best fit within specific keys, the underlying algorithms powering these innovations, and measurable business benefits realised.

Overview of the ODI (SA) Japanese 20Keys System

The 20Keys system is a comprehensive lean management model emphasising continuous improvement through systematic workplace and process enhancements. Its keys are:

Key 1: Cleaning and Organising to make work easy

Key 2: Goal alignment

Key 3: Small group activities

Key 4: Reducing Work-in-Process

Key 5: Quick Changeover Technology

Key 6: Kaizen of Operations

Key 7: Zero Monitor Manufacturing/Production

Key 8: Coupled Manufacturing/Production

Key 9: Maintaining Machines and Equipment

Key 10: Workplace Discipline

Key 11: Quality Assurance

Key 12: Developing Your Suppliers

Key 13: Eliminating Wasteful Activities

Key 14: Empowering Employees to Make Improvements

Key 15: Skill Versatility and Cross-Training

Key 16: Production Scheduling

Key 17: Efficiency Control

Key 18: Using Information Systems

Key 19: Conserving Energy and Materials

Key 20: Leading Technology and Site Technology

(Source: Iwao Kobayashi, 1995; ODI (SA) Website)

AI-Driven Enhancements Across Key 20 Keys Focus Areas

This section details select keys with strong AI alignment and transformative potential, explaining objectives, AI-enabled innovations, core algorithms, and illustrative case studies. Priority is given to examples from South African industry, complemented by global benchmarks.

Key 1: Cleaning and Organising to make work easy

Objective: Achieve and sustain an orderly, efficient, and safe workplace through the 5S methodology: Sort, Set in Order, Shine, Standardise, Sustain.

AI Enhancements:

• Computer Vision: AI-powered cameras continuously scan work areas to detect clutter, misplaced tools, or safety hazards, alerting supervisors in real time.
• Layout Optimisation: Machine learning analyses worker movement patterns to recommend optimal workspace layouts that minimise wasted motion and enhance ergonomics.

Algorithms:

• Convolutional Neural Networks (CNNs): CNNs excel at image recognition, identifying visual anomalies like disorganised tools or debris (Goodfellow et al., 2016).
• Reinforcement Learning (RL): RL simulates various layout configurations, learning which arrangements maximise efficiency by trial-and-error (Sutton & Barto, 2018).

Case Studies:

• South Africa: A leading automotive parts manufacturer implemented CNN-driven vision AI systems that reduced tool search times by 15%, increasing worker productivity (Silcock, 2023).
• Global: Toyota employs RL to optimise 5S workplace layouts, cutting non-value-adding activities by 10% (Forbes, 2023).

Key 2: Goal Alignment

Objective: Ensure organisational activities align with strategic goals through transparent objective management and KPI tracking.

AI Enhancements:

• Real-Time AI Dashboards: Integrate diverse data streams to provide live KPI monitoring and alert management to deviations.
• Predictive Analytics: Forecast potential impacts of decisions on performance metrics, enabling proactive resource reallocation.

Algorithms:

• Time-Series Forecasting (ARIMA, LSTM): Predict KPI trajectories, with LSTM networks adept at modeling complex temporal patterns (Brownlee, 2020).
• Decision Trees: Analyse production data to prioritise corrective actions based on likely outcomes (Quinlan, 1986).

Case Studies:

• South Africa: A steel manufacturer used LSTM models to forecast production KPIs, reducing delays due to misaligned objectives by 20% (SAISI Newsletter, 2023).
• Global: General Electric’s AI dashboards leverage decision trees, improving decision efficiency by 25% (GE Reports, 2021).

Key 4: Reduce Work-In-Process (WIP)

Objective: Optimise inventory levels to minimise waste and shorten lead times, supporting just-in-time delivery.

AI Enhancements:

• Demand Forecasting: Machine learning integrates historical and external data (market trends, seasonality) to forecast demand more accurately.
• Supply Chain Optimisation: Algorithms fine-tune replenishment schedules and logistics to reduce storage costs.

Algorithms:

• Random Forests: Ensemble methods analyse multiple variables affecting demand, enhancing prediction accuracy (Breiman, 2001).
• Genetic Algorithms: These simulate evolutionary processes to optimise replenishment timing, balancing stock availability and cost (Holland, 1992).

Case Studies:

• South Africa: Collaboration between a food processing firm and the University of Pretoria employed random forest models, improving demand forecast accuracy and aligning supply with demand (UP Industrial Engineering, 2023).
• Global: Unilever’s AI-driven supply chain optimisation reduced inventory costs by 15% and lead times by 10% (DigitalDefynd, 2025).

Key 5: Quick Changeover Technology (SMED)

Objective: Minimise setup and changeover times to increase manufacturing flexibility.

AI Enhancements:

• Predictive Sequencing: AI analyses historical setups to recommend optimal changeover sequences.
• Digital Twins: Simulate and test changeover processes virtually to identify efficiency gains.

Algorithms:

• Reinforcement Learning: Learns and improves setup sequences dynamically, minimizing downtime (Sutton & Barto, 2018).
• Monte Carlo Simulations: Probabilistic modeling to optimise changeover schedules accounting for uncertainties (Metropolis & Ulam, 1949).

Case Studies:

• South Africa: Wits University applied deep RL to supply chain inventory management, demonstrating improved demand fulfillment compared to classical forecasting (SAJIE, 2025).
• Global: Siemens’ MindSphere platform uses Monte Carlo methods, reducing downtime by 30% (Siemens, 2022).

Key 6: Kaizen of Operations

Objective: Continually refine manufacturing methods to boost efficiency and cut costs.

AI Enhancements:

• Process Mining: AI algorithms analyse production logs to identify bottlenecks and redundant steps.
• Data-Driven Recommendations: Machine learning suggests improvements based on historic process outcomes.

Algorithms:

• Alpha Miner Process Mining: Extracts workflow models from event logs to highlight inefficiencies (van der Aalst, 2011).
• Gradient Boosting (XGBoost): Predicts effects of method changes on output and quality (Chen & Guestrin, 2016).

Case Studies:

• South Africa: The growing process analytics market in textiles and manufacturing leverages AI for rapid method improvement (6Wresearch, 2023).
• Global: Bosch achieved a 12% cost reduction using XGBoost for manufacturing method optimisation (McKinsey, 2021).

Key 7: Zero Monitor Manufacturing/Production

Objective: Automate equipment and process monitoring to minimise human oversight and reduce downtime.

AI Enhancements:

• Real-Time Anomaly Detection: AI continuously analyses IoT sensor data to detect faults instantly.
• Predictive Alerts: Early warnings enable preventive interventions before failures occur.

Algorithms:

• Autoencoders: Neural networks that model normal operational patterns and flag deviations (Hinton & Salakhutdinov, 2006).
• Recurrent Neural Networks (RNNs): Monitor time-series sensor data for trends or anomalies (Graves, 2013).

Case Studies:

• South Africa: Mining firms Autolectron and RAMJACK deploy AI-based real-time monitoring reducing equipment downtime (Mining Weekly, 2014).
• Global: GE’s use of RNNs for process monitoring increased operational efficiency by 20% (GE Reports, 2021).

Key 9: Maintaining Machines & Equipment

Objective: Maximise uptime through predictive and preventive maintenance.

AI Enhancements:

• Failure Prediction: AI models forecast equipment failures using historical sensor data.
• Optimised Scheduling: Machine learning plans maintenance windows to reduce operational disruption.

Algorithms:

• Long Short-Term Memory (LSTM): Excels at predicting failures from time-series data (Hochreiter & Schmidhuber, 1997).
• Survival Analysis: Statistically models equipment lifespan to optimise maintenance timing (Klein & Moeschberger, 2003).

Case Studies:

• South Africa: Bell Equipment and Sappi adopt AI-driven predictive maintenance, improving operational reliability (ODI SA, 2024).
• Global: GE’s predictive maintenance system reduced maintenance costs by 10-15% (GE Reports, 2021).

Key 11: Quality Assurance

Objective: Maintain consistent product quality through automated inspection and process control.

AI Enhancements:

• Visual Inspection: AI systems detect defects with high precision.
• Quality Prediction: Historical data informs early warnings of quality deviations.

Algorithms:

• Convolutional Neural Networks (CNNs): Identify surface defects and assembly errors (Goodfellow et al., 2016).
• Support Vector Machines (SVMs): Classify quality issues from production parameters (Cortes & Vapnik, 1995).

Case Studies:

• South Africa: KwaZulu-Natal electronics manufacturer reduced PCB defects by 17% using CNN-based inspection (SAJEMS, 2024).
• Global: BMW’s AI systems achieve 99% defect detection accuracy using SVM (BMW Group, 2023).

Key 12: Developing Your Suppliers

Objective: Strengthen supplier performance and reliability.

AI Enhancements:

• Supplier Segmentation: Clustering identifies high- and low-performing suppliers.
• Delivery Forecasting: Predictive models anticipate supply chain disruptions.

Algorithms:

• K-Means Clustering: Groups suppliers for targeted development (MacQueen, 1967).
• Prophet Time-Series Forecasting: Predicts delivery reliability (Taylor & Letham, 2018).

Case Studies:

• South Africa: A beverage manufacturer improved supplier delivery times by 13–16% using clustering (DALRRD, 2023).
• Global: Unilever reduced supply disruptions by 20% through AI forecasting (DigitalDefynd, 2025).

Key 13: Eliminating Waste

Objective: Minimise all forms of waste—material, time, energy.

AI Enhancements:

• Waste Source Identification: Decision trees analyse production data for waste hotspots.
• Optimisation: Linear programming minimises resource use.

Algorithms:

• Decision Trees: Target key waste drivers (Quinlan, 1986).
• Linear Programming: Optimises resource allocation (Dantzig, 1963).

Case Studies:

• South Africa: Paper manufacturer cut material waste by 18% via AI analysis (ODI SA, 2024).
• Global: Toyota reduced material usage by 15% using optimisation algorithms (Forbes, 2023).

Key 16: Production Scheduling

Objective: Optimise scheduling to maximise throughput and minimise bottlenecks.

AI Enhancements:

• Dynamic Scheduling: AI predicts and adjusts schedules based on real-time data.
• Simulation: Digital twins test scheduling scenarios before implementation.

Algorithms:

• Genetic Algorithms: Solve complex scheduling balancing multiple constraints (Holland, 1992).
• Reinforcement Learning: Adapts schedules dynamically (Sutton & Barto, 2018).

Case Studies:

• South Africa: University of Johannesburg demonstrated genetic algorithms improving batch chemical plant scheduling (SACAIR, 2023).
• Global: Siemens reduced downtime by 30% using RL-based scheduling (Siemens, 2022).

Key 17: Efficiency Control

Objective: Continuously monitor and improve operational efficiency.

AI Enhancements:

• Real-Time Dashboards: Track efficiency KPIs and suggest improvements.
• Anomaly Detection: Identify sudden efficiency drops early.

Algorithms:

• XGBoost Gradient Boosting: Predicts efficiency trends (Chen & Guestrin, 2016).
• Isolation Forest: Detects anomalies in performance data (Liu et al., 2008).

Case Studies:

• South Africa: Furniture manufacturer improved efficiency through centralised data dashboards (Eybers & Mayet, 2020).
• Global: Bosch reduced costs by 12% using anomaly detection (McKinsey, 2021).

Key 18. Using Information Systems

Objective: Leverage integrated information systems for data-driven decisions and transparency.

AI Enhancements:

• Natural Language Processing (NLP): Extracts insights from unstructured data like reports.
• Predictive Analytics: Provides foresight on operational trends.

Algorithms:

• BERT (Bidirectional Encoder Representations from Transformers): Advanced NLP model for text analysis (Devlin et al., 2018).
• LSTM Networks: For real-time predictive analytics (Hochreiter & Schmidhuber, 1997).

Case Studies:

• South Africa: Johannesburg logistics firm enhanced Balanced Scorecard with BERT for superior decision-making (DUT, 2020).
• Global: GE’s AI systems improved efficiency by 20% using LSTMs (GE Reports, 2021).

Key 19. Conserving Energy and Materials

Objective: Reduce consumption of energy and raw materials to promote sustainability.

AI Enhancements:

• Energy Usage Optimization: Machine learning analyzes consumption patterns and adjusts settings.
• Material Efficiency: Predictive models recommend process adjustments.

Algorithms:

• Particle Swarm Optimization (PSO): Efficiently minimizes energy use by tuning machine parameters (Kennedy & Eberhart, 1995).
• Regression Models: Forecast material usage trends (Hastie et al., 2009).

Case Studies:

• South Africa: Cement manufacturer achieved 15% energy savings using AI-enabled energy management systems (IEEE-NCPC-SA, 2024).
• Global: Tesla reduced energy costs by 15% at its Gigafactory using regression analytics (Tesla, 2024).

Key 20. Leading Technology and Site Technology

Objective: Adopt and integrate advanced technologies to drive operational excellence.

AI Enhancements:

• Digital Twins: AI-powered virtual replicas simulate and optimise operations.
• Technology Adoption: Reinforcement learning optimises how new technologies integrate into workflows.

Algorithms:

• Deep Learning: Enables detailed simulation and analysis for digital twins (LeCun et al., 2015).
• Reinforcement Learning: Guides effective technology deployment (Sutton & Barto, 2018).

Case Studies:

• South Africa: Mining companies like Exxaro employ digital twins combined with deep learning to boost productivity by over 18% (EngineerIT, 2024).
• Global: Siemens reported 20% cost reduction through AI-led technology integration (Siemens, 2022).

Keys with Limited Direct AI Alignment

Certain keys remain more human-centric but can benefit indirectly from AI:

• Key 3: Small group activities: NLP tools like BERT help prioritise ideas but cannot replace human collaboration.
• Key 8: Coupled Manufacturing/Production: Scheduling algorithms assist but integration is complex.
• Key 10: Workplace Discipline: AI tracks metrics; culture and discipline are core.
• Key 14: Empowering employees to make improvements, Key 15: Skill Versatility and cross training: AI supports personalised training recommendations.

Practical Considerations for AI Integration

• Data Infrastructure: Robust IoT networks and cloud data storage are essential (McKinsey, 2021).
• Workforce Upskilling: Employee training to operate and trust AI tools is critical (Deloitte, 2020).
• Ethical AI Use: Compliance with South Africa’s POPIA and ethical standards ensures transparency (IEEE SA, 2023).
• Cost-Benefit Analysis: Companies must carefully assess AI implementation costs against expected efficiency gains.

Conclusion

The fusion of AI technologies with the ODI (SA) 20 Keys system heralds a new era in lean manufacturing and operational excellence. AI transforms core keys—such as Cleaning and Organising, Rationalising Systems, and Information Systems usage—by enabling real-time insights, predictive analytics, and dynamic optimisation. South African manufacturers across automotive, food processing, mining, and other sectors are already realising substantial gains in quality, throughput, and energy efficiency.

Global leaders like GE, Siemens, Toyota, and Bosch demonstrate that AI-enhanced lean systems provide not only measurable returns on investment but also essential agility and sustainability in the AI-driven Industry 4.0 landscape.

By embedding AI into the 20 Keys framework, manufacturers future-proof their operations, unlocking unprecedented levels of efficiency, responsiveness, and environmental stewardship required for competitive advantage in today’s digital age.

The 20 Keys system was developed in Japan by Iwao Kobayashi when he, after completing industrial studies at university, joined Mitsubishi Heavy Industries. Soon after joining them, he developed the first mixed-lot automated assembly line in Japan (and arguably in the world). He was also known as the expert in Japan on quick changeover technology, and shared learning experiences with other great Japanese engineers like Taiicho Ohno, and Shigeo Shingeo. Practical, in the workplace learning together with inputs from employees, the shopfloor and production technologies, led to the development of the 20 Keys. He later authorised a timeless book on productivity improvement, “20 Keys to Workplace Improvement’. To read more about the 20 Keys Operations Improvement System, please click here.

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A line-up of excellent speakers, long-time and new implementations, from manufacturing, production, HR, Retail and administrative industries, shared their best practices and learnings. Our keynote speaker was Martin Preece: Interim Chief Executive Officer: Gold Fields.

After listening to so many inspiring presentations it was only appropriate that recognition should be given to some people who have played outstanding roles in their companies to help these stories become a reality.

Huibie Jones, MD, and our respective ODI facilitators, gathered to present the Special Awards Ceremony.

As most of you are aware, all ODI qualifications are aligned to a Continuous Improvement journey. As it has been a while since we were able to have an in-person conference, we made use of the opportunity, and had more than one Top Achiever for the different qualifications.

TOP ACHIEVER AWARDS

National Certificate: Production Technology ID: 58781 / NQF Level 2

This qualification equips learners with the necessary skills and knowledge to efficiently perform tasks and activities, in order to continuously improve operational excellence. Click here to read more.

National Certificate: Production Technology ID: 58785 / NQF Level 3

This qualification provides learners with the range of learning and skills required to be able to perform a series of activities to support manufacturing, engineering, and technology processes. Learners will acquire a range of skills in the identification of production parameters in manufacturing, engineering, and technology industries, and basic strategies to achieve them. Click here to read more.

National Certificate: Management ID: 83946 / NQF Level 3

This qualification aims at equipping every first-line manager with the essential knowledge and skills necessary to:

• Develop, lead and inspire productive workplace teams.
• Ensure that all team members are developed to their full potential.

The manager of the first-line manager needs to coach his/her first-line managers, and is, as such, involved in the programme. A simple-to-use benchmarking system forms the basis for ongoing coaching and development. Click here to read more.

Wispeco Aluminium: Nikita De Lange (Absent)

FETC: Generic Management: PROCESS MANUFACTURING ID 57712 / NQF Level 4

This qualification aims to prepare first-line managers in a manufacturing environment to undertake a broader management role in their organisations. It lays the foundation for further management development and movement into more senior positions. First-line managers may include team leaders, supervisors, foremen, and section heads. Click here to read more.

National Certificate: Generic Management: GENERAL MANAGEMENT ID 59201 / NQF Level 5

This qualification is designed to enable a person to manage first-line managers in an organisational entity. First-line managers may include team leaders, supervisors, junior managers, section heads, and foremen. The focus of this qualification is to enable learners to develop competence in knowledge, skills, attitudes, and values. Click here to read more.

National Certificate: Productivity (Also available as E-learning) ID 49793 / NQF Level 5

This qualification is based on a proven methodology for sustainable business improvement and consists of one Management System Module, to create a common vision, and eight practical Modules, to make operations more competitive. Click here to read more.

None of the above will be successful without the necessary on-site support. The following Best Workplace Mentor and Support awards went to individuals who excelled in their role as a mentor.

BEST WORKPLACE MENTOR AND SUPPORT AWARDS

Grain Field Chickens: Wally Kok (Absent)

Evidence is seen in the workplace of how it all comes together and for this, ODI recognised three leaders in the field of Continuous Improvement for their contributions towards Operations Excellence.

CONTRIBUTION TOWARDS OPERATIONS EXCELLENCE AWARDS

The ODI Team is extremely proud of all the candidates who received awards. To receive an award a candidate must display great

• Enthusiasm, not only do well, themselves but

• Encourage those on the learning journey with them. Must be

• Energetic and complete tasks promptly

• Excellence; understand and define Operations Excellence in every day tasks.

It was agreed by the full ODI team that these candidates fulfilled all these requirements. A huge WELL DONE, to them all.

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Digistics (Pty) Ltd. offers Supply Chain Management and Value-Added Logistics Execution. They operate out of six Distribution Centres in Cape Town, Durban, Port Elizabeth and Johannesburg and has become a significant player in leading multi-temperature distribution operations throughout South Africa.

Digistics’ journey began in 1995, when ASP Distributors (Pty) Ltd opened up in South Africa, in partnership with Spar. With a national infrastructure, ASP pioneered multi-temperature distribution within the South African Quick Service Restaurant industry.

A management buy-out in 2003 led to the establishment of Digistics (Pty) Ltd. With an aggressive growth plan, the company secured a number of new, long-standing contracts.

Due to significant growth over a short space of time, the decision was made to bring a partner on board. 51% of the shares was sold to Super Group Holdings in 2012, making the business a Super Group subsidiary company. In 2017, Super Group bought out the balance of the remaining shareholding.

It is said that people are an asset; Digistics believes that everything revolves around people. In order to do what they do, Digistics need leaders to build a best-in-class customer-focused business. They do have those leaders on their team. You will find leadership at every level, and each employee in their team of more than 795 makes decisions every day to put their customers’ businesses first.

Striving for world-class supply chain management and operations excellence, Digistics enrolled members of staff to complete ODI’s NQF3, 4 and 5 Generic Management Learnerships facilitated by Mbali Tshabalala, Michael Foxon and Maryke Bergh.

Learners were welcomed by their HR Executive – Cheryl Farley.

ODI’s Mbali Tshabalala, facilitated the NQF3 Generic Management group of learners.

Micheal Foxon facilitated the NQF4 Generic Management group of learners.

Maryke Bergh facilitated the NQF5 Generic Management group of learners.

The learnerships offered by ODI are carefully selected, to support companies on their journey of Continuous Improvement. To find out how ODI can help your Continuous Improvement initiative, contact us, by clicking here.

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BBF Safety Group is an integrated workplace safety solutions provider that helps customers create safe working environments.

In 2014, four of South Africa’s largest safety footwear manufacturers joined forces to create BBF Safety Group (Pty) Ltd. The merger created the largest safety footwear manufacturer in Africa with more than 250 years of combined experience, producing over 4.5million pairs of footwear and gumboots per annum.

BBF Safety Group enrolled delegates to complete ODI’s Operations Excellence implementation programme – facilitated by George Meiring.

At ODI our mission is to provide holistic solutions that promote people development and operations excellence, through training, coaching and consulting, supported by a range of excellent products. To read more about us, click here.

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We are offering an online service for 20 Keys training and implementation support. The service, based on the 20 Keys system, is tailored to your specific needs, according to the stage of your operations excellence journey. Support varies from individual and group-training sessions, to Key Leader action plan progress reviews, and next steps discussions, using specific tools and techniques, implementation of small group projects, and any other relevant support. The service is available on an hourly basis; scheduled according to your availability, time constraints, and convenience.

This service is in addition to the 20 Keys e-Learning courses (for each of the 20 Keys) that are also offered online, and for which we already have a substantial number of registered learners.  The courses consist of studying a particular Key (the manual is available online), then doing a Quiz on it, which must be passed (a few tries are allowed), after which the learner needs to complete a practical, in the workplace, project. All instructions are available online. Evidence on the project is then submitted online, with relevant documentation, statistics, photos, etc. It is marked, with comments and advice on strengthening it (a few tries/refinements are allowed). When the project is accepted, a Completion of Course Certificate is issued. For organisations, the benefit is not just more understanding of the Keys, but tangible

• Quality,
• Cost Effectiveness,
• Delivery,
• Safety and
• Morale improvements from the projects.

ODI provides support, and where more than one person enrol per Key, we also have WhatsApp groups (per Key), where questions and advice are discussed.

Please contact Johan Benadie at johan.benadie@odi.co.za (082 415 0102)  for a discussion on your specific needs.

One only needs to look at the essence of the 20 Keys programme, to realise that it speaks to the heart of survival for any organisation.

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“Benefits of using Blended e-Learning in your Operations Excellence Implementation”

Jason and Chantelle shared DBSSSA’s Operations Excellence journey and how key people in their organisation, are involved in the National Certificate in Productivity (NQF5 ID49793). Click here to view the album: e-Learning NQF5 National Certificate in Productivity, DBSSSA & Huibie Jones.

Jason started the presentation and gave an overview of DBSSSA:

• The business is based in Kimberley with a sales office in Johannesburg.
• Established in 1972.
• Clean, Sort, Value and Sell De Beers Consolidated Mines SA diamond production.
• Employ 137 individuals.

DBSSSA approached ODI to become one of the key partners on their road to Operational Excellence. Building OE capacity is a critical pillar to their OE strategy. They decided that the Productivity Learnership offered by ODI was a perfect fit to equip all leaders with the required OE skills. Click here to read more about this qualification.

The Modules covered in the certificate include:

Chantelle then gave an overview of how the Productivity Learnership is done. Chantelle and her colleagues do:

• Contact sessions (face-to-face).
• Online Quizzes.
• Online Audio Content.
• Online Chat platforms.
• Online submission of practical activities.

They found that:

• The site is user friendly.
• Accessing the site is easy.
• The framework is trendy and nifty.
• The Modules only unlock when the study school is scheduled.
• You cannot access the next chapter unless you complete the current activity.
• The online chat allows them to sit as a team, and chat with the lecturer.

Benefits of this programme include:

• Learnership allows for immediate improvement.
• Traditional learning does not allow for practical implementation in the workplace.
• The learnings need to be implemented in the workplace, before submitting your practical assignment.
• Modules link with company strategy for Operational Excellence.
• Tools and techniques are relevant and easy to use.

Chantelle shared success stories in term of:

Module 2: Goal Alignment

Module 3: Efficient Workplace Organisation.

5S Training session in progress below.

Module 4: Teamwork

Chantelle encouraged everybody to take up the challenge to learn more, and to always implement what you are learning!

To read more about the speaker presentations at our recent ODI conference where we celebrated 30 years of Operational Excellence, click on the following links:

1. Len Hansen – Consultant at Astral Operations, presented: “My Journey with Organisational Development International (ODI) since 1991.”
2. Esbe du Toit: Organisational Improvement Manager at Wispeco Aluminium, presented: “Celebrating Innovation … A snapshot of our journey towards world-class.”
3. Theo van Strijp: Managing Director at GFC, presented: “Grain Field Chickens: Road to Excellence Award.”
4. Forona Stephens: Human Resources Business Partner at GWK and her topic of discussion was: “Think Big, Start Small, Unlock Excellence.”
5. Wouter Olivier Managing Director of Sondor Performance Foams, presented: “People are the Foundation to Building a Culture of Continuous Improvement.”
6. Moemedi Merafhe: Strategy & Business Improvement Manager, Debswana Diamond Company and he spoke about : “MBA Lean Implementation Journey”
7. Nikki Moodley: Operations Improvement Executive, Astral Foods and her topic of discussion was “20 Keys… The Astral Way.”
8. Doug February – General Manager at Nampak, presented “Operational Excellence … Good to Great”
9. Lapologang Laps Letshwenyo: Business Improvement Coordinator at Morupule Coal Mine in Botswana, presented “MCM Lean Journey – Current status, successes and way forward”

Author: Huibie Jones

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The first speaker for the day was Len Hansen – Consultant at Astral Operations. Len’s topic of discussion was: “My Journey with Organisational Development International (ODI) since 1991.” Click here to read more about his presentation.

The second speaker was Esbe du Toit: Organisational Improvement Manager at Wispeco Aluminium. Esbe’s topic of discussion was: “Celebrating Innovation … A Snapshot of our Journey towards World-class.”

Wispeco in a nutshell

• Largest manufacturer of aluminium extrusions in Africa, with its own melting and casting facility, nine extrusion presses, international quality certified surface finishing plants (powder coating and anodising).
• Market leader in architectural systems development and innovation.
• Wholly owned subsidiary of Remgro Ltd with ±1000 employees.
• Registered training provider offering fabrication training to customers, the previously disadvantaged youth, and deaf learners.
• Thirty official distributors in Southern Africa.
• Ecospecifier Green Rating on Wispeco aluminium profiles due to the extensive recycling of post-consumer and industrial aluminium waste.
• BBBEE level 4 offering 100% for procurement spent.

The term “World-class” is not taken lightly at Wispeco, Esbe spoke about how they have entered an era where they are competing on a global level. Wispeco is therefore constantly challenged to remain cost efficient, as they compete against low cost imports.

Recently Wispeco commissioned the first vertical powder coating plant in the Southern Hemisphere. A giant leap for Wispeco!

To run a world class plant like this, a dream team was needed.

The five most important lessons learnt to make such a project succeed were:

1. Maintaining equipment in a world-class way [KEY 9].
2. Connecting the heart-rate monitor early on: What you measure, is what you get.
3. Maintaining quick changeovers [KEY 5].
4. Establishing trust relationships with suppliers [KEY 12].
5. An informed and equipped team [KEY 2 & 3]: All hands on deck.

Most important lesson learnt:

Investing in world-class technology at the right time, and in the right areas of the business, can lead to quantum leaps in efficiencies and improvement.

Author: Huibie Jones: MD at ODI

To view the full album of the recent 2019 ODI Conference – Celebrating 30 years of operations excellence, click here.

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