What is happening in Iran ?

When the Islamists overthrew Shah Reza Pehlavi and took power in 1970, the Iranians fell to religious radicalism. One of my colleagues in the Uty is an Iranian Professor. 34,000 people have become part of history including 200 children over the past one year and she dare not return to Iran, because she fears she will also be part of history. Iranians want the Islamist radicals out of power. 

This will be the war to liberate Iran of Islamists. Iranians have rich cultural heritage and are a proud group of people. 

Iran presently has inflation of 45% and food inflation of 70%, 1.5 million Iranian Rial is a US dollar and GDP grew -2.5% (negative) last year. People are fed up of the Islamists. 🫢🫢🤔

Davos WEF '26 Deliberations at Alliance School of Business Bangalore

Ashutosh Patki talk - WEF ‘26, Davos,  ASB 6 Feb ‘26

Ashutosh shared his insights and experiences from attending the World Economic Forum (DAVOS) in 2026, providing Alliance School of Business, Bangalore MBA sem 4 Operations and BBA sem 6 operations students besides students from Journalism with an inside view of the event's significance and impact on global trade, supply chains, and geopolitical dynamics. He highlighted how DAVOS serves as a platform for leaders to engage in informal discussions, fostering trust and facilitating high-impact decisions. Through stories and examples, Ashutosh explained how narratives shift at DAVOS, influencing financial markets and strategic directions. He also discussed India's evolving presence at the forum and the strategic importance of networking and building connections. The session concluded with Ashutosh emphasizing the value of proactive networking and the importance of developing a startup mindset for future success.

DAVOS Insights and Global Impact

Ashutosh shared his experiences and insights from attending the World Economic Forum (DAVOS) and discussed its significance in global diplomacy and business. He highlighted how informal leader-to-leader conversations at DAVOS can lead to significant outcomes, such as the 1988 DAVOS Understanding between Greece and Turkey. Ashutosh also explained how DAVOS influences global business narratives, using the example of how climate change was reframed as a financial risk by central bankers, leading to a shift in investment strategies and risk management practices. He encouraged the students to think about how they would respond as CEOs to the emerging understanding of climate risk as a financial risk.

India's Rising Influence at Davos

Ashutosh discussed his experience covering the World Economic Forum in Davos, highlighting how India's presence and influence have evolved over the past decade. He noted that Indian leaders, including chief ministers, have become more proactive in attending Davos to attract investment and engage with global leaders. Ashutosh also shared insights into the geopolitical risks and themes discussed at the forum, such as geo-economic confrontation, interstate conflict, and technology governance. He emphasized the importance of de-risking strategies for organizations in the current globalized world.

DAVOS Investment Strategy Insights

Ashutosh discussed the intense investment attraction at the Maharashtra Promenade, highlighting the efforts of Chief Ministers and Union Ministers like Devindra Fadnavis and Revanth Reddy in securing MOUs. He explained the "DAVOS playbook" which includes access to decision-makers, sending market signals, converting ideas into reality, and follow-through to realize value. Ashutosh also mentioned the importance of private meetings over panels for strategic networking at DAVOS.

Davos Insights on Global Strategy

Ashutosh discussed the importance of private meetings at Davos, emphasizing that they provide more meaningful connections than panel sessions. He shared insights from a CNBC interview with a CEO about China's strategic absence from Davos 2026, highlighting how He Lai Feng, China's vice premier, delivered reassurance on economic stability and openness to foreign investment. Ashutosh also noted the strong presence of AI, digital asset, and blockchain companies at Davos, which some CEOs found unusual.

DAVOS and Venture Capital Dynamics

Ashutosh discussed the relationship between DAVOS visibility and venture capital, noting that sectors gaining prominence at DAVOS often seek to transition from emerging to institutional status. He emphasized that while narrative intensity and capital allocation can drive market expectations, they may not always align with valuation reality, citing recent market corrections in AI and tech stocks. Ashutosh also highlighted the shift in digital finance towards infrastructure, with a focus on tokenization and stablecoins as potential game-changers in the financial system. He concluded by sharing insights from DAVOS sessions, including discussions on monetary policy and the potential impact of blockchain technology on financial systems.

India's Supply Chain Diversification Strategy

Ashutosh discussed the impact of global supply chain recalibration, highlighting India's diversification strategy in trade agreements, including the EU-India FTA and potential deals with GCC and the UK. He emphasized how India's approach to supply chain recalibration has evolved, particularly in response to geopolitical uncertainties and the dominance of China in critical minerals processing. Ashutosh also noted that the economic disruptions caused by Trump's policies will have lasting effects, even if he is no longer in power, making it challenging to revert to the pre-Trump status quo.

Strategic Shift in Supply Chains

Ashutosh discussed the emergence of a new supply chain route, the India-Middle East-Europe corridor (IMEC), as a strategic alternative to the traditional Silk Route, which now bypasses China due to European Union's concerns about trading risks and human rights issues. He explained how India's Chabahar port deal with Iran has been terminated, prompting a shift towards IMEC, which is gaining traction with the Middle East and European Union through existing FTAs. Ashutosh also emphasized the importance of networking and digitalization for business success, encouraging students to build connections with CEOs and CFOs through cold emails and meetings.

15 TQM tools ..

 15 commonly used tools in Total Quality Management (TQM), compiled from widely recognized quality management practices. The first seven are the classic "Seven Basic Quality Tools" (also known as 7 QC Tools), developed by Kaoru Ishikawa and foundational to TQM for problem-solving and process improvement. 

The remaining are additional key tools frequently cited in TQM implementations for advanced analysis, planning, and continuous improvement.

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1. Cause-and-Effect Diagram (Fishbone Diagram or Ishikawa Diagram) — Identifies potential root causes of a problem by categorizing them (e.g., people, processes, materials).

2. Check Sheet (Tally Sheet) — A simple data collection tool to record and count occurrences of events or defects systematically.

3. Control Chart — Monitors process stability over time by plotting data points against control limits to detect variations.

4. Histogram — Displays the frequency distribution of data to show patterns and variations in processes.

5. Pareto Chart — A bar chart that prioritizes issues based on the 80/20 rule (80% of problems from 20% of causes).

6. Scatter Diagram — Plots two variables to identify relationships or correlations between them.

7. Flowchart (Process Map) — Visualizes the steps in a process to identify inefficiencies or bottlenecks.

8. Run Chart — A time-series plot to track trends and shifts in data over time (often considered an extension of basic tools).

9. Statistical Process Control (SPC) — Uses statistical methods to monitor, control, and improve process performance.

10. Root Cause Analysis (RCA) — Systematic methods (e.g., 5 Whys) to dig into the underlying reasons for defects.

11. 5 Whys — A questioning technique to drill down to the root cause by asking "why" repeatedly.

12. Benchmarking — Compares processes or performance against industry best practices.

13. Quality Function Deployment (QFD) — Translates customer needs into technical requirements (often using House of Quality).

14. Failure Mode and Effects Analysis (FMEA) — Identifies potential failures in a process or product and their impacts.

15. Six Sigma Methodology — A data-driven approach (integrated into TQM) to reduce defects and variability using DMAIC (Define, Measure, Analyze, Improve, Control).

Making of an entrepreneur

Jio - Digitisation of a nation ..

Physical engine of AI - Data centre..

How Michelin reinvented the tyre business..

AI brain for autonomous vehicles ..

How Amazon India optimised it's operations..

Hayes Wheelwright Model (1985) ..

The Hayes and Wheelwright model (often referred to as the four-stage model of operations strategy or manufacturing's strategic role) is a foundational framework in operations management. Developed by Harvard professors Robert H. Hayes and Steven C. Wheelwright in their 1984 book *Restoring Our Competitive Edge: Competing Through Manufacturing* (building on their earlier 1979 work), it describes how an organization's operations function (manufacturing or service delivery) evolves in its contribution to overall business strategy and competitive advantage.

The model presents operations as progressing through four stages, from being a neutral (or even negative) factor to becoming a powerful source of competitive edge. It is typically visualized as a 2x2 matrix with two axes:

- Internal vs. External focus  
- Neutral vs. Supportive contribution  

 

The Four Stages Explained

Stage 1: Internally Neutral  
This is the lowest level of maturity. Operations are viewed as a **barrier** or "necessary evil" by other parts of the business. The primary goal is to **avoid mistakes** and minimize negative impact on the rest of the organization (e.g., preventing breakdowns, quality issues, or delays). Operations are reactive, inward-looking, and lack strategic direction. They simply "make the stuff" without surprises, but underperform consistently, holding the company back. Many struggling or immature organizations start here.

Stage 2: Externally Neutral  
The operations function breaks out of internal negativity by benchmarking against competitors and adopting **industry best practices**. The aim is to achieve **parity** — to be as good as (but not better than) rivals in terms of cost, quality, delivery, etc. Operations adopt standard approaches (e.g., similar suppliers, quality systems, or workforce practices) to meet external benchmarks. This stage is common for most companies: operations are no longer a weakness, but they don't create any unique advantage.

Stage 3: Internally Supportive  
Here, operations become **proactively aligned** with the business strategy. The function develops a credible operations strategy that supports the overall competitive priorities (e.g., low cost, differentiation, speed, or flexibility). Operations reach "best in class" levels within the industry and are coordinated with structural (e.g., capacity, technology) and infrastructural (e.g., workforce, quality systems) decisions. The business can now exploit operations capabilities for better pricing, faster delivery, or superior products to gain market share. This is where operations truly support and enable the strategy.

Stage 4: Externally Supportive
The rarest and highest level — operations become the foundation of the company's competitive success. The function is innovative, proactive, and forward-looking, often driving the entire business strategy. Operations provide unique capabilities that competitors can't easily match (e.g., breakthrough processes, flexibility, or technology leadership), putting the company "one step ahead." The organization builds its strategy around what operations can deliver, creating sustainable advantage. Very few companies reach this stage (examples historically include world-class performers like Toyota in its prime or certain tech giants today).

Key Insights from the Model
- Progression is sequential: Organizations typically move upward from Stage 1 → 2 → 3 → 4 as they mature.  
- Stages 1 and 2 are neutral (operations neither help nor significantly harm strategy).  
- Stages 3 and 4 are supportive (operations actively contribute to success).  
- The shift from internal to external focus marks a major leap in strategic impact.  
- The model is both descriptive (how operations currently contribute) and prescriptive (encouraging ascent to higher stages for competitive edge).

Applications and Relevance
Originally focused on manufacturing, the model applies equally to services, supply chains, and modern digital operations. It remains highly relevant in 2026 for assessing how operations (including AI-driven processes, sustainability, or agile manufacturing) can move beyond parity to true differentiation.

In summary, the Hayes and Wheelwright model reminds us that great companies don't treat operations as a back-office function — they elevate it to become a strategic weapon. Ascending the stages requires deliberate investment in capabilities, alignment, and innovation.

What happened at Indigo airlines in India ?

This discussion would not have happened in any other academic campus in the country. 

The Indigo employees were used to a highly efficient hectic safe work schedule across the country. This was disturbed by the assessment of potential future health problems of employees in flights endangering passenger safety and the govt organised initiatives inclyding reducing weekly work hours and schedule for flying staff meant with good intentions to improve flight safety in general across the country. 

Indigo took it easy and did not take enough precautions early on to increase flight crew, as lean principles and high employee utilisation were topmost in their mind. They delayed implementation of govt policies leading to the issue.

VSM symbols and Value Stream Map .. ..

 

Deep Learning output, from a blackbox ?

Deep learning models, particularly large neural networks like those used in computer vision or natural language processing, are generally considered "black boxes." This means that while we can observe the inputs and outputs, the internal workings—such as exactly which neuron processes which specific piece of information—are not transparently understandable.

When can this be properly understood or analysed ? Is the output from Deep Learning systems optimised or randomised ? Can we understand working of Deep Learning systems better ? Can any other digital system optimally replace this blackbox of neurons and network ?