Nikhil Sawant

Though in most of the organizations across industries, best practices are well documented and widely available, there are only few who are able to harness them to achieve world-class excellence because the very essence of success lies in creating an ecosystem where best practices can be made easily accessible and explainable, implemented through a strong leadership intent & support through an efficient and effective change management mechanism. There only few companies who succeed in leveraging best practices and achieve excellence because They accentuate on creating the right environment or eco-system to give the necessary impetus to best practice sharing and implementation. SME forums are well calendarized events in such organizations for fruitful discussion/deliberation on the best practices and how they can be deployed in various functional areas keeping in perspective cost reduction and risk mitigation objectives. They focus on creating training capsules/ modules so that best practices are understood holistically. Why, How, When, Where & Who aspects are known. Training workshops are organized and the best practices are explained with an industry example or success story for better retention and successful implementation Metrics are put in place to capture and measure implementation of best practices viz Best Practice Implementation Index (BPII) and the workforce is often rewarded based on tangible outcomes. Culture of experimentation is encouraged to test the best practices in diverse areas of relevance though the outcomes or benefits may not be significant Best practice implementation is managed through change control hub so that it is understood in the right spirit & context, there is buy-in for implementation from all stakeholders and the implementation is monitored and the outcome is tracked & measured For successful implementation of best practices and to institutionalize them, there is a strong leadership intent, support and involvement, amplified by the organizations vision and mission statements. There are workforce behavioral aspects or pre-conceived notions which may emerge as showstoppers in implementation of best practices. Successful organizations often leverage the Japanese concept of Nema washi to get the stakeholder buy-in or acceptance which helps in smooth implementation of best practices The leadership uses confidence building measures to ensure any apprehensions or perceived counter views or adverse notions are addressed in a timely manner to ensure successful implementation of best practices in the organization. Conclusion - Organizations will be able to harness best practices to achieve world-class excellence if there is · Demonstrated leadership intent and support backed by its vision/mission statement · A sustainable ecosystem where best practices can thrive · Existence of institutionalized ever-evolving learning cultural · Data and metrics driven approach · Strong culture of rewards and recognition · Robust change control framework

Capacity planning is critical to ensure total demand is serviced with accuracy and within the prescribed timelines, to meet contractual obligations, pre-empt or manage disruptions, sustain operations, ensure operational resiliency, navigate through challenges and ensure client satisfaction. In most of the organizations, capacity planning is done taking into consideration the following direct & indirect factors/aspects :- Processing volume arrival trends & patterns Seasonality of volume - Cyclical volume due to macro & micro economic conditions, market events etc Existing Baseline - Available time per FTE, Volume processed per FTE, Volume that can be processed in available time Cycle time at task level, Lead time, Takt Time Throughput Process shrinkages Learning curve Process complexity Turnover rates - current and anticipated Time it takes to hire attrition backfills Peak demand System downtime Set-up time Coverage window specified in Service level agreement Labour laws Permissible breaktimes Holiday calendar Production enablers Productivity Utilization Efficiency Shift Alignment Peaks & troughs Atomic level resiliency Recovery Planning Level of upskilling Manual touchpoints Automation Digital transformation initiatives Overtime & Night Shift allowance Very simple example of capacity calculation/ planning: if the available time per FTE per day is 480 minutes Production enablers = 80 minutes Actual available time per FTE per day = 480-80 = 400 minutes Production enablers includes deduction for meeting time, calls, training time, holidays, learning curve, hiring time etc Daily demand is to process 20000 widgets Time taken to process 1 widget is 2 minutes Then total demand in terms of minutes = 20000 *2 = 40000 minutes # FTEs required to service the total demand = 40000/400=100 FTEs 100 FTEs are required to process 20000 widgets per day. *FTE = Full Time Employee Above example is a simple illustration of capacity calculation/ planning. However the actual process is much more complex with nut & bolt level deep-dive involving complex calculations, extrapolation of numerical data basis the underlying assumptions and carefully baking in the aforementioned 30 influencing factors.

Break-even analysis can be leveraged in financial improvement Six Sigma projects in following ways: To ascertain if the project is financially viable by comparing costs and savings To define clear financial targets to achieve project success. To allocate resources more efficiently through a cost structure drill down To build trust among stakeholders though financial accountability. To assess financial risks and associated impact on the project's viability To measure progress and performance against financial targets. To take informed data driven decisions based on cost-benefit trade-off. To provide financial justification for the project to stakeholders. To prioritize projects based on their financial value. To analyze different scenarios and permutations to understand potential outcomes. To track financial progress and adjust/adapt the strategies as required. To perform a nut & bolt level cost-benefit analysis to understand the project's impact. To compare the project's financial performance against benchmarks in the industry. To control costs by identifying expenses (fixed + variable) To assess the return on investment by understanding the break-even point. To Identify areas for improving process efficiency. To create accurate budgets/baselines based on the break-even analysis. To forecast financial outcomes and plan for future improvements. To Identify areas for cost control/ reduction and efficiency gains. To Increase transparency and trust in financial planning and reporting. Other example where break even analysis could be leveraged in lean six sigma project is Energy Efficiency project where company aims to implement energy saving measures. If we consider the fixed cost as USD 500K, Variable cost of USD 50 per unit and cost savings of USD 150 per unit through reduced energy consumption. The breakeven point will be calculated as Fixed cost/ (Savings per unit – Variable cost per unit) = 500000/ (150-50) = 5000 units The energy efficiency measures need to save energy of at least 5000 units to break even.

ISO 31000 is a very well-known risk management construct. ISO 31000 provides a holistic framework for identifying, evaluating and managing risks across an organization, emphasizing on the importance of establishing a risk management framework & culture and integrating it in the decision-making processes. While FMEA is a framework to identify possible failures that may exist in the design of a product or process and assessing their impact, probability of occurrence and risk-based prioritization. Merging FMEA and ISO 31000 principles can have numerous advantages as summarized below: Helps in creating a holistic and agile risk identification framework covering all potential risks Helps in risk prioritization based on technical aspects and its alignment with strategic goals and objectives. Helps to align mitigation strategies with holistic risk management goals, directs resources to address high-priority risks Industry examples where FMEA & ISO 31000 are used to effectively manage risks: In automobile companies, integrating FMEA with ISO 31000 can address potential failures, ensure adherence to regulatory norms and improve product quality and safety features. In aerospace industry due to high safety standards, combining ISO 31000 & FMEA helps in analysing potential failures in various aircraft components like tail assembly, fuselage structure, engine, propeller and landing gear and improves maintenance and monitoring system The combined effect of ISO 31000 and FMEA provides a very potent tool to improve risk prioritization, mitigation, and overall risk management system.

KPI stands for key performance indicator, a metric to measure performance over time for a specific business objective. KPIs provide targets that teams can aim for, milestones to track progress and insights that help people across the organization take better data-driven decisions. Key performance indicators help every department in an organization march ahead at the strategic level from Finance and HR to Marketing & Sales. Have summarized below some of the Key Performance Indicators (KPIs) to measure/ascertain Collaboration Effectiveness: Cross-Functional Communication & Co-ordination Score 1. Evaluation of communication effectiveness among team members from different functions. 2. Will facilitate improved communication and co-ordination thereby reducing delays and misunderstandings 3. Highlights communication gaps through feedback and boosts collaboration through training 4. Healthcare companies optimize patient care and improve their experience by reducing wait time through inter-disciplinary co-operation and communication Interdepartmental Collaboration Quotient 1. Measures collaboration effectiveness between different functional units or teams 2. Improves interdepartmental coordination & collaboration to optimize workflows and achieve shared goals 3. Highlights areas of inter-functional area friction and opportunities for improved collaboration through joint initiatives 4. Companies like Airbus leverage Interdepartmental Collaboration Quotient to strengthen coordination between production, supply chain and engineering teams for aircraft manufacturing projects. Milestone Achievement Rate Measured as % Project milestones completed on time. Ensures adherence to delivery timelines and helps in tracking progress towards project milestones. Helps in identifying improvement needed in tracking mechanism, co-ordination, task level supervision and management Technology companies leverage Milestone Achievement Rate to ensure timely product releases and related service deployments Knowledge Sharing Ratio Ratio of shared knowledge or insights within a team Improves and encourages collaboration & co-operations and reduces redundant work in processes. Identifies silos and fosters a culture of learning and knowledge/information exchange Consulting firms like BSG leverage expertise across diverse teams & projects Collaborative Problem-Solving Capability Measures team's ability to jointly address and resolve project-related challenges Strengthens problem-solving skills and promotes adaptive responses to issues. Identifies opportunities for upskilling and team training to enhance problem-solving effectiveness. Pharma companies often measure collaborative problem-solving capability to drive collaborative problem resolution in drug development effort. By tracking the aforementioned KPIs to measure collaboration effectiveness, companies can gain valuable insights in communication processes, decision-making efficiency, team dynamics and overall quality of collaboration. Implementing improvements based on these KPIs can promote a culture of collaboration & co-operation, enhance teamwork & efficiency and drive successful outcomes is sync with the organizational goals of timely delivery and reduced inefficiencies.

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 Japanese term "Nemawashi" refers to the creating a foundation for a decision or project by having informal discussions with stakeholders before formal meetings or announcements. It involves building consensus to ensure that everyone is on the same page and that potential hurdles or concerns are addressed in advance. The term literally translates to "root binding," which metaphorically suggests that the way the roots are prepared before planting a tree, relationships and understandings should be nurtured before formal actions are taken. it is a common practise in Japanese business culture and accentuates the importance of collaboration and consensus-building. In English, Nemawashi can be referred to as “lobbying”, “greasing the skids”, “testing the waters”, “obtaining buy-in”, “getting people on the bandwagon”, “sending up a trial balloon”, “offline persuasion”, “getting everyone on the same page” and “building consensus”. However, none of them truly captures the essence of Nemawashi being an ongoing organizational process rather than a one-time event Nemawashi’ is widely used in Japanese companies, particularly in Toyota. In Toyota, Nemawashi is considered as the first step in decision making where the managers share information about the proposed change with their employees to create the foundation for upcoming changes in the organization and getting buy-in on specific business decisions that may impact them. By doing so, changes are met with little to no resistance as everyone provides their approval. Have encapsulated below some of the examples on how Nemawashi can be used to align stakeholders to ensure successful deployment of strategic initiatives 1.Unilever marketing team having focused group discussion with customers on new product concept before finalizing the design 2.A Vice President, operations having chat with different AVPs and officers over informal coffee session to ascertain their reaction to overall department level restructuring before making a formal announcement 3.A project manager of a leading IT company having informal chat during a team dinner session to understand showstoppers before presenting a detailed project plan to senior leadership

Boundary spanning means activities undertaken by individuals or organizations to engage with, and combine the knowledge, resources, and relationships across their internal and external environments and adapt to dynamic business ecosystem. Boundary spanning has its origin in the systems theory which sees an organization as an open system interacting with its environment. Boundary Spanning initiatives helps in institutionalizing the culture of collaboration, shared goals and objectives thereby, breaking down the functional silos. This improves decision making and enhances overall organizational efficiency. Example, Companies like Flipkart, Amazon, Myntra etc. encourage managers to collaborate across business units, this facilitates cross functional teamwork by breaking down silos and fostering Innovation. Technology giants like Microsoft, Google and Apple encourage cross functional teams to collaborate on projects. This interdisciplinary approach augments innovation by capitalizing on diverse knowledge, cognitive sparks, skillsets and views. Big FMCG companies often establish cross functional teams across geographies and regions to align and adapt their product and marketing strategies to diverse cultural preferences which helps them to effectively navigate the fast and ever evolving market landscapes. Some of the high-level examples of boundary spanning: · Strategic Alliances on security like NATO & QUAD · Multi-national economic alliances like G7, G20 & BRICS · Mergers & Acquisitions · Research & Development collaborations Boundary spanning helps organizations to thrive in ever evolving, complex and dynamic business environment. The real-world examples aptly demonstrate how boundary spanning initiatives helps in breaking down silos, promotes cross-functional teamwork and drives organizational success by harnessing collective knowledge and insights of diverse stakeholders across boundaries.

Nobelist Daniel Kahneman's book, Thinking, Fast and Slow introduces readers to two systems of thinking that our brain uses to process information and solve problems. System 1 thinking is the automatic mode, not under voluntary control, more intuitive, based on emotions, vivid Imagery and associative memory etc. leading to quick decision making but may be error prone. System 2 thinking is slow, conscious, deliberate, logical, more analytical and effortful, often used for solving complex problems and is more reliable. Leaders using system 1 thinking often excel in ever evolving situations where quick decisions are a necessity. Such leaders may excel in crisis management. Leaders using system 2 thinking are generally good at strategic planning and solving complex problems. To balance System 1 and system 2 thinking, leaders must recognize when to rely on intuitions/instincts and when to engage in deeper analysis. Example: In case of a cyber security breach, the CEO may need to act quickly and implement a response plan based on instincts and threat/risk assessment – System 1 thinking After the initial response to a crisis, the CEO consults with cybersecurity experts & conducts a more detailed analysis of the situation and devises a comprehensive strategy to prevent future breaches- System 2 thinking To summarize: By balancing System 1 and System 2 thinking and harnessing the strengths of each system appropriately, leaders can navigate through ever evolving high-pressure situations and long-term strategic planning with confidence and clarity.

In the digital era, black box paradox simply put is the inverse relationship between AI based decision making & transparency and trust. It is imperative to understand the rationale behind AI-generated decision making to pre-empt or reduce scope for bias, discrimination and unpleasant consequences. There are different ways of balancing use of complex AI model-based decision making and transparency and trust like use of explainable AI techniques, incorporating ethical considerations, adherence to industry standards and regulations on AI transparency, extensive documentation and analysing the decision making of trained machine learning models to make it more understandable to humans for ease of debugging and to detect any instance of data poisoning etc. Example of balancing act – E- commerce websites that analyses massive amounts of online data of its customers like their behavioural patterns, spending trends, search history, online content accessed, time spent online to spur sales by suggesting product mix, providing lucrative pricing, offering discounts etc should ensure there are new and ethical ways of collecting and analysing data, ensuring privacy protection, eliminating bias/discrimination and implementing explaining AI techniques to ensure transparency & accountability. While use of AI driven decision making is inevitable, it should be leveraged for betterment of humans and not to replace their ingenuity and consciousness.

Black Box Paradox presents a formidable challenge in this digital wave of Artificial Intelligence. The dilemma is the balancing act of using sophisticated AI algorithms for their improved decision-making capability and at the same time ensuring humans are able to demystify the rationale behind AI-generated outcomes. We can make AI based decision making more understandable to humans by using explainable AI techniques, accentuating on ethical considerations, adhering to prescribed industry standards on transparency, involving domain experts, incorporating controls to pre-empt data poisoning, making debugging easy for human interpretation etc Large multinational banks often use AI based algorithms to assess credit worthiness of their customers and to detect frauds while ensuring trust & transparency in the decision-making process by adhering to ethical standards, eliminating bias/discrimination, being compliant with laws and regulations and in sync with Industry standard on transparency. Blackbox paradox can be addressed if the purpose is ethical baked in human consciousness.