Remembering Sir Ratan Tata: A Legacy of Leadership and Compassion

Prasad AjinkyaLeave a comment

The world mourns the loss of Sir Ratan Tata, a titan of industry and a beacon of philanthropy, who passed away at the age of 86 on October 9, 2024. His passing marks the end of an era for the Tata Group and the broader business community, both in India and globally.

A Visionary Leader

Ratan Tata’s journey with the Tata Group began in 1962, when he returned to India from the United States. Over the decades, he transformed the conglomerate into a global powerhouse, overseeing landmark acquisitions such as Corus, Jaguar Land Rover, and Tetley Tea. Under his leadership, the Tata Group’s revenues soared, and its influence expanded across diverse sectors including steel, automotive, IT, and hospitality.

A Heart for Philanthropy

Beyond his business acumen, Ratan Tata was deeply committed to philanthropy. He believed in using business as a force for good, a principle that guided the Tata Group’s operations. The Tata Trusts, which control a significant portion of the group’s shares, have funded numerous initiatives in education, healthcare, and rural development. His efforts have left an indelible mark on society, improving countless lives.

Tributes Pour In

Tributes have poured in from all corners of the globe. Prime Minister Narendra Modi described Tata as “a visionary business leader, a compassionate soul, and an extraordinary human being”. Leaders from various industries and sectors have echoed these sentiments, highlighting his humility, kindness, and unwavering commitment to making the world a better place.

A Personal Reflection

For many, Ratan Tata was more than just a business leader; he was a mentor and a role model. His leadership style was characterized by integrity, empathy, and a relentless pursuit of excellence. He once said,

I don’t believe in taking right decisions. I take decisions and then make them right.

This philosophy not only defined his career but also inspired countless others to strive for greatness.

A Lasting Legacy

As we bid farewell to Sir Ratan Tata, we remember a man whose legacy will continue to inspire future generations. His contributions to business and society are immeasurable, and his spirit of innovation and compassion will live on in the countless lives he touched.

Rest in peace, Sir Ratan Tata. Your legacy will forever be a guiding light.

Citizenship in a Democracy

Prasad AjinkyaLeave a comment

Voting day in Mumbai is always a heated affair.

By late afternoon, the voting turnout has been pretty low. In fact, it was lesser than 30% at 1pm. This benchmark is a pretty poor number for one of the most populated cities in this country, if not the world.

Why, then this low figure? There could be multiple reasons for this which most readers will rattle off!

High temperatures

With temperatures touching the high 30s and humidity in the high 90s, the sweltering heat feels like a suffocating blanket on everything. If you have been outside these days without the safety of the office AC, you will feel the continuous sapping of energy and always feel dehydrated at the end of every excursion outside the cool interiors.

Working offices

Section 135B exists, but only in principle. Most offices in Mumbai and other metropolitan cities have been working throughout the day, with a half-day being given to employees.

The problem with this specific clause is that for those employees who actually want to vote the leave is not really needed, and for those who do not want to vote, the leave is just an additional leave. Hence most companies are choosing to interpret it as such – you apply for a leave, and it shall be granted, however coming to office and pushing off early won’t be considered as a half day.

Long weekend

With elections in Mumbai being planned on Monday and the paid holiday for employees pretty much guarantees everyone a three-day long weekend to plan their trips.

Having to come back from their weekend trips to stand in long queues in this heat is something that a lot of people may not look forward to.

Having said that, why citizenship in the title?

Voting should be an act of citizenship

The reason is simple. I believe that by choosing to actively participate in the election of the world’s largest democracy, all of us are making the choice of being a citizen.

Being a citizen doesn’t necessarily mean simply standing in a queue and casting your vote in a ballot box. It means, actively working towards the organizational goals of the country.

Sadly, this is a trait that hasn’t been inculcated in a lot of people. Folks simply do not know what citizenship is or what does it mean to be a citizen.

I am providing a video of what I think acting like a citizen entails. It doesn’t stop at voting, it has a much more engaged definition.

As the markets went in their roller coaster, and eventually normalcy returned, I cannot help but think that even though the elections went by pretty smoothly – our citizens haven’t really changed.

Setting Up a Healthy Engineering Culture: A Blueprint for Success

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engineering culture

As organizations strive to build innovative products and deliver exceptional value to their customers, fostering a healthy engineering culture becomes paramount. A strong engineering culture not only attracts top talent but also drives productivity, collaboration, and long-term success. In this blog post, we’ll explore the key elements of a healthy engineering culture and provide actionable steps to set it up within your organization.

What Is Engineering Culture?

An engineering culture encompasses the shared values, norms, and practices that define how engineers work together to achieve common goals. It’s the DNA of your technical team, influencing everything from code quality to communication patterns. Here are some essential features of a robust engineering culture:

  1. Collaboration and Communication:
    • Encourage open communication and cross-functional collaboration. Foster an environment where engineers can freely exchange ideas, seek feedback, and learn from one another.
    • Use tools like Slack, Microsoft Teams, or other communication platforms to facilitate real-time discussions and knowledge sharing.
  2. Continuous Learning and Professional Development:
    • Invest in learning opportunities for your engineers. Provide access to conferences, workshops, online courses, and mentorship programs.
    • Encourage engineers to stay updated with industry trends, best practices, and emerging technologies.
  3. Agile Development Practices:
    • Adopt agile methodologies (e.g., Scrum, Kanban) to promote iterative development, shorter release cycles, and adaptive planning.
    • Regularly review and adapt your processes based on feedback and performance metrics.
  4. Code Reviews:
    • Make code reviews a standard practice. They improve code quality, knowledge sharing, and alignment with coding standards.
    • Encourage constructive feedback and ensure that reviews are respectful and focused on improvement.
  5. Engineering Excellence:
    • Set high standards for technical excellence. Encourage engineers to write clean, maintainable code and follow best practices.
    • Invest in tools and practices that enhance code quality, such as static analysis, automated testing, and continuous integration.
  6. Innovation and Experimentation:
    • Create space for innovation. Allow engineers to explore new ideas, experiment with technologies, and propose improvements.
    • Celebrate successful experiments and learn from failures.
  7. Diversity and Inclusion:
    • Build a diverse engineering team that brings different perspectives and experiences. Embrace diversity in gender, ethnicity, background, and thought.
    • Foster an inclusive environment where everyone feels valued and respected.

How to Build an Engineering Culture

  1. Lead by Example:
    • Leadership plays a crucial role in shaping culture. Demonstrate the desired behaviors, communicate the vision, and actively participate in cultural initiatives.
    • Encourage transparency, accountability, and empathy.
  2. Define Core Values:
    • Collaborate with your team to define core values that align with your organization’s mission. These values should guide decision-making and behavior.
    • Examples of core values: integrity, customer focus, continuous improvement, and teamwork.
  3. Promote Psychological Safety:
    • Create an environment where engineers feel safe to express their opinions, ask questions, and take calculated risks.
    • Avoid blame culture and encourage learning from mistakes.
  4. Recognize and Reward Success:
    • Celebrate achievements, both big and small. Recognize engineers who go above and beyond.
    • Consider peer recognition, spot bonuses, or team outings as ways to appreciate contributions.
  5. Invest in Team Building:
    • Organize team-building activities, offsites, and hackathons. Strengthen relationships and build trust among team members.
    • Encourage social interactions beyond work-related discussions.
  6. Measure and Improve:
    • Regularly assess your engineering culture. Use surveys, feedback sessions, and metrics to gauge satisfaction and identify areas for improvement.
    • Iterate and adapt based on the feedback received.

Conclusion

A healthy engineering culture is not built overnight; it requires consistent effort, alignment, and commitment. By fostering collaboration, learning, and excellence, you can create an environment where engineers thrive, innovate, and contribute to the success of your organization. Remember that culture is not just what you say—it’s what you do every day.

Different Frameworks in Large Language Models (LLMs)

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Abstract LLM models

Introduction

We live in a world where language is at the heart of communication and understanding. From everyday conversations to complex business interactions, the power of language cannot be underestimated. Add to that the complexities of deep learning models trying to understand and generate human languages, and you have another language source. With large language models (LLMs), the boundaries of language processing and generation have been pushed even further.

What are Large Language Models?

Large language models (LLMs) are a revolutionary breakthrough in the field of natural language processing and artificial intelligence. These models are designed to understand, generate, and manipulate human language with an unprecedented level of sophistication. At their core, LLMs are complex neural networks that have been trained on vast amounts of textual data. By leveraging deep learning techniques, these models can capture the intricate patterns and structures inherent in language. LLMs are capable of learning grammar, semantics, and even nuances of expression, allowing them to generate text that closely resembles human-authored content.

The development of LLMs has been a result of continuous advancements in language models over the years. From the early rule-based systems to statistical models and now deep learning approaches, the journey of language models has been marked by significant milestones. The evolution of large language models has been fueled by the availability of massive amounts of text data and computational resources. With each iteration, models have become larger, more powerful, and capable of understanding and generating language with increasing accuracy and complexity. This progress has opened up new possibilities for applications in various domains, from natural language understanding to machine translation and text generation.

Understanding the Capabilities of LLMs

To truly appreciate the capabilities of LLMs, it is essential to delve into their wide range of applications. LLMs can be used for tasks such as:

  1. Language Translation: LLMs excel at translating text from one language to another, providing accurate and contextually relevant translations.
  2. Text Summarization: LLMs can summarize lengthy articles or documents into concise and informative summaries.
  3. Sentiment Analysis: By analyzing text, LLMs can determine the sentiment (positive, negative, or neutral) expressed in a piece of content.
  4. Creative Writing: While limited, LLMs can generate creative content, including poems, stories, and dialogues.

One of the most remarkable features of LLMs is their ability to generate coherent and contextually relevant text. By feeding them a prompt or a partial sentence, LLMs can complete the text in a way that aligns with the given context and adheres to the rules of grammar and style. This opens up exciting possibilities for content creation, automated customer support, and personalized employee experiences.

How Large Language Models Work

Architecture of LLMs

To grasp how Large Language Models (LLMs) operate, it’s important to understand their underlying architecture. LLMs typically follow a transformer-based architecture, which has proven to be highly effective in natural language processing tasks. Key components of this architecture include:

  • Multiple Layers: LLMs consist of multiple layers, including feedforward layers, embedding layers, and attention layers.
  • Attention Mechanisms: LLMs employ attention mechanisms, like self-attention, to weigh the importance of different tokens in a sequence, allowing the model to capture dependencies and relationships.

Types of LLMs

There are different types of large language models, including:

  1. GPT (Generative Pre-trained Transformer): A decoder-only transformer-based model.
  2. BERT (Bidirectional Encoder Representations from Transformers): An encoder-decoder model.
  3. T5 (Text-to-Text Transfer Transformer): An autoencoder model.
  4. Hybrid Models: These combine different architectural components.

In summary, LLMs represent a significant leap in natural language understanding and generation. As research continues, we can expect even more powerful and versatile LLMs to shape the future of language-based AI applications.

Vanity Metrics: What They Are and Why You Should Avoid Them

Prasad AjinkyaLeave a comment
Futility of vanity metrics

As a marketer, you probably use various metrics to measure and evaluate your marketing performance and success. Metrics such as website traffic, social media followers, email subscribers, and video views can help you understand how your marketing efforts are reaching and engaging your target audience. However, not all metrics are equally useful and meaningful. Some metrics may look impressive and flattering, but they may not actually reflect the true value and impact of your marketing activities or that of your business. These metrics are known as vanity metrics.

What are vanity metrics?

Vanity metrics are metrics that make you look good to others, but do not help you understand your own performance in a way that informs future strategies. These metrics are often easy to measure and manipulate, but they do not indicate any real return on investment (ROI) or customer behavior. Examples of vanity metrics include:

  • Website traffic: The number of visitors or sessions on your website may seem like an important indicator of your website’s popularity and reach, but it does not tell you anything about the quality and relevance of your traffic, or how your traffic converts into leads or customers.
  • Social media followers: The number of followers or fans on your social media accounts may seem like a measure of your social media influence and authority, but it does not tell you anything about the engagement and loyalty of your followers, or how your followers interact with your brand or products.
  • Email subscribers: The number of subscribers on your email list may seem like a measure of your email marketing potential and growth, but it does not tell you anything about the deliverability and open rate of your emails, or how your subscribers respond to your email campaigns.
  • Video views: The number of views on your videos may seem like a measure of your video marketing reach and impact, but it does not tell you anything about the retention and completion rate of your videos, or how your viewers take action after watching your videos.

Why you should avoid vanity metrics

Vanity metrics may be tempting and satisfying to track and report, but they can be misleading and harmful for your marketing strategy and goals. Here are some reasons why you should avoid vanity metrics:

  • They do not help you make data-driven decisions: Vanity metrics do not provide any actionable insights or feedback that can help you improve your marketing performance and outcomes. They do not tell you what works and what does not work, what to do more of and what to do less of, or what to change and what to keep. They do not help you optimize your marketing tactics and channels, or allocate your marketing resources and budget effectively.
  • They do not help you align with your business objectives: Vanity metrics do not align with your business objectives, such as increasing sales, revenue, or profit. They do not show you how your marketing activities contribute to your bottom line, or how they generate value for your business and your customers. They do not help you demonstrate your marketing ROI, or justify your marketing spend and efforts.
  • They do not help you build trust and credibility: Vanity metrics do not build trust and credibility with your stakeholders, such as your management, your team, your partners, or your customers. They do not reflect the true quality and impact of your marketing work, or the real needs and preferences of your target audience. They may even damage your reputation and credibility, if your stakeholders discover that your metrics are inflated, manipulated, or irrelevant.
  • They can be open to subjective interpretations: Vanity metrics can be interpreted in a variety of methods, thus creating confusion instead of giving a clear direction towards efforts.

How to avoid vanity metrics

To avoid vanity metrics, you need to focus on metrics that are relevant, meaningful, and actionable for your marketing strategy and goals. These metrics are often called actionable metrics, as they help you take action and make decisions that improve your marketing performance and success. Here are some tips on how to avoid vanity metrics and use actionable metrics instead:

  • Define your marketing goals and objectives: Before you start measuring and evaluating your marketing performance, you need to define your marketing goals and objectives, and align them with your business goals and objectives. Your marketing goals and objectives should be SMART: specific, measurable, achievable, relevant, and time-bound. For example, instead of having a vague goal of increasing website traffic, you can have a SMART goal of increasing website traffic by 10% in the next quarter, by targeting a specific segment of your audience, using a specific channel or tactic, and measuring a specific metric or outcome.
  • Choose your key performance indicators (KPIs): Based on your marketing goals and objectives, you need to choose your key performance indicators (KPIs), which are the metrics that indicate whether you are achieving your goals and objectives, or not. Your KPIs should be relevant, meaningful, and actionable for your marketing strategy and goals. For example, instead of using website traffic as a KPI, you can use website conversion rate, which measures the percentage of your website visitors who take a desired action, such as signing up for a newsletter, downloading a white paper, or making a purchase.
  • Track and analyze your data: Once you have chosen your KPIs, you need to track and analyze your data, using various tools and methods, such as Google Analytics, dashboards, reports, and experiments. You need to track and analyze your data regularly and consistently, to monitor your marketing performance and progress, and to identify any trends, patterns, or anomalies. You also need to track and analyze your data in context, by comparing it with your benchmarks, targets, or competitors, and by segmenting it by various dimensions, such as source, channel, device, or audience.
  • Take action and improve: Based on your data analysis, you need to take action and improve your marketing performance and outcomes. You need to use your data to make data-driven decisions, such as what to do more of and what to do less of, what to change and what to keep, or what to test and what to implement. You also need to use your data to optimize your marketing tactics and channels, and to allocate your marketing resources and budget effectively. You also need to measure and evaluate the impact of your actions and improvements, and to iterate and refine your marketing strategy and goals accordingly.

Conclusion

Vanity metrics are metrics that make you look good to others, but do not help you understand your own performance in a way that informs future strategies. They are often easy to measure and manipulate, but they do not indicate any real return on investment or customer behavior. Examples of vanity metrics include website traffic, social media followers, email subscribers, and video views.

To avoid vanity metrics, you need to focus on metrics that are relevant, meaningful, and actionable for your marketing strategy and goals. These metrics are often called actionable metrics, as they help you take action and make decisions that improve your marketing performance and success. To avoid vanity metrics and use actionable metrics instead, you need to define your marketing goals and objectives, choose your key performance indicators, track and analyze your data, and take action and improve.

By avoiding vanity metrics and using actionable metrics, you can improve your marketing performance and outcomes, align with your business objectives, and build trust and credibility with your stakeholders.

API Based Economy in India: A New Paradigm for Growth

Prasad AjinkyaLeave a comment
Digital India

APIs, or Application Programming Interfaces, are the building blocks of the digital economy, enabling software applications and systems to communicate and exchange data with each other. APIs are essential for creating seamless and integrated digital experiences, as well as enabling innovation and collaboration across various sectors and domains.

India and the APIs

India, as one of the fastest-growing and most diverse economies in the world, has a huge potential to leverage APIs to transform its businesses, industries, and society. According to a report by NASSCOM, the Indian API market is expected to grow at a CAGR of 17.2% from 2019 to 2024, reaching $5.1 billion by 2024.

The report also identifies six key drivers for the growth of the API economy in India, namely:

  • Digital transformation: As more businesses and organizations adopt digital technologies and platforms to enhance their efficiency, productivity, and customer satisfaction, APIs play a vital role in enabling interoperability, scalability, and agility.
  • Government initiatives: The government of India has launched several initiatives and policies to promote the adoption and development of APIs, such as the India Stack, a set of open APIs that provide access to various digital infrastructure and services, such as Aadhaar, UPI, eKYC, and eSign. The government has also mandated the use of APIs for various public services and schemes, such as GST, FASTag, and Ayushman Bharat.
  • Startup ecosystem: India has a vibrant and dynamic startup ecosystem, with over 50,000 startups operating in various domains, such as fintech, e-commerce, healthtech, edtech, and agritech. These startups rely on APIs to access and offer various solutions and services, such as payments, logistics, analytics, and cloud computing.
  • Consumer demand: The Indian consumer market is one of the largest and most diverse in the world, with over 1.3 billion people and a growing middle class. The Indian consumers are increasingly demanding and expecting personalized, convenient, and seamless digital experiences, which can be delivered by APIs.
  • Data explosion: India is witnessing a massive surge in data generation and consumption, driven by the proliferation of smartphones, internet penetration, social media, and online platforms. According to a report by Cisco, India’s IP traffic is expected to grow at a CAGR of 26% from 2018 to 2023, reaching 21.5 exabytes per month by 2023. APIs enable the efficient and effective management, analysis, and utilization of this data, creating value and insights for businesses and consumers.
  • Innovation and collaboration: APIs foster a culture of innovation and collaboration, as they allow businesses and organizations to create and offer new and improved products, services, and solutions, by leveraging the capabilities and resources of other entities. APIs also enable the creation of new and niche markets and segments, such as peer-to-peer lending, microfinance, and social impact.

Key benefits of using APIs

The API economy in India is creating new opportunities and challenges for businesses, industries, and society. Some of the benefits of the API economy include:

  • Enhanced customer experience: APIs enable businesses to offer personalized, convenient, and seamless digital experiences to their customers, by integrating various solutions and services, such as payments, delivery, loyalty, and feedback. APIs also enable businesses to reach and engage new and untapped customer segments, such as rural and unbanked populations, by leveraging the digital infrastructure and platforms provided by the government and other entities.
  • Increased efficiency and productivity: APIs enable businesses to optimize and automate their processes and operations, by connecting and synchronizing various systems and applications, such as ERP, CRM, and inventory management. APIs also enable businesses to reduce their operational costs and risks, by outsourcing and accessing various solutions and services, such as cloud computing, analytics, and security, from third-party providers.
  • Improved innovation and competitiveness: APIs enable businesses to innovate and differentiate themselves from their competitors, by creating and offering new and improved products, services, and solutions, by leveraging the capabilities and resources of other entities. APIs also enable businesses to collaborate and partner with other entities, such as startups, government, and academia, to co-create and co-deliver value and impact.

Risks and challenges ahead

However, the API economy in India also poses some challenges and risks, such as:

  • Data privacy and security: APIs involve the exchange and sharing of sensitive and personal data, such as identity, financial, and health information, which can be vulnerable to breaches, leaks, and misuse. Therefore, businesses and organizations need to ensure that they comply with the relevant laws and regulations, such as the Personal Data Protection Bill, 2019, and the Information Technology Act, 2000, as well as adopt best practices and standards, such as encryption, authentication, and authorization, to protect the data and the rights of the data subjects.
  • Quality and reliability: APIs need to ensure that they provide consistent, accurate, and reliable data and services, as they can affect the performance and functionality of the applications and systems that depend on them. Therefore, businesses and organizations need to ensure that they test, monitor, and maintain their APIs, as well as adopt quality and reliability metrics and measures, such as SLAs, uptime, latency, and error rates, to ensure the satisfaction and trust of their customers and partners.
  • Regulation and governance: APIs need to comply with the relevant laws and regulations, as well as the policies and guidelines of the entities that provide or consume them. Therefore, businesses and organizations need to ensure that they understand and adhere to the legal and contractual obligations and responsibilities, as well as the ethical and social implications, of their APIs. They also need to establish and enforce clear and transparent governance mechanisms and frameworks, such as API documentation, versioning, and lifecycle management, to ensure the accountability and sustainability of their APIs.

The API economy in India is a new paradigm for growth, as it enables businesses, industries, and society to leverage the power and potential of the digital economy, and create value and impact for themselves and others. How we leverage this and grow on to become the largest economy is something that still remains to be seen and this is where the next set of technology companies should be working on.

Generative AI in lending

Prasad AjinkyaLeave a comment
AI content creator generated using DALL-E

The Indian lending market is one of the fastest-growing and most diverse in the world, with a huge potential for financial inclusion and social impact. According to a report by Boston Consulting Group, the Indian lending market is expected to grow from $1.2 trillion in 2019 to $3.5 trillion by 2024, driven by the increasing demand for credit from individuals, small businesses, and rural segments.

Problems in the lending industry

However, the Indian lending market also faces several challenges, such as high operational costs, low credit penetration, complex regulatory environment, and high credit risk. Traditional lending models rely on manual processes, limited data sources, and rigid criteria, which result in inefficiencies, delays, and exclusions. Moreover, the COVID-19 pandemic has exacerbated the situation, as lenders face increased defaults, liquidity crunch, and changing customer behavior.

To overcome these challenges and tap into the opportunities, lenders need to adopt innovative and agile solutions that can enhance their efficiency, scalability, and profitability. This is where generative AI, a branch of artificial intelligence that can create novel and realistic content, such as text, images, audio, and video, comes into play.

What can generative AI do?

Generative AI can transform the Indian lending landscape by enabling lenders to:

  • Automate and optimize the lending process: Generative AI can automate and optimize various steps of the lending process, such as customer acquisition, verification, underwriting, disbursal, and recovery. For example, generative AI can create personalized and engaging marketing campaigns, analyze alternative and unconventional data sources, such as social media, e-commerce, and geolocation, to assess creditworthiness and risk, generate customized loan offers and contracts, and create interactive and empathetic chatbots and voice assistants to facilitate communication and collection.
  • Enhance fraud detection and prevention: Generative AI can enhance fraud detection and prevention by identifying and flagging suspicious patterns and anomalies in the data and transactions. For example, generative AI can detect fake or tampered identity proofs and documents, such as Aadhaar cards, PAN cards, and bank statements, by comparing them with the original or authentic versions. Generative AI can also detect fraudulent or malicious behavior, such as identity theft, money laundering, and cyberattacks, by analyzing the behavioral and transactional data of the customers and the lenders.
  • Innovate and diversify the lending products and services: Generative AI can innovate and diversify the lending products and services by creating new and tailored solutions that cater to the specific needs and preferences of the customers. For example, generative AI can create dynamic and flexible loan products that adjust to the changing circumstances and requirements of the customers, such as income fluctuations, emergencies, and life events. Generative AI can also create new and niche lending segments and markets, such as peer-to-peer lending, microfinance, and social impact lending, by leveraging the power of the crowd and the network.

Challenges in using generative AI

Generative AI is a new frontier for the Indian lending industry, as it offers immense possibilities and benefits for both the lenders and the customers. However, generative AI also poses some challenges and risks, such as ethical, legal, and social implications, data quality and security issues, and human-machine interaction and collaboration challenges. Therefore, generative AI needs to be adopted and implemented with caution and responsibility, ensuring that it is aligned with the values and goals of the stakeholders and the society.

I am not even going to talk about the compliance risk and the risk of using a pre-cooked model which may not even be similar to the target audience.

Generative AI is not a magic bullet that can solve all the problems of the Indian lending industry, but it is a powerful and promising tool that can augment and enhance the existing capabilities and solutions. Generative AI can help the Indian lenders to become more efficient, scalable, and profitable, while also serving the customers better and faster.

However, smart and crisp solutions are yet to be seen in the Indian market, and this is an area of work for us at Homeville.