Maximizing Business Potential Through End-to-End Data Solutions
Sam Mantle is the CEO of Lingaro Group, bringing extensive experience in digital transformation and technology leadership. He has held senior leadership roles at Luxoft and Novartis, driving growth and innovation across industries like healthcare and digital engineering. Passionate about building high-performance teams, Sam is based in Basel, Switzerland. He holds a master’s degree in Aerospace Engineering from the University of Bristol and Paul Sabatier University. Prior to Lingaro, he spent over a decade at Novartis in senior IT and CIO roles, leading technology transformations across Europe, Asia, and the US.
In the recent interaction with Mandvi Singh, Managing Editor, siliconindia, Sam Mantle shared his insights on Maximizing Business Potential Through End-to-End Data Solutions.
End-to-end data solutions play an essential role in helping businesses gain a competitive edge by enabling better decision-making. By leveraging the data available about their operations, customers, and market trends, businesses can make more informed decisions that drive their success.
Many industries, particularly those in consumer products and fast-moving consumer goods (FMCG), have long relied on real-time data to guide business decisions. For example, sales and marketing executives use this data to understand which products are selling in specific regions, the profiles of consumers in the market, and how best to target marketing efforts to convert potential customers. Additionally, real-time data allows businesses to streamline supply chains, ensuring products reach end consumers quickly, affordably, and reliably.
How Data End-to-End Solutions Drive Competitive Edge
The ability to use real-time data to drive decisions often sets successful businesses apart from average ones. Industries that value the immediate availability of data such as consumer products, retail, consumer health, and life sciences have shown how such insights can lead to continuous advancement. The adoption of data-driven decision-making in these sectors helps businesses reduce costs, maximize revenue, and improve overall performance. As a result, businesses are increasingly adopting the same principles that FMCG companies have used to gain a competitive advantage. However, integrating data across systems and functions presents challenges, but overcoming them can offer significant rewards, making data a powerful tool for gaining an edge in the marketplace.
To overcome data integration challenges, the first strategy companies should adopt is to define a clear data strategy. Many companies often rush into building data lakes or data swaps, making it hard to extract valuable insights. It’s crucial to align the strategy with business objectives by understanding key drivers, identifying value areas, and determining market positioning. After this, companies should define data governance, master data management principles, and design the necessary data assets and environments to support the strategy.
Just like building a house requires a blueprint, creating a successful data environment requires careful planning to align with business goals. As data evolves and AI is integrated, companies must be agile, adapting models continuously. To support this, businesses must have robust support processes in place to both build but also to change the wheels as you're driving along the road.
Unlocking Data: Powering AI, Cybersecurity, and Governance
AI and machine learning are not essentially designed to meet the necessities of data but their effectiveness is largely dependent on the quality of data fed into them. While AI and machine learning capabilities, especially generative AI, are evolving at a frenetic pace and creating buzz within the industry, the power of these technologies actually comes from the data supporting them. Even the best models today are only as good as the data they were trained on. For instance, anyone can use tools like ChatGPT, but it is what data and prompts are used to generate results that hold the real value.
Companies are strengthening data governance to mitigate ESG reporting capabilities by ensuring strong compliance and controls around their IT environments and data assets. While cybersecurity is a critical and complex issue, companies recognize the importance of collaborating with cybersecurity experts to protect their environments. The focus on data governance, however, lies in ensuring that any data entering a company's environment is protected and monitored using strict security protocols. Many companies often neglect the monitoring component, which is essential to maintaining security.
The majority of the work is done within client environments, so the exposure of their data to the external world is minimal, and in many cases, companies do not even have access to real-time data, which is carefully protected and held away. Companies emphasize the importance of partnering with experts in the cybersecurity field, just as they focus on expertise in data management. This partnership ensures robust security measures and protects sensitive data from potential risks.
Data-Driven ESG and GCC Growth
Companies providing data solutions believe that the ESG (Environmental, Social, and Governance) agenda is evolving rapidly and is becoming an important space for their work. They help their clients build up ESG reporting capabilities, not only to meet regulatory obligations but also to understand where they stand in terms of sustainability. They emphasize that no company can improve unless it measures its progress. The challenge many companies face today is that they are unable to measure their ESG impact due to a lack of solid data reference points. These companies view ESG reporting as both a necessity and a competitive advantage, with many businesses now prioritizing sustainable suppliers. By adopting and tracking ESG principles internally, they demonstrate their commitment and credibility in this space, helping clients align their strategies with sustainability goals.
The focus on expanding GCCs (Global Capability Centers) in India is driving significant growth and innovation. The agenda of these GCCs is highly data-centric, which aligns with the emphasis on data specialization that many companies, like Lingara, have advocated for years. Recognizing the importance of data, many large enterprises are developing internal capabilities within these GCCs in India.
For companies in the data space, this is an ideal opportunity. They have long emphasized the need for dedicated expertise and ownership of data. Companies must take internal ownership of managing data assets, but they also need to partner with experienced firms to guide them through the process. The goal is to build a collaborative relationship where knowledge is shared openly and transparently, supporting clients in taking ownership while guiding them through this critical journey. Data ownership will only become more important in the future, and companies are eager to assist clients in accelerating their progress.
Looking Ahead
Strategic partnerships are crucial for companies offering data services. These companies rely on strong relationships with hyperscalers like Microsoft, Google, and AWS to advise clients on the best data setups. As large enterprises shift toward hybrid environments to reduce risks, these partnerships help clients navigate multiple platforms. The company also collaborates with smaller data-focused partners like Databricks, ensuring a comprehensive understanding and trusted support for clients.
In the recent interaction with Mandvi Singh, Managing Editor, siliconindia, Sam Mantle shared his insights on Maximizing Business Potential Through End-to-End Data Solutions.
End-to-end data solutions play an essential role in helping businesses gain a competitive edge by enabling better decision-making. By leveraging the data available about their operations, customers, and market trends, businesses can make more informed decisions that drive their success.
Many industries, particularly those in consumer products and fast-moving consumer goods (FMCG), have long relied on real-time data to guide business decisions. For example, sales and marketing executives use this data to understand which products are selling in specific regions, the profiles of consumers in the market, and how best to target marketing efforts to convert potential customers. Additionally, real-time data allows businesses to streamline supply chains, ensuring products reach end consumers quickly, affordably, and reliably.
How Data End-to-End Solutions Drive Competitive Edge
The ability to use real-time data to drive decisions often sets successful businesses apart from average ones. Industries that value the immediate availability of data such as consumer products, retail, consumer health, and life sciences have shown how such insights can lead to continuous advancement. The adoption of data-driven decision-making in these sectors helps businesses reduce costs, maximize revenue, and improve overall performance. As a result, businesses are increasingly adopting the same principles that FMCG companies have used to gain a competitive advantage. However, integrating data across systems and functions presents challenges, but overcoming them can offer significant rewards, making data a powerful tool for gaining an edge in the marketplace.
To overcome data integration challenges, the first strategy companies should adopt is to define a clear data strategy. Many companies often rush into building data lakes or data swaps, making it hard to extract valuable insights. It’s crucial to align the strategy with business objectives by understanding key drivers, identifying value areas, and determining market positioning. After this, companies should define data governance, master data management principles, and design the necessary data assets and environments to support the strategy.
Just like building a house requires a blueprint, creating a successful data environment requires careful planning to align with business goals. As data evolves and AI is integrated, companies must be agile, adapting models continuously. To support this, businesses must have robust support processes in place to both build but also to change the wheels as you're driving along the road.
Many industries, particularly those in consumer products and fast-moving consumer goods (FMCG), have long relied on real-time data to guide business decisions.
Unlocking Data: Powering AI, Cybersecurity, and Governance
AI and machine learning are not essentially designed to meet the necessities of data but their effectiveness is largely dependent on the quality of data fed into them. While AI and machine learning capabilities, especially generative AI, are evolving at a frenetic pace and creating buzz within the industry, the power of these technologies actually comes from the data supporting them. Even the best models today are only as good as the data they were trained on. For instance, anyone can use tools like ChatGPT, but it is what data and prompts are used to generate results that hold the real value.
Companies are strengthening data governance to mitigate ESG reporting capabilities by ensuring strong compliance and controls around their IT environments and data assets. While cybersecurity is a critical and complex issue, companies recognize the importance of collaborating with cybersecurity experts to protect their environments. The focus on data governance, however, lies in ensuring that any data entering a company's environment is protected and monitored using strict security protocols. Many companies often neglect the monitoring component, which is essential to maintaining security.
The majority of the work is done within client environments, so the exposure of their data to the external world is minimal, and in many cases, companies do not even have access to real-time data, which is carefully protected and held away. Companies emphasize the importance of partnering with experts in the cybersecurity field, just as they focus on expertise in data management. This partnership ensures robust security measures and protects sensitive data from potential risks.
Data-Driven ESG and GCC Growth
Companies providing data solutions believe that the ESG (Environmental, Social, and Governance) agenda is evolving rapidly and is becoming an important space for their work. They help their clients build up ESG reporting capabilities, not only to meet regulatory obligations but also to understand where they stand in terms of sustainability. They emphasize that no company can improve unless it measures its progress. The challenge many companies face today is that they are unable to measure their ESG impact due to a lack of solid data reference points. These companies view ESG reporting as both a necessity and a competitive advantage, with many businesses now prioritizing sustainable suppliers. By adopting and tracking ESG principles internally, they demonstrate their commitment and credibility in this space, helping clients align their strategies with sustainability goals.
The focus on expanding GCCs (Global Capability Centers) in India is driving significant growth and innovation. The agenda of these GCCs is highly data-centric, which aligns with the emphasis on data specialization that many companies, like Lingara, have advocated for years. Recognizing the importance of data, many large enterprises are developing internal capabilities within these GCCs in India.
For companies in the data space, this is an ideal opportunity. They have long emphasized the need for dedicated expertise and ownership of data. Companies must take internal ownership of managing data assets, but they also need to partner with experienced firms to guide them through the process. The goal is to build a collaborative relationship where knowledge is shared openly and transparently, supporting clients in taking ownership while guiding them through this critical journey. Data ownership will only become more important in the future, and companies are eager to assist clients in accelerating their progress.
Looking Ahead
Strategic partnerships are crucial for companies offering data services. These companies rely on strong relationships with hyperscalers like Microsoft, Google, and AWS to advise clients on the best data setups. As large enterprises shift toward hybrid environments to reduce risks, these partnerships help clients navigate multiple platforms. The company also collaborates with smaller data-focused partners like Databricks, ensuring a comprehensive understanding and trusted support for clients.
