In the wake of the transformation steering facility management to the next level in multiple segments, understanding the purpose, process and procedures of implementing technology takes priority. Today, data-driven facility management is paving the way with newer concepts and practices that are intricate and result-oriented. Read on to discover the ultimate goal of achieving sustainability through facility management, understand the live real-time data collection & analysis, case study of implementing sustainability with real-time data analysis and a service provider’s perspective as an enabler of both data and sustainability.

Triumph of Transformation with Sustainability

The cleaning industry is undergoing a significant transformation, driven by automation and sustainability. As mechanisation takes hold, cleaning staff are empowered to move into skilled labour roles, and businesses can improve cleaning consistency. The shift from labour-hour pricing to outcome-based pricing will reshape how cleaning services are priced, focusing more on the results rather than the headcount. The future of cleaning lies in mechanisation, smarter technology, and a more sustainable approach that benefits businesses, workers, and the environment alike.

Changing society’s perception of frontline cleaning staff is a crucial step toward achieving multiple objectives in the cleaning and facility management industry. Traditionally, cleaning work has been seen as a low-skilled, repetitive job. However, by training cleaning staff to operate advanced machinery, we can elevate their roles to skilled positions, which in turn improves both job satisfaction and overall efficiency. This shift results in faster, more consistent cleaning, reduced labour turnover, and increased customer satisfaction, all contributing to long-term cost savings.

Mechanisation allows a smaller, better-equipped workforce to cover larger areas in less time — whether in offices, hospitals, warehouses, or public spaces. The focus is not just on reducing labour but on empowering staff with the right tools to complete tasks more effectively and efficiently. This is a win-win for both cleaning personnel and the organisations they serve.

Workers’ Training

The introduction of automation in cleaning does not lead to job losses; rather, it empowers workers by upgrading their roles from manual labourers to skilled technicians. By training cleaning staff to operate specialised machines, their skills are enhanced, and their roles become more valuable. These workers move into higher salary brackets, experience more job stability, and are less likely to leave their positions, which significantly reduces turnover.

Furthermore, mechanisation helps to improve job satisfaction. Cleaning staff, once frustrated by the repetitive nature of manual work, now have the opportunity to learn new skills, operate advanced machines, and take pride in their work. This shift enhances both productivity and morale. As a result, a more motivated and highly skilled workforce leads to better resource management — whether in terms of time, energy consumption, or the use of cleaning chemicals.

Automation and Mechanisation

Automation in the cleaning industry is an inevitability that offers a number of advantages. By adopting mechanisation, businesses can reduce their reliance on human labour while increasing the consistency and efficiency of cleaning operations. Automation also drives higher wages by making cleaning a more skilled profession, which in turn attracts a more talented workforce.

As mechanisation takes hold, the focus will shift from labour hours to the actual results of cleaning. The days of pricing cleaning services based on the number of workers or labour hours are numbered. Instead, the industry is moving toward an outcome-based pricing model where customers pay for the result — clean, well-maintained spaces — rather than the input of time and labour.

Cleaning Costs and Customer Expectations

One of the major hurdles the cleaning industry faces is shifting how cleaning services are priced. Traditionally, cleaning contracts have been based on labour hours, with costs calculated by the number of workers and the amount of time spent cleaning. As mechanisation takes over, this pricing model will need to evolve. Instead of negotiating based on the number of workers or the hours worked, customers will begin to pay for the outcome: the quality of cleanliness delivered.

Moreover, as the industry embraces automation, the expectation is that businesses will see a return on their investment. Automated systems are more efficient, use fewer resources, and provide more consistent results. The challenge for service providers will be to show customers the long-term value of automation — demonstrating that investing in mechanised cleaning leads to both financial savings and improved cleanliness over time.

Balancing People, Environment, and Responsibility

Sustainability is at the heart of the cleaning industry’s evolution. Mechanisation and automation are not only about improving efficiency but also about minimising environmental impact. Cleaning operations consume large amounts of water, electricity, and chemicals, and automation can help reduce this consumption. Machines designed to optimise resource usage — whether it is water, chemicals, or energy — help the industry reduce its ecological footprint while still delivering high-quality results.

The key to sustainability is also in the responsible use of chemicals. Many cleaning chemicals, if not used properly, can be harmful to both the environment and the cleaning staff. By monitoring chemical usage, ensuring proper training, and using eco-friendly alternatives, the cleaning industry can improve its environmental reputation and contribute to a more sustainable future.

Improving Cleaning Quality

The challenge remains for businesses to shift the perception of cleaning from a necessary but undervalued task to an essential service that adds value. While some customers may struggle to see the financial return from cleaning services, the industry is working to prove that automated and mechanised cleaning leads to higher quality outcomes.

Ultimately, customers should focus less on the number of people cleaning their space and more on the results. Instead of negotiating based on labour costs or the number of workers, businesses should look to the quality of the cleaning service and the results it delivers. The ultimate goal is a clean, well-maintained environment, and the industry is transitioning to a model where cleaning services are priced based on the results they provide, rather than the input costs.

Challenges and Investments

While the move toward mechanisation offers clear benefits, it requires a financial commitment. For businesses to adopt automation, the investment must be financially viable. Labour costs, training, and equipment maintenance must all be factored into the decision to switch to mechanised systems. However, with the right investment, businesses can achieve significant long-term savings, both in terms of operational costs and improved cleaning outcomes.

When implementing automation, it is also essential to choose the right equipment for the job. Over-spending on equipment may lead to unrealistic expectations, while under-spending can result in poor outcomes. Ensuring that the equipment is properly sized for the application site is crucial. Additionally, regular training and maintenance are necessary to keep equipment running efficiently and to maximise its lifespan.

The article draws inference from the President & CEO, Tennant Company, Dave Huml’s, keynote address at the DigiFM Conference held during the Clean India Show, sharing the practices implemented by the global player.

Analysing Data in Facility Management Real Time Poll Report

Facility management is ever-evolving, with big data emerging as a game-changing tool for optimizing operations, enhancing efficiency, and driving cost savings. Recent polls conducted among industry professionals at the DigiFM Conference in the Clean India Show 2024, shed light on the awareness, benefits, challenges, and potential of big data in facility management. Here is an in-depth analysis of the findings and their implications along with the expert opinion of Raghupathy Vaidyanathan, Associate Vice President-Global Workplace Solutions, HCL Tech; Rohit Arora, Chief Growth Officer-Support Services, Compass Group and Yogeshchandra Bhatt, Head Facility, Mumbai Metro One Pvt. Ltd.

What are the primary sources of big data in facility management?

Analysis

A majority (60.61%) of respondents recognized the importance of leveraging all available data sources — IoT sensors, Building Automation Systems (BAS), maintenance records, energy consumption meters, and occupant feedback surveys — highlighting the growing emphasis on integrated data-driven strategies in FM.

•     Building Automation Systems (BAS) emerged as the second most significant standalone source, garnering 21.21% of votes. This underscores the reliance on BAS for centralized control and data collection in modern buildings.

•     Maintenance records were the third most-cited source (12.12%), reflecting their importance in ensuring operational efficiency and predicting future needs.

•     The IoT sensors and energy consumption meters each received only 3.03% of votes, while occupant feedback surveys were not selected at all. This suggests that stakeholders see limited value in isolating individual data streams compared to integrating them for holistic insights.

Experts

The poll results emphasize that facility management professionals increasingly favour integrated approaches to big data utilization. By combining multiple sources, FM can achieve a deeper understanding of building performance, operational efficiency, and user satisfaction, paving the way for smarter, more sustainable facility operations.

Data plays a critical role in optimising resource utilisation, especially when it comes to managing costs. Accurate data is essential for effective cost management; without it, inefficiencies can arise. Digitalising records is vital, particularly for compliance with ISO standards. It is also necessary to establish a centre of excellence within the facility management team, focusing solely on big data analytics to drive informed decision-making.

The first step in digital transformation is capturing data through digital tools like apps. As the process progresses, automation can be introduced with the use of IoT sensors. Moving from digitalisation to automation, the next step is integrating intelligence to interpret the collected data, allowing big data to bring all essential information together for smarter decisions.

Which of the following is NOT a benefit of using big data in FM?

Analysis

The majority of respondents (34.38%) correctly identified “increased maintenance costs” as NOT a benefit of big data. In fact, big data analytics reduces maintenance costs by

1.   Predictive Maintenance: Identifying potential failures before they occur through analysis of equipment usage and sensor data

2.   Optimized Schedules: Reducing unnecessary maintenance and extending equipment lifespan

3.   Resource Allocation: Enhancing efficiency in labour and material usage

The high accuracy in this poll indicates a growing understanding of big data’s practical advantages in facility management.

How can big data help improve facility management decisions?

Analysis

A commanding majority (68.27%) recognized that big data enhances decision-making in all the listed ways, including:

•     Predictive maintenance for cost savings and minimized downtime.

•     Energy efficiency through data-driven optimization of HVAC and lighting.

•     Space utilization analysis to maximize efficiency.

•     Real-time monitoring to maintain safety and comfort.

Experts & Audience

1.   Predictive maintenance influences energy efficiency and resource utilisation.

2.   A holistic approach (“all of the above”) is vital for effective facility management decisions.

3.   Big Data supports budget planning by forecasting capital expenditure (capex) requirements based on predictive analytics.

4.   Big Data enables real-time decision-making by leveraging data from multiple sources to improve facility operations.

5.   Predictive maintenance uses data patterns from sensors to pre-empt equipment failures, reducing downtime.

6.   Transitioning from manual to digital data collection aids in optimising resource utilisation and identifying operational anomalies.

7.   Predictive models streamline maintenance scheduling and resource allocation.

8.   Predictive maintenance is fundamental as it encompasses other aspects like energy efficiency and space utilisation.

9.   Comprehensive data analysis helps integrate activities like cleaning, energy efficiency, and space utilisation into predictive maintenance frameworks.

10. Space utilisation is subjective and context-dependent (e.g., hotels optimising laundry facilities).

11. Predictive maintenance acts as the foundation for planning energy efficiency, real-time monitoring, and other facility decisions.

12. Consensus: Predictive maintenance is the cornerstone of facility management improvements, influencing energy efficiency, space utilisation, and real-time monitoring.

What is the most important step in data analysis for FM?

Analysis

Over half the respondents (56%) identified data cleaning as the most critical step. This underscores its importance in ensuring data accuracy and reliability, which form the foundation for all subsequent analysis and decision-making.

Experts

Sensitive data related to day-to-day functions must be protected, emphasising the importance of securing it. The data analysis process for facility management begins with data collection. Accurate data capture is essential, as errors lead to incorrect outcomes.

The role of a data analyst is crucial, especially in interpreting the data. Data visualisation, such as dashboards or graphs, helps in presenting the data effectively, aiding in decision-making. Data cleaning, also known as data homogenisation or data massaging, is important, particularly when consolidating data from various sources. Proper data cleaning ensures consistency for analysis and representation.

The rise of regulations in the field highlights the increasing importance of adhering to data privacy standards and practices. Accurate data collection, cleaning, and visualisation are key in data analysis, while data security concerns — especially breaches and cyber-attacks — are critical in facility management today.

What are the biggest challenges in managing big data in facility management?

Analysis

Nearly half (47.37%) of respondents acknowledged that managing big data involves multiple challenges, including quality, security, costs, and skill gaps. Effective solutions require addressing all these interconnected issues simultaneously.

Experts

Resistance to change, especially from higher management, is a significant barrier.

•     Emphasising cost and complexity alongside the return on investment (ROI) can address these challenges.

•     Cost concerns vary by industry, as facilities typically do not generate revenue directly.

•     Industry-specific needs and ROI analysis should guide cost-related discussions.

•     Cost is less of a challenge at the CXO level if a strong business case and ROI are presented.

•     Resistance to change is a larger issue than cost, as decision-makers often prefer familiar processes.

•     Demonstrating the benefits through proof-of-concept (POC) can help overcome resistance.

•     Linking data analytics to ESG compliance and risk mitigation can strengthen business cases.

•     Clients increasingly value tools that enhance sustainability reporting.

•     Cost-related concerns often arise because decision-making on capital expenditure happens at higher levels.

•     Demonstrating benefits directly to these decision-makers can mitigate cost objections.

•     Clients often fail to see immediate value in digitisation and AI, leading to hesitance in adoption.

•     The decision to invest depends heavily on the asset owner’s willingness to recognise the long-term benefits.

•     Differentiating technology costs from regular operations in proposals is a challenge.

•     Highlighting how technology contributes to smart facilities can encourage acceptance.

•     Tech-savvy business leaders in new facilities are more receptive to smart solutions.

•     Providing accurate data and numbers in proposals ensures better acceptance.

Consensus: The high accuracy in this poll indicates a growing understanding of big data’s practical advantages in facility management.

What is the primary benefit of using IoT devices in facility management?

Analysis

A large majority (68.97%) highlighted the comprehensive benefits of IoT, including
real-time monitoring, predictive maintenance, and energy efficiency, showcasing
its pivotal role in modern facility management.

Experts

• Advocates for using all data sources, especially IoT sensors, in facility management.
• IoT devices can be attached to various equipment (e.g., trash cans, soap dispensers, entry/exit points).
• Benefits include:
  • Real-time monitoring for better operational oversight.
  • Predictive maintenance to anticipate equipment failures, reducing costs.
  • Energy efficiency through automation and usage pattern analysis (e.g., lights controlled by occupancy).
• Example: IoT implementation in a large IT organisation in South India significantly improved energy efficiency.
• Observes a contradiction in feedback on IoT benefits:
  1. Earlier emphasis on predictive maintenance shifted to real-time monitoring in later discussions.
  2. Highlights the need for clarity on IoT’s primary advantage in FM.
• The growing affordability and adoption of IoT solutions in facility management.
• Major challenge: Integration of IoT systems into a unified platform.
• Stress the importance of a single-pane dashboard for streamlined data access and executive decision-making.

How can AI and machine learning be used to improve facility management?

Analysis

The overwhelming majority (73.17%) recognized the broad applicability of AI and ML, from predictive maintenance to energy optimization and space utilization, illustrating their transformative potential.

Experts

•     AI is not yet widely adopted in most current FM systems.

•     AI offers significant benefits, such as:

•     Predictive maintenance for equipment upkeep and energy optimization.

•     Energy optimization through improved machine efficiency.

•     Space utilization with adaptable solutions based on use cases.

•     AI can transform facility operations by shifting from reactive to proactive management.

•     Proactive operations enabled by AI improve efficiency and operational effectiveness.

•     AI and Big Data have a symbiotic relationship:

•     AI relies on large datasets from Big Data for training.

•     Big Data analytics often require AI tools for deeper insights.

•     Predictive maintenance is a key application of AI and Big Data in FM.

What is the biggest challenge in implementing a big data solution in a large facility?

Analysis

A significant majority (62.2%) acknowledged the interconnected challenges of cost, complexity, and resistance to change, highlighting the need for strategic planning and effective change management in big data adoption.

Experts

•     Manpower costs dominate FM budgets, influencing decisions on tech investments, with cost perception often leading clients to view advanced technologies as unnecessary expenses.

•     Capex decisions are typically made at higher levels, limiting service provider access to advocate for advanced solutions. Pricing models based on headcount or SLAs hinder the adoption of efficiency-driven technologies.

•     Demonstrating benefits at decision-making levels is critical to overcoming cost barriers and convincing asset owners to consider tech adoption separately from traditional costs. A strong business case with ROI can help overcome objections.

•     Big Data adoption faces challenges, with resistance to change being a significant barrier rather than just cost concerns. Asset owners often fail to see immediate value in technological investments, complicating efforts to drive adoption.

•     CXOs prioritize actionable data for strategic decision-making, and aligning with ESG goals while demonstrating ROI through Proof of Concept (POC) can be effective in driving adoption, especially for innovations like smart cleaning.

•     Integrating data analytics with ESG and sustainability reporting, adds value and aligns with regulatory requirements, making a stronger case for technology adoption in FM.

•     Cost concerns in facility management depend on whether facilities are seen as revenue generators or cost centres. Decisions are often influenced by management’s comfort with traditional methods, with resistance to change being a key obstacle.

•     Cost and complexity of new technologies should be justified through clear value propositions and ROI, which can help overcome scepticism. Tailored approaches are needed as FM expenses vary across industries.

•     Tech-savvy leaders in new-age businesses are more receptive to Big Data and analytics, and integrated smart technologies in new facilities help ease the adoption process. These trends are increasingly common in modern facilities.

Airports Lead in Energy Efficiency & Sustainability

Case Study

Airports across the country are increasing the outreach towards reducing the carbon footprint, with increasing awareness to replace regular operations with sustainability, recycling waste and working towards helping the environment. These moves are in step with the Airport Authority of India’s (AAI) goal to achieve Net Zero by 2030. Speaking at a high level DigiFM Conference at the Clean India Show, Amit Jain, Association General Manager, Engineering & Maintenance at Navi Mumbai International Airport (NMIA) and Bharti Singh Kalappa, Facilities Head at Noida International Airport (NIA) discussed on Technology-enabled Sustainability and Energy Efficiency initiative taken by their respective airports.

Mumbai and Delhi airports have received the highest level of 4+ carbon accreditation from the Airports Council International (ACI) for their focused decisions to become green airports. Cochin Airport, with the distinction of operating fully on solar energy, has also won the Champions of the Earth award from the United Nations.

Solar Energy and Sustainable Design

Solar energy has been a key focus at both Navi Mumbai and Noida airports. Both speakers mentioned the importance of integrating sustainable design decisions right from the outset. Bharti explained, “It starts with the design phase. We work hand-in-hand with the design team, discussing every single detail. Even something as simple as choosing the right stone, we check its reflection ratio. When selecting lighting, we ensure it aligns with energy management principles.” She went on to mention that technology plays an equally important role, starting from recruitment. “For instance, we use AI-enabled technology to streamline recruitment, saving valuable time. By digitizing these processes, we also reduce paper consumption, which is a part of our commitment to sustainability.”

Both airports have seen the evolution of technology, from halogen bulbs to CFLs and now to LED lights, leading to energy savings that can be used elsewhere. Amit Jain elaborated, “For instance, our airport runway halogen lights have been replaced with LEDs. Each light consumes 30-35 watts, and we’ve replaced about 700 to 800 lights. That’s a huge saving.”

Sustainable aviation fuel (SAF) adoption is another area where both airports are focusing efforts, even though it comes at a higher cost. Bharti added, “For a domestic flight, jet fuel consumption is around 5,000 to 6,000 litres. We’re also reducing paper usage by adopting WIM modelling. And we’re seeing the rise of biogas plants at our facilities, which helps reduce waste. All water generated from F&B is being reused as part of our goal to achieve Zero Waste by 2030.”

Sustainability and Carbon Neutrality Efforts

The efforts of NMIA and NIA are fully aligned with the Ministry of Civil Aviation’s initiatives to promote carbon neutrality across airports in India. The implementation of solar panels, either under net metering or captive modes, alongside the adoption of self-consumption of solar and renewable energy, is happening at a significant scale. More than 100 Indian airports have adopted 100% green energy procedures.

“Solar energy is by far the most effective solution,” said Bharti. “The cost of installing solar panels has decreased over the years and is now subsidized, which makes it much more accessible compared to earlier. For airports, solar power works best since it provides a continuous supply of energy, especially in remote areas where electricity can be hard to come by.”

Cochin International Airport Limited (CIAL) was one of the early adopters of solar energy, starting in 2013. Just two years later, they scaled up to 13.11MW of power generation and are now fully operational on solar energy. According to CIAL, their green energy generation has reached 25 crore units, with 75 lakh units coming from their hydro power project.

To further support sustainability, CIAL has also installed two fast-charging stations for electric vehicles at both the domestic and international terminals.

Lifecycle Approach to Sustainability

Discussing the lifecycle of airport infrastructure, Amit Jain shared insights: “When it comes to sustainability, we have to look at the entire lifecycle. For a 30-year building lifecycle, the Capex cost comes down to just 2%. The bigger picture is the operating costs, which account for about 98%. So, even if a building is not 100% energy-efficient, the decision to use solar lights, hydrogen, and electric vehicles should be weighed carefully, as they can help bring down operational costs significantly in the long run.”

Amit also mentioned that at airports, engineering and maintenance costs can account for up to 30-35% of the entire operational budget, making it important to consider sustainability from an operational standpoint for long-term benefits.

Tech-enabled Sustainability and Energy Efficiency Solutions

Some of the noteworthy tech-enabled sustainability and energy-efficient solutions include:

•     Cutting down on thermal energy usage by switching to solar in the facility management industry

•     Replacing paper-based records with tablets, significantly reducing paper use

•     Using digital dashboards to minimize in-house paper usage

•     Maintaining e-checklists and QR-code-based processes for facility management

•     Real-time digital monitoring of energy consumption — water, electricity, and gas — to earn carbon credits

•    Implementing SCADA systems for energy management to monitor lighting and reduce CO2 emissions

10-Step Approach to Harness Real-Time Data Optimising facilities, enhancing performance & building smarter spaces

Understanding Real-Time Data in Facility Management

Real-time data involves the continuous collection and analysis of metrics such as energy usage, equipment performance, and occupancy. It empowers facility managers to identify inefficiencies, predict issues and take proactive action. For instance, monitoring HVAC systems in real-time can reduce downtime by up to 40% and energy costs by up to 30%. Beyond cost savings, real-time insights enhance occupant comfort, ensure compliance with safety standards, and streamline resource allocation.

Identifying Key Data Sources

Every facility has a wealth of data waiting to be captured. Critical sources include energy consumption, water usage, indoor air quality, and maintenance requests. Tools like EnOcean PIR sensors optimize space utilization, while Honeywell Healthy Buildings Dashboards improve air quality, boosting employee productivity by up to 15%. Water usage sensors like Aquamonix prevent wastage and reduce costs associated with leaks and damages.

Implementing Data Collection Systems

Efficient data collection hinges on the right tools and infrastructure. IoT hubs, such as Advantech’s IoT Edge Gateway, and wireless networks like Cisco’s Industrial Wireless System create unified systems for real-time monitoring. For example, vibration sensors on HVAC units detect anomalies and trigger automated service requests, significantly reducing disruptions and repair costs.

Centralizing Data Storage

A well-structured storage system is critical for managing data efficiently. Platforms like AWS IoT Core and Cisco Edge Intelligence centralize data, making it accessible and secure. Hybrid storage solutions ensure data availability during connectivity outages, providing redundancy. A logistics firm that adopted Veeam Backup successfully prevented data loss during server crashes, ensuring smooth operations.

Data Analysis Techniques

Data becomes actionable through analysis. Descriptive analytics platforms like Tableau summarize trends, such as peak energy usage, while predictive tools like IBM SPSS Modeler forecast potential equipment failures. For example, a manufacturing facility analysing compressor runtime data reduced downtime by up to 30%, proving the value of predictive analytics in facility management.

Visualizing Data Insights

Effective visualization bridges the gap between raw data and actionable insights. Dashboards powered by Microsoft Power BI provide real-time snapshots of critical metrics, while heatmaps from SmartDraw help identify underutilized spaces. For instance, retail spaces adjusted lighting and HVAC schedules based on occupancy heatmaps, saving up to 20% on energy costs.

Driving Decision-Making with Data Insights

Real-time insights enable facility managers to make informed decisions that drive efficiency. Tailoring cleaning schedules to high-traffic areas can reduce costs by up to 15%, as seen in a hotel chain. Predictive maintenance strategies extend equipment lifespan while reducing repair costs. Dynamic resource allocation, driven by live data, ensures that operations run at peak efficiency.

Continuous Monitoring and Feedback Loops

The process of leveraging data doesn’t end with initial implementation. Continuous monitoring tools like Honeywell Forge provide updates on equipment performance, while platforms such as SimpliField enable instant alerts for anomalies. Automated lighting adjustments based on occupancy data reduce energy wastage, further enhancing operational efficiency.

Training and Engaging Staff

Even the most advanced systems are only as effective as the team managing them. Training staff in CAFM tools and IoT systems ensures they can leverage real-time data effectively. Certifications in predictive maintenance platforms like IBM Maximo empower teams to reduce downtime and repair costs. Workshops on data visualization tools like Power BI also enable facility managers to independently generate actionable reports.

Evaluating Performance and Adjusting Strategies

Regularly reviewing performance metrics ensures long-term success. Metrics like Mean Time to Repair (MTTR), energy savings, and occupancy efficiency highlight areas of improvement. For instance, adjusting HVAC schedules based on occupancy patterns enabled a corporate office to reduce lighting costs by up to 20% in unoccupied spaces. Continuous updates and stakeholder feedback refine these strategies further.

The Future of Facility Management with Real-Time Data
Real-time data is more than a tool—it’s a transformative strategy for driving efficiency, sustainability, and innovation. By following this comprehensive 10-step process, facility managers can unlock the full potential of their spaces, transforming them into smarter, more responsive environments. From IoT sensors and centralized dashboards to predictive analytics, these tools equip IFM professionals to lead the way toward a more data-driven future.
Contributed by Christopher Blessing, Managing Director, Caere India Pvt. Ltd