Shaily Verma: A Pragmatic, Trusted and Influential Leader 

Data-enabled decisions are crucial for businesses in the modern world. Data is the fuel that drives innovation, efficiency, and growth in any industry. Data can help businesses understand their customers, competitors, markets, and trends better. It can also help businesses optimize their processes, products, services, and strategies to achieve their goals and objectives.

However, data alone is not enough. Businesses need to have the right tools, skills, and culture to analyze, interpret, and act on the data they collect. Data-enabled decisions are those that are based on evidence, logic, and insights derived from data, rather than on intuition, assumptions, or opinions. Data-enabled decisions can help businesses improve their performance, reduce their risks, and increase their competitive advantage. As an enabler of informed decisions through data, Shaily Verma keeps her company focused on business growth and the improvement of operational efficiencies. As the Director of Data Analytics at DAMAC Group, Shaily heads her efficient team to manage data assets for measurement & business improvement.

Decoding the Data                              

Data-enabled decisions are not easy to make. They require a lot of effort, time, and resources. They also require a lot of collaboration, communication, and trust among the stakeholders involved. Data-enabled decisions are not always perfect or final. They need to be constantly monitored, evaluated, and revised based on new data and feedback. Data-enabled decisions are not a one-time event, but a continuous process of learning and improvement.

As the Director, Shaily has developed a roadmap for the data transformation journey with an agenda of AI enablement and rolled out data science models while maintaining data quality. She developed DAMAC’s in-house Data CoE (Centre of Excellence) team, which efficiently generates business value via data science, analysis, visualization, and integration projects. She has also developed a data management and governance overarching roadmap which also includes AI for ethics and regulatory (GDPR/ legal) projects. Other data science projects she oversees are Demand forecasting, product pricing modeling, process optimization & control, Customer segmentation, and more. She ensures that her data team is constantly working with enterprise solutions and identifying business opportunities via deep-dive correlations and data models.

A Pragmatic Leader

Shaily has a rich experience of 17 years in the Digital space, out of which 15 years are in the Data domain (focusing on Data science, data engineering & data analytics insights). She started her professional journey as a software developer in a Fortune 500 company before taking up data analytics. She specializes in building Centre of Excellence teams for data analytics, data science, and data engineering functions at the group level that boost business growth. She has successfully executed 3 data transformation projects in her previous 3 organizations to create data assets with a time-bound data strategy.

Shaily has a knack for developing data science use cases that are relevant to the business, linked to the business outcome, and implementing generative AI data models such as AI-enabled chatbots, conversational AI, virtual tours, AI-based image enhancements, NLP algorithms generative AI to customize communication with leads. She leads with an inclusive, collaborative, and team-oriented approach while delivering quality results. “I bring practicality and a plan to scale in all my work,” she says.

Making Data Work for Organization

Even though organizations know the value of data, there’s still data illiteracy in the organizations as to how to best utilize it. “Every organization should be data-driven, and the decision-making should have the requirement to use data insights. Understanding AI but using it with ethics avoids the unconscious data biases while using algorithms and predicting based on historical data, which might be completely skewed by major events in the world,” says Shaily.

Shaily would often encounter challenges while she pushed for the right data collection methodologies. This was crucial for the adoption of AI-enabled systems throughout organizations. Other obstacles came in the form of lack of digital support and finding the right talent for the job. 

Another challenge that Shaily faced on her path to success was culture change. She addressed the problem of different cultural implications by organizing weekly data science sessions while also allocating one business data resource to each business. It helped to foster the use of centralized data in the decentralized working operations model. This created a safe environment to get positive reinforcement and some great feedback from peers.

Shaily created a safety net among the teams so that ideas could thrive and can be adopted without fear and ego. She also encouraged staff to have multiple skills besides the main specialization to constantly challenge themselves while providing executive goals exposure. Her strong strategy helped her bring a positive impact on the business and helped her team to overcome various challenges. Shaily concludes, “If you connect the team to the bigger goals and executive agendas and keep them informed on the futuristic aspirations, the Team elevates their thinking within their domains.”

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