Topic: Data-driven Decisioning in the Future of Business and Work
In today's fast-paced business environment, making the right decisions can mean the difference between success and failure. This presentation will explore the role of data-driven decision-making in the future of business and work. It will cover the advantages of data-driven decision-making over anecdotal evidence, the difference between data as signals and actionable data, and the benefits of artificial intelligence in decision-making. The presentation will also discuss the importance of inclusive models and how models can become polluted if not regularly refreshed. Finally, the presentation will address the question of when to trust your gut and when to rely on data.
- The advantages of data-driven decision-making over anecdotal evidence: While anecdotal evidence may be compelling, it can be biased and unreliable. Data-driven decision-making, on the other hand, is based on objective data and can lead to better outcomes.
The difference between data as signals and actionable data: Not all data is created equal. Data, as signals can provide insights, but actionable data, is necessary to make informed decisions. It is essential to identify actionable data to make informed decisions.
The benefits of artificial intelligence in decision-making: AI can analyze vast amounts of data quickly and accurately, identify patterns and trends, and provide insights that would be impossible to discover manually. AI can help businesses make better decisions by providing actionable insights and predictions.
In conclusion, data-driven decision-making is critical in the future of business and work. By relying on objective data, identifying actionable data, and using AI to analyze and provide insights, businesses can make better decisions and achieve greater success. However, it is also essential to ensure inclusive models and regularly refresh them to avoid pollution. Knowing when to trust your gut and when to rely on data is also a critical factor in decision making.
Linda is a transformational Software Leader, Board Member, and Certified Software Quality Engineer (ASQ-CSQE) with extensive experience driving organizational change to optimize quality and execution for software teams. She has successfully led digital transformation of teams for multiple industries and platforms, and executed multiple organizational agile testing and automation transformations. Linda is influential in planning, design, project management, integration, development, deployment and Customer Experience for enterprise software projects, and is currently the VP of Platform Engineering for Commercial Solutions at Mastercard.