Companies struggling to be data-driven despite investing in big data and analytics. Lack of data culture and treating data as a business asset are major obstacles. People and process issues are main challenges to successful adoption of Big Data/AI initiatives.
Organizational alignment, cultural resistance, and lack of data understanding are the key challenges in implementing a data-driven culture.
Data quality and automation are crucial for a data-driven organization, contributing to a strong data-driven culture.
Meaningful business value can only be derived from data when organizations address the human side through processes, communication, and training.
Deep dives
Companies struggling to become data-driven
Many companies are finding it difficult to adopt a data-driven culture, according to a survey. The initiative of becoming data-driven is proving to be a challenge and organizations are struggling to live up to their ambitions. Lack of organizational alignment and cultural resistance are identified as major obstacles. Technology is not the main issue, as only 7% of survey participants cite it as a problem.
Defining a data-driven company
A data-driven company is one that relies on data to make decisions and drive performance. It involves aligning corporate goals with data-driven initiatives and using data to measure and track performance. The company's departments and individual employees play a role in the data-driven culture, ensuring that actions are based on data and supporting the overall corporate goals.
Importance of data quality and automation
Data quality and automation are crucial for a data-driven organization. High-quality data is necessary to build trust and make accurate decisions. Automation of data processes ensures timely access to information without delays or manual intervention. It also eliminates opinion-based decisions and ensures that data is sourced from reliable systems. Both data quality and automation contribute to a strong data-driven culture.
Challenges in implementing data culture
Organizational alignment, cultural resistance, and lack of data understanding are key challenges in implementing a data culture. The survey highlights the need for clear objectives and alignment with business goals. Successful data culture initiatives often start with specific key projects that align with the overall organizational strategy. It requires buy-in from executive leadership, engagement from business units, and a focus on both short-term needs and long-term goals.
Addressing the human side of data
Meaningful business value can only be derived from data when organizations are serious and creative about addressing the human side of data. Processes, communication, and training play an important role in building a data-driven culture. Clear expectations, documentation of work processes, and executive sponsorship are essential for successful implementation.
Mike, Seth, & Tommy delve into the alarming findings of NewVantage Partners' 2019 Big Data and AI Executive Survey, which revealed that companies are failing in their efforts to become data-driven despite investing heavily in big data and analytics. They discuss the main obstacles faced by firms, such as a lack of data culture and treating data as a business asset, and why people and process issues are the main challenges to successful business adoption of Big Data/AI initiatives.
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