Cedric Chin, founder of Commoncog, shares his expertise on the analytics development lifecycle and the importance of data in business decisions. He discusses how data teams should not be sidelined as mere IT support. The conversation dives into the challenges of communicating data's value to leaders, the limitations of traditional BI tools, and innovative open-source solutions. Cedric also highlights the historical significance of Excel at Amazon and the need for a data-centric culture to foster collaboration and improve outcomes across organizations.
Collaboration between data professionals and business leaders is essential for improving understanding and generating meaningful insights aligned with business objectives.
Implementing Statistical Process Control (SPC) enables organizations to distinguish between routine and exceptional variations, fostering informed decision-making and ongoing operational improvement.
Data professionals can drive significant change within their organizations by demonstrating data-driven insights through metrics, even without direct executive support.
Deep dives
The Intersection of Data and Business Operations
The discussion highlights the critical intersection between data analysts and operators, emphasizing the need for both data professionals and business people to improve their understanding of each other's domains. Cedric Chin argues that while data practitioners strive for data literacy among business personnel, it's equally important for data practitioners to learn how to ask meaningful questions that align with business objectives. The podcast stresses that the flow of information should not be one-sided; instead, collaboration and mutual learning can lead to better insights. Effective communication between data teams and business operators can enhance overall business performance and decision-making.
Learning from Amazon's Business Review Practices
Cedric Chin shares insights from his analysis of Amazon's Weekly Business Review (WBR), a process exemplifying successful data-driven management. He argues that data should primarily serve to establish statistical process control rather than simply answering stakeholder questions. This approach allows organizations to continuously understand and modify complex processes based on data-driven insights. By understanding the flow of controllable input metrics to output metrics, businesses can better identify key drivers of performance and adapt their strategies effectively.
Bridging the Gap Between Data and Business
The conversation points out a common issue within organizations: business leaders often ask questions that do not lead to actionable insights or meaningful results, which can lead to frustration among data teams. Cedric Chin highlights the importance of helping business executives frame their queries in ways that generate useful data insights, encouraging a more strategic use of data. By addressing this challenge, data professionals can better support business goals and ensure that data serves its intended purpose of driving effective decision-making. This collaboration fosters an environment where data is valued as a critical asset rather than just a service.
Statistical Process Control as a Business Capability
The podcast discusses the relevance of Statistical Process Control (SPC) for organizations aiming to enhance operational efficiency and performance. Cedric shares that SPC allows businesses to differentiate between routine variation and exceptional variation, enabling effective decision-making based on data. By implementing SPC methodologies, businesses can create a clearer understanding of their operations, identify areas needing improvement, and foster a culture of continuous learning and adaptation. This approach not only enhances data-driven decision-making but also promotes collaboration across departments, ultimately driving organizational success.
Empowering Data Professionals to Drive Change
The conversation emphasizes that data professionals can initiate significant changes within their organizations even without direct executive support. By employing process control principles, data practitioners can demonstrate the value of data-driven insights through concrete metrics and actionable findings. An example shared in the podcast illustrates how a marketing professional used process control to optimize Google Maps listings, leading to increased calls and actionable insight for the organization. This showcases the potential for data professionals to influence business outcomes and underscores the transformative impact of effective data usage in aligning with organizational goals.
Cedric Chin runs Commoncog—a publication about accelerating business expertise. He joins Tristan to talk about the analytics development lifecycle, how organizations value (or misvalue) data, and why “data teams are not some IT helpdesk to be ignored.”
For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.
The Analytics Engineering Podcast is sponsored by dbt Labs.
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