People and Data - a summary.

 

This is a summary of the book titled “People and Data” written by Thomas C. Redman and published by Kogan Page in 2023. Data is essential for people to act meaningfully in business, government, and private life. It is the fuel that runs the world and requires high-quality data. However, individuals and businesses often fail to prioritize data when building technological infrastructure, organizing operations, or choosing new tech tools. He urges companies to modernize their approach to and use of data, focusing on improving data quality and aligning data and business priorities. Companies must optimize their application of quality data, including ordinary employees in their approach and involving them in data generation.

Data enables meaningful action in private life and commerce, such as anticipating and shopping for needs, making rational home-purchasing decisions, and analyzing sales trends and supply chains. However, the data space has problems, such as distrust of data and the monetary cost of bad data. Businesses must make their data work by utilizing data science technologies or engendering a data-driven culture. Leaders must organize their businesses to emphasize data use and build technological infrastructure to support data use at the firms' required scale.

Organizations must reconfigure their "organization for data" to address data quality. This reconfiguration should consider five issues: people involved, data flow, information technology management, teams working on data, and people leading data-driven projects. Missing people is the single most important force holding data programs back. Data becoming a business's central driver requires the involvement of everyone in the company, including non-specialist roles. Better data use will increase revenue, lower costs, reduce errors, and foster a closer relationship between employees and customers.

Organizing for data involves smooth and coordinated movement of data between departments and people, with technology and data managers separate. Transformation comes from both the bottom-up and top-down, with young employees offering innovations and senior leadership managing coordination. Everyone should join the "data generation," as the prevalence of politically motivated misinformation has changed people's views on low-quality data.

All organizations must prioritize improving data quality, as only about 3% of companies' data meets basic quality standards and only 16% of managers trust the data they commonly use. The most transformative uses of data involve data-driven decision-making, data-driven cultures, and treating data as assets.

Small data is more important for most companies than big data, as it improves a company's operations, products, and customer acquisition. Companies often overlook the value of small data, as it involves fewer people and uses hundreds of data points. Small data projects offer more problem-solving opportunities and can reduce time wasted in interactions between colleagues and streamline in-house work processes.

Data is a team sport, but silos can inhibit effective teamwork. To address this, companies must build "fat organizational pipes" – channels of two-way communication between departments, individuals, and up and down the company hierarchy. These pipes include the "customer-supplier model," "data supply chain management," "data science bridge," and "common language."

Organizations must align their data and business priorities, and a data team should include executives, technology experts, and those managing data supply chains. Data teams should include an executive, entrepreneur, developer, and data security officer. Effective communication and collaboration between data creators and customers are crucial for increasing data quality and reducing errors.

Data projects require strong leadership and data program coordinators to empower employees with independence and responsibilities. Companies should align data projects with business priorities, form data teams, and interact with employees daily. They should understand project problems, embrace aspirations, address anxieties, and train employees to solve their own problems.

Previous book summaries: BookSummary42.docx
Summarizing Software: SummarizerCodeSnippets.docx