Even with a wealth of information at our fingertips, making decisions in our fast-paced business world can be challenging. A survey conducted by McKinsey found that ineffective decision-making can cost a Fortune 500 company about $250 million in annual wages, showcasing how these decisions often have high-stakes repercussions.
As the volume of data grows, organizations recognize the vital role of efficient information processing in improving decision-making. This increased demand for producing results drives efforts to strengthen decision science processes through stronger data management practices.
Understanding how businesses can harness this potential begins with a closer look at the impact of information and decision science on day-to-day operations.
The Impact of Information Science on Workplace Efficiency
Information science is used to organize, manage, and optimize data in the workplace.
By improving the accessibility and retrieval of data, information science enables professionals to spend less time searching for data and more time interpreting it. Companies use information science to enhance efficiency in the workplace by:
- Centralizing and categorizing data: Companies use advanced database systems and knowledge management platforms to streamline workflows.
- Deloitte uses internal knowledge-sharing systems to accelerate collaboration and reduce project turnaround times.
- IBM’s Watson Discovery uses Artificial Intelligence (AI) to organize unstructured data, helping teams quickly find relevant insights.
- Gaining insights with data mining and predictive analytics: Organizations apply data mining and predictive analytics to uncover trends and make proactive decisions.
- Walmart uses predictive models to optimize inventory and supply chain logistics.
- Mayo Clinic leveraged predictive analytics to anticipate patient risk and personalize care, improving efficiency and outcomes during the COVID-19 pandemic.
Beyond storage and structure, information science equips organizations to harness data as a tool for strategic growth.
Understanding The Science of Decision Making
For businesses to effectively leverage data in their decision-making processes, they must grasp the fundamentals of decision science. But what is decision science?
Decision science is a discipline that focuses on how individuals and organizations make informed choices. Drawing from economics, psychology, data science, and statistics, decision science supports strategic and operational decision-making in complex and uncertain environments. At its core, decision science uses statistical analysis and data modeling to evaluate options, predict outcomes, and reduce risk.
Effective decision-making starts with quality data, which is where information science and decision science intersect. By applying empirical data and quantitative techniques, businesses can strengthen their decision-making processes and align choices with their strategic goals.
Across industries, companies are applying decision science in tactical ways:
- Amazon uses decision science to analyze consumer behavior patterns, enabling personalized recommendations, optimized pricing, and demand forecasting. This approach keeps the company agile and competitive.
- In the financial sector, JPMorgan Chase uses decision science to perform risk assessments and scenario analysis to evaluate how certain climate scenarios could impact investment portfolios.
By understanding what decision science is and how it’s applied, companies can better anticipate trends, respond to challenges, and make data-driven decisions that move their business forward.
Integrating Information and Decision Science in Business Operations
The power of integrating information and decision science lies in its ability to turn raw data into actionable insights quickly and efficiently. As businesses face mounting pressure to stay competitive, they turn to technologies that can interpret data in real time, empowering teams to make smarter decisions faster.
In everyday operations, this integration comes to life through tools like business intelligence platforms that combine centralized data sources with real-time analytics. These tools allow teams to seamlessly analyze, visualize, and act on data, driving operational efficiency and aligning decisions with business goals. This integration also enhances collaboration across departments, breaking down barriers and encouraging data sharing.
By bringing together information science and decision science, organizations boost their agility in the face of a rapidly changing market. It also encourages a culture where decisions are driven by evidence, not guesswork, leading to better outcomes across the board.
That said, as the data landscape evolves, so must the expertise that drives it, making continuous learning a key factor in staying ahead.
Embrace the Future of the Information and Decision Sciences: Pursue an MPS from Cornell Bowers CIS
Information and decision science are transforming business operations, improving efficiency, driving innovation, and enabling smarter decision-making across industries. As emerging technologies like AI, machine learning, and real-time analytics evolve, the demand for professionals who can harness and apply data will continue to grow.
The Master of Professional Studies (MPS) in Information Science from the Cornell Ann S. Bowers College of Computing and Information Science prepares students to meet that demand. This interdisciplinary program equips graduates with the tools to analyze data, understand user behavior, and design systems that drive informed decisions in real-world settings.
If you are ready to make an impact at the intersection of technology, data, and strategic thinking, an MPS degree in Information Science can help you build the career you envision.
Download our resource—From Classroom to Career: Cornell Bowers CIS’s Information Science Degree—to learn more about the career outcomes of the MPS program and what you can expect post-graduation.
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