Unit 5: Operations Management — 5.9 Management Information Systems
What are Management Information Systems (MIS)?
Management Information Systems (MIS) are integrated systems used by organizations to collect, process, store, and disseminate information for efficient and effective decision-making. MIS enables organizations to track performance, monitor operations, and support planning at all levels.
Functions: Data collection, analytics, reporting, forecasting, and automating repetitive tasks.
Data Analytics in MIS
Data analytics is the science of examining raw data using statistical and computational tools to draw conclusions, find patterns, and drive strategic business decisions.
- Descriptive Analytics: What happened?
- Predictive Analytics: What will happen?
- Prescriptive Analytics: What should we do?
Key Formula: Moving Average (for demand forecasting)
MA = \frac{D_{t-1} + D_{t-2} + ... + D_{t-n}}{n} Where: D_{t-1} = previous demand, n = number of periods
MA = \frac{D_{t-1} + D_{t-2} + ... + D_{t-n}}{n} Where: D_{t-1} = previous demand, n = number of periods
Cybersecurity in MIS
Cybersecurity encompasses the practices and technologies that protect MIS against unauthorized access, data breaches, viruses, and cyber-attacks. Ensuring secure flows of sensitive organisational data is an essential part of modern MIS.
- Firewalls and encryption technologies
- Authentication and user access controls
- Real-time monitoring and incident response
- Cybersecurity policy and employee training
Cyber Risk Formula (Qualitative):
Risk = Threat \times Vulnerability \times Impact
Risk = Threat \times Vulnerability \times Impact
Artificial Neural Networks & Artificial Intelligence
Artificial Neural Networks (ANNs) are AI models structured like the human brain, used to process complex data, recognize patterns, and make predictions. Artificial Intelligence (AI) is the broader concept of machines capable of performing human-like cognitive functions—learning, reasoning, and problem-solving.
- Uses of ANNs: Image and speech recognition, fraud detection, forecasting, customer segmentation
- AI and MIS: Automates routine analysis, enables smart decision-support, and optimizes business processes.
ANN Example Formula (Neuron Activation):
y = f\left( \sum_{i=1}^{n} (w_i \cdot x_i) + b \right) Where: x_i = input, w_i = weight, b = bias, f = activation function
y = f\left( \sum_{i=1}^{n} (w_i \cdot x_i) + b \right) Where: x_i = input, w_i = weight, b = bias, f = activation function
AI’s Contribution to MIS: Speed, accuracy, scalability, personalized analysis, continuous learning
Digital Taylorism
Digital Taylorism (or "algorithmic management") refers to the use of technology, data, and algorithms to monitor, control, and optimize worker performance, much like Taylor's Scientific Management in the 20th century. In MIS, digital Taylorism leverages real-time analytics and monitoring for efficiency.
- Employee tracking and productivity analysis
- Standardization of workflows and procedures
- Real-time performance metrics
- Ethical considerations: privacy, autonomy, data misuse risks
Example Metric of Digital Taylorism (Productivity):
Productivity = \frac{Output}{Input}
Productivity = \frac{Output}{Input}
Conclusion
Management Information Systems power modern operations by transforming data into actionable intelligence, safeguarding organizational data, and integrating new AI-driven tools for productivity and control—while raising important questions about privacy and ethical management.