IT for Management is about using information technology as a tool for running and shaping a business, not about programming. The management question is always the same: which systems help us decide better, work faster or compete differently, and what do they cost and risk? This article revisits the key ideas with examples.
1. Information systems in organisations
Data are raw facts, information is data processed to be meaningful, and knowledge is information applied with experience. An information system (IS) combines people, process, hardware, software, data and networks to collect, process, store and distribute information.
Systems match management levels:
| System | Users | Purpose | Example |
|---|---|---|---|
| Transaction processing (TPS) | Operations | Record routine transactions fast and accurately | Billing, ticket booking, payroll entries |
| Management information (MIS) | Middle managers | Summary and exception reports | Monthly sales by region |
| Decision support (DSS) | Analysts, managers | Models and what-if analysis for semi-structured decisions | Pricing simulator, demand model |
| Executive support (ESS) | Senior management | Dashboards of key indicators | CEO scorecard |
| Knowledge management and office systems | Knowledge workers | Create, share and store knowledge | Wikis, collaboration suites |
Information has value when it is accurate, timely, relevant, complete and accessible.
In the real world: UPI is, at heart, a TPS of enormous scale: the National Payments Corporation of India (NPCI) processes billions of small transactions a month, and banks and apps built MIS and analytics on top of it.
2. IT and competitive strategy
IT affects strategy in three ways: it cuts cost, differentiates products and services, and enables new business models. Porter’s Five Forces and the value chain show where IT adds advantage: automating primary activities and supporting activities, raising switching costs, and lowering entry barriers or raising them. The IT–business alignment problem is making technology spend follow business goals, and IT governance assigns decision rights, risk control and value tracking.
In the real world: Walmart built its advantage on supply-chain IT (satellite network, point-of-sale data and sharing sales data with suppliers). Netflix replaced video rental with streaming and recommendations. Airlines built reservation systems in the 1960s that later became a source of power for the firms that owned them.
3. Enterprise systems: ERP, CRM and SCM
Enterprise Resource Planning (ERP) integrates finance, HR, manufacturing, procurement, sales and inventory on a single database, so every function sees the same data in real time. Benefits: less duplicate entry, better control and faster closing of books. Drawbacks: high cost, long implementation, change management and the temptation to bend the business to the software. Typical modules: finance, materials management, production planning, sales and distribution, and human capital management. Examples of vendors: SAP, Oracle, Microsoft Dynamics, and Workday in HR.
| System | Focus | What it does |
|---|---|---|
| ERP | Internal operations | One integrated record of the business |
| CRM | Customers | Contacts, sales pipeline, service tickets, campaign analytics; builds customer lifetime value |
| SCM | Suppliers to customers | Planning, procurement, logistics, inventory visibility; reduces the bullwhip effect (small demand changes amplifying upstream) |
| HRMS/HCM | People | Payroll, attendance, recruitment, performance, learning |
Implementation approaches: big bang, phased and parallel; customisation versus using the standard process (fit-to-standard).
In the real world: in 1999 Hershey had trouble delivering orders at Halloween after launching a new ERP and supply chain system together, a famous case of implementation risk. Most large Indian companies run SAP or Oracle for core processes, and HR modules such as SAP’s human capital management handle payroll and leave for large workforces.
4. Data, databases and business intelligence
A database management system (DBMS) stores data in an organised way and controls access. Relational databases use tables and SQL; NoSQL stores (document, key-value, graph) suit flexible or very large data. Data warehouses hold integrated historical data for analysis, fed by ETL (extract, transform, load); data marts serve single departments; data lakes keep raw data in many formats.
Business intelligence (BI) turns data into decisions through reporting, dashboards, OLAP (slicing a cube by time, product and region) and data mining (finding patterns: classification, clustering, association rules). Analytics goes from descriptive (what happened) to diagnostic (why), predictive (what will happen) and prescriptive (what should we do). Big data is characterised by volume, velocity and variety.
In the real world: supermarkets mine basket data to place goods and design offers, and banks use predictive models to score credit risk and spot fraud. Amazon and Netflix recommendations come from analysing behaviour across millions of users.
5. Networks, internet and cloud computing
A network connects computers: LAN, MAN, WAN; the internet is a network of networks, and an intranet is a private one that uses internet technology; an extranet gives partners access. Standard layers and protocols (TCP/IP, HTTP) allow interoperability. Wi-Fi, 5G and IoT extend networks to mobile and connected devices.
Cloud computing delivers computing as a service over the network:
| Model | You get | Example |
|---|---|---|
| IaaS | Virtual machines, storage, networks | AWS EC2, Google Compute Engine |
| PaaS | Platform to build and run apps | App-hosting platforms |
| SaaS | Finished software | Email, CRM, collaboration tools |
Deployment: public, private, hybrid and multi-cloud. The business case: shift from capital expense to pay-as-you-go operating expense, scale up and down on demand, and faster launches; the risks are cost sprawl, vendor lock-in, data location and security. Outsourcing and managed services follow the same make-or-buy logic.
In the real world: start-ups launch on cloud with no hardware, Netflix runs on public cloud to absorb peak demand, and governments set data localisation and compliance rules that influence where data may sit.
6. E-commerce and digital business
E-commerce models: B2B, B2C, C2C, B2G. Revenue models: sales, commission, subscription, advertising, freemium. Digital payments, marketplaces, platforms and network effects (a service becomes more valuable as more people use it) shape competition. Digital transformation means redesigning processes and customer experience around technology rather than just digitising old steps.
In the real world: Flipkart, Amazon and Zomato are platform businesses that connect buyers and sellers, and Aadhaar-based eKYC and UPI form India’s public digital infrastructure on which private firms build products.
7. Security, risk and ethics
The CIA triad defines security goals: confidentiality, integrity, availability. Threats: malware, phishing, ransomware, insider misuse, denial-of-service and weak passwords. Controls: authentication (passwords, multi-factor), authorisation, encryption, firewalls, backups, disaster recovery and business continuity plans, and staff awareness. Law: India’s IT Act, 2000 and the data protection law govern cybercrime, digital signatures and personal data. Ethical issues include privacy, intellectual property, algorithmic bias and the digital divide.
In the real world: most breaches start with a phished password, which is why companies enforce multi-factor authentication. A recovery plan that has never been tested is a plan on paper only.
8. Systems development and emerging technology
The systems development life cycle (SDLC): planning, analysis, design, implementation, testing, deployment and maintenance, in a waterfall way or iteratively with Agile. Choices: build, buy or rent (SaaS). A feasibility study checks technical, economic (cost–benefit, ROI, payback) and operational fit. Prototyping and user involvement reduce risk. A CIO leads IT strategy.
Emerging technologies: artificial intelligence and machine learning (automating prediction and content), robotic process automation, blockchain, IoT and low-code tools. The management task is to judge value, risk and readiness, not to chase every trend.
One-minute recap
| Topic | Key idea | Where you meet it |
|---|---|---|
| Information systems | Data to information; TPS, MIS, DSS, ESS | Reports, dashboards |
| IT and strategy | Cost, differentiation, new models; alignment | Walmart, Netflix, UPI |
| ERP, CRM, SCM | One integrated record; customer and supplier systems | SAP, Oracle, Salesforce-type CRM |
| Data and BI | DBMS, warehouse, OLAP, mining, analytics | Recommendations, fraud detection |
| Networks and cloud | LAN to internet; IaaS, PaaS, SaaS | Hosting, SaaS tools |
| E-commerce | B2B, B2C, platforms, network effects | Marketplaces, payments |
| Security | CIA triad, controls, IT Act | MFA, backups, compliance |
| Development and trends | SDLC, Agile, build–buy–rent, AI | Projects, vendor choices |
Next in MBA Revisited: Organizational Behavior – II.
Written by Claude, Anthropic’s AI assistant, as part of MBA Revisited, a quick refresher of the PGDM subjects one at a time.