Lecture 1 â Introduction to business analytics Business analytics is the ...
Lecture 1 – Introduction to business analytics Business analytics is the ability of firms to collect, analyse and act on data. It is the ability to generate knowledge such as: - What products customers want? - What prices will customers pay? - How many will each customer buy? - Why do they buy? Why do they buy more? - How do problems affect the bottom line? - To predict demand, performance and problems. - Identify opportunities, discover new segments. It is the use of data, information technology, statistical analysis, quantitative methods and mathematical or computer-based models, to helps managers make better decisions. It is a combination of (STAP) skills, technologies, applications and processes used by organisations to gain insight into their business based on DISQM-C to drive or guide business planning. Competing on Analytics In order for organisations to compete on analytics, Davenport suggests they must have data, personnel and procedures. Where is the data in an organisation? Operational systems: They are used to run day to day business operations – also known as Transaction processing systems. It uses OLTP databases to store daily business transactions. OLTP is a computer system where time-sensitive, transaction-related data is processed immediately and is always kept current. It is used for order entry, financial transactions, and CRM and retail sales. It is a class of information systems that facilitate and manage transaction-oriented applications, typically for data entry and retrieval transaction processing. Characteristics of data under this system: - Transaction-oriented - May be inconsistent and incomplete - Volatile (changing continuously) - Current. Databases are everywhere. - Efficient transaction processing Automatic data capture Easy retrieval Data quality, errors, inconsistencies - Automating business processes Production, Marketing, Accounting, Sales Databases are great, but
- Too many of them Everybody wanted 1 or 2 or more Production, Marketing, Accounting, Sales - Everybody got what is best for them IBM, Oracle, Access, Excel, file drawers - Created the problem databases were meant to solve Inconsistent, incompatible, inaccessible data As a result, data are not effectively employed and hence opportunities for improving performance are missed and there are problems with analysing data to improve decisions and performance. Organisations need to store data for day to day operations. Data is being stored in many databases (usually duplicating data across them, and usually incompatible with each other). Organisations could make use of this data to improve the decision making process through some sort of business analytics or business intelligence. This could be accomplished via some sort of computer system(s). What is decision making? It is a thought process of selecting a logical choice from available options. It is a process of identifying and selecting – solve a specific problem – choice making which is part of decision making, i.e., select one option from a set of alternatives. There are programmed decision (structured decisions for routine problems) and nonprogrammed ones (unstructured decisions for unique and unusual problems – rational decision making). Simon (Nobel Lecture) on rational decision making in organisations: “ We do know how the information processing system called Man, faced with complexity beyond his ken, uses his information processing capacities to seek out alternatives, to calculate consequences, to resolve uncertainties and thereby – sometimes, not always – to find ways of action that are sufficient unto the day, that satisfice”. Examples of analytics Experiments - test alternative strategies, product designs - different interest rate v/s fees - ad messages - incentives (cash back v/s loyalty points) Identify best customer segment - for each product design, promotion - identify optimum price Simulate effect on financial performance Decisions justified by data - Compensation, rewards, advertising, pricing, R&D, mergers, acquisitions - “In God we trust. All others bring data”
- Too many of them Everybody wanted 1 or 2 or more Production, Marketing, Accounting, Sales - Everybody got what is best for them IBM, Oracle, Access, Excel, file drawers - Created the problem databases were meant to solve Inconsistent, incompatible, inaccessible data As a result, data are not effectively employed and hence opportunities for improving performance are missed and there are problems with analysing data to improve decisions and performance. Organisations need to store data for day to day operations. Data is being stored in many databases (usually duplicating data across them, and usually incompatible with each other). Organisations could make use of this data to improve the decision making process through some sort of business analytics or business intelligence. This could be accomplished via some sort of computer system(s). What is decision making? It is a thought process of selecting a logical choice from available options. It is a process of identifying and selecting – solve a specific problem – choice making which is part of decision making, i.e., select one option from a set of alternatives. There are programmed decision (structured decisions for routine problems) and nonprogrammed ones (unstructured decisions for unique and unusual problems – rational decision making). Simon (Nobel Lecture) on rational decision making in organisations: “ We do know how the information processing system called Man, faced with complexity beyond his ken, uses his information processing capacities to seek out alternatives, to calculate consequences, to resolve uncertainties and thereby – sometimes, not always – to find ways of action that are sufficient unto the day, that satisfice”. Examples of analytics Experiments - test alternative strategies, product designs - different interest rate v/s fees - ad messages - incentives (cash back v/s loyalty points) Identify best customer segment - for each product design, promotion - identify optimum price Simulate effect on financial performance Decisions justified by data - Compensation, rewards, advertising, pricing, R&D, mergers, acquisitions - “In God we trust. All others bring data”
