Introduction to Data-Driven Decision

Topic 1 – Introduction to Data-Driven Decision

1. Data and Business strategy

🡪 Idea in strategy comes from

1. Bruce Henderson, founder of BCG 🡪 The Napoleonic idea of concentrating mass against weakness, of overwhelming the enemy.

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🡪 The more you do of something, disproportionately the better you get.

Therefore, he found a logic for investing in such kinds of overwhelming mass in order to get competitive advantage. That was the introduction of a military concept of strategy into the business world.

1. Michael Porter, professor at the Harvard Business School

Porter agreed but pointed out that business have multiple steps to them. Each of the components might be driven by a different kind of strategy.

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🡪 What holds a business together is transaction costs 🡪 you need to coordinate. Therefore, the nature and role and boundaries of the cooperation are defined by transaction costs.

Those premises are invalidated.

Two components to transaction costs:

• Processing information
• Communication

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🡪 Those components have been radically transformed since Porter and Henderson. Now, that those falling transaction costs have profound consequences, because if transaction costs are the glue that hold value chains together, and they are falling, there is less to economize on. There is less need for vertically integrated organization and value chains at least can break up.

Today, we need to think about strategy as the curation of these kinds of horizontal structure where things like business definition and even industry definition are actually the outcomes of strategy. For example, we need to work out how to accommodate collaboration and competition simultaneously.

1. Data Challenges for businesses: Understanding the different types of analytics

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Analytics: Data analytics is the process of examining datasets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software.

🡪 Evolution of analytics

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🡪 Identifying data and analytics needs

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🡪 Types of analytics

1. Descriptive (Information): What happened in the Business?

• Links the market to the firm through information
• Aid the manager to make actionable decisions
• Principles for systematically collect and interpret data that can aid decision-makers

1. Diagostic (Insights): Why is something happening in the Business?

• Diagnostic analytics get into the root cause
• Determining the factors and events that contributed to the outcome
• Data discovery, data mining and correlational analysis
• E.g. Attribute importance, sensitivity analysis, principal component analysis and conjoint analysis

1. Predictive (Insights): What is likely to happen in the future?

• Detect trends
• Detect clusters
• Detect exceptions

Using customer data to predict what they will do in the future.

1. Prescriptive (Decision/Action): Sowhat? And now what?

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🡪 Marketing research Methods

The process of Marketing Research follows five steps:

(1) Research problem or question formulation

(2) Determination of sources of information and research design

(3) Data collection method selection

(4) Data collection

(5) Data analysis and interpretation

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🡪 Research types

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Data: Information, especially facts or numbers, collected to be examined and considered and used to help decision-making. OR

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