Lect 1.1 - Introduction to Business Analytics PDF

Business Analytics and Strategy Chapter: 1 Foundations of Business Dr. Muhammad Ahmad Mazher Analytics and Strategy PhD University Kuala Lumpur, Malaysia Mobile/WhatsApp: +92 335 711 2...

Business Analytics and Strategy Chapter: 1 Foundations of Business Dr. Muhammad Ahmad Mazher Analytics and Strategy PhD University Kuala Lumpur, Malaysia Mobile/WhatsApp: +92 335 711 2000 [email protected] What is Business? ❑ The term business refers to an organization or enterprising entity engaged in commercial, industrial, or professional activities. ❑ A business is an activity carried out with the aim of making economic profit. ❑ Business can operate in different sectors, such as trade, industry, technology, or services and contribute to economic growth (GDP) and employment in any society. ❑ A legally recognized organization designed to provide goods & services to consumers, businesses, and governmental entities. What is Analytics? ❑ Analytics involves computationally analyzing data, or statistics. Finding, interpreting, and communicating data patterns is its purpose. It also involves using data patterns to make decisions. ❑ Analytics provides insights and useful data that may not be seen otherwise. ❑ Business analytics employs data insights to make better decisions to boost sales, cut expenses, and enhance operations. ❑ Data analytics turns raw data into actionable insights. It encompasses data-driven tools, technologies, and procedures for trend detection and problem solving. ❑ Data analytics can enhance corporate processes, decision-making, and growth.  What is Strategy? ❑ Comprehensive plan to attain a goal or group of goals. Strategy is used in business, military operations, politics, sports, and other disciplines where planning and decision- making are vital. ❑ A business strategy is an organization's plan to achieve its goals and mission. It entails choosing and distributing resources to maximize the company's competitiveness and satisfy stakeholders. ❑ Strategy Comprise ▪ Vision & Mission ▪ Goals & Objectives ▪ Analysis & Planning ▪ Allocation of Resources ▪ Competitive Positioning ▪ Implementation & Execution Overview 1. Introduction to Business Analytics * The process of collecting, analyzing, and interpreting data to make informed business decisions and optimize outcomes. * It's all about using data to answer important questions and make smart decisions to grow your business. * Business analytics and strategy is like being a detective for your business. * Business analytics and strategy refers to the use of data analysis and perceptions to make informed decisions and develop effective business plans. The key components of BA comprise *Data collection, *Statistical analysis, *Predictive modeling, and *Data visualization Goal: Turning data into actionable insights. Real World Examples: Amazon, Netflix, Walmart Tool Used: Power BI, R, Python, Excel, etc. Overview 1.1 Scope of Business Analytics Descriptive Analytics: Understanding past performance and identifying trends. Predictive Analytics: Forecasting future outcomes based on historical data. Prescriptive Analytics: Recommending actions for optimizing business outcomes. Data Science Integration: Includes machine learning and AI techniques for deeper insights. Industry Applications: Finance, economics, retail, marketing, supply chain, etc. Four Types of Data Analytics 1. Predictive Analysis Predictive analysis may be the most used category of data analytics. Businesses use predictive analytics to identify trends, correlations, and causation (interconnection). The category can be further broken down into predictive modeling and statistical modeling; however, it’s important to know that the two go hand in hand. 2. Prescriptive Analysis Prescriptive analytics is where AI and BIG DATA combine to help predict outcomes and identify what actions to take. This category of analytics can be further broken down into optimization and random testing. Using advancements in ML (Machine Learning), prescriptive analytics can help answer questions such as “What if we try this?” and “What is the best action?” You can test the correct variables and even suggest new variables that offer a higher chance of generating a positive outcome. Four Types of Data Analytics 3. Diagnostic Data Analytics While not as exciting as predicting the future, analyzing data from the past can serve an important purpose in guiding your business. Diagnostic data analytics is the process of examining data to understand the cause and event or why something happened. Techniques such as drill down, data discovery, data mining, and correlations are often employed. 4. Descriptive data analytics Descriptive analytics are the backbone of reporting—it’s impossible to have business intelligence tools and dashboards without them. It addresses basic questions of “how many, when, where, and what.” Once again, descriptive analytics can be further separated into two categories: ad hoc reporting and canned reports. Overview 2. Statistical Foundations for Business Analytics - Descriptive Statistics – summarize and describes data using mean, median, mode, variance, S.D etc. - Probability Theory – the mathematical framework for predicting future events. Application in BA consist of assessing risk and opportunities - Hypothesis Testing – formulating null and alternative hypothesis, conducting test (Z, t, Chi- square), and interpretation (acceptation/rejection) - Regression Analysis – technique to identify relationship between variables through simple/multiple. Overview 3. Strategic Thinking and Decision-Making Steps – define objectives, analyze internal & external environment, formulate strategy, implement and evaluate progress. SWOT Analysis – Strength, Weaknesses, Opportunities, and Threats. Decision-Making Framework – it consist of * Rational Decision-Making Model – Systematic approach based on data and logic. * Pros & Cons Analysis – Weighs advantages and disadvantages of each option. * Decision Trees – Graphical representation of possible choices and outcomes.  Overview ❑ 4. Data Management and Cleaning Data – Data refers to raw, unprocessed facts, figures, symbols, or statistics that have no intrinsic (core/key/fundamental) meanings. In its raw form, data lacks context and organization, making it difficult to interpret or use effectively. Data can take various forms, including text, numbers, images, audio, and more. It serves as the foundational building block for information and knowledge. Data Collection Methods – Data consists of two types such as primary data and secondary data. Data Quality Assessment and Cleaning – Inaccurate data leads to poor decision and policy formation. Data Cleaning Process – It consists of handling missing data, identifying outlier, standardizing formats. Data Warehousing and Data Mining Techniques – It consists of Data Warehousing – Centralized storage of structured and unstructured data Data Mining – Extracting useful patterns and trends from large datasets. Why Business Analytics & Strategy? ❑ Business analytics provides marketers with valuable insights and ability to enhance customer understanding ❑ Moreover, business analytics enables marketers to measure the success of their marketing initiatives. ❑ In addition, business analytics empowers marketers to stay ahead of market trends and gain a competitive edge. ❑ It combines data analysis, statistical modeling, predictive analytics, and data visualization to help businesses gain a competitive edge and make informed choices. ❑ Business analytics is not just about analyzing historical data; it involves forecasting future trends and outcomes to guide strategic planning and resource allocation. In conclusion, business analytics can help marketers maximize their marketing efforts. Marketers may improve results by analyzing customer data, monitoring campaign success, and following market trends. In a data-driven world, business analytics helps marketers be proactive, respond, and achieve their goals. Importance & How Does It Works? ❑ Smart Decisions: Business analytics helps you make decisions based on evidence, not guesswork. ❑ Customer Insights (understanding): You can understand your customers better. ❑ Efficiency: It helps you run your business more smoothly. You can optimize your supply chain, manage your finances better, and reduce waste. ❑ Competitive Edge: By analyzing data, you can stay one step ahead of your competitors. You can spot trends before others do and adjust your strategy accordingly. i. Data Collection: First, gather data from various sources like sales records, customer feedback, and website visits. Think of this as collecting puzzle pieces. ii. Data Analysis: Then, you put those puzzle pieces together. Analytical tools and techniques help you find patterns, trends, and insights in your data. iii. Decision-Making: Armed with these insights, you can make informed decisions. It's like having a map to navigate your business journey. Measures of Business Analytics & Strategy 1. Key Performance Indicators (KPIs) KPIs are quantifiable metrics that gauge the performance of a business in achieving its strategic objectives. Examples include revenue growth, customer acquisition (gaining) cost, customer retention rate, and conversion rates. 2. Return on Investment (ROI) ROI measures the profitability of specific investments or projects. It helps organizations assess whether a particular strategy or initiative is generating a positive return relative to its cost. For example, if a company invests in a marketing campaign, ROI will assess the campaign's impact on revenue compared to the amount spent. 3. Market Share Market share measures a company's portion of the total market sales within a specific industry. It indicates a company's competitive position and its ability to capture a larger share of the market compared to rivals. 4. Customer Lifetime Value (CLV) CLV assesses the total revenue a business can expect from a single customer throughout its engagement with the company. It helps in tailoring marketing and service strategies for customer retention and loyalty. Measures of Business Analytics & Strategy Examples: Let's consider an e-commerce company Scenario 1 (KPIs – Key Performance Indicators): The company analyzes its conversion rates (the percentage of website visitors who make a purchase). If the conversion rate is low, it indicates that the current strategy might not be effectively converting visitors into customers. The company can then adjust its website design or marketing tactics to improve this KPI. Scenario 2 (ROI – Return on investment): The company invests in a new mobile app. By analyzing the ROI, the company can determine whether the app generates more revenue than its development and marketing costs. If the ROI is positive, it's a strategic move to continue investing in the app. Scenario 3 (Market Share): The company tracks its market share in the online retail industry. If it realizes a decline in market share, it may signify increased competition or a need to expand product offerings to regain its position. Scenario 4 (CLV - Customer Lifetime Value): By analyzing customer lifetime value (CLV), the company identifies its most valuable customers. It can then develop loyalty programs or personalized marketing strategies to retain and maximize revenue from these customers. Importance of BA for Student ❑ Enhanced Decision-Making In summary, the study of Business ❑ Competitive Advantage Analytics and Strategy equips ❑ Strategic Thinking students with a diverse set of skills ❑ Problem Solving and knowledge that are highly ❑ Innovation relevant to the modern business ❑ Global Relevance landscape. Whether they pursue ❑ Job Opportunities careers in data analysis, consulting, entrepreneurship, or management, ❑ Adaptability these skills are invaluable for ❑ Leadership Skills success. ❑ Real-World Application