Business Data Analytics Ch 4

A system that captures & measures financial transactions and communicates financial performance to interested parties is called a ...

financial reporting system Note: In many contexts, the terms "financial reporting system" and "accounting reporting system" are used interchangeably.

The concept that expresses financial information in relation to some relevant figure or base is called ...

"financial ratio analysis."

Sequence Check:

A method used in data validation to ensure that data is in the correct order or sequence. It helps identify missing, duplicate, or out-of-sequence data entries. If there's a gap or repetition in the sequence, it could indicate errors or omissions in the data. Example: In a dataset representing invoice numbers, a sequence check would reveal if any invoice numbers are missing or duplicated.

autonomous analytics system

A form of analytics that utilizes advanced technologies, such as artificial intelligence (AI) and machine learning (ML), to automate and enhance the analytics process. refers to the ability of analytics systems to operate independently and intelligently, leveraging tech itself to perform data analysis, generate real-time insights, and make decisions without constant human intervention. Example: An autonomous analytics system for a retail company might automatically analyze customer purchase patterns, predict future trends, optimize inventory levels, and generate recommendations for marketing strategies, all without direct human involvement.

You've developed a hypothesis that it is faster to source artificial Christmas trees from Indonesia (to Seattle) than from the Philippines (to Seattle). Using statistical analysis, how would you test that hypothesis? Why is this an example of diagnostic analytics?

A t-test could be used to test the hypothesis, comparing the sourcing time from Indonesia to Seattle to the sourcing time of Philippines to Seattle.

Fuzzy Matching:

A technique for identifying and match similar but not necessarily identical strings or data entries. It accounts for variations, misspellings, or slight differences in data. Helps in cleaning and consolidating data effectively. Example: In a customer database, fuzzy matching might be applied to identify similar names or addresses that have slight variations (e.g., "John Smith" vs. "Jon Smithe").

Does an analyst "Analyze the data" before or after finding the appropriate data to address a specific question? Explain.

ANALYZE THE DATA is the third step of the SOAR analytics model. Once we know our ques- tion (SPECIFY THE QUESTION) and acquire and clean the appropriate data (OBTAIN THE DATA), we are ready to perform the appropriate analytics to address the question.

Suppose that an examination of banking transactions at Wells Fargo reveals more check amounts starting with 9's than with 3's. Do these findings match what Benford's Law predicts? Why or why not?

According to Benford's Law, in any large, randomly produced set of natural numbers, a higher percentage of numbers in a population of numbers starts with 1 than any other digit, followed by those that begin with 2, then 3, and so on. So, no. Unless there is a specific explanation for why there are more leading digits with 9's instead of 3's, we'd want to investigate the situation to explain why this phenomenon is occurring.

Benford's Law (first-digit law):

An observation about the frequency distribution of leading digits in many real-life sets of numerical data. It states that in many naturally occurring collections of numbers, the leading digits are not evenly distributed. It predicts a higher frequency of smaller digits (1, 2, 3) compared to larger ones (7, 8, 9). Example: When analyzing a dataset of invoice amounts or population figures, Benford's Law might predict that more numbers will start with 1 or 2 than with 8 or 9. Deviations from this law can sometimes indicate anomalies or irregularities in the data.

Why is answering the question of "why" something occurred consistent with exploratory business analytics, as opposed to confirmatory analytics?

Answering the "why" question aligns with exploratory analytics because it involves an open-ended exploration of data to uncover insights and potential explanations for observed phenomena, rather than confirming specific hypotheses as in confirmatory analytics.

Characteristics of Autonomous Analytics:

Automation: The system can automatically handle various aspects of the analytics process, including data preparation, modeling, analysis, and reporting. Machine Learning: Autonomous analytics often incorporates machine learning algorithms to adapt and improve over time based on patterns and feedback. Continuous Improvement: The system can learn from new data, adjust models, and improve its analytical capabilities over time without explicit programming.

What are similarities and difference between diagnostic and descriptive analytics?

Both descriptive and diagnostic analytics are rooted in past data, they analyze and interpret data that has already been collected. Descriptive and diagnostic analytics have different objectives, so answer different types of questions... - Descriptive Analytics: Aims to answer the question "What happened?" It focuses on summarizing and presenting data to provide a clear understanding of past events. - Diagnostic Analytics: Aims to answer the question "Why did it happen?" It involves a more in-depth analysis to uncover the root causes of specific outcomes identified in the descriptive analysis. Diagnostic analytics requires us to ask more questions than descriptive analytics and examine additional data sources to determine why something did or did not happen in comparison with expectations.

Why are vertical analysis and horizontal analysis both considered to be descriptive analytics techniques?

Both vertical and horizontal analyses are descriptive because their main objective is to describe the structure, composition, and changes in financial statements without necessarily explaining the reasons behind those changes. Their primary purpose is to describe what occurred, addressing the question "What happened over time?"

The term "customer credit score" would not typically be included in a typical Customer Relationship Management (CRM) system because...

CRM systems primarily focus on managing and analyzing customer interactions and relationships rather than financial aspects like credit scoring.

Liquidity Ratios:

Current Ratio: Current Assets / Current Liabilities Quick Ratio: (Current Assets - Inventory) / Current Liabilities

Debt Ratios:

Debt-to-Equity Ratio: Total Debt / Shareholders' Equity Interest Coverage Ratio: Earnings Before Interest and Taxes (EBIT) / Interest Expense

SW Airlines has a frequent flier program called Rapid Rewards, which gives its customers free flights after accumulating points from flying on SW Airlines. Which type(s) of analytics would be needed to understand if the benefits of running the Rapid Rewards program are greater than the costs of administering the program and giving free flights?

Diagnostic analytics may be used to figure out how much additional revenue Southwest takes in as a result of its Rapid Rewards program. Descriptive analytics could assess the costs associated with administering the program and giving away free flights. *The benefits of the frequent flier program likely include loyal customers who choose to fly on SW Airlines rather than other carriers, thereby increasing Southwest's revenue.

Prescriptive Analytics:

Goes beyond predicting future outcomes; it recommends actions to optimize or improve those outcomes. It leverages data, algorithms, and business rules to provide actionable insights. Example: An e-commerce platform uses prescriptive analytics to recommend personalized product offerings to customers based on their browsing history, preferences, and current trends, aiming to maximize sales and customer satisfaction.

Why is finding anomalies and outliers consistent with exploratory business analytics?

Finding anomalies and outliers is consistent with exploratory business analytics because it involves an open and flexible exploration of data to discover unexpected patterns or irregularities. Detecting anomalies is not about confirming preconceived notions or hypotheses but rather about uncovering insights that may have been overlooked, making it well-aligned with the exploratory approach.

The technique used to find potential equivalents when there is less than an exact fit is:

Fuzzy matching

Adaptive/Autonomous analytics:

How can we continuously learn using artificial intelligence? Can we learn from past and current events with adaptive learning? (Chapter 11)

In vertical analysis, when looking at the cost of goods sold (COGS) on the income statement, we compare it to the total sales. The relevant base, or the number we use for comparison, is the net sales. To calculate the vertical analysis percentage for COGS, you take the cost of goods sold and divide it by the net sales (relevant base). Then, multiply the result by 100 to get a percentage. This percentage helps us understand ....

How much of the total sales is being used to cover the cost of producing or purchasing goods sold by the company.

The system that is an information system for managing all interactions with past, current, and potential employees is:

Human resource management system

Four principal business information systems at a company contain much of the data needed for descriptive analytics:

Human resource management systems (HRMS) Customer relationship management (CRM) systems Supply chain management (SCM) systems Financial reporting (accounting) systems (FRS)

Efficiency Ratios:

Inventory Turnover: Cost of Goods Sold / Average Inventory Receivables Turnover: Net Sales / Average Accounts Receivable

Why is investigating why product recommendations affect conversion rates at Walmart.com (getting the people who read product reviews to actually buy the products reviewed) an example of diagnostic analytics instead of predictive analytics?

Predictive analytics involves forecasting future outcomes. Diagnostic analytics entails answering the question "Why did it happen?" In this case, the emphasis is on understanding the existing behavior ("why did some people buy the products after reading reviews at Walmart.com, and other people did not?") rather than predicting future behavior.

Market Ratios:

Price-to-Earnings Ratio (P/E Ratio): Market Price per Share / Earnings per Share (EPS) Dividend Yield: Dividends per Share / Market Price per Share

2. Diagnostic Analytics phase:

Purpose: delves deeper into the data to identify relationships and drivers of observed patterns.it builds on descriptive analytics by digging into WHY certain events occurred. It involves analyzing historical data to understand the reasons behind specific outcomes, patterns, trends Methods: Comparative analysis, root cause analysis, and correlation analysis are common diagnostic analytics methods. Example: A company notices a sudden drop in website traffic and employs diagnostic analytics to investigate the possible reasons, discovering that the decrease is linked to a recent change in the website's user interface.

1. Descriptive Analytics phase:

Purpose: involves summarizing and presenting a comprehensive view of historical data to provide insights into WHAT has happened in the past. It aims to describe and understand patterns, trends, and key features of the data. Methods: Techniques like summary statistics, data visualization, and reporting are used to present a clear picture of historical data. Example: If a retail company analyzes its sales data from the past year to identify best/worst-selling products, peak sales periods, and customer demographics

Profitability Ratios:

Return on Assets (ROA): Net Income / Total Assets Return on Equity (ROE): Net Income / Shareholders' Equity

Financial variables provide insights into an entity's financial performance, position, and ability to meet its obligations, aiding in financial decision making. Critical financial variables to understand the health and stability of businesses or individuals include....

Revenue: The total income generated by a business from its primary operations. Expenses: The costs incurred by a business in the process of generating revenue. Profit (or Net Income): The positive difference between revenue and expenses. Assets: Resources owned or controlled by an entity, such as cash, inventory, property, and investments. Liabilities: Obligations or debts that an entity owes to external parties, such as loans or accounts payable. Equity: The residual interest in the assets of an entity after deducting liabilities; it represents ownership. Cash Flow: The movement of cash into and out of a business, indicating liquidity (the amount of money it has on hand and its ability to quickly convert assets into cash) Return on Investment (ROI): A measure of profitability, often expressed as a percentage, representing the return on an investment relative to its cost. Debt-to-Equity Ratio: A financial leverage ratio that compares a company's total debt to its total equity. Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA): A measure of operating performance before certain expenses. Working Capital: The difference between current assets and current liabilities, reflecting short-term liquidity.

What is required to determine whether a finding is an anomaly or outlier?

Set an Expectation -- define a threshold that determines what is "normal" for your data. This could be based on past observations, industry standards, or common expectations. Data points beyond this limit might be considered outliers.

Which Excel Data Analysis ToolPak technique would be most useful in forecasting the level of sales a firm will experience, given its level of advertising expense? Would this analysis be considered predictive analytics or descriptive analytics?

The technique that would be most useful for forecasting the level of sales based on advertising expense is the "Regression" analysis. This type of analysis falls under the category of predictive analytics. It involves using historical data and statistical algorithms to make predictions about future events or trends. If you were merely describing the relationship between sales and advertising expenses without forecasting future sales, it would be considered descriptive analytics.

Identifying Anomalies/Outliers phase:

This is a subset of both descriptive and diagnostic analytics, focusing on recognizing irregularities or unexpected deviations from typical patterns. *Anomalies: data points that deviate significantly from the norm. Often a first step in diagnostic analytics is to look for and identify unusual, unexpected results or transactions. Don't immediately assume something is wrong. Verify the data, and if it's indeed an outlier, investigate why it's different. d/t errors, unusual events, or genuine changes? Methods: Statistical techniques, machine learning algorithms, and visualizations are employed to detect anomalies. This process helps highlight data points that might require further investigation to understand their origins or implications.

What visualization type would you use to show a trend over time?

To show a trend over time, a line chart is a commonly used and effective visualization type. A line chart make it easy to visualize the progression of a variable over a continuous time axis with the upward or downward slopes indicating the direction of the trend.

Predictive Analytics:

Using statistical algorithms and machine learning techniques to FORECAST FUTURE OUTCOMES based on historical data. It aims to predict what might happen in the future. Example: A credit card company might use predictive analytics to assess a customer's likelihood of defaulting on a payment based on their past spending behavior, credit history, and other relevant factors.

Descriptive analytics:

What happened? What is happening? (Chapter 4)

Prescriptive analytics:

What should we do, based on what we expect will happen? How do we optimize our performance based on potential constraints? (Chapter 5)

Diagnostic analytics:

Why did it happen? What are the causes of past results? Why are the results different than expectations? (Chapter 4)

Predictive analytics:

Will it happen in the future? What is the probability something will happen? Can we forecast what will happen? (Chapter 5)

An Employee Management System

a broader term that can encompass various aspects of managing employees, including their performance, development, and engagement. It may include elements of HR management but can extend beyond to cover aspects like project assignments and task tracking. Example: An employee management system could include features for tracking employee performance goals, providing feedback, and assigning tasks.

Accounting Reporting System:

a component of a broader financial system that focuses on recording and reporting financial transactions. It involves the collection, classification, and organization of accounting data for reporting purposes. Example: In an accounting reporting system, transactions such as sales, purchases, and expenses are recorded in ledgers and journals. These records are then used to prepare financial statements and reports, providing a detailed view of an organization's financial activities.

A Human Resource Management System (HRMS)

a comprehensive software solution that integrates multiple HR functions. It includes modules for employee records, payroll, benefits administration, recruitment, and other HR-related tasks. Example: An HRMS could allow HR professionals to manage employee data, track attendance, process payroll, and handle recruitment all within a single platform.

Customer Credit Score:

a numerical representation of a customer's creditworthiness. It is often used by financial institutions, lenders, and businesses to assess the risk associated with extending credit to a customer. Example: If a bank uses a credit scoring system, a customer with a high credit score (indicating a good credit history) may be eligible for lower interest rates on loans, while a customer with a lower credit score (indicating a riskier credit history) may face higher interest rates or may be denied credit.

Customer Payment History:

a record of a customer's past payments for products or services. It tracks whether the customer has paid on time, missed payments, or has a history of late payments. Example: In a subscription-based business, tracking customer payment history helps identify whether a customer consistently pays their subscription fees on time. It helps assess the reliability of the customer in meeting financial obligations.

Financial Reporting System:

a set of tools and processes that organizations use to collect, process, and present financial data. It helps in creating reports and statements for internal and external stakeholders to assess the financial health and performance of the company. Example: An organization might use a financial reporting system to generate quarterly income statements, balance sheets, and cash flow statements. These reports provide insights into revenue, expenses, assets, liabilities, and cash flow.

Financial Reporting System:

a set of tools, processes, and procedures used by organizations to gather, process, and present financial information to internal and external stakeholders. It plays a crucial role in summarizing and communicating the financial health and performance of a company. Example: An organization might use a financial reporting system to generate periodic reports such as income statements, balance sheets, and cash flow statements. These reports help management, investors, and regulators understand the company's financial position and performance.

Customer Relationship Management System (CRM):

a software tool or platform that helps businesses manage and analyze interactions with their customers. It typically includes features for tracking customer interactions, managing leads, and improving customer engagement. Example: A company might use a CRM system to store customer contact information, track communication history, and manage sales opportunities. This allows the organization to provide personalized services, target marketing efforts, and enhance overall customer satisfaction.

Financial Statement Generation System:

a specialized tool or software designed to automate the process of creating financial statements. It streamlines the generation of reports such as income statements, balance sheets, and cash flow statements. Example: An accounting department might use a financial statement generation system to input financial data, apply accounting rules and regulations, and produce accurate and compliant financial statements. This helps save time, reduce errors, and ensure consistency in financial reporting.

t-test

a statistical test used to evaluate the size and significance of the difference between two means

employee compensation system

a structured approach to managing and administering employee pay and benefits within an organization. It includes processes for setting salaries, bonuses, incentives, and other forms of compensation. Example: A company might use an employee compensation system to determine salary levels based on factors such as experience, skills, and job responsibilities. It may also include bonus structures tied to individual or team performance.

What is the name of the information system that gives a customer's order history?

customer relationship management system

In practice, these three types of analytics often work together in a cyclical manner. Insights gained from ________ analytics may lead to further investigation using ________ analytics, and the identification of ________ may prompt a revisit of the descriptive and diagnostic analyses. This process enhances the understanding of data and supports informed decision-making based on a thorough inspection of historical information.

descriptive --- > diagnostic --- > anomalies

Evaluating trends over time addresses the question "What happened?", which is consistent with _____ ______

descriptive analytics.

5 types of business analytics:

descriptive, diagnostic, predictive, prescriptive,and adaptive/ autonomous analytics.

Customer Contact History:

ecords interactions and communications between a business and its customers. It includes details of phone calls, emails, support tickets, and other touchpoints. Example: A customer contact history might show that a customer called the customer support hotline three times in the past month with questions about product features. This information is valuable for providing personalized assistance and understanding customer needs.

Trend Analysis (AKA "Horizontal Analysis"):

examining data over time to identify patterns, tendencies, or trends. It is often used to analyze trends over time (the historical performance) of key metrics and then make predictions about future trends. Horizontal analysis is a technique used in descriptive stats Example: A company looks at monthly sales over the past 2 yrs (e.g. sales trend analysis) - A consistent upward trend? growing sales - A declining trend? indicates challenges needing att'n

What type of analytics includes descriptive and diagnostic analytics to summarize and explain performance?

exploratory analytics

The system that captures and measures financial transactions and communicates financial performance to interested parties is:

financial reporting system

exploratory business analytics:

has less focused on predicting future events with statistical certainty. involves describing past performance, exploring summary performance statistics (data) to uncover new insights, detect patterns, or relationships, identify anomalies and outliers, and checking assumptions - often w/o a predefined question. Example: A retail company may conduct exploratory analytics on its sales data to identify unexpected trends or correlations. This could involve visualizing the data in various ways and exploring different variables to gain insights without having a specific question in mind.

Diagnostic analytics, descriptive analytics, and identifying anomalies/outliers are three _______ components within the broader field of data analytics, each serving a distinct purpose in the analytical process.

interrelated

Growth [rate] Analysis:

involves assessing the percentage increase or decrease in specific metrics over a period, providing insights into the rate of change or growth. Example: A company's revenue was $1 million last year and $1.5 million this year. Growth rate can be calculated as ($1.5 million - $1 million) / $1 million * 100, resulting in a growth rate of 50%. This indicates a 50% increase in revenue.

Vertical Analysis:

involves expressing each line item in a financial statement as a percentage of a base item on the same statement. - It helps assess the proportions of different components within a single financial statement. Calculate percentages: For each line item on the financial statement, divide the value of that item by the value of the chosen base item and multiply by 100 to express it as a percentage.

confirmatory business analytics:

involves testing specific hypotheses using statistical methods to draw conclusions about the data based on a predetermined question or theory. well suited for judging the likelihood of future events. Example: A pharmaceutical company may use confirmatory analytics to test the effectiveness of a new drug. The hypothesis might be that the drug significantly reduces symptoms compared to a placebo. The analysis would involve statistical tests to confirm or reject this hypothesis based on the collected data from clinical trials.

Supply Chain Management System:

involves the coordination and management of all activities involved in the production and distribution of goods and services, from the acquisition of raw materials to the delivery of the final product to the end customer. Example: A retail company might use a supply chain management system to track the movement of products from suppliers to warehouses and distribution centers, and finally to retail stores. This system helps optimize inventory levels, reduce costs, and improve overall efficiency.

Customer Profitability:

measures the net profit a business earns from serving a particular customer over a specific period. It takes into account the revenue generated from the customer and the costs associated with serving that customer. Example: A retailer may analyze customer profitability by considering factors such as the total purchases made by a customer, the associated marketing and operational costs, and any returns. This analysis helps identify high-value customers contributing significantly to the company's profits.

The type of analytics that analysts perform often depends on the type of ______ ______.

questions asked

Minimums, Maximums:

refers to the lowest and highest values in a dataset or a set of observations. Analyzing minimums and maximums helps identify the range and extremes in the data. Example: In a sales dataset for a retail store, the minimum value might represent the lowest daily sales recorded, while the maximum value would represent the highest daily sales.

summary statistics

statistics that summarize a great deal of numerical information about a distribution, such as the mean and the standard deviation

What is the name of the information system that shares product demand schedules with suppliers to ensure timely fulfillment of supplies needed for delivery is:

supply chain management system

What system tracks the sequence of processes to move a product from raw materials to final customer delivery?

supply chain management system

Ratio Analysis:

the examination and interpretation of relationships between different financial variables in a company's financial statements. - Ratios help assess performance, efficiency, and financial health. - Ratios are calculated by dividing one financial metric by another. Example 1: if you want to know a company's financial leverage, you'll calculate it's debt-to-equity ratio. Divide its total debt by total equity. Higher ratio = higher financial risk. Example 2: divide a company's current assets by its current liabilities to calculate liquidity ratio. A company w/ $500k in current assets and $250k in current liabilities has a ratio of 2:1, indicating having twice as much assets to cover its liabilities.

Bank Statement Reconciliation:

the process of comparing and matching a company's internal financial records, such as cash transactions in its accounting system, with the information on its bank statement. The goal is to ensure that the two sets of records align and to identify any discrepancies. Example: A company may reconcile its bank statement by comparing its own records of deposits, withdrawals, and transactions with the bank's statement. If there's a discrepancy, it could be due to outstanding checks or deposits that haven't cleared.

Manufacturing System:

the set of processes, resources, and technologies used to produce goods on a large scale. It encompasses the design, planning, and control of the production process. Example: An automobile manufacturing company may have a manufacturing system that includes assembly lines, quality control processes, and automated machinery to produce cars efficiently. The manufacturing system ensures that products meet quality standards and are produced in a cost-effective manner.

Counts:

the tallying or counting of occurrences of a particular event or item. It is a basic descriptive analytics technique that provides a numerical representation of the frequency of occurrences. Example: In a customer satisfaction survey, counts might be used to tally the number of responses falling into different satisfaction levels (e.g., satisfied, neutral, dissatisfied). The count for each level provides insights into the distribution of customer opinions.

Data included in the HRMS may include the following:

∙ Employee recruiting data and leads ∙ Employee training (current and desired certifications) ∙ Employee payroll and compensation (including tax elections such as 401(k) contribu- tions, number of dependents, and amount of state and federal withholding) ∙ Employee benefits (stock options, bonuses, health insurance) ∙ Employee annual reviews (prior and current year reviews, ratings received) ∙ Employee absenteeism (how often work is missed) ∙ Employee career progression (prior and current roles) ∙ Employee satisfaction and sentiment survey results