Unit 2-1: Analytical Decision-Making PDF

Zeal Group of Management Institutes  GC 05 - Business Analytics(105) 3 Credits Zeal Group of Management Institutes  Unit-2 Analytical decision-making Analytical decision-making process, characteristics of the analytical decisio...

Zeal Group of Management Institutes  GC 05 - Business Analytics(105) 3 Credits Zeal Group of Management Institutes  Unit-2 Analytical decision-making Analytical decision-making process, characteristics of the analytical decision making process. Breaking down a business problem into key questions that can be answered through analytics, Characteristics of good questions, Skills of a good business analyst, The Basic Tools of Business Analytics - Data exploration and visualization (using tools like Excel, Tableau, or Power BI), Concept of Statistical analysis and hypothesis testing (Hypothesis testing numerical / tests not expected) Data Visualization: Concept of Data Visualization, Popular Data Visualization tools, Exploratory Data Analysis(EDA), Data Cleaning, Data Inspection. Zeal Group of Management Institutes  Analytical decision-making process Analytical decision-making is a process that involves systematically gathering and analyzing information to make a sound and logical decision. It consists in identifying and evaluating alternatives based on available data and weighing the pros and cons of each option to arrive at the most effective and efficient solution. Zeal Group of Management Institutes Steps involved in the analytical style of decision-making: ⮚ Identifying the problem or opportunity: The first step in analytical decision-making is identifying the problem or opportunity that needs to be addressed. This may involve identifying areas of the team that are underperforming or identifying new opportunities for growth or improvement. ⮚ Gathering data: Once the problem or opportunity has been identified, the manager then collects data that is relevant to the situation. This can include internal sales figures, customer feedback, or employee performance metrics. ⮚ Analyzing the data: With the data in hand, the manager needs to explore it to identify key patterns, trends, and insights that will inform their decision-making process. This can involve using statistical analysis, data visualization tools, or other techniques to help make sense of the data. ⮚ Developing alternatives: Based on the analysis, the manager develops multiple options or solutions to the problem. These may involve different strategies, tactics, or approaches to address the problem or take advantage of the opportunity. Zeal Group of Management Institutes ⮚ Evaluating alternatives: With the alternatives identified, the manager then evaluates the pros and cons of each option. This may involve using different tools to help compare the alternatives based on various criteria such as cost, feasibility, or potential impact. ⮚ Selecting the best solution: Based on the evaluation, the manager then selects the best solution or alternative to pursuing. This may involve selecting a single option or combining elements of multiple opportunities to create a customized solution. ⮚ Implementing the decision: Once the solution has been selected, the manager must implement it. This may involve developing an action plan, allocating resources, and communicating the plan to stakeholders. ⮚ Monitoring and evaluating: Finally, the manager needs to monitor the effectiveness of the decision and make adjustments as necessary. This may involve tracking key metrics, taking feedback from stakeholders, and improving the solution over time. Zeal Group of Management Institutes  characteristics of the analytical decision making process. 1. Data-Driven Fact-based: Decisions are based on data, facts, and empirical evidence rather than intuition or emotion. Quantitative analysis: Involves collecting, analyzing, and interpreting quantitative data to make informed decisions. 2. Systematic and Structured Step-by-step process: It follows a defined series of steps, such as identifying the problem, gathering data, analyzing options, and making a choice. Clear methodology: The process uses established frameworks or models (e.g., SWOT analysis, cost-benefit analysis, decision trees). Zeal Group of Management Institutes  Continued…. 3.Logical and Rational Objective: Strives to remove personal biases or emotions, focusing on logic and reason. Cause-and-effect: Analytical decision-making considers the cause-and- effect relationships between options and outcomes. 4. Problem-Focused Clear problem identification: The process begins with a precise understanding of the problem to be solved. Goal-oriented: Focuses on finding solutions that best address the specific problem or objective. Zeal Group of Management Institutes Continued…. 5. Evaluation of Alternatives Comparative analysis: Multiple alternatives are compared based on defined criteria (e.g., costs, benefits, risks). Weighted decision-making: Alternatives are often evaluated by assigning weights to criteria based on their importance. 6. Risk Assessment Risk vs. reward: Considers the risks associated with each alternative and weighs them against potential rewards. Uncertainty management: Attempts to reduce uncertainty through forecasting, simulations, or sensitivity analysis. Zeal Group of Management Institutes  Continued… 7. Time-Consuming Thorough analysis: It typically takes more time because it requires careful data gathering, analysis, and consideration of multiple factors. Detailed documentation: Each step in the process is often documented to ensure transparency and accountability. Zeal Group of Management Institutes  How to Breaking down a business problem into key questions that can be answered through analytics 1.Identify the Business Problem: Clearly define the problem or goal. For example, “Why are sales declining in the last quarter?” 2.Understand the Context: Gather background information about the problem. This includes understanding the business environment, market conditions, and internal processes. 3.Formulate Hypotheses: Develop potential explanations for the problem. For instance, “Sales are declining due to increased competition or changes in customer preferences.” ? Zeal Group of Management Institutes 4.Define Key Questions: Break down the problem into specific, answerable questions. For example: What are the trends in sales over the past year? How have customer demographics changed recently? What are the competitors’ strategies 5.Determine Data Requirements: Identify the data needed to answer these questions. This could include sales data, customer feedback, market analysis, etc. 6.Collect and Analyze Data: Gather the necessary data and use analytical tools to examine it. Look for patterns, correlations, and insights that address your key questions. 7.Interpret Results: Analyze the findings to understand the root causes of the problem. For example, you might find that a specific product line is underperforming or that a new competitor has entered the market. 8.Make Data-Driven Decisions: Use the insights gained from your analysis to make informed decisions. This could involve adjusting marketing strategies, improving product features, or targeting a different customer segment. Zeal Group of Management Institutes Characteristics of good questions: Good questions in business analytics are crucial for deriving meaningful insights and making informed decisions. 1.Clear and Specific: The question should be precise and unambiguous. For example, “What was the revenue growth rate in the last quarter?” is clearer than “How did we do last quarter?” 2.Relevant: The question should align with the business goals and objectives. It should address a specific problem or opportunity that the business is facing. 3.Actionable: The question should lead to insights that can drive action. For instance, “Which marketing channel has the highest ROI?” can help in reallocating marketing budgets effectively. 4.Measurable: The question should be framed in a way that it can be answered with data. For example, “What is the customer satisfaction score for our new product?” is measurable. Zeal Group of Management Institutes 5.Time-Bound: Including a time frame can help in understanding trends and making timely decisions. For example, “How has customer churn changed over the past six months?” 6.Contextual: The question should consider the context of the business environment, market conditions, and internal processes. For example, “How did the recent price change affect sales in our key markets?” 7.Comparative: Comparative questions can provide deeper insights by comparing different periods, segments, or metrics. For example, “How do our sales this quarter compare to the same quarter last year?” 8.Hypothesis-Driven: Good questions often stem from a hypothesis that can be tested. For example, “Is the decline in sales related to the recent changes in our product features? Zeal Group of Management Institutes Question:on above topic : Q1.)How can we break down the challenge of declining customer retention into key analytical questions, and what characteristics should these questions possess to ensure they lead to actionable insights? Q.2)In light of our recent data showing a decline in customer retention, how can we effectively break down this challenge into key analytical questions? What specific characteristics should these questions have to ensure they yield actionable insights that can help improve our retention strategy? Zeal Group of Management Institutes Skills of a good business analyst: A good business analyst (BA) requires a mix of technical, analytical, and interpersonal skills to effectively bridge the gap between business needs and technology solutions 1. Analytical Thinking and Problem Solving Critical thinking: Ability to analyze complex problems, break them down into smaller components, and evaluate possible solutions. Data interpretation: Skills in analyzing data, interpreting trends, and using insights to support business decisions. Root cause analysis: Identifying the underlying causes of business problems and inefficiencies. 2. Communication Skills Active listening: Understand stakeholder needs and concerns by listening effectively. Verbal communication: Articulate complex concepts in a clear and concise manner to both technical and non-technical stakeholders. Written communication: Document requirements, processes, and analysis clearly and professionally. Presentation skills: Effectively present findings, recommendations, and business cases to stakeholders. Zeal Group of Management Institutes  3. Stakeholder Management Collaboration: Ability to work with cross-functional teams including developers, managers, and customers. Expectation management: Set clear expectations, manage stakeholder needs, and address conflicts. Influencing and negotiation: Advocate for changes or solutions while considering stakeholder viewpoints and limitations. 4. Technical Skills Data analysis: Proficiency in tools like Excel, SQL, or other data analytics tools to extract and analyze data. Requirements gathering: Ability to document and define functional and technical requirements. Understanding of software development: Basic understanding of programming languages, databases, and software development methodologies (e.g., Agile, Scrum). Business intelligence tools: Familiarity with tools like Tableau, Power BI, or other reporting/visualization platforms. Zeal Group of Management Institutes 5.Business Knowledge Industry-specific knowledge: Understanding the industry, market, and competitive landscape in which the business operates. Business process improvement: Ability to analyze and improve business processes to increase efficiency and effectiveness. Financial acumen: Understanding of how business decisions affect financial outcomes, and ability to build financial models. 6. Problem-Solving and Innovation Creativity: Thinking outside the box to come up with innovative solutions to business challenges. Decision-making: Ability to weigh options and make decisions based on data, stakeholder input, and potential outcomes. Adaptability: Being flexible and willing to adapt approaches to changing business needs and environments. Zeal Group of Management Institutes  7.Project Management Skills Time management: Prioritizing tasks, managing time efficiently, and delivering results within deadlines. Task organization: Ability to break down projects into smaller tasks and track progress. Risk management: Identifying potential risks and developing mitigation strategies. 8. Documentation and Specification Writing Process documentation: Ability to map out current and future processes in detail. Requirements specification: Write clear and concise business and functional requirements, user stories, and use cases. Modeling techniques: Use modeling tools like UML diagrams, process flows, and wireframes to visualize and communicate requirements. 9. Attention to Detail Accuracy: Ensuring all analyses and documentation are precise, as small errors can lead to significant consequences. Thoroughness: Carefully considering all aspects of a problem or solution to ensure nothing is overlooked. Zeal Group of Management Institutes  10. Negotiation and Conflict Resolution Mediation skills: Ability to mediate between stakeholders with differing priorities or views to arrive at a solution. Balancing stakeholder needs: Finding a compromise between business goals, technical limitations, and stakeholder interests. 11. Leadership and Teamwork Influence without authority: Lead initiatives and drive change without having formal authority over team members. Collaboration: Work effectively with teams across different departments and functions to achieve common goals. Zeal Group of Management Institutes  The Basic Tools of Business Analytics - Data exploration and visualization The tools that business analysts include statistical tools. It combine the quantitative and qualitative data from different business systems and incorporate them into a repository. These business analytics applications are packed with powerful features and facilitate efficient data collection, analysis, and presentation in real-time. They also provide businesses with a holistic overview of key insights that improve efficiency, productivity, and profitability. Zeal Group of Management Institutes  Data Visualization tools Zeal Group of Management Institutes  Tools Used For data exploration and visualization 1. Excel: ⮚ Excel is still the most versatile tool used for business analytics. It is one of the cheapest, most accessible, and easiest to use. ⮚ With powerful features like form creation, PivotTable, VBA( Visual Basic for Applications), etc, it can work with small as well as large amounts of data. ⮚ Excel is one of the easiest tools to pick up, you will even find professionals from any background excelling in Excel. ⮚ A row limit of 1,048,576 rows and a column limit of 16,384 columns. Zeal Group of Management Institutes  ⮚ Microsoft Excel is a software application designed for creating tables to input and organize data. ⮚ It provides a user-friendly way to analyze and work with data. ⮚ The image below provides a visual representation of what an Excel spreadsheet typically appears like Zeal Group of Management Institutes What is a Cell A spreadsheet takes the shape of a table, consisting of rows and columns. A cell is created at the intersection point where rows and columns meet, forming a rectangular box. Zeal Group of Management Institutes The address or name of a cell or a range of cells is known as Cell reference. It helps the software to identify the cell from where the data/value is to be used in the formula. We can reference the cell of other worksheets and also of other programs. Zeal Group of Management Institutes 2.Statistical Analysis System (SAS) is a software suite that has been developed by SAS Institute, one of the leaders in analytics. It is useful for performing advanced analytics, multivariate analyses, business intelligence, data management functions, and also for conducting predictive analytics. SAS programming workflow: SAS programming applications are characterized by the flow control specified in the below diagram Zeal Group of Management Institutes  3.Microsoft Power BI: Power BI is a Data Visualization and Business Intelligence tool by Microsoft that converts data from different data sources to create various business intelligence reports. It provides interactive visualizations using which end users can create reports and interactive dashboards by themselves. Navigating Power BI: Power BI provides a plethora of various tool and services to make creative, interactive and intelligent Business Reports. Zeal Group of Management Institutes  On following the above steps, the dataset will be uploaded and a window will pop up. This window is called the Query Editor What is Query Editor? Query Editor in Power BI is used to edit or format the data files before they are loaded into the Power BI Model. The Query Editor plays the role of an intermediate data container where you can modify data type or the way the data is stored by selecting the particular rows and columns. Views in Power BI There are 3 different types of views in Power BI. You can switch between the 3 views using Navigation Pane. Zeal Group of Management Institutes Zeal Group of Management Institutes Report View: Report view is a section of Power-BI where you can create any number of report pages with visualizations. This view provides a designing environment where you can move visualizations around, copy and paste, merge, and so on. You can add one/multiple pages here for various visualization of BI-Reports. Data View: Data view is a section of Power-BI that helps you inspect, explore, and understand data. It’s different from how you view tables, columns, and data in Power Query Editor. With Data view, you’re looking at your data after it has been loaded into the model. Relationship View (Model View): Model view shows all of the tables, columns, and relationships in your model. This view can be especially helpful when your model has complex relationships between many tables. Zeal Group of Management Institutes  Various tools and panels in Power-BI Zeal Group of Management Institutes  The Power-BI provides various tools and services:Modelling Ribbon: You can perform various functionalities using this panel. Upload datasets. Make calculations. Edit data types. Format data category for a column. Insert visualizations. Fields list: This list contains elements of your uploaded dataset. You can select a table or column to view in the data grid. Navigation Pane: This panel controls the different views of Power BI (Report/Data/Model). Visualization Pane: There are many different types of visualizations in Power- BI that help depict your report in various ways. This panel provides over 30 visualizations.Few important visualizations are listed below. Zeal Group of Management Institutes  Stacked 1 Bar/Column 6 Tree Maps Charts Clustered Tables and 2 Bar/Column 7 Matrix Charts Line/Area 3 Charts 8 Pie Charts 4 Ribbon Charts 9 Python-Scripts 5 Waterfall Charts 10 R-Scripts Zeal Group of Management Institutes Building Blocks of Power-BI: There are 4 major building blocks that make Power-BI a very powerful tool. Zeal Group of Management Institutes  4. Tableau ⮚ Tableau is another powerful Analytics tool that can connect to any data source and create customizable data visualizations, maps, and dashboards. ⮚ Its powerful data discovery and data-cleaning function allow users to perform analytical functions in seconds. ⮚ It is easy to learn, robust, and does not include any complex scripting. ⮚ Tableau’s statistical functions help users to perform in-depth analyses and predict patterns based on current and historical data. ⮚ Tableau is very famous as it can take in data and produce the required data visualization output in a very short time. ⮚ Tableau also allows you to prepare, clean, and format data of all types and ranges and then create data visualizations to obtain actionable insights that can be shared with other users. Zeal Group of Management Institutes  Products Offered by Tableau 1. Tableau Desktop Tableau Desktop is a desktop application that is the fundamental offering of Tableau. You can use Tableau Desktop to create interactive data visualizations, perform unlimited data exploration, create charts and dashboards from the data, etc. It also allows connections to the data on the cloud or in local memory, whether the data is an SQL database, spreadsheet data, big data, or data on Google Analytics, Sales force, etc. You can get Tableau Desktop as a part of the Tableau Creator package for 70 USD per month with a free trial of 14 days. 2. Tableau Public Tableau Public is a free software provided by Tableau. It is used to create data visualizations and data charts that can be embedded into blogs, web pages, etc. or transferred using social media. You can create visualizations in Tableau Public using the Tableau Desktop Public Edition. However, the downside of Tableau Public is that the data visualizations created here are accessible by everyone on the internet and cannot be saved privately. So this product is best for students who are still learning Tableau, hobbyists, journalists, bloggers, etc. who are fine with creating public data visualizations. Zeal Group of Management Institutes Tableau Online Tableau Online can be used to create data visualizations, storyboards, data charts, etc. that are fully hosted on the cloud and not on local servers. You can create your visualizations and share them with other people online using a web browser or the Tableau mobile app. There is no need to worry about software upgrades or hardware scaling or server configuration while using Tableau Online as it is a totally online hosted service. So you can set up Tableau Online in minutes and start reaping the benefits as a single user or company. You can get this service as a part of the Tableau Creator package for 70 USD per month with a free trial of 14 days. 4. Tableau Server Tableau Server is a server product for your organization that needs to be installed on a Windows or Linux server. This is widely used in the industrial domain with many IT companies installing Tableau Server to create interactive data visualizations, perform unlimited data exploration, create charts and dashboards from the data, etc. while being sure that their data is safe and secure. Tableau Server can integrate with existing security protocols in companies such as Kerberos, Active Directory, OAuth, etc. to ensure data security while also providing data insights. You can get this service as a part of the Zeal Group of Management Institutes  Domo Domo is a complete cloud-based business analytics platform that integrates multiple data sources and provides wide connector support. It is easy to use and offers micro and macro-level visibility and helps users see real-time data. It is often used by both small and large-scale companies. Domo is designed to assist businesses in finding effective solutions and taking informed actions from the insights gained. You can combine cards, text, and images in the Domo dashboard so that you can guide other people through the data while telling a data story as they go. Zeal Group of Management Institutes Concept of Statistical Analysis and Hypothesis Testing Statistical Analysis refers to the process of collecting, organizing, interpreting, and presenting data to uncover underlying patterns, trends, or relationships. It is used to make data-driven decisions in various fields such as business, healthcare, social sciences, etc. There are two main types of statistical analysis: 1. Descriptive Statistics: This involves summarizing or describing the main features of a dataset. It includes: ○ Measures of central tendency (mean, median, mode) ○ Measures of dispersion (range, variance, standard deviation) ○ Graphical representations (charts, graphs, histograms) 2. Inferential Statistics: This involves making inferences or predictions about a population based on a sample of data. It often includes: ○ Hypothesis testing ○ Confidence intervals ○ Regression analysis Zeal Group of Management Institutes Hypothesis Testing Hypothesis testing is a method used in inferential statistics to determine whether there is enough evidence in a sample of data to infer that a certain condition is true for the entire population. 1. Formulating Hypotheses: ○ Null Hypothesis (H₀): It assumes that there is no effect or no difference, and any observed differences are due to random chance. Example: "There is no significant difference between the average test scores of two groups." ○ Alternative Hypothesis (H₁): It is the opposite of the null hypothesis and suggests that there is a significant effect or difference. Example: "There is a significant difference between the average test scores of two groups." 2. Test Statistics: A test statistic is calculated from the sample data. Examples include t-statistic, z-statistic, and chi-square statistic. The choice of the test depends on the type of data and the hypothesis being tested. 3. P-value: The P-value indicates the probability of observing the test statistic, or one more extreme, assuming the null hypothesis is true. A small P-value (typically less than 0.05) suggests that the null hypothesis can be rejected, meaning the evidence supports the alternative hypothesis. Zeal Group of Management Institutes  1. Decision: ○ If the P-value is less than the significance level (α, often 0.05), reject the null hypothesis. ○ If the P-value is greater than the significance level, fail to reject the null hypothesis (meaning there is not enough evidence to support the alternative hypothesis). Basics Terms in Hypothesis Testing 2. Significance Level (α): The threshold for determining whether the P-value is low enough to reject the null hypothesis. Common values are 0.05 or 0.01. 3. Type I Error (False Positive): Rejecting the null hypothesis when it is actually true. 4. Type II Error (False Negative): Failing to reject the null hypothesis when it is actually false. 5. Power of the Test: The probability of correctly rejecting a false null hypothesis. It is related to the sample size and effect size. Zeal Group of Management Institutes  Data Visualization: Concept of Data Visualization, Popular Data Visualization tools, Exploratory Data Analysis(EDA), Data Cleaning, Data Inspection. Concept of Data Visualization Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data. The key aspects include: Purpose: The primary purpose is to communicate information clearly and efficiently to users. It helps in making complex data more understandable and enables quick insights. Benefits: ○ Enhances data comprehension. ○ Facilitates pattern recognition and trend analysis. ○ Supports decision-making by providing visual insights. ○ Engages audiences effectively through visual storytelling. Zeal Group of Management Institutes Popular Data Visualization Tools Several tools are widely used in the industry for data visualization, each offering unique features and capabilities: Tableau: A powerful and widely used tool for creating interactive and shareable dashboards. It connects to various data sources and provides a drag-and-drop interface for visualization. Power BI: Developed by Microsoft, this tool integrates seamlessly with other Microsoft products. It allows users to create reports and dashboards with ease. D3.js: A JavaScript library for producing dynamic and interactive data visualizations in web browsers. It provides flexibility but requires knowledge of programming. Matplotlib and Seaborn: Libraries in Python used for static, animated, and interactive visualizations. Seaborn is built on top of Matplotlib and provides a higher-level interface for drawing attractive statistical graphics. Google Data Studio: A free tool that turns your data into informative, easy-to-read, easy- to-share, and fully customizable dashboards and reports. QlikView/Qlik Sense: Business intelligence tools for data visualization and dashboard creation, known for their associative data modeling and intuitive user interfaces. Zeal Group of Management Institutes Exploratory Data Analysis (EDA) EDA is a critical step in data analysis, focusing on summarizing the main characteristics of a dataset, often using visual methods. Key components include: Descriptive Statistics: Calculate measures like mean, median, mode, standard deviation, and variance to summarize data. Visual Techniques: ○ Histograms: To understand the distribution of numerical data. ○ Box Plots: To identify outliers and visualize the spread of data. ○ Scatter Plots: To observe relationships between two continuous variables. ○ Correlation Matrices: To see relationships between multiple variables. Purpose: EDA helps in detecting patterns, spotting anomalies, testing hypotheses, and checking assumptions before applying more formal statistical analyses. Zeal Group of Management Institutes Data Cleaning Data cleaning, or data scrubbing, is the process of correcting or removing inaccurate records from a dataset. Essential steps include: Handling Missing Values: Identifying and addressing missing data through imputation, deletion, or leaving them as-is depending on the analysis. Removing Duplicates: Identifying and eliminating duplicate records to ensure data integrity. Correcting Inaccuracies: Fixing errors in data entry, such as typos or incorrect values. Standardizing Data: Ensuring consistent formatting (e.g., date formats, currency symbols) across the dataset for uniformity. Zeal Group of Management Institutes Data Inspection Data inspection involves examining the data to understand its structure, quality, and relevance. It includes: Initial Review: Looking at the dataset to get a sense of its size, structure, and types of data present. Data Profiling: Analyzing the dataset to summarize its characteristics (e.g., distributions, uniqueness of values, data types). Validation Checks: Ensuring that the data meets specific criteria or standards before analysis (e.g., checking ranges, categories, and data types). Visualization: Using simple visualizations to inspect data distributions and identify anomalies or trends that warrant further investigation. Zeal Group of Management Institutes  Thank You Zeal Group of Management Institutes