Forecasting & Estimation Techniques PDF 2024-2025

FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025 LAODENIO (TOPIC 1) IMPORTANCE OF FORECASTING IN MANAGERIAL DECISION-MAKING WHAT IS FORECAST...

FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025 LAODENIO (TOPIC 1) IMPORTANCE OF FORECASTING IN MANAGERIAL DECISION-MAKING WHAT IS FORECASTING? Forecasting is a process of predicting future conditions of the economy, trends, or outcomes based on historical data, current conditions and statistical analysis. “What will our sales next year?" “How much demand will there be for a product?” “What sources will we need in the future?” IMPORTANCE OF FORECASTING IN MANAGERIAL DECISION-MAKING 1. Better Planning: Managers can set realistic goals and allocate resources effectively. 2. Risk Reduction: Forecasting identifies potential challenges and opportunities, enabling managers to prepare for uncertainties like economic downturns or market changes. 3. Improved Decision-Making: Data-driven forecasts provide a foundation for making informed choices about investments, pricing, and expansion strategies. 4. Operational Efficiency: By predicting demand, companies can optimize inventory levels, avoid overproduction and reduce waste. 5. Strategic Advantage: Forecasting helps managers stay ahead of competitors by anticipating market trends and adapting strategies proactively. JIMENEZ (TOPIC 2) QUALITATIVE METHODS IN FORECASTING QUALITATIVE METHODS: - Is a process that employs professional judgment to forecast a company's financial future. By determining and evaluating the connection between current understanding of previous operations and possible future operations, skilled staff members carry out qualitative forecasting. This enables the experts to estimate a GROUP 3 BSA 1-2 1  FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025 company's potential future performance based on their own thoughts and data gathered from other sources, such as market research or staff surveys. - https://www.indeed.com/career-advice/career-development/qualitative- forecasting DELPHI METHOD: - A group of specialists is questioned one-on-one to get their thoughts. One way to avoid prejudice and make sure that any agreement regarding business forecasts comes from the expert viewpoints alone is to interview or collect data from the experts one at a time rather than in a group. After reviewing the experts' answers, other staff members ask follow-up questions until they arrive at a prognosis that makes sense for the business. - https://www.indeed.com/career-advice/career-development/qualitative- forecasting MARKET RESEARCH: - Market research evaluates the success of a company's services or products by introducing them to potential customers and recording details about how they react. Companies can conduct market research with the help of their own employees or by hiring outside agencies that specialize in market research activities. - Some ways to conduct market research include focus groups, consumer surveys, or blind product testing, where a customer tries a product without having heard of it before. Based on participant reactions, companies can decide which products or services to continue producing and which might need revision in the production stage. - https://www.indeed.com/career-advice/career-development/qualitative- forecasting SCENARIO ANALYSIS: - is the process of estimating the expected value of a portfolio after a given period of time, assuming specific changes in the values of the portfolio's securities or key factors take place, such as a change in the interest rate. - https://www.investopedia.com/terms/s/scenario_analysis.asp#:~:text=Investopedi a%20%2F%20Julie%20Bang PERCENTAGE OF ACCURACY (POA) The percentage of accuracy is used in forecasting to describe how closely values predicted fall within actual outcomes. It is frequently applied in various fields, for example, weather prediction, demand forecasting, and financial projections. GROUP 3 BSA 1-2 2  FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025 LAZARO (TOPIC 3) QUANTITATIVE FORECASTING METHOD It is a data based mathematical process that sales teams use to understand performance and predict future revenue based on the historical data and patterns.These results then give business to make decisions that ensure their continued success. Types of Quantitative Forecasting Methods 1. Naive Forecasting - a straightforward technique that assumes you will perform as you did last time. 2. Seasonal Forecasting - uses historical data to predict what same future season would look like 3. Revenue Run Rate - a financial performance indicator that converts a company's current revenue into an annual figure. 4. Historical Growth Rate - commonly used if there has been significant growth in business performance and you want to understand how big the change was. 5. Linear Regression - requires in-depth analysis to understand certain variables in your sales process that affect sales performance and forecast. TIME SERIES ANALYSIS Time series forecasting involves analyzing data that evolves over some period of time and then utilizing statistical models to make predictions about future patterns and trends. It takes into account the sequential nature of data where each observation is dependent on previous observations. ECONOMETRIC MODELS Econometrics uses statistical and mathematical models to develop economic theories, test hypotheses, and forecast future trends from historical data, comparing results against the tested theory. Econometrics was pioneered by Lawrence Klein, Ragnar Frisch, and Simon Kuznets. All three won the Nobel Prize in economics for their contributions KEY TAKEAWAYS  Econometrics uses statistical methods to develop theories, test hypotheses, and forecast future economic trends.  Techniques include regression models and null hypothesis testing. GROUP 3 BSA 1-2 3  FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025  Critics argue it prioritizes statistical models over economic reasoning. Commonly used econometric models Linear Regression Models: predicts a dependent variable using one or more independent variables, assuming a linear relationship between them. Time Series Models: analyze data collected over time to forecast future values and identify trends and cyclic patterns. Panel Data Models: These use data that combines cross-sectional and time- series dimensions, allowing more complex analysis and control for unobserved heterogeneity. Simultaneous Equations Models: These are used when there are interdependencies between the variables, requiring the estimation of multiple equations at once. REGRESSION ANALYSIS Regression analysis is a statistical method used to estimate relationships between dependent and independent variables, assessing their strength and modeling future relationships, particularly in complex data sets with nonlinear relationships. MACHON (TOPIC 4) COMBINED OR HYBRID APPROACH TO FORECASTING A hybrid or combined approach to forecasting combines multiple forecasting techniques to improve accuracy and reliability in predicting future market trends. By integrating both qualitative and quantitative methods, these approaches leverage the strengths of different models, allowing businesses to respond more effectively to market dynamics and uncertainties. Key Characteristics of a Hybrid Approach: 1. Diverse Methodologies: Combines qualitative and quantitative methods, statistical models, and machine learning techniques. 2. Flexibility and Adaptability: Adapts to different types of data (structured, unstructured) and timeframes (short-term, long-term). Adjust changing input and condition. 3. Improved Accuracy: Reduces the limitations of individual methods by averaging or selecting the best-performing forecasts. GROUP 3 BSA 1-2 4  FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025 HYBRID METHODS 1. Combination of Time-Series Models- Uses methods like ARIMA (Autoregressive Integrated Moving Average) and Exponential Smoothing together to capture both trend and seasonality. 2. Ensemble Methods- Aggregates outputs from multiple models (e.g., linear regression, random forests) by averaging or weighting their results.Often used in demand forecasting and financial predictions. 3. Qualitative + Quantitative Models- Combines expert judgment or market analysis with data-driven forecasting techniques. 4. Bayesian Hybrid Models- Integrates probabilistic reasoning (Bayesian methods) with deterministic models for uncertainty. ADVANTAGES  Improved forecast accuracy.  Flexibility to handle diverse data types.  Adaptability to dynamic market conditions.  Enhanced decision-making confidence. CHALLENGES OF HYBRID FORECASTING  Requires advanced expertise and resources.  Risk of overfitting or model complexity.  Need for consistent validation and monitoring The hybrid approach has a wide range application to different industries. The following are some of the industries that apply a hybrid approach. Business: Demand forecasting, sales predictions. Supply Chain: Inventory management, lead-time prediction. Weather: Combining physical models with statistical approaches. Healthcare: Patient flow predictions or outbreak modeling. When selecting a forecasting method, several factors should be considered to ensure the most appropriate technique is chosen for the specific situation. Some of the key factors to consider include: GROUP 3 BSA 1-2 5  FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025 Data Availability: The availability of historical data is crucial. Some methods, such as time series analysis, require a significant amount of past data to be effective. Accuracy Requirements: The level of accuracy required for the forecast will influence the choice of method. For instance, if high precision is essential, more complex methods like econometric modeling or machine learning may be necessary. Time Horizon: Different methods are suitable for short-term, medium-term, or long-term forecasts. The time horizon of the forecast will impact the choice of method. Data Patterns: Understanding the patterns present in the data, such as seasonality, trends, and irregular fluctuations, will guide the selection of an appropriate forecasting method. Resources and Expertise: The availability of resources, including computational power and expertise in specific methods, will influence the choice of forecasting technique. Cost and Time: Considerations regarding the cost and time required to implement a forecasting method are important, especially for businesses with limited resources. External Factors: External factors such as market conditions, technological advancements, and regulatory changes may also impact the choice of forecasting method. SUMMARY Hybrid forecasting is a powerful tool in managerial economics, enabling more accurate and comprehensive predictions. Combing methods bridges gaps in data interpretation and model capabilities. Managers can better navigate uncertainties and make informed decisions. REFFERENCES - https://www.investopedia.com/terms/f/forecasting.asp - https://www.mdpi.com/2079-9292/12/9/2019 - https://www.sciencedirect.com/science/article/abs/pii/0305048377900081 GROUP 3 BSA 1-2 6  FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025 JAVELLANA (TOPIC 5) CHOOSING THE RIGHT FORECASTING TECHNIQUE An appropriate forecasting method depends on many factors: the nature of the data, the time horizon, and the needs of an organization. It determines the accuracy and power required of the techniques and hence governs selection, as mentioned in a report by Harvard Business Review. Nature of Data The nature and quality of available data greatly influence the selection of the type of forecasting technique to be used. If you have a long history of data, quantitative methods such as time series or causal models are appropriate. However, when data are limited, one may resort to qualitative methods like the Delphi technique or marketing research. Time Horizon The time horizon of the forecasting technique also serves to play a vital role. Short-term forecasts(up to one year) usually focus on immediate trends and patterns hence based on time series analysis. Long-term forecasts (beyond one year) usually base their negotiations on causal models to account for the economic factors bringing a broad objective of the markets. Specific Needs of the Organization Think about which approach is better suited to the unique requirements of your organization. Market research might be the best solution if you need to make projections for demand for a newly released product. Time-series analysis is a better way to go if the more important thing is ensuring the optimal level of inventory based on historical sales information. GROUP 3 BSA 1-2 7  FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025 LAURENTE (PRINCIPLES 1-6) 12 EFFECTIVE PRINCIPLES OF FORECASTING 1. Be methodical: Consistent in following effective processes and proven systems using a systematic and repeatable approach that creates a space for enhancement and growth of the company. Application: Following this process makes the forecast reliable and effective for allocating budget for it is proven and commonly used. 2. Look back to look forward: Reviewing the past occurrences should be at least twice as far into the past to generate patterns in forecasting the future. - History as a basis of predicting the future and utilizing it for better projection of budget. Ex. This can be related to Incremental budgeting since incremental budgeting methods are based from the previous budget period and adjust it to conclude for the current budget. 3. Embrace Uncertainty: Since there is no exact or perfect forecast, the entity may face unexpected scenarios and sudden changes. The company should have contingency plans for the budget and learn to adapt from it. - “The only constant in this world is change” 4. Quantify your uncertainty where possible: Gather data and measure possibilities to maximize strategies and provide accurate information that are useful for decision making specifically in allocating budgets. Ex. A merchandise type of company is analyzing and estimating the price changes of a certain product from its performance in the market. It enables them to determine when to adjust their inputs to create more sales. 5. Be aware of wildcards: It is important to acknowledge possible uncertain scenarios or events that are unlikely to happen. Recognizing these factors mitigates the risk and increases comprehensive forecasting. 6. Greater accuracy is found in the aggregate: The credibility and accuracy of forecast is based on the outcome of a larger category or group rather than individual. It is also known as the law of large numbers. - Was also claimed as the heart of statistics for it yields reliable predictions. GROUP 3 BSA 1-2 8  FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025 TYPES OF KEY METHODS PROS CONS BUDGETING 1. Start with the User friendly; easy to Expending INCREMENTAL Prior Period’s understand & implement, unnecessary cost, BUDGETING Budget practical approach, Risk of Budgetary 2. Review Each Stability and Predictability, Slippage and lack Line Efficiency, Less of Innovation, (Department) Resistance, Focus on 3. Forecast Strategic Priorities. Revenue 4. Account for New Product Lines or Mixes 1. Identify every Competitive Edge in the Requires ACTIVITY activity associated market, helps view the Understanding BASED with a particular business as a single unit (complex), BUDGETING cost. and not in the form of resource 2. Calculate the departments., Elimination consumption, baseline of units of Bottlenecks - Helps to costly required for each function smoothly, implementation, activity. Improves relationship short term 3. Determine the between organization & budgeting cost per unit of customers. every activity and then multiply it by the number of times the activity will be performed. 1. Define your Aligns business and IT, The value can be VALUE audience. Increases business agility, difficult to quantify, PROPOSITION 2. Develop your Improves Customer time-consuming. BUDGETING value proposition Experience, Boosts ROI results are only as 3. Test your value good as the data, proposition constant 4. Implement your reassessment- value proposition ensuring the same delivery results of value. GROUP 3 BSA 1-2 9  FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025 1. Start from Efficiency, Accuracy, Resource ZERO BASED Scratch Better Cost Control, Intensive, Short- BUDGETING 2. Categorize Reduce Waste, Promotes Term Focus, Lack Expenses - List Optimization in Business of Expertise, It’s all the categories Process Management, Disruptive 3. Justify Every Stops Budget Creep, Expense- Improvement of interrogating Coordination every cost and Communication 4. Prioritize and Allocate 5. Monitor and Adapt: ZBB is an ongoing process. Regularly track your spending and adjust your plan as needed. JIMENA (PRINCIPLES 7-12) Subtitle: “Applying Forecasting Insights to the 50/30/20 Budget Rule” 7. Take Heed of the S Curve: Growth often follows an S-shaped curve: slow start, rapid growth, and leveling off. - The 50/30/20 rule may need adjustments during rapid income changes. 8. The Longer the Time, the More that Can Go Wrong: Longer-term predictions are less reliable due to increased uncertainty. - Regularly review your budget, even if using the 50/30/20 rule. 9. Look for the Oddballs: Pay attention to unusual data points that could indicate risks. - Fixed rules like 50/30/20 might overlook rare, significant expenses. 10. Hold Strong Views Weakly: Be open to changing your forecasts as new data emerges. GROUP 3 BSA 1-2 10  FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025 - The 50/30/20 rule allows for budget adjustments based on new financial information. 11. Combine Methods Independently: Using multiple forecasting methods gives a more reliable prediction. - Consider both qualitative and quantitative data when using the 50/30/20 rule. 12. Know When Not to Forecast: Avoid making detailed predictions in high uncertainty; prioritize flexibility. - The 50/30/20 rule may not apply well during financial instability. SUMMARY These principles help refine budgeting strategies, guiding when to use or adapt the 50/30/20 rule. Call to Action: Regularly review your financial situation and be ready to adjust your budget. What are pros and cons of the 50/30/20 budget for long-term saving? The 50/30/20 budget rule is an easy way to manage money by dividing it into 50% for needs, 30% for wants, and 20% for savings. It is simple to follow and helps people save for future goals while keeping spending balanced. However, the rule may not work for everyone. Some people might face unexpected costs, like medical bills, that the rule doesn’t account for. Others might find it hard to save 20%, especially if their income is low. While the rule is a good guide, it needs to be adjusted based on each person’s situation to make it truly effective. GROUP 3 BSA 1-2 11  FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025 LAZO (TOPIC 7) LIMITATIONS OF FORECASTING (FORECASTING VS BUDGETING) Forecasting Forecasting is the process of estimating future events based on historical data and current trends. It involves analyzing past patterns and making educated predictions about future outcomes. Limitations of Forecasting Unexpected events - such as natural disasters, economic crises, or political upheavals, can significantly impact forecasts. Data Quality and Availability - Accurate forecasting relies on quality data. Human Error - Forecasting models and techniques are developed and interpreted by humans, who are prone to biases and errors in judgment. This can lead to inaccurate forecasts. Complexity of Economic Systems - Economic systems are complex and interconnected, making it difficult to predict future trends with absolute certainty. Budgeting Budgeting is the process of creating a financial plan that outlines expected income and expenses over a specific period. It involves allocating funds to different activities and tracking actual spending against the budget. Forecasting vs Budgeting Forecasting Budgeting Focus Predicting future trends Allocating resources Time-Frame Short-term, medium-term, Typically short-term or or long-term: annual Purpose Purpose Inform decision- Plan financial activities making Output Forecasts of future events Financial plan with budgeted amounts GROUP 3 BSA 1-2 12  FORECASTING AND ESTIMATION TECHNIQUES ECO 9-32: ME S.Y 2024-2025 INFLUENCERS  JAVELLANA, ALLYZA BEA P.  JIMENA, JOHN JAMES P.  JIMENEZ, IRISH ALEXANDRIA D.  LAODENIO, JONA MARIE G.  LAURENTE, JOEBANN DALE D.  LAZARO, RAINIER M.  LAZO, CHARLENE ROSE S.  MACHON, JOANA GRACE G. GROUP 3 BSA 1-2 13