3.1 Overview-of-Forecasting-Process

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Overview of Forecasting Process
This presentation outlines the forecasting
process. Forecasting is crucial for business
success. We will explore the steps involved. This
helps in making informed decisions.
by Jitendra Tomar
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What is Forecasting and Why is it Important?
What is Forecasting?
Importance
Forecasting predicts future outcomes using data
analysis. It analyzes historical data, spots
trends, and estimates future events, applicable
to sales, demand, and finances. Accurate
forecasting helps organizations prepare for
changes and decide wisely.
Forecasting is key for resource allocation,
helping businesses use resources well. It
supports strategic planning by predicting market
conditions. It also aids decision-making,
offering a way to evaluate options and assess
risks, leading to better profits and a stronger
competitive edge.
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The Five Steps of the Forecasting Process
Define Purpose
Clearly define the forecast's objective,
including the timeframe, level of detail, and the
decisions it will inform. Understanding the
purpose ensures the forecast meets specific needs.
Gather Data
Collect and analyze historical data from relevant
sources, ensuring data accuracy and completeness.
Identify trends, patterns, and outliers to inform
the forecasting model.
Select Method
Choose an appropriate forecasting method based on
the data characteristics, forecast horizon, and
desired accuracy. Consider quantitative
techniques like time series analysis or
qualitative approaches such as expert opinions.
Evaluate
Assess forecast accuracy using appropriate
metrics like Mean Absolute Deviation (MAD) or
Root Mean Squared Error (RMSE). Refine the
forecast based on the evaluation results,
adjusting parameters or exploring alternative
methods.
Monitor
Track forecast performance continuously and
control variations by comparing actual outcomes
with predicted values. Update the forecast
regularly and adapt the forecasting process to
improve future accuracy.
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Step 1 Define the Purpose of the Forecast
Clarity
Scope
Impact
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Understand the forecast's specific goals,
ensuring that all stakeholders are aligned on
what the forecast aims to achieve. Define the key
performance indicators (KPIs) that the forecast
will target.
Determine the time horizon and granularity of the
forecast, specifying whether it's short-term,
mid-term, or long-term. Consider whether you need
daily, weekly, monthly, or quarterly data.
Identify the key decisions that will be
influenced by the forecast, such as resource
allocation, budgeting, and strategic planning.
Understand how the forecast will inform these
decisions and what actions will be taken based on
the results.
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Step 2 Gather and Analyze Historical Data
Collect Relevant Data
Analyze Trends and Patterns
Ensure Data Accuracy
Gather historical data points from various
sources to ensure a comprehensive dataset for
analysis. Include all relevant variables that may
impact the forecast.
Identify trends, patterns, and anomalies within
the historical data to understand underlying
drivers and potential future behaviors. Use
statistical methods to uncover significant
relationships.
Verify data accuracy and reliability by
cross-referencing sources and cleaning
inconsistencies. Implement quality control
measures to minimize errors and ensure the
integrity of the dataset.
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Step 3 Select and Apply a Forecasting Method
Qualitative Methods
Quantitative Methods
Use expert opinions and market research to gain
insights on trends and demand.
Apply time series analysis (ARIMA, exponential
smoothing) based on historical data. Use
regression models to find relationships and
improve accuracy.
Hybrid Approaches
Combine qualitative insights with quantitative
data. Integrate expert opinions with time series
analysis for refined accuracy.
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Step 4 Evaluate and Refine the Forecast
Bias
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Assess systematic over- or under-prediction
trends.
Accuracy
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Measure the degree to which the forecast aligns
with actual outcomes.
Error
Quantify the variability between forecast and
actuals.
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Evaluate the forecast using key metrics such as
accuracy, bias, and error. Refine models based on
performance insights derived from this
evaluation. Addressing these areas ensures higher
precision and reliability in future forecasts.
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Step 5 Monitor and Control the Forecast
Track
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Continuously monitor forecast performance against
actual results. Utilize key performance
indicators (KPIs) to track forecast accuracy and
identify deviations or discrepancies promptly.
Adjust
Adjust forecasting models based on observed
performance and changing conditions. Refine
parameters, incorporate new data, or switch
methodologies to better align predictions with
actual outcomes.
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Improve
Implement control measures to enhance forecast
accuracy and reliability. Regularly review and
update the forecasting process, incorporating
feedback and insights to drive continuous
improvement.
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By actively monitoring, adjusting, and improving,
organizations can ensure their forecasts remain
relevant, accurate, and effective in guiding
decision-making processes.