Time series forecasting is a powerful set of tools ranging from simple series forecasting to sophisticated causal modeling. So why are many FP&A professionals reluctant to take advantage of these methods? Today’s automated time series forecasting software is very accessible to financial and business analysts and can be leveraged to augment your planning process, drive market understanding, and improve your forecasts.

Time Series Forecasting Software Can Automatically Identify Seasonality in Your FP&A Data

Most businesses experience demand that is significantly driven by seasonality. This seasonality can be used to not only explain trends, but also to improve forecast accuracy. Examples of seasonality drivers include:

  • Holidays
  • Customer Buying Patterns
  • Subscription Renewals
  • Weather Changes

Seasonality usually occurs at monthly, weekly, daily, or even hourly time intervals. However, detecting and incorporating seasonality into a forecast using spreadsheets can be difficult and certainly time-consuming. The good news is that time series software can automatically detect and incorporate seasonality into your forecasts.time series forecasting

Visualization of Multiple Trends and Events Can Help Explain What Is Driving Your Business Results.

Many FP&A teams incorporate non-financial market or competitive market time series data into their spreadsheet analyses. These time series can come from internal sources such as marketing spend or from external data sources such as competitive activity or market share data. Time series software allows FP&A professionals to incorporate all relevant data into a single powerful visualization to help understand what is happening in the market. More importantly, if these other data series have predictive power, they can be incorporated into more accurate FP&A forecasts.

Baseline Forecasts: Augmenting Your Existing FP&A Forecasting and Planning Process.

This is the most important. An FP&A team typically spends years developing their own custom planning and forecasting process. This process is usually very time consuming and involves many highly-experienced individuals who know the business and product categories. This expertise is critical to the planning process and time series forecasting should not be used to replace this process. Instead, time series forecasting is often best utilized to produce initial baseline forecasts which can then be tweaked by Finance and category experts. Then, after the initial forecasts have been completed, time series forecasting software can then be used to easily re-forecast once new data or changes to the business take place. Another key benefit of time series forecasting!

Contact eCapital to discuss how time series forecasting software can help improve your FP&A forecasts and reduce the time required to complete them.

Chris Engstrom

Chris has spent over 25 years building analytics and data science solutions in the areas of Tech and Med Tech. His passion for technology, new ideas and business value-driven solutions brought him to eCapital Advisors where he currently leads the Advanced Analytics and Machine Learning consulting practice.

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