Hi, everyone. As we previously discussed, forecasting is the process of making informed estimates of future performance using historical data, trends, evaluations of strategic choices, and assessed impacts of macro-economic events. Throughout this video, we'll review the forecast process and key considerations when building a future outlook. The forecasting process begins with a retrospective analysis or look back at past financial results to see if there's a trend that will likely continue in the future. And we previously learned, sometimes, before using past financial results, you may need to remove the noise in the numbers or one-time and unusual items that are not considered a part of the core ongoing operating results of the business. As a starting point, you want to make the appropriate non-GAAP adjustments so that your trend is reflective of the ongoing operating results of the business. There are several items that frequently appear in a company's financial statements that may need to be adjusted out as one-time or unusual. Items such as restructuring expenses, litigation expenses, discontinued operations, gains and losses on asset dispositions and impairments, unusual income tax expense or benefit items, and acquisitions and divestitures. You want to make sure that the historical financial results provide a consistent and comparable baseline to serve as a starting point for your forecast. As we go through the forecasting process, including adjusting historical financial statement for one-time and unusual items, there are two important things to keep in mind. Number one, consistency is critical. As you build your forecast model, ensure that the forecast assumptions you develop are well documented and consistent. For example, if you project an increase in revenue due to a new product introduction, you must be consistent throughout your forecasted income statement by including all items that typically go with a product launch, such as advertising, research and development, trade promotion, etc. Consistency with your assumptions will be a big determining factor in the accuracy of the forecast you develop. And number two, level of precision. Keep in mind that the one thing I can guarantee about a forecast is that it will not be 100% accurate. Oftentimes, you're dealing with multiple variables, large numbers, and significant complexity. As such, more detail will not usually lead to higher accuracy. In fact, the opposite is usually true. My advice is to focus on what matters, and prioritize key drivers. For example, it energizer, we had over 3000 SKUs of different battery packs and different battery sizes. We could have spent a lot of time forecasting all 3000 SKUs to develop a revenue estimate. However, the top 100 SKUs represented over 75% of the total revenue for the company. As such, we prioritized forecasting the top customers and top SKUs when developing our income statement projections, and simply using a trend-based approach for the other 2900 items. This is a good example of the need to focus on what matters. Again, my advice is to not fall in the trap of believing the more detail, the better. Oftentimes, taking a simplified approach will yield a greater level of accuracy. To recap the forecasting process. First, begin with pulling historical financial results from a company's 10k filing. Next, remove one-time or unusual items so that you're able to analyze core ongoing operational results and trends. Third, as you develop your forecast assumptions, ensure that you remain consistent throughout your modeling. And finally, identify the key drivers, and determine the level of detail necessary to build your forecast. Oftentimes, less is more.
