The ancients did it with oracles, tea leaves, and dreams. Thankfully, today’s forecasting has the potential to be much more reliable. However, bad projections still abound. Here are five reasons why your forecasting may be more of an optimistic oracle than an evidence-based projection.
1) Focusing On One Point
Business forecasting is similar to weather forecasting. Short-term probabilities are much more likely to be accurate than long-term predictions, but a healthy projection needs to look at multiple points in the distance. Many businesses lose track of their numbers by picking one point and focusing on it, to the exclusion of all else. This means that major economic weather events can creep up without warning.
2) A Lack Of Departmental Alignment
Companies prefer it when forecasts are neatly packaged. Having a uniform forecast that applies to all departments is the ideal. However, when using tools such as Excel this is very challenging to accomplish. A range of possibilities need to be considered for every department, and this can quickly become complex and chaotic. One solution is to use centralised software that can view the entire picture and create a coherent forecast.
3) Bias & Optimism
Optimism is a good thing. Without it, most ideas would never leave the page. However, it can also become a lead weight if bias clouds judgement. The business world does not help the situation: in a cut-throat environment, a good idea needs to be marketed with a smile that beams confidence. However, this confidence needs to be firmly grounded in cold facts rather than hopes and dreams. Using concrete numbers can help overcome biases and blind spots.
4) Getting Lost In The Patterns
There are multiple potential variables involved in any forecasting scenario. Therefore, examining past data can be a useful way to make future projections. However, things change. Changes can be subtle, such as a dent in the supply chain. Or, they can be significant, such as new legislation radically altering the playing field. Previous patterns can fall out of sync with reality, and an over-reliance on old data is a common reason for forecasting failure.
5) Human Error
Numerical inaccuracies happen on a daily basis. A missing zero here, a switched number there… maths can go haywire very rapidly with the simplest of mistakes. Hidden in the murky depths of spreadsheets, errors frequently go unnoticed. Failure is often put down to a misreading of the market, or poor planning and execution. In reality, a typo may just as easily be to blame. Comprehensive supply chain management software can keep a digital eye on numbers, and improve accuracy.
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