How do forecasting errors impact your company's financial performance?

Overestimation of demand can lead to excess inventory, increasing storage costs and potential waste. Underestimation results in lost sales and insufficient stock. Budget misallocations due to inaccurate forecasts affect resource utilization and operational efficiency. Cash flow management becomes challenging, potentially requiring emergency funding or resulting in uninvested surpluses. Long-term strategic decisions based on faulty forecasts can misdirect investments, affecting profitability and market opportunities. Additionally, forecasting errors can harm supplier and customer relationships due to erratic ordering or failure to meet demand, and impact employee morale due to operational inefficiencies.

Some of the reasons for forecasting errors are lack of in depth knowledge on market, customer requirement, lack of knowledge on product fitment (right product for right market). Lack of competitor knowledge and of their product is another reason for errors.

It's very common to see revenues increasing without considering all that is going to be necessary to achieve it, such as more investments in marketing, staff, equipment... How much is it necessary to spend for each dollar increase in revenue?

One of the most common and easily avoidable error contributing to forecast error is lack of market knowledge. For example building numbers while ignoring the size of the market of category, specific flavor and pack. For example projecting growth % while in reality the total market size is not that huge. Proposing new product while ignoring the cannibalistic of the pack on existing products due to size, price, margin and consumer preference/trend

Os erros de previs?o resultam de desafios intrínsecos à modelagem e análise preditiva. A qualidade dos dados desempenha um papel crucial, pois informa??es imprecisas, desatualizadas ou incompletas comprometem a robustez do modelo. Suposi??es simplificadoras do modelo introduzem viés e podem n?o refletir a complexidade real do ambiente de negócios. O viés humano, influenciado por preferências e emo??es, contribui para decis?es falhas na configura??o do modelo. Fatores externos, como eventos imprevisíveis e mudan?as no mercado, representam desafios adicionais, enquanto o ruído aleatório reflete a variabilidade inerente a sistemas complexos.

Accurate forecasting is crucial for the success of any business. By avoiding errors in forecasting, companies can ensure efficient cash flow management, optimal budgeting and resource allocation, and maintain investor confidence. Accurate forecasting also enables businesses to improve operational efficiency, make strategic decisions that lead to growth opportunities, and maintain financial stability. By recognizing the importance of accurate forecasting, companies can stay ahead of the competition and confidently achieve their goals.

We can also add another 2 types of error, into the list. 3. Data-related errors- defined as inaccuracies/errors resulting from poor data quality, incomplete information and outdated datasets. 4. Volatility errors:- defined as unexpected fluctuations/errors resulting from underestimating market volatility.

Consequences are higher inventory leading to higher carrying cost, stress on working capital, or stock out position leading to loss of market share, higher debt/ over leveraging the balance sheet, loosing to the competition, eventually loosing business.

Consequences are missed revenue opportunity and increased cost, as underestimating sales demand can lead to stock-outs while overstating leads to excess inventory, and inaccurate supply forecasting will lead to delivery delays and inefficient inventory management. In some cases errors in forecasting also leads to inadequate resource allocation and misguided decision-making.

Accurate forecasting is utmost important, improper forecasting leads to high inventory level, block of working capital, heavy inventory carrying cost and also impacting on new product launches and the company ultimately ending up with customer dissatisfaction. It also has an impact on high ROCE.

Forecasting errors can have far-reaching consequences that can negatively impact decision-making processes. One of the most significant consequences of forecasting errors is that they can lead to inaccurate revenue forecasts. For instance, if the revenue driver is understated, the revenue forecast will also be understated. This can lead to a distorted financial picture and can impact the bottom line of the company. Moreover, when actual results appear favorable, the variance may show a significant gap favorably, leading to an erroneous interpretation of the financial situation. Therefore, it is crucial to ensure that the forecasting process is as accurate as possible to avoid any adverse impact on the organization.

Here are some common mistakes to avoid when forecasting : Ignoring historical data: Historical data is a valuable resource for forecasting. Ignoring it can lead to inaccurate predictions. Overlooking external factors: External factors such as economic conditions, market trends, and competition can have a significant impact on a company’s financial performance. Ignoring these factors can lead to inaccurate predictions. Failing to update forecasts: Forecasts should be updated regularly to reflect changes in the business environment. Failing to do so can lead to inaccurate predictions. Relying too heavily on a single forecast: Relying too heavily on a single forecast can lead to inaccurate predictions.

To enhance forecasting accuracy, we need to optimize the errors, and factors leading to it. Companies can use AI and ML for analytics for more accurate forecasting, regular check-in models implemented to update per changes in external and internal factors. Companies can adopt "Room for Error" approach, developing multiple scenarios to account for uncertainties and potential changes as compared to plan, and advance consideration of predictive errors.

I have always found it help to speak to stakeholders while preparing forecast figures, once you have the input from stakeholders you can build the figures after factoring in the financial and non financial aspects impacting the financials. It is always helpful for management if they can see 2 sets of scenarios one that is naked i.e. accounting for the on going trend of sales, product mix, maw material pricing and one which is a suggested one incorporating the realistic efficiency, productivity and mix management iniatives so that management can clearly see what is the size of the prize if these listed initiatives are taken.

The main way to identify errors is to compare actual with the forecasts and always look for the root cause of the error. Once identified, the error and the root cause must be discussed, so that the following steps can be taken: -Complete understanding of the error and the consequences -Communicating the error and consequences to stakeholders -Correction of the error in the root cause -Action plan to avoid repeating the error in the future

I found it helpful to improve the error analysis, especially with seasonal data; of course, after comparing the actual vs. forecast or plan is that especially with seasonal data, to deseasonalize it first and apply it to the index, then reseasonalize it. Afterward, apply the determination of coefficients to see the relationship of the data, and if the results are very close to 100%, the correlation proves the accuracy.