You’re about to start a new project. What are some common forecasting mistakes you should avoid?

Primeiro ponto é deixar de verificar os possíveis riscos de compliance com a área especializada e com a Diretoria Jurídica. Segundo é n?o aproveitar o conhecimento das área de Auditoria Interna e Controles Internos (onde existe obviamente) que já podem ter participado de vários outros projetos anteriores.

There are a lot of unknowns that might change the final product of a project, therefore making predictions based on historical data is a huge mistake. While reviewing past results might provide some insight, it doesn't take into consideration the fact that market conditions, consumer demands, technical complexity, and team chemistry are all adaptive. You may avoid making this error by regularly verifying your assumptions with relevant, current data. Constantly revising forecasts in light of new information ensures their accuracy and adaptability. Using real-time data, a future-focused approach may improve projections and shield against the limitations of previous trends.

Most forecasts mistakes are statistical like mean percentage error, root mean squared error, mean absolute percentage error, mean squared error A quantitative forecast that is based on historical data can be skewed if the data is insufficient or bad.

Some common forecasting mistakes to avoid include underestimating costs, neglecting to account for unexpected expenses, and relying too heavily on historical data without considering current market conditions.

The biggest issue with historical data is that because it is verifiable we rely on it more than other information. Other forms of information such as market conditions, customer demands, and technical challenges are themselves forecast. The available information limits their reliability. However, they can get us thinking in the what-if frame to discourage. Same-As-Last-Year thinking.

A critical forecasting mistake is neglecting external effects in favor of internal project criteria like scope, budget, and timetable. Ignoring competitors, regulations, economic trends, or environmental concerns might significantly change the outcomes. To stay away from this pitfall, constantly monitor the project's surroundings and do comprehensive risk assessments. Identify potential threats and opportunities to provide a clearer picture of what lies ahead. The project's preparedness and its ability to handle unforeseen challenges and opportunities are both enhanced when the significance of external dynamics is acknowledged.

Rapid shifts in consumer preferences, seasonal variations, and unpredictable market trends make it challenging to predict and adapt to changing demand accurately. Thus, A regular review is a must

It is easy to focus only on internal factors as those are what we can control. However, ignoring external factors makes it difficult to plan for and respond to those factors. This can limit our options as the period unfolds.

Disregarding external factors like market trends or regulations can undermine project forecasts. Integrating external data enriches analysis, offering a broader perspective. Acknowledging these influences enhances forecast accuracy, enabling better decision-making and adaptability to challenges and opportunities in the project environment

Overconfidence or pessimism can lead to unrealistic forecasts. Ignoring an important element in forecasting can lead to erroneous projections and unrealistic forecasts. Maintaining objectivity and relying on evidence is crucial, as historical data can provide valuable insights. Combining approaches and comparing outcomes is recommended. Forecasts are unpredictable, so it's essential to account for external factors like economic circumstances, industry trends, and regulatory changes. Regularly revising forecasts to reflect new data and changing situations is crucial to avoiding becoming obsolete and erroneous.

Many people make the mistake of judging based on emotions or preconceptions. Too optimistic or pessimistic perceptions of the project's complexity and risks may overstate these elements. Thus, any implausible forecasts threaten dependability and efficiency. Objective methods like statistical models, expert opinions, and historical averages may reduce this inaccuracy. If we eliminated subjective aspects like liking and emotion, forecasts may be more accurate. An evidence-based approach with a cautious and hopeful mentality may help understand project challenges and make more accurate forecasts.

I way to prevent being overconfident or overly pessimistic is to be both. Forecast the pessimistic and the optimistic view. Compare these two forecasts and create the most likely forecast to present. This is time-consuming but advances in technology have made it doable.

Extremes of overconfidence or excessive pessimism can be detrimental. Overconfidence may lead to underestimating challenges and risks, potentially setting unrealistic expectations. Conversely, excessive pessimism can breed reluctance to take necessary risks and seize opportunities. Striking a balance between optimism and caution promotes a realistic assessment of the project's potential, fostering innovation while ensuring prudent risk management. This balanced perspective encourages adaptability, resilience, and a greater likelihood of project success.

Yes, i would say that the decision should be taken with a more realistic and rational approach rather than over ambitiousness.

Stakeholders bring diverse perspectives, expertise, and insights that enrich the project's planning and execution. Their involvement fosters buy-in, alignment, and a sense of ownership, which are vital for project success. Excluding stakeholders risks overlooking key considerations, leading to misunderstandings, resistance, and ultimately, project failure. Engaging stakeholders from the outset ensures their needs and expectations are addressed, enhancing collaboration, mitigating risks, and increasing the likelihood of achieving project objectives.

There is a greater chance of missing insights, creating unrealistic expectations, and inciting opposition or conflict in new project forecasts that do not involve stakeholders. It is essential to actively involve stakeholders, ask for their feedback, address their concerns, and make sure everyone is on the same page and invested in the forecasting process in order to avoid these mistakes. Teamwork becomes better, forecasts turn out to be more accurate, and interest in the project's goals increases.

Many people avoid involving stakeholders because they won't understand the process. This is a deficiency of the forecaster, not the stakeholder. They don't have to understand the process to pass on insights. The forecaster has to recognize the insights and incorporate them into the forecasts. Most of the insights will not be in a numeric formate which is also more difficult for many forecasters.

Access to accurate data along (along with a recorded audit trail of previous forecasting activities. Everything changes over time including channels, agent preferences and unplanned absences. Therefore it’s essential to stay on top of change and factor it into the forecast.

Not revising or updating your forecasts should have become an outdated concept in 2020. The Covid pandemic showed just how fast things can change. In order to keep the control features of budgets and forecasts we need to articulate what assumptions were used in the original budget or forecast and how they have developed and changed. We should also try to keep the bottom line as unchanged as possible.

Failure to apply lessons learned from previous forecasting errors puts project completion and progress at risk. Stagnation and the recurrence of errors due to inadequate error analysis can damage project results and stakeholder trust. The effect of lost chances for advancement is another factor to consider. Maintaining a competitive edge and improving your forecasting methods for long-term success can be achieved through conducting post-mortem reviews, investigating anomalies, identifying their sources, and implementing solutions.

It's also highly important to consider the uncertainty behind those forecasts. "100 +/- 2" does not equal "100 +/- 50"... Yet both are forecasts of 100. Forecasts can give the false impression that the future is known in advance. Forecasts provides insights and clues. But of course, the future remains unwritten yet. Although black swans could not be forecasted, "usual uncertainty" surrounding the demand could be expressed. Where most make the assumption that the uncertainty is normally distributed, it's important to note that it's actually almost never the case ! Probabilistic forecasting is the best answer to generating forecasts that fully describe possible scenarios.

-Rigid Forecasting Models: Using overly rigid forecasting models that do not adapt to changing circumstances can lead to inaccurate forecasts. Employ flexible forecasting techniques that can accommodate evolving project dynamics. -Ignoring Feedback Loops: Neglecting to incorporate feedback loops from actual performance data can result in forecasts that are disconnected from reality. Continuously monitor and adjust forecasts based on real-time feedback to improve accuracy over time.