You want to improve your forecasting skills. What’s the best way to start?

Forecast means projection & It will never be 100% accurate but to make it reliable it needs to be more closer to reality. To bring in closer to reality one needs to consider the following 1) Internal factors - organisation strength & weakness to deliver including the past trends, innovation & scalability 2) External factors - Market Trends, Economic conditions, resource availability & Industry performance 3) Customer insights - very critical as there may be some factors from their end that might affect or delay things 4) Thorough Risk Assessment - assess potential risks and challenges that could impact the projection. Add contingency accordingly.

One vital thing in forecasting is that all involved are on the same page. As you will be working with data from different departments you should make sure to communicate clearly with all involved parties what information you need and how you expect it to be presented (and WHEN!).

There is no silver bullet for forecasting, the best way is to look at the SKUs/product portfolio and bucket them by type of forecasting that will work best e.g. predictive, collaboarative or ML based. At the end of the day achieveing 100% accuracy is a mirage and business should have simulation/what-if models to deal with unforeseen events.

If you're seeking to improve your forecasting skills, keep the following pointers in mind: - Understand the fundamental concepts and techniques. - Refer to reliable resources for study purposes. - Practice with real-world data. - Experiment with different models. - Evaluate accuracy and seek feedback. - Learn from mistakes. - Stay updated with the latest trends. - Continuously practice to improve your skills. I believe these are the fundamental points to consider while attempting to enhance your forecasting abilities.

1) Proficiency in fundamental forecasting skills 2) Insight into stakeholder and company procedures 3) Choosing the appropriate tool, whether Excel or a system 4) Accurate identification and estimation of the activity drivers crucial for forecasting 5) Reviewing inputs by comparing planned figures with actual data 6) Seek feedback and update process

A tool is just an enabler, real value is to understand the demand management process in an organization. Demand management is how you oversee and manage customer demand. It involves understanding what your customers want, plus the necessary steps to fulfill those wants. This helps you plan for upcoming demand, and make sure you're in a place to meet it by proactively forecasting for it. Tools to forecast can be as simple as an excel forecasting model or more complicated AI models, what ever provides a decent starting accuracy coupled with forecast value add what a demand planner can deliver works best

Improving your forecasting skills requires laying a strong foundation in the basics. Without this understanding, mistakes are inevitable and performance suffers. Seminars, trainings, and courses are essential for honing your skills and gaining valuable experience. Additionally, practical application with real data using various forecasting tools is crucial. This hands-on approach not only enhances your skillset but also deepens your comprehension of the strengths and weaknesses inherent in different techniques.

Information is the true tool. One should possess hand in hand knowledge about the business for which the forecast is being prepared. Ask to get newer facts pop-up, identify opportunities, pointers where there could be risk, contingencies. The more the clarity easier it is to identify the risks and deviations that will need to tweak the numbers or update the forecast. Putting numbers into spreadsheets or using dashboards will only work well if the inputs provided is based on solid understanding of the business and how it has a monetary impact on the organisation.

You gotta know where do you need to get in terms of precision, sometimes basic tools as different types of “averages” should be very reliable. Although, is very important to master the tools: it’s easier to convince someone using models reulsting from a more complex tool as Machine Learning, but even easier to make mistakes if you do not master it.

I would strongly suggest before you look for “tools”, build your model in excel so you gain a better understanding of the numbers and their relations to one another. Understanding how certain data points impact the bigger picture is key to being a better forecaster. Once you have mastered the ability to see the forest through the trees and the trees through the forest, then look for software or an automation tool is assist you. These tools will NOT be an asset, until you have mastered the details.

You don’t “practice” with real data, you use it! You will never know where you are headed if you don’t know where you came from. Start by taking the last 24 months of performance to understand trends. Use those trends to be realistic about future performance. I find using monthly data to be more granular and therefore easier to forecast. Once you have your forecast built, save it but also make a copy. Use the copy to update your forecast with actual monthly data. The model should reforecast out the remaining months based upon the most recent inputs. Compare your working model with your static model monthly to determine variances and reasons.

There are many factors which one should take in mind while forecasting of a product 1) Organic Growth 2) Inorganic Growth 3) Penetration of the product 4) Economic factors 5)Natural calamity 6)New brand entry 7) Govt regulations

Practicar con datos y escenarios reales es clave para mejorar en pronóstico. Usar datos propios o en línea, junto con estudios de caso, refuerza el aprendizaje y revela tendencias. Es vital comparar nuestros resultados con benchmarks y analizar errores para ajustar estrategias. Compartir experiencias sobre el uso de datos reales puede enriquecer nuestro conocimiento colectivo. ¿Qué conjuntos de datos han sido útiles? ¿Cómo interpretan y aplican sus pronósticos? Esta colaboración fortalecerá nuestras habilidades de previsión.

In current wave of big data, it is important to understand what data streams are available to use for forecasting, it can be your historical shipment data, customer order data, POS data or external influencers like data from social media or even syndicate data which can show overlapping trends and populate a good statistical co-related forecasts with simple models. Key would be to identify & correct for outliers in your data even before you start your journey

Looking for actuals is the best way to assess what should be the correct number each month. We might have a different budget in the previous year, but actuals give us a sense of how higher or lower we should go for better accuracy.

Participar de fóruns, grupos de estudos direcionados, networking ativo facilita conhecer e tirar duvidas das novas ferramentas. A tecnologia facilita muito essa interação - utilize!

Forecasting always works 2-ways, so having continuous feedback, open to listen and act is very important for improving your reliable forecasting skills. Best ways for improving the forecasting skills are not just having professional meetings, but sometimes a small connects like corridor visits or coffee breaks with someone who can share on-ground intelligence and which directly or indirectly connect the dots for you to add better intelligence to your forecast report.

THe market & customer is king.We need real time data analysis & also keep check on WH stocks. Forecasting can be made with past data but the events can be registered by human intervention.

Rolling forecasts helps to keep up with trends and changes as the forecast is reviewed regularly to update the consumer behaviour, market trends, economic changes and new developments.

Acompanhar variáveis externas deve fazer parte das atividades rotineiras. Políticas cambiais, econômicas, politicas que influenciem em qualquer uma das variáveis que se utiliza na criação de projeções - deve ser entendida e refletida nas simulações.

Em meu trabalho busco aqui mesmo na plataforma Linkedin, notícias do mercado e opiniões públicas compartilhadas por CFO/COO e afins do segmento em que trabalho. Relatórios de consultorias especializadas são também uma excelente fonte de visão macro dos cenários.

One important ratio to analyze in forecasting is the Historical CAGR - 1Y/3Y/5Y to determine the growth rate which helps in forecasting.

Forecasting can sometimes feel like the elephant in the room even when you have done it countless times and have the skills to analyze the data/insights. 3 ways to help improve your forecasting are: 1. Courageous Mindset- Lean on the data and insights to help you find the patterns that will guide you but dare to see the things the data doesn’t always spell out. You can’t tell the future with certainty but you can predict with higher accuracy the path forward when you use data to influence your creativity. 2. Ask Questions- Forecasting should be collaborative. You should be asking other departments, your consumers/ clients, and your business leaders questions to help inform your projections. 3. Leave room for sudden market shifts!

Use a variety of data sources. When forecasting, it is important to use a variety of data sources in order to get the most accurate picture possible. This data can come from surveys, customer data, financial data, data gathered from social media, data gathered from sensors, and more. Use a variety of methods and models. There are many methods and models that can be used for forecasting, such as statistical methods, econometric methods, time series analysis, and machine learning. Each method has its own strengths and limitations, and it is important to choose the appropriate method for the problem at hand. You can also combine different methods and models to improve your forecasts.

In my experience, always help to collect as much data as possible by having conversations with team , colleagues about planned activities, challenges etc. such information will help to forecast better.

It's essential to consider broader factors such as understanding the industry landscape, staying updated on economic indicators etc... Additionally, nurturing soft skills like effective communication and collaboration can enhance your ability to interpret and communicate your forecasts effectively. Lastly, connecting with peers, mentors, and industry experts can provide invaluable insights and support as you navigate the world of forecasting. Embracing these broader considerations ensures a well-rounded approach to forecasting success!

The only thing for sure on forecasting is it will always be wrong. Even when you get the expected results, most of the time it happens in ways different than what was predicted.