La única guía de previsión de ventas que necesita para dominar el arte de la previsibilidad

 Sales forecasting, in simple terms, is the process of revenue estimation by predicting how much a sales unit can sell a product or service in the upcoming week, month, quarter, or year.

When it comes to one of the most important numbers to a business, the sales forecast sits at the top dictating other variables related to marketing, hiring, prospecting, and even product development. 

Accurate sales forecasting is both an art and a science, and getting it right is a tough task even seasoned salespeople struggle with as Gartner reports only 45% of sales leaders have high confidence in forecasting the accuracy of their organization. So, what goes into sales forecasting, and why is it tricky? This article explores. 

¿Qué es la previsión de ventas? 

When businesses produce a sales forecast, they estimate the figure of what they expect the sales revenue to look like. It estimates how much of the product or service they can sell in a period of time, such as a month, quarter, or year.  

Some of the best sales forecasts can predict revenue with a good degree of accuracy depending on the inputs and the time frame of the prediction. 

Similar to how minimum advertised price tracking allows companies to keep a finger on the pulse and adjust to changes in the market, an accurate sales forecast provides valuable insights because it is based on historical data. 

Sales forecasts are generally made using data from previous performances, and the sales forecasting techniques differ based on the inputs. For example, the forecast might be made based on the intuition of the sales rep or using data and trends fed into artificial intelligence.  

Sales forecasts made by sales reps are used by managers to estimate the business the team brings. Forecast data from teams are used by the directors to anticipate sales by the department and the VP of sales uses collective data from the departments to project organizational sales. 

Las previsiones de ventas responden a dos importantes cuestiones empresariales. 

• ¿Cuánto espera vender? 
• ¿Y en qué plazo? 

Cada oportunidad de venta tiene una cantidad proyectada como negocio potencial para la empresa y los equipos de ventas tienen que llegar a una cifra realista que represente el nuevo negocio y su marco temporal. 

Responder a estas dos preguntas ayuda a la organización a fijar objetivos y crear planes de estrategia de ventas. 

Why do we need sales forecasting? 

Las previsiones crean un punto de referencia para el futuro en el que las empresas pueden confiar para tomar importantes decisiones empresariales. Las previsiones precisas también establecen a las empresas como líderes del mercado y confieren credibilidad en el sector. Estas son algunas de las formas en que la previsión de ventas afecta al funcionamiento de una empresa: 

1. Toma de decisiones estratégicas 

Sales forecasting can reveal emerging trends and prompt decision-makers to rectify a problem or capitalize on a foreseeable opportunity. For example, a 30% negative deviation from the sales target might uncover poor management or underperforming sales units or even indicate competitors upping their game.  

On the other hand, a positive deviation would indicate the need to recruit more resources to capitalize on the opportunity. Forecasting sets the baseline, which aids in timely action and course correction. 

2. Trazar el camino a seguir 

La previsión resulta especialmente útil en épocas de bajo rendimiento. Permite a los responsables trazar líneas más claras y fijar mejores objetivos para reducir los daños e incluso motivar a los equipos mediante hitos y planes de acción. 

3. Toma de decisiones financieras 

Una previsión precisa de las ventas desempeña un papel crucial en diferentes ejercicios de modelización financiera. Determinan: 

• Inventario: Las previsiones de ventas precisas se realizan a través de suposiciones fundamentadas sobre los hábitos de compra de los consumidores o los aumentos o disminuciones estacionales de la demanda. Estas previsiones ayudan a planificar y gestionar el inventario, lo que contribuye a la utilización eficiente del capital circulante. Esta eficiencia se extiende luego a una mejor planificación y contratación de materias primas. 
• Cash Flows: Cash flows are directly affected by sales revenue. Accurate sales forecasting can help model cash movements that allow companies to plan for any shortfalls or windfalls in the future. 

¿Cómo es una buena previsión de ventas? 

A good sales forecast is highly accurate and easily understandable by different stakeholders. It is also well-balanced against time, effort, and the costs associated with the forecasting technique.  

Ideally, an accurate forecast model should be built with reliable economic methods. The forecast model should use an algorithm finely tuned to the business and pick relevant data with little manual intervention to make accurate predictions. 

However, realistic forecasts are more subjective and time-consuming. Other than the existing numbers, it becomes important to factor in the sales rep’s assessment of future performance.  

These perceptions can vary significantly from one sales rep to another, depending on their approach and experience.  

For example, a seasoned rep’s 50% sales estimate might be an understatement compared to a different rep’s 60% estimate, which might be overly optimistic. 

¿Quién se encarga de hacer las previsiones de ventas? 

Each organization has its own set of forecast owners depending on the type of business and the hierarchies. Typically, the people who make sales forecasts are: 

1. Sales reps: The people who do the actual selling know their customers and the target market. They are able to set reliable estimates for how much they can sell in a week or month, or quarter based on the market conditions. 
2. Sales Leaders: The sales leaders pick the numbers from their individual units and make an estimate for their higher-ups. The forecasts can vary based on their seniority - third-line managers, for example, typically consider a wider set of numbers and previous trends in close rates to come up with a forecast, while first-line managers consider opportunities to make their forecasts. 
3. Product Leaders: Product leaders base sales estimates on what product is available for selling and the time frame for its release. 

Sales forecast approaches 

Existen dos enfoques principales para la previsión de ventas: 

1. Enfoque descendente 

In the top-down approach, sales forecasting starts with the bigger picture and works downward to define the milestones needed to reach the target.  

With such a large estimation, there’s much scope for rushed and ill-defined judgments that can lead to unrealistic expectations. However, the approach is useful for quickly establishing optimistic organization-wide benchmarks in established companies. 

2. Enfoque ascendente 

The bottom-up approach is a conservative and granular approach that takes into account the resources held by the company. 

The bottom-up approach takes a practical look at the efficiency of the business and figures out the variables which can be tweaked to increase sales. This approach relies heavily on existing data to create a more structured and realistic perspective for sales forecasting purposes. 

Sales forecasting methods 

Los métodos de previsión de ventas pueden dividirse a grandes rasgos en cualitativos y cuantitativos. Los métodos cualitativos se basan en el juicio subjetivo de los representantes de ventas y los responsables de la toma de decisiones, mientras que los métodos cuantitativos se basan en datos, cifras y modelos estadísticos. 

1. Qualitative sales forecasting 

Qualitative sales forecasting often uses 5 major methods. These methods are based on informed opinions about the markets, trends, and prospects. The surveys involved are often time-consuming and expensive. The top 5 methods include: 

• The panel method or jury of executive opinion method: As the name suggests, the approach involves executive groups discussing sales predictions to reach a consensus. One of the main advantages of the method is that experienced members of the jury can bring in plenty of wisdom to the predictions. The same can also be a disadvantage as bad predictions can be made by dominant members of the jury with biased views. 
• Delphi method: The Delphi method is iterative in nature and involves surveying each expert independently. The output is then shown to the experts so their responses can be reconsidered in light of the broader consensus. The approach is an antidote to the groupthink that can dominate a jury approach. 
• Customer surveys: In this method, prospects or a sample of the customers are surveyed about their purchase plans in the short and long terms. For larger markets, various survey methods can be employed to determine a generic trend. 
• Sales force composite method: This method forecasts sales by pooling the collective numbers of forecasts of individual sales reps. These numbers are then reviewed by the heads and sales managers along with product owners to make distilled forecasts. While the approach has its merits, it also doesn’t take factors such as new trends, regulatory changes, and product innovation into the picture. 
• Scenario planning: Scenario planning is an all-encompassing approach that doesn’t come up with a single accepted forecast. Instead, it models different scenarios to let companies prepare for uncertain sales outcomes. This method is used for estimates sales over a long period of time, such as three years or more. Under scenario planning, variables such as recessions, disruptive technologies, changes in prices, and other things that affect sales are brainstormed. 

2. Quantitative sales forecasting 

La previsión cuantitativa de ventas utiliza datos y modelos estadísticos para predecir las ventas a diferentes escalas temporales. He aquí dos de los métodos más utilizados: 

• ‍Time series method: The approach works under the assumption that sales trends historically repeat over seasons and sales cycles. Hence it uses historical, chronologically ordered data to make sales forecasts. Future sales are calculated by historical sales multiplied by the growth rate. Some of the popular techniques include exponential smoothening, moving averages, ARIMA, and X11. 
• ‍Casual method: In this method, the historical cause and effect between sales and market variables are taken into account for forecasting. With the casual method all possible variables that can affect sales are modeled to make accurate forecasts for the future. The variables include factors such as customer sentiment, third-party surveys, macroeconomic trends, and internal sales results. Popular casual techniques include linear or multiple regression, leading indicators, and econometric approaches. 

Sales forecasting examples 

He aquí dos ejemplos de métodos cualitativos y cuantitativos de previsión de ventas: 

1. Método intuitivo (cualitativo) 

The intuitive method is the simplest of the qualitative methods for sales forecasting. The approach relies strongly on the performance and experience of sales reps in closing deals and their track record of matching up to expectations.  

The method is quite helpful if there’s no historical data to make a forecast for the month or quarter. Instead, the “intuition” or the “gut feeling” of the sales reps based on their initial contact with the prospect is used to determine how much sales can be done.  

2. Método histórico (cuantitativo) 

As discussed earlier, the historical method is an example of the time-series forecasting technique, which uses historical data to make future predictions.

To account for the variables such as growth, inflation, fluctuations in demand, and other variables, an estimated growth rate is multiplied by the historical sales to arrive at the future forecast.  

How to design a sales forecasting plan? 

La previsión de ventas requiere una sólida base de técnicas matemáticas y un conocimiento detallado del ciclo de ventas típico. Junto con los datos pertinentes, se pueden utilizar los siguientes pasos para diseñar un plan de previsión de ventas: 

1. Elección del método de previsión 

Los datos de ventas pasadas y los modelos de previsión son esenciales para construir nuevos modelos para el futuro. Para hacer previsiones fiables, se pueden utilizar varias técnicas de previsión de ventas más sencillas, como la previsión por etapas de oportunidad, la previsión histórica, la previsión por duración del ciclo, etc. Las previsiones de mayor precisión pueden hacerse con modelos que requieren más datos, como la regresión múltiple y la suavización exponencial. 

2. Determinación del calendario de previsiones 

El tipo de plan depende de si la previsión se realiza para un periodo de tiempo definido, como mensual o trimestral, o si el seguimiento de las ventas se realiza sólo para una producción concreta. Los factores estacionales, como un lanzamiento durante un trimestre concreto, también pueden afectar a la previsión. Por lo tanto, ese trimestre puede tener que considerarse de forma diferente. 

3. Desglose del ciclo de ventas 

La cronología de cada venta influye en la previsión de ventas. Desglosando el ciclo de ventas en función del tiempo medio dedicado a cada etapa, es posible determinar la duración media del ciclo de ventas. 

4. Utilizar las tendencias de las métricas de ventas 

Utilizando los datos históricos más recientes, pueden definirse variables como el precio medio de venta y el porcentaje de tasa de renovación para la nueva previsión. También deben incorporarse a la previsión otras variables como las tasas de conversión, los índices de rotación, la trayectoria media de crecimiento y los ingresos recurrentes anuales (ARR). 

5. Crear una plantilla de previsión 

Generate a template based on the sales cycle, objectives, metrics, and specifics of the sales teams. Smaller companies with limited resources can use a tool like Microsoft Excel when there are fewer products to track.

Larger organizations with automated tools that connect to the CRM can utilize the features of automation to make estimates. For instance, lead enrichment software can predict when a prospect is on the verge of conversion. This data can be used to make highly accurate forecasts for different sales cycles. 

6. Compartir los documentos formalizados con los equipos 

Es necesaria una documentación formalizada para compartir el plan con los equipos con total transparencia. Es esencial que los representantes de ventas entiendan cómo se hace la previsión, para que tengan un conocimiento sólido de sus objetivos y cuotas. 

How to accurately forecast sales? 

Una previsión de ventas precisa es un delicado equilibrio entre la incorporación de las tendencias históricas, los cambios internos, la fluctuación del mercado y la presión de la competencia. He aquí 5 pasos que conducen a la precisión en la predicción: 

1. Evaluación de la tendencia histórica 

Para sentar las bases de una previsión de ventas, es esencial crear un "índice de ejecución de ventas", que son las ventas previstas para el periodo de ventas. Los datos históricos del año anterior pueden separarse en función del precio, el producto, el representante de ventas, el periodo de ventas y otras variables para crear un índice de ejecución de ventas para la previsión. 

2. Incorporación de cambios 

El índice de ejecución de ventas debe modificarse en función de diversas variables, como la fijación de precios, la promoción, los canales, los clientes y los cambios de producto. Estas variables proporcionan un índice de ejecución de ventas más realista para el periodo de ventas. 

3. Anticipación de las tendencias del mercado 

Las tendencias del mercado, como los cambios en el comportamiento de la competencia, los cambios legislativos, las fusiones de empresas, etc., pueden lanzar una bola curva en los momentos más inesperados. Es esencial tener en cuenta estos cambios para crear modelos de previsión en caso de que se produzca un cambio de tendencia en el mercado. 

4. Seguimiento de la competencia 

Es imprescindible vigilar a la competencia para conocer su impacto en el mercado objetivo con acciones como la variación de precios, el lanzamiento de nuevas funciones o nuevas campañas. También hay que vigilar a la nueva competencia para conocer su impacto en la cuota de mercado. 

5. Incluidos los planes de negocio 

Business strategic plans that have an effect on growth, hiring, targeting new markets or kicking off new campaigns can all have an impact on future sales. Therefore, it is important to make forecasts while keeping sight of business plans. 

How Compass can help with sales forecasting 

Compass provides valuable tools—Simulation and Estimator—that enhance the accuracy and efficiency of sales forecasting by offering data-driven insights into commissions, performance, and potential earnings. Here’s how: 

1. Optimizing commission plans through simulation 

Compass allows admins to simulate different commission structures, adjusting rewards, milestones, and metric logic. This helps in evaluating how changes impact sales performance, leading to a more accurate sales forecast. 

2. Understanding earnings from pipeline opportunities 

The Estimator tool provides salespeople with insights into their potential earnings from pipeline deals. This visibility helps in sales forecasting, allowing teams to plan better and stay motivated to close deals. 

3. Enhancing revenue predictability 

By testing and refining commission strategies, businesses can improve their sales forecasting accuracy with Compass. Identifying trends and performance patterns ensures a more reliable sales forecast and supports data-driven decision-making. 

4. Driving performance with informed adjustments 

Sales leaders can use simulation insights to make informed adjustments to incentive plans. This not only improves team motivation but also strengthens sales forecasting, making it easier to set realistic sales targets. 

With Compass, you can fine-tune your commission plans, maximize sales performance, and achieve more accurate sales forecasting. Start using Compass to optimize your revenue strategy now! 

Principales retos de la previsión de ventas 

Elaborar previsiones precisas de forma sistemática puede ser todo un reto para las organizaciones. He aquí algunos de los principales obstáculos a los que se enfrenta la mayoría: 

1. Accuracy: Companies, especially startups who are bootstrapping tend to rely on spreadsheets for forecasting, which can introduce huge accuracy issues to the forecasts. Even companies with CRMs struggle with poor adoption across the company, with employees not entering data on time, data silos, incomplete data, and inaccuracies. 
2. Subjectivity of forecasts: While forecast quality does depend on good decisions and judgment when predictive analysis takes a backseat to the subjective analysis, it can miss real drivers of accuracy. 
3. Universality: Sales forecasts that are not useful for stakeholders across the company are ineffective in producing results. Good forecasts always have relevant and understandable data for different teams across the company. 
4. Inefficiency: Inefficiency can often make it into forecasts when there are multiple owners, varied inputs that remain unreconciled, and too many revisions and different versions. 

Previsión de ventas en tiempos impredecibles 

Tiempos impredecibles son acontecimientos como las grandes catástrofes, una crisis como la pandemia de COVID o una agitación económica repentina. Estos acontecimientos pueden dar la vuelta de repente a las previsiones de ventas. En cuanto se produce uno de estos acontecimientos, es importante que los directivos de las empresas sepan lo siguiente: 

• El estado actual de la cartera de ventas 
• El mejor y el peor escenario 
• ¿Cuánto ha cambiado la previsión durante la semana o el mes? 

A real-time view of the sales pipeline is critical in such situations to make an instant business decision that can minimize the damage from a disruptive event.  

The CRM solution and automation are what would cushion an inevitable blow to the forecasts. Reliable instantaneous data is what would help business leaders to pivot territories and resource deployment that can have a strong bearing on the continuity or dissolution of the business. 

Reflexiones finales 

Making an accurate sales forecast is both an art and a science that combines the well-developed intuition of an experienced salesperson and reliable data fed into forecasting algorithms.  

While it is essential that sales teams have the skills to make good forecasts relying on simple spreadsheets and back-of-the-napkin calculation methods, reliable forecasts need software solutions that can give real-time insights and projections based on data. Take Compass as an example.  

By testing and refining commission strategies, businesses can improve their sales forecasting accuracy. Identifying trends and performance patterns ensures a more reliable sales forecast and supports data-driven decision-making. Schedule a call to know more! 

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