codleo consulting


Jan 24, 2024 10:07 AM

As all sales leaders know, it is expected of them to generate correct revenue predictions to guide them.  The question that confronts them is of accuracy & wholesomeness in the pipeline information. Plus, how can they make predictions against short and long-term revenue goals? Good forecasting is reliant on accurate & up-to-date data and a comprehension of past performance. Useful review depends on monitoring the right market factors, client requirements, and modifications on a large scale.  This is all academic talk unless the team and the management have a tech stack that can enable them to perform with the data at hand.

Below are the ways to obtain better business forecasting:

  1. The right employees should be involved and responsible. This way all concerned are equally responsible for accuracy in forecasting. People in different departments and roles are equally important in contributing to this process.   Anyone who is involved in creating opportunities can be involved in fuelling accuracy and enhancing the quality of the pipeline. Formulation of a consistent process provides the sales teams with the outline they require to keep predictions in real-time. Participation in forecasting ought to be linked to business objectives as well as individual performance so that all comprehend the value of their inputs.

  2. Identify important KPIs. A forecast can be qualitative if the pipeline it is based on is as well. To fuel the quality and correctness of opportunity data, sales leaders must identify the important metrics that are relevant to the company. It is crucial to regiment the stages of the sales funnel for the various sellers, so they all work with the same selection of exit criteria.

  3. Data quality is non – non-negotiable. There is no substitute for the same. If the data is clean and accurate it leads to accurate business forecasts. If it’s not, God help the company. Good quality data is useful when used to engine predictive models & analytics to turbocharge the process. Using a revenue intelligence solution, companies can find opportunities or renewals that are shaky, locate high-growth accounts, and drive reliable revenue growth so that the sales team can sell more efficiently.

  4. Pilot revenue prediction decisions with data-led visibility.  Ignite the company’s data culture by motivating the staff to utilise data to validate their decisions. With predictive analytics & Artificial Intelligence capabilities, companies can empower the sales team and managers to validate their daily decisions.

  5. Design an analytics feedback process.  After the management ensures that the staff possesses the raw skills to explore new data and do their study, they can reveal unique sales strategies to woo clients. Conduct regular reviews where sales personnel can assist colleagues in identifying tactics that work and the scope of enhancement. If a person is doing well in branding a particular item, it can be a learning for others. 

Tags : Business
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