Revenue predictability works to forecast an organization’s revenue over a certain period of time, typically quarterly or annually. Accurately predicting revenue is necessary for short-term goals like setting business budgets, and long-term goals like scaling business growth. This forecasting takes into account existing data to make educated projections about future sales. It requires both quantitative and qualitative information to create models which will predict how much revenue an organization is likely to generate. Most importantly, revenue forecasting and predictability rely on quality data from reliable sources.
Topping the Polls
In a recent DealHub poll conducted, respondents were asked to rate their #1 resolution for 2023. The overwhelming majority (67%) chose to Improve revenue predictability.
The results of the poll show that revenue predictability is top of mind for most revenue leaders looking to survive and thrive beyond the current market climate.
Not only does revenue predictability offer business security, but it takes advantage of scalability, meaning that businesses can grow easily with the model in place and expand as needed. An additional benefit and one not to take lightly is peace of mind, freeing leaders from what can be overwhelming anxiety caused by fluctuating sales and unpredictable cash flows.
Intelligent Tools Make All the Difference
Although relatively new, revenue intelligence and sales intelligence tools have made forecasting a lot easier for companies looking to make smart revenue projections, identify precarious deals, and ensure that opportunities are not lost by the wayside. In essence, revenue intelligence tools turn data into insights for better real-time decision-making.
Revenue intelligence tools automate the process of gathering and leveraging data to help organizations make smarter and more accurate predictions based on customer reality instead of opinions. However, the best tools make sure to utilize real-time data that is both comprehensive and grounded in reality.
The main characteristics of good revenue intelligence are revenue acumen, performance, and optimization. Acumen combines multiple sources of data to create predictable revenue forecasts.
Performance works to generate profitable revenue by creating incentives that motivate sales professionals, and optimization focuses on agility and speed to identify necessary changes that require a shift in plans.
Data Done Right
Data-driven leaders who employ business intelligence systems understand the importance of revenue predictability grounded in analytics.
According to a McKinsey report, the organizations they lead are 23 times more likely to report outperforming their competitors, nine times more likely to retain customers, and up to 19 times more profitable.
Here are the 3 fundamental components of revenue predictability to achieve success:
- Data Collection
When data is collected and tracked from multiple touch points over a period of time, and then analyzed in a credible way, it becomes possible to measure trends and behaviors that indicate progress and success, or in some cases the lack thereof. Insist on using only factual information and remove any pieces of data that rely solely on opinion.
- Data Integrity
Data integrity refers to digital information’s validity, reliability, and trustworthiness. This includes its safety regarding assurance that the data is uncorrupted and suited for its intended purpose and can only be accessed or modified by those with proper authorization.
Data integrity matters in the same way that traditional quality control fulfills its purpose. Data that’s kept complete, accurate, consistent, and safe throughout its entire lifecycle is key to achieving revenue predictability. One error in a dataset can have a knock-on effect, severely impacting an organization’s most critical decision-making.
- Data Analysis
Data analysis is essential in helping organizations optimize their performance by gaining a better understanding of their customers, improving sales and targeting, reducing costs, and allowing for the creation of better problem-solving strategies.
With good data comes indisputable evidence. Coupled with effective quality monitoring, organizations are empowered to be proactive rather than reactive. When data analysis is done right and efficiently, organizations become equipped with the answers to respond to challenges before they become full-blown crises.
We would all love a crystal ball that would help us see clearly into the future. But the gift of clairvoyance, interestingly, is actually in historic and existing data. Utilizing this data to achieve revenue predictability is the secret to sales leaders’ success.
