Statistics For Sales Leaders
Sales is a game of statistics. Yet, many founders and sales leaders fail to recognize the importance of data-driven decision-making. Founders with passion and vision often over-rely on instincts and guts. It’s like playing roulette, picking your lucky number, and expecting to win. This article discusses the importance of statistics and how founders, entrepreneurs, and sales leaders can apply statistics to make better decisions.
The odds of picking your lucking number in roulette is 1 in 37, or 2.7 percent. The odds a startup will fail the first year is 1 in 5, or 20 percent. While the failure rate of startups may be high, many successful entrepreneurs learned to mitigate risks with better decision-making. In other words, learning to apply basic statistics to their business can stack the odds of success in their favor. Let’s explore.
Don’t Cringe at Statistics
The word statistics makes many of us non-math buffs cringe. Statistics often involve complex formulas, jargon, and abstract concepts that may seem intimidating to non-mathematical people. However, statistics help leaders manage uncertainty and risk in their decision-making process. According to online sources, between 60-75 percent of small businesses fail within ten years, depending on the industry. If you are a founder, that stat may change your thinking on the value of statistics.
CEOs, investors, and board members all value certainty. The value of statistics is that it provides certainty by calculating uncertainty. For example, a VP of Sales will likely be replaced after consecutive years (or quarters) of missing forecasts. This uncertainty creates anxiety about the future for all senior stakeholders. Anxiety is not caused by a lack of information–anxiety is caused by the lack of certainty about the future. Sales leaders can reduce anxiety by increasing certainty. The demand for certainty is enormous, and sales leaders that provide it will always have a competitive advantage in the market.
Information, Data, and Statistics
Information, data, and statistics are related but are distinct concepts in the field of quantitative analysis. The difference is that information and data refer to raw, unprocessed facts, numbers, or observations. Businesses can obtain data from unlimited sources. Data is often the starting point for analysis but statistics can be used to extract insights, patterns, or trends.
On the other hand, statistics refers to organizing, summarizing, analyzing, and interpreting data meaningfully. Statistics can be thought of as a toolbox of techniques that help transform data into knowledge. Statistics can involve calculating measures of central tendency and can be used to predict the outcome, describe the current situation, and asses the relationship between one thing and another. Statistics allows for more informed decisions or better recommendations based on the available data.
In short, data is the information collected, while statistics is the process of analyzing and interpreting that information. Data is necessary for statistical analysis, but statistics provide the framework and tools for making sense of data. For example, statistically speaking, can you answer the following question?
What is the probability of a lead becoming a customer based on company size? If the evidence showed companies with less than 50 employees had a probability of 1 in 37 becoming clients, would that help manage the opportunity? With those odds, you could come to Vegas and play roulette.
Sales managers are bad at estimating probabilities, not because they lack intelligence but because we are humans. We all have natural tendencies (bias) to underestimate the risks of a particular deal or overestimate the likelihood of what we want to happen. From our experience, we’ve found sales leaders frequently make overly optimistic forecasts that fail to come to fruition. Missing the numbers creates uncertainty and disappointment and undermines the credibility of the sales team.
To illustrate this point, I suggest comparing overly optimistic sales managers to a gambler at a casino. Like gamblers, sales managers can convince themselves they have a winning hand, even when the odds are stacked against them. They may keep doubling down on their bets, hoping their luck will turn, only to leave the table empty-handed in the end. Just as a skilled gambler knows when to walk away, a good sales manager needs to be able to accurately assess the risks and probabilities of a particular deal, hire leads, and numerous other data points to make informed decisions based on that assessment.
Using Statistics in Sales
Statistics is not as hard as non-mathematicians make it out to be. Using statistics to make better decisions is within reach of most sales leaders. Consider the following scenario: AVP of Sales wants to make better decisions in analyzing the performance of a sales team. Understanding the win rate for the entire team and individual reps would help identify areas of opportunity and strengths.
The formula for win rate is:
(Number of won deals / Total number of deals both won and lost) * 100
The math for a sales rep who wins 10 out of 60 deals in a quarter is:
(10 / 60) x 100 = 16.67%
This means that the rep successfully won approximately one out of every six deals they pursued. By comparing an individual rep’s win rate to the average win rate for the sales team or the target win rate for the quarter, a VP of Sales can assess the rep’s performance and identify any areas for improvement.
As a Vice President of Sales, understanding key statistical concepts and formulas can help inform data-driven decision-making and drive sales success. Here are a few key concepts and formulas to consider:
1. Mean: It is the average of a set of numbers. Sales leaders want to know the average profit by reps, but this can be influenced by extreme outliers.
For example, five sales reps have the following profits per month:
$3,000 + 12,000 + 16,000 + 17,000 + 20,000/5= $13,600
2. Median: It is the middle value in a data set. It is used when there are outliers or extreme values. To mind the median, you arrange numbers in descending order and select the middle value:
$3,000, $12,000, $16,000, $17,000, $20,000
In this case, the middle value is $16,000 since it is the third value in the ordered list. The median is the value that separates the higher half from the lower half of sales performers.
These are just a few examples of the key statistical concepts and formulas that can be useful for a sales leader. The specific concepts and formulas to focus on may depend on the company’s detailed data and sales goals. A sales leader who understands statistics can effectively communicate sales data and analysis to other stakeholders within the company. Statistics gives all stakeholders a higher level of thinking about the sales results they are achieving.
Making Statistics Easier
Fortunately for us non-math majors, several tools and resources are available to help us with statistics in our daily work. A few include:
- Statistical Software: There are several software programs available that can help sales leaders conduct statistical analyses without needing to know complex formulas. These programs have user-friendly interfaces and can help automate the calculations necessary for statistical analysis.
- Data Visualization Tools: Data visualization tools can help present complex data in a more visual and easily understandable format. These tools can help make statistical data more accessible and understandable to a broader audience.
- Consult with Data Analysts or Statisticians: Organizations can seek help from a data analyst or statistician for more complex statistical problems. These professionals can help with data collection, analysis, and interpretation and can provide guidance on statistical methodologies.
Every sales organization wants to say they are data-driven. However, sales leaders often rely on gut instincts and raw data. Being genuinely data-driven means going beyond raw data and understanding sales performance’s underlying trends and drivers. A data-driven sales organization will use statistics to inform and guide strategic decision-making. By embracing a statistical approach, sales leaders can gain a competitive edge by making more informed decisions and optimizing sales performance based on quantitative insights.
Sherlock Holmes may have said it best, “It is a capital mistake to theorize before one has data.”
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