Sales Organizations Stumble In Defining Sales Metrics
Only one in four organizations have a standard organization-wide definition for sales metrics. Research and advisory company Gartner, in its “State of Sales Analytics” report, says that this lack of metric definition standardization is a key roadblock to sales analytics’ ability to drive commercial success. The report also notes that only 55 percent of sales teams standardize metrics across all business units, regions and teams within the sales function itself.
“Without unified sales metrics definitions, sales analytics teams will struggle to help end users understand the analysis they are producing,” says Steve Rietberg, senior director analyst in the Gartner Sales practice. “In worst-case scenarios, this means sales analytics leaders will not even be aware of the confusion, and other functional leaders will make decisions based on erroneous assumptions and intuition.”
In May through June of 2020, Gartner surveyed 299 sales leaders and found that 19 percent of sales organization still define sales metrics ad hoc, meaning definitions are developed as part of each request for analytics and not necessarily reused. Instead, sales organizations need to make metric standardization the foundation for sales analytics’ role in commercial decision making.
“When different data dialects exist in an organization, they may have justification for variations in how a metric is defined and interpreted,” adds Rietberg. “Sales analytics leaders must be cognizant of dialects and flexible enough to support them.”
Gartner defines data dialects as the variations of an organization’s common interpretation of data that emerge within specialized groups, often aligned by customer segment, business process or technical domain.
To establish standard definitions for sales metrics and better ensure their adoption, Gartner recommends sales analytics leaders poll key stakeholders to identify and understand the metrics most important to various audiences in the organization. It says that the information is necessary to design a set of standardized metrics that satisfies the different users’ requirements and eliminate variations in definitions.