4 ways to harness the power of ‘revenue intelligence’ and boost sales

In a nutshell, revenue intelligence is a framework for thinking and a way to measure all things that influence company growth to help guide operations.

In contrast to business intelligence, an analysis of core business metrics to answer specific strategic questions, revenue intelligence identifies measurable KPIs tied to specific growth drivers from all facets of the business and provides a holistic, transparent view of how the company creates value.

Armed with this knowledge, each department can understand its contribution to the bottom line and make informed decisions to drive more growth. 

During a time of unprecedented uncertainty, business leaders who adopt revenue-intelligence practices can more easily navigate the landscape ahead and take advantage of knowing exactly how each possible action might influence their business’ financial future. 

Here are four ways to make revenue intelligence easier to implement:    

Hire the right people

It might sound cliché but harnessing the full power of revenue intelligence starts with hiring the right person or people for the job. No matter what senior operations role, leaders with the right soft and analytical skills to champion this idea are key. 

As Carly Fiorina, former president and chair of Hewlett-Packard Co., said: “The goal is to turn data into information and information into insight.”

More than just a data scientist, the revenue-intelligence role requires an ability to create compelling stories based on the available data and turn them into inspired, collaborative actions at every level. These stories need to resonate across teams, including the C-suite, product, marketing, engineering, finance and sales teams. 

By default, this new role requires broad knowledge across operations, because in order to communicate effectively, this executive needs to “speak the language” of every department, know each department’s goals, how they function and how they interact with each other.

Look beyond sales 

Holding the front-line sales team responsible for all things revenue-related might be tempting, but many other factors contribute to a company’s bottom line. Using revenue intelligence’s collaborative approach, there are no business silos. Each function knows which KPIs they’re responsible for and by extension, how those KPIs influence sales.

For example, suppose your company is a custom software-development shop that charges customers based on coding hours. Engineers don’t want their projects to go over estimate, so they are typically incentivized to give the largest estimate possible to ensure there’s enough buffer. 

Sales, on the other hand, needs the customer to purchase, and engineering’s higher estimates make projects seem more expensive and less competitive.  Sales doesn’t typically understand how much effort goes into coding. Conversely, engineering isn’t normally aware of how buffer hours may impact the ability to close a sale. By only looking at the sales department’s activity, and not considering decisions made by others, there’s a likely negative impact on the team’s ability to sell. 

This is where revenue intelligence comes in. By identifying the KPIs in relation to revenue that engineering is responsible for and weaving them into a relatable story with targets that the engineering team’s leadership can use as guidance, a wise company breaks down those departmental silos that stand in the way of maximizing revenue at every step. 

Create a glossary 

In order to support data transparency and keep the entire organization on the same page, it’s a good idea to create a glossary of all KPIs. Be sure to include descriptions and how they’re calculated, along with maps to where they exist in the database. You’ll thank me for this later. 

Jim McHugh, VP at NuWave Solutions, writes: 

“… data warehouse documentation is critical to the success of the project. This documentation will help both the business users and the technical teams understand the source, the transformation and storage of the data they need to consume. These documents are the foundation upon which the warehouse will be built.”

A data warehouse reference guide serves multiple purposes: 

Makes the data more accessible across the company.
Empowers workers to find the data they need and run their own reports. 
Frees up time for data scientists to work on more pressing strategic efforts.
Improves data quality, consistency and accuracy.
Speeds up role transitions and employee training.
Increases transparency and clarity.
Provides historical context on how and why certain data matters.

Leverage automation tools 

Creating and maintaining a single source of truth for your company’s growth-driving KPIs for each department does not have to be difficult. There are many tools, both paid and free, that can make this task easier. Understanding the various tools already available will help uncomplicate the process of setting up a revenue-intelligence system.