Unlocking Revenue Transformation

Shownotes

In today’s episode, Naren Chawla discusses the concept of revenue intelligence and how it can help businesses improve their overall revenue cycle. He shares how revenue intelligence can help identify where revenue is leaking and the challenges and benefits of focusing on an organization’s current customers to grow revenue. Listen as he explores some of the key metrics that should be tracked to optimize an organization’s revenue process. Finally, he provides examples of how revenue intelligence can be used to improve an organization’s process and impact its top line.

About the Guest

Naren is Head of Product Management for CX & NetSuite Analytics at Oracle. For the past two decades, Naren has been involved in creating category-leading “new” businesses from conception to launch in Analytics, Data Management, and Cloud space at leading Enterprise Software companies, including Salesforce, Oracle & SAP.

Connect with Naren Chawla

Key Takeaways

B2B organizations are facing a problem because they don’t have visibility into their entire revenue cycle.
Revenue intelligence is the process of bringing data from different systems together to figure out where revenue is leaking and how to improve it.
Revenue growth can be increased by focusing on the current customers and identifying where leaks are occurring, as well as being very efficient in growing revenue.
There are general KPIs that can be used to measure success, such as campaign ROI, sales velocity, and win rate. However, each business will have its own specific KPIs that need to be defined and tracked.
Revenue transformation is the process of transforming revenue from one source to another, typically to increase profitability.

Quote

“The b2b organizations are facing problems because they don’t have visibility… There are silos across it marketing runs campaigns, they don’t know they generate leads, whether these leads are high quality and bad quality.” – Naren Chawla

Highlights from the Episode

Can you tell us a bit about your background and your current role at Oracle?

Naren Chawla has been in database software companies for almost two decades and is currently a product manager at Oracle. He has been involved in conceptualizing an application around analytics and is now trying to disrupt the BA market.

Can you explain to our listeners the concept of Revenue Intelligence?

Revenue intelligence is a concept that focuses on figuring out where revenue is being leaked in a company’s journey from marketing to invoicing and collections. This is done by bringing data from all the different systems that are involved in this process into one place. This allows for questions to be asked about which customers are good or bad, what margins and profitability look like, and what is and is not working.

What are some of the pain areas B2B organizations face in the whole lead-to-cash cycle, and how does Revenue intelligence help solve these problems?

B2B organizations face several pain points in the lead-to-cash cycle, including lack of visibility, silos, and inefficient use of resources. Revenue intelligence can help solve these problems by providing visibility into the entire cycle, identifying opportunities for improvement, and automating key tasks.

How did you go about defining the various KPIs at every stage in this process?

Naren Chawla defines various KPIs at different stages of a process, including campaign ROI, sales velocity, and win rate. He notes, however, that each business will have its own specific KPIs that need to be defined and tracked.

Can you cite certain revenue intelligence use cases that could optimize an organization’s processes and impact its topline? Are you able to dive a bit deeper into and walk us through the top 3 use cases for revenue intelligence that could optimize an organization’s processes and impact its topline?

the three main use cases for revenue intelligence that could optimize an organization’s processes and impact its topline are – (1) Revenue Transformation: Looking at the entire sales cycle to identify margins, profitability, and areas where the sales team could be more effective. (2) Marketing Effectiveness: Joining data from sales and marketing systems to see which campaigns are most effective in influencing sales. (3) Next-Gen Sales: Using machine learning to tell sellers which opportunities to focus on and predict pipeline outcomes.

How are you and your organization adapting to the current economic downturn?

Oracle has adapted to the current economic downturn by reorganizing its company, investing in revenue operations, and realigning its sales and marketing teams.

Is there a book, blog, newsletter, website, or video that you would recommend to our listeners?