Quote-to-RevenueOctober 27, 2022

Webinar Recap: Data Centricity & Streamlining the Quote-to-Revenue Process

Alissa Camarillo

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In our latest webinar, co-hosted by experts in Quote-to-Revenue from Neocol, Logik.io, and RightRev, we highlight the challenges from RevOps and Finance teams as they navigate digital transformations and the best practices to ensure successful transformation projects. Whether you’re moving away from manual processes and looking to automate for the first time or consolidating and replacing existing inefficient processes and systems, we unpack how to begin from any stage of your transformation journey. Below is a recap of key challenges and solutions:

What initial challenges do customers face when engaging with a Quote-to-Revenue Project, and how can you better prepare?

  1. 1. Identify key stakeholders early

Consider the data that Revenue teams rely on from upstream systems and involve cross-functional teams that manage and analyze the same data early in the scoping phase. Jenn Meehan, SVP of Revenue Automation at Neocol shares, “All too often, we see that our clients aren’t identifying all of the key stakeholders that need to be involved in the project.” Critical stakeholders are excluded from the project because of a lack of resources to meet critical deadlines. Still, they’re pulled into the project mid-way, and by then, their input is too late or requires some areas to be re-scoped, which can result in delays and added costs.

Key takeaway: Identify all the different areas that the project will impact, including upstream processes that will impact the revenue data downstream. Consider how changes might affect existing processes and create opportunities for new streamlined paths. Engaging key stakeholders early will ensure proper documentation of requirements, resulting in successful implementations and efficient adoption of new systems.

2. Prioritize change management

Change can stem from audit adjustments, adopting new revenue models, new organizational leadership, or new system implementations. While nobody likes change, setting the expectation for the transition early will ensure department-wide alignment. Let team members embrace the change by helping them understand that it aims to alleviate current pain points, reduce burnout, and get to the ideal state of process efficiency.

What advice would you give a company that thinks they are getting by with their existing, sometimes, manual processes?

Make the time to think about how to optimize technology to automate risk-prone tasks.

Many companies have invested in Quote-to-Revenue transformation projects to scale their business and alleviate the shortcomings of manual processes. But those transformations were often scoped in siloes and without a cross-functional strategy. Focusing on one piece of the puzzle at a time sometimes requires additional headcount to bridge gaps between systems with manual workarounds and to maintain customizations for data accuracy and completeness.  

Simply getting by to meet one area’s audit and period-close reporting requirements is not enough to enable a company to adopt new revenue models, adapt to their customer’s demands and stay ahead of their competition without creating additional challenges and inefficiencies. 

As companies realize this, the shift has been away from technology for technology’s sake and towards more streamlined data, process efficiency, and end-to-end visibility. Amanda Martinez Carrillo, Senior Director of Solutions Consulting at RightRev states, “We’re seeing a shift in investment for better data analytics and talent retention.” The right technology enables a business to access accurate and complete data. It strengthens the business users’ role in growth and scalability by mitigating the risk of burnout and human errors.

Burnout is a considerable risk for companies since they rely heavily on the accuracy of their revenue accountants’ calculations. In a recent Ernst & Young article, they state that along with data and analytics being a top priority, the most successful technology transformations put humans – committed leadership and empowered employees – at its center.1 The risk of getting by with spreadsheets and non-scalable processes is too big, considering revenue is one of the most critical numbers in the financial statement.

The importance of data centricity throughout the Quote-to-Revenue process

Quality data depends on human action and reliable technology. The dependency on the accuracy of upstream data is imperative to optimize the Quote-to-Revenue process. Incorrect Quote data flows downstream to billings, revenue, fulfillment, and cash application, resulting in underwhelming customer satisfaction (internal and external). 

From a data perspective, to avoid some of the challenges we’ve outlined above, there are a few data prerequisites you need to address to have a successful project starting point:

  1. Identify critical data fields 
  2. Assess the ability to systemize your data for automation and system ingestion
  3. Ensure data completeness and accuracy, including historical data

Consider people, processes, and data when engaging in projects that include data migrations. A best practice is to collaborate with resources that understand the systems and business policies to evaluate the impact of data transformation on downstream processes. 

Integrated data is a valuable asset for sales strategy and revenue accounting and for creating visibility to support customers and maintain customer satisfaction. For example, with accurate revenue data, a business could analyze what product lines are generating more revenue and evaluate the need to discontinue, improve or introduce new ones. In addition, a new go-to-market and pricing strategy, when paired with the corresponding revenue policy, would proactively streamline a process that could result in defining quoting system requirements to properly trigger the right downstream impact for approvals, fulfillment, billing, and revenue. 

Chris Haussler of Logik.io describes,

“If a CPQ project starts with the intention of shoring up something in sales, it won’t take long to realize that the only reason to sell anything is to get revenue recognized…and it’s part of the lifeblood of businesses to understand how you want to go-to-market and how it impacts how revenue is recognized.”

Chris Haussler, Director of Product Management and Customer Experience
Logik.io

As witnessed with manufacturing or hardware companies that started offering services, warranties, or goods as a service, their revenue recognition had to change, so having the end in mind as you are quoting to the customer becomes imperative to ensuring policy adherence. In addition, this will eliminate the need to clean up data after the fact and be reactive instead of introducing policy and automation from day one.

Conclusion

The goal of any automation project should be to obtain accurate data and create efficient processes that result in the flexible configuration of future revenue models, scalability, and customer satisfaction.

Stop-gap measures and disconnected applications prevent businesses from realizing the expected value of any transformation investment. A unified platform provides flexibility to configure and automate every step, with integrated data and processes between sales and finance.  Logik.io and RightRev have developed solutions that enable end users to keep downstream data consistent with upstream pricing and quoting offerings on the Salesforce platform. Watch the webinar below or contact sales for a demo of RightRev.

1. Jim Little, EY Global Microsoft Alliance Lead and EY Americas Technology Strategy Lead. Ernst & Young, “The CIO Imperative: Is your technology moving fast enough to realize your ambitions?” Apr 22, 2022.

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