By Esperanza Arellano, Director - Sustainevolve, Canada
In recent years there has been a trend to switch from traditional Sales Operations to a Revenue Operations Model, a relatively new concept to integrate Marketing, Sales, and Customer Success Teams to achieve revenue goals with a customer’s journey approach and an end-to-end unified holistic model. The most compelling reasons are related to breaking down silos that impact revenue results and collaboration across teams to generate results.
Why Choose RevOps for an AI Transformation
If you have already transitioned to a more holistic approach, and are planning to continue your improvement journey, perhaps you may be thinking about incorporating the AI component to enhance your RevOps model. If that is the case, you may have wondered what the best way is to adopt AI to your current RevOps model, and here we will discuss a few ideas for your next AI RevOps Transformation.
How to Implement Revenue Operations Models Aligned with Your AI Transformation
First, it is important that before undertaking any major AI Transformation impacting your Revenue Teams Marketing, Sales, and Customer Success, a RevOps model is implemented to prepare the path forward for success. And, when deciding how to best implement your Revenue Operations Model, there are several options that your organization may consider.
Adopt A World-Class Thought Leadership Model
Gartner provides a Thoughtful Revenue Operations Implementations Guide, with 6 core attributes to guide your transformation journey with steps and lessons. The model is comprehensive for the following reasons:
Align Your AI Implementation Plan with Your RevOps Implementation Model
When planning your RevOps AI Implementation Goals, your RevOps Model, and your AI Implementation Plan must be aligned together. A simple approach is to organically integrate your AI Implementation with your SMART Goals. Having in mind how your AI Implementation will play a role in your SMART Goals, it automatically becomes part of your RevOps strategy.
Dissolve The AI-ROI Dilemma
AI Implementations need to generate buy-in from senior executives. C-Level stakeholders particularly, pay attention to the ROI when considering decisions and budget considerations.
Develop AI-ROI Specific Use Cases that can assist in justifying the AI Implementation so that the project can move forward.
This step is critical for any major business decision, and AI is not an exception. The reality shows that many AI projects do not consolidate because AI technology investments cannot be justified with specific ROI use cases.
Conversations with multiple stakeholders need to take place before any decisions can be made and each stakeholder can influence the decision for the AI Implementation. Articulating the specific benefits of an AI implementation may take a great portion, if not the greatest portion of your plan.
AI Implementations Enable End-to-End Processes
If your AI Implementation is focused particularly to enhance Marketing, Sales, or Customer Success Teams, it is key to have an end-to-end approach to address a core need of a customer’s journey as the goal is to break silos across teams.
AI Implementations Connect Technology & Processes
AI capabilities are only useful if they enable integrated process workflows as this allows for automation to reduce time in repetitive tasks that can assist revenue teams in focusing on revenue-generating and customer-oriented tasks.
AI Projects Need Data-Driven Organizations
Many organizations are realizing that data readiness comes first before any AI Implementation. RevOps Teams, rely on data to accomplish their performance-driven goals. A robust Data Architecture is a major step for a successful RevOps AI Transformation.
AI Technologies Support Human Centered Organizations
Often AI implementations forget that the purpose is to solve human and business problems. With the continuous emergence of AI solutions, it is easy to place technology at the center while forgetting technology is an enabler. The goal is to solve a business, human-oriented problem or achieve a business goal. It is important to have specific use cases and focused areas to solve with AI Implementations.
Data Literacy
Implementing AI to achieve revenue goals requires a data-driven discipline.
The Benefits of an AI Transformation RevOps Center of Excellence
As a leader in your organization, the formation of a culture around excellence is a concept that may be part of your ambitions to bring your initiatives to a different level. That is one of the reasons why the idea of a RevOps AI Center of Excellence makes sense as a culminating component of your strategy.
A Chief AI Officer (CAIO) can lead AI initiatives along with a subdivision focused on Revenue Operations AI Transformation Center of Excellence (RevOps, AICoE) to leverage AI to achieve their revenue objectives
The benefits can be multiple:
Conclusion
While many organizations struggle today with establishing a more consistent process around their Revenue Operations Teams, your organization can start by adopting quick steps to get the conversation started.
Most of the time, spending time around the specific goals that you need to accomplish and creating specific use cases is worth it. Instead of jumping into complex AI Transformations to boost revenue, it is sound to look at Revenue Teams to see if there are silos and core areas that can be enhanced with a RevOps Model to assist in building a more business-oriented AI Transformation.
Having a big picture and forming a culture of excellence will not only assist your specific Revenue Operations goals but will foster a broader impact across your entire organization.
