Beyond Revenue Operations
Where we're going, we won't need headcount.
The only thing evolving faster than business is technology.
Tech’s evolution is accelerating thanks to the reinforcing relationship between science and technology.
As we unlock new discoveries stemming from scientific advancements, our ability to create technology increases. More powerful technology then becomes available which opens the door to new scientific breakthroughs.
Science and tech are in a feedback loop because of this.
Sometimes science and technology require a bridge - called engineering.
Business and tech are also in a feedback loop.
New technology brings entirely novel products, services & industries into existence. As industries form, new techniques and tech are invented.
The Rise of Revenue Operations
Rarely, entirely new functions within business are invented - such as revenue operations.
Revenue operations, often referred to as RevOps, aims to break down silos between sales, marketing, and success teams. This is achieved by aligning these traditionally separate functions - along with their systems, data and workflows.
RevOps is a bridge between all the departments.
RevOps seeks to drive growth through operational efficiency and effectiveness.
RevOps is also the function within business that captures the largest share of the energy waves created by new tech - like AI.
AI is quickly becoming the master tool to analyze efficiency and sustain efficacy. Right now AI typically takes the form of clusters of Artificial Narrow Intelligence models working together.
The Bad News: AI & Automation breakthroughs are already translating to headcount reductions.
Even RevOps will lose headcount thanks to our silicon-based buddies.
...but we're also best positioned to deliver the value of AI.
Data centralization: RevOps serves as the unifying force that brings together data from sales, marketing, success, product, support, finance and everywhere else. This centralization of data is ideal for AI, which thrives on large, diverse, and integrated data sets. The more data that AI has access to, the more accurate and insightful its analyses can be.
Predictive analysis and forecasting: RevOps, with its cross-departmental perspective, can effectively leverage AI for predictive analysis and forecasting. AI can analyze historical data patterns, customer behaviors, and market trends to forecast sales, predict customer churn, and make recommendations for future actions.
Automation and process efficiency: AI can help automate repetitive tasks and streamline processes, such as data entry, lead scoring, and customer segmentation. By automating these tasks, RevOps can reduce manual effort and errors, increase efficiency, and enable teams to focus on more strategic initiatives.
Personalization at scale: AI can analyze customer data to segment customers and predict their preferences, helping businesses tailor their offerings to individual customer needs at a scale that would be impossible manually. This personalization can lead to improved customer experiences and increased customer loyalty.
Decision-making: AI can help RevOps by providing data-driven insights that can inform strategic decisions. AI can analyze data to identify trends, spot opportunities, and predict outcomes, thereby helping RevOps make better, more informed decisions.
The future of business is driven by technology.
Revenue operations is the most tech-exposed function in business, and it will be increasingly responsible for transforming operations as a whole.
Beyond Revenue Operations
Revenue Operations is evolving as a result of technological breakthroughs.
With the rise of AI, the traditional RevOps model is experiencing transformative changes in several ways:
Increased Efficiency and Scalability: Automation can handle repetitive tasks, freeing up the team to focus on more strategic activities. For example, AI can be used to automate data entry and management, deal registration, order processing, compliance checks, and many other time-consuming tasks.
Improved Decision-Making: AI can handle vast amounts of data and provide actionable insights. This can aid in strategic decision-making for aspects like pricing strategies, determining upsell and cross-sell opportunities, forecasting revenue, and identifying bottlenecks in the revenue cycle.
Enhanced Customer Experience: AI can help in personalizing the customer experience based on individual preferences and behavior, thereby improving customer satisfaction and loyalty, and ultimately, revenue.
Predictive Capabilities: AI and machine learning models can forecast customer behavior and market trends, allowing businesses to anticipate needs and opportunities for growth.
RevOps teams are moving beyond the pure Operations mandate and becoming more vital as orchestrators of an increasingly automated revenue engine.
Here's how this is playing out right now:
1. Orchestrating Automation and Integration: As more parts of the revenue cycle become automated, RevOps will have to ensure all these automated processes work in harmony. The role will involve integrating various automation tools and technologies, managing data flows between them, and ensuring that they align with the organization's broader goals.
2. Data Analysis and Strategy Development: With AI processing large amounts of data, RevOps will have to analyze this data to identify trends and insights, and use these to develop revenue strategies. This will include interpreting AI-generated forecasts and making decisions on resource allocation and strategic initiatives.
3. Change Management: The adoption of AI and automation will inevitably involve significant changes to workflows and processes. RevOps will have to manage these changes, ensuring that they're implemented smoothly and that all stakeholders understand and accept the new systems.
The future of RevOps in the era of AI and automation is promising but will involve significant adaptation and evolution. It will demand a shift from simply managing operations to orchestrating an interconnected, automated revenue engine, ensuring it functions continuously, efficiently and effectively.
It will be instrumental in aligning AI capabilities with business strategies, translating insights into actions, and driving revenue growth in an increasingly digital and automated business environment.
Now that we’ve moved Beyond Revenue Operations…
Where are we headed?
Revenue Command and Control
The future is Revenue Command & Control, encompassing these four elements:
Revenue Design: Designing efficient and profitable revenue engines
Revenue Engineering: Building revenue engines
Revenue Operations: Running revenue engines efficiently
Revenue Intelligence: Analyzing revenue engine health and performance
Revenue Design Revenue Design is the strategic planning and conceptualization of a company's revenue model. Design is involved in setting revenue goals, identifying revenue streams, and defining key performance indicators (KPIs). It also delves into the creation of process maps to understand and optimize the customer journey and sales pipeline.
Revenue Engineering In Revenue Engineering, the focus shifts to the construction of the revenue infrastructure, discussing how to select, implement, and manage the necessary technology to track, analyze, and optimize revenue processes. Engineering focuses on the role of automation, system integration, and data management in ensuring an efficient and effective revenue engine.
Revenue Intelligence Revenue Intelligence examines the role of data in driving revenue. Intel involves the techniques and tools for data collection, analysis, and interpretation, emphasizing how these can generate actionable insights. It explores how these insights can be used for decision-making, forecasting, and supporting other components of Revenue Operations.
Revenue Operations Revenue Operations delves into the daily activities that ensure the smooth functioning of the revenue engine. It looks at performance monitoring, process management, troubleshooting, and continuous improvement as essential tasks in operations. It also emphasizes the importance of stakeholder alignment across various teams in the organization.
No longer can revenue operations be asked to “make it work better” if we aren’t able to significantly alter the revenue engine design and/or engineering.
Vision of the Future of Business
Headcount across departments will diminish as a result of AI.
Sales development and customer success will see the largest impact from this.
As AI systems continue to gain functionality we're going to have agents capable of...
-selling
-marketing
-customer success'ing
RevOps will evolve into a role that orchestrates these AI agents.
We’ll monitor the progress of the agents, help them coordinate and optimize their impact.
Where does the Command and Control come in?
Control refers to Statistical Process Control, and measuring the processes related to generating revenue to ensure they are efficient.
Command refers to using revenue intelligence analytics and process control data to inform changes to tactics and strategy to ensure revenue quotas are met.
This approach is quite powerful, as it integrates the analytical and control aspects of revenue management into a single, cohesive system.
Here are a few components and benefits of Revenue Command and Control:
Data Analysis: A core aspect of this system involves constantly analyzing data related to the company's revenue streams. This includes customer behavior data, sales team performance data, marketing campaign efficacy, and product performance. The insights gained from this data analysis are invaluable in optimizing revenue-generation strategies and tactics.
Process Control: By using Statistical Process Control (SPC), you can monitor and control the processes involved in generating revenue. This might involve identifying bottlenecks or inefficiencies in the sales process, or in how products or services are delivered. It can also involve detecting shifts in market conditions or customer behavior.
Revenue Forecasting: Using historical data and predictive analytics, your system provides accurate revenue forecasts. This could help the company make better strategic decisions and anticipate potential issues in the future.
Dynamic Strategy Modification: This is where the "Command" component really shines. Based on insights from your data analysis and process control efforts, you could dynamically adjust strategies and tactics to optimize revenue generation. This could mean shifting resources to a more profitable product line, adjusting pricing, modifying sales tactics, or implementing new marketing strategies.
Performance Measurement: This system could include robust metrics and KPIs to measure the effectiveness of different strategies and tactics. This could provide further feedback to refine and improve the revenue command and control system.
Operational Efficiency: With a good understanding and control over the revenue generation processes, the operational efficiency of your business could significantly improve, leading to lower costs and higher profits.
Implementing a Revenue Command and Control system is challenging.
It requires a combination of sophisticated data analytics software, operational adjustments, and some culture change within your organization. But if done correctly, it provides a significant boost to your revenue generation capabilities.
Businesses can best “capture” the energy from advancements in technology by investing in their revenue operations.
The most successful firms are already moving Beyond Revenue Operations to an integrated Revenue Command and Control function.
This new model extends the role of RevOps to strategically designing and building revenue engines, and utilizing data-driven intelligence for decision-making, forecasting, and supporting operations.
This integrated system of:
data analysis
process control
revenue forecasting
dynamic strategy modification
performance measurement
operational efficiency
is the future. It offers a robust method of optimizing revenue generation & retention capabilities.
As mentioned, technology is accelerating thanks to the reinforcing relationship between science and technology.
This new model of business operations uses tech to the fullest in order to reach and sustain growth goals.
The only thing evolving faster than business is technology.
..and now we understand why that is, and how moving Beyond Revenue Operations can help us make the most of Life in the Singularity.
This is incredible I've really enjoyed reading this. It's amazing what a layman can deduce from the basic level of filtration available to their scope of understanding merely by indicators of intrigue. This is a very forward thinking conceptual framework for what feels like the future as I would like to see it formed. Excellent.
This is the thesis, AND active deployment, Revscale Sales is working on. I have activated the Revscale AI in my LinkedIn Sales Navigator channel and it is generating 5+ 1 to 1 interactions a week. AI is on par with my email automated sequencing and will compound learning to outperform my automations in the next month is my bet.