Sales, marketing, customer success, and operations have a long history of trying to find alignment. First, it was between sales and marketing. Then sales, marketing, and customer success. Now, it's all four trying to see where and how they overlap to create revenue-generating efficiency and collaboration for the business's benefit.
While operation teams were the first department tasked to achieve this alignment, ops teams quickly became siloed efforts in themselves, leading to many applications and tools designed to link ops with sales, marketing, and customer success.
Most companies try to find a magic bullet to solve this dilemma—a single software tool that can bring it all together or even an inspired executive who's worked magic at other companies.
While there's nothing wrong with these approaches, let's remember why operations models exist in the first place: to dismantle silos and create a company-wide mindset around building revenue flow throughout the entire organization. With that in mind, we sat down with Art Harding, Chief Operating Officer at People.ai, to better understand the three operations models, the pros and cons between them, and what that means for the future of RevOps.
The Three Ops Models
Over the last five years, three primary operations models have emerged: distributed, centralized, and hybrid.
Centralized Model consists of integrated teams reporting into an operational leader where the lines of business being served is the customer.
Distributed Model has teams reporting into specific departments (i.e., marketing ops reports into marketing, sales ops reports into sales) and serving within those lines of business.
Hybrid Model is a combination of both: ops teams still report into their respective departments much like in a distributed model, but in this case, there's a dotted line to a centralized RevOps team.
Centralized vs Distributed vs Hybrid
A centralized model offers a wide range of benefits, including improved governance and better control, and more efficiency over priorities and spend. Additionally, this model is great for establishing sustained and scalable velocity and momentum. "This model also tends to attract more senior operational leaders as they'll have much larger projects to manage," says Harding.
Centralizing strategic and operational functions forces companies to institute governance for rationalizing priorities, timelines, and investments. It also improves the operators' and analysts' abilities to do an intellectually authentic analysis of what they see in the data or numbers.
A distributed model offers a bit more flexibility and creativity with a faster turnaround time to turn initiatives into action. However, this model tends to be less efficient, cost-effective, and less controlled than a centralized model.
While the distributed model accelerates execution on proven operating structures, it may also open the floodgates for lines of business users to covet their operation and data teams to forward a specific narrative. "This could trigger a sort of 'battle of the ops' scenario where each department's operating team is then challenging the conclusion of the other," cautions Harding.
A hybrid model will include a mix of operational models combined between both centralized and distributed. A hybrid model's benefit is the ability to manage at scale; however, that does come at the cost of it being a more complex option than the other models.
Which Model Is Right For Your Business?
Suppose your business already has a proven or known operating structure. In that case, you can choose to distribute your operations more with a proven governance and allow teams to make quicker decisions at the edge. This distributed model also tends to be a better fit for global organizations.
If your business is still maturing, creating new business processes & capabilities, and preparing for scale, the centralized model may be a better fit. “This can extend to domestic companies that are looking to retire operational debt or prioritize new investments,” says Harding.
Large, more mature enterprises may choose to look at both models (i.e., the hybrid model) from a high altitude and mix and match depending on the arm of the business they’re looking to serve.
The Rise of RevOps
Whenever we see technology applied to the way we work or live, we tend to see several things happen: old ways of working are displaced, new types created, and a reduction in the number of reactive actions. Within the world of sales and marketing, the addition of technology, data, and AI will answer all three of these points and help teams spend less time on low-value tasks.
The good news is that businesses have already made a lot of progress in those areas via their digital transformation efforts. Offloading low-value tasks has freed up space for department leaders to have a chance to look across the aisle finally and better understand the leading indicators in each function, i.e., the early signs of future success. It’s here that real alignment can take shape as leaders begin to see that “business processes within sales are no more a sales process than lead routing is a marketing business process,” says Harding. “If today’s buyer and customer journeys demand integration, shouldn’t the same be asked of our own business?”
Today, leaders from sales ops, marketing ops, and finance connect the dots between these siloed digital capabilities in their business processes and the larger, more integrated buyer and customer journey. It’s here that built the foundation of RevOps. “What’s more is that these processes can be integrated and enhanced with AI and data so that predictable patterns in each of these functions can automatically trigger signals, awareness, or real-time action,” says Harding.
The Future of Operations & AI
"If you believe that the buyer and customer journey is an integrated experience and that everything from sales method to leads to who your team is meeting with can help you operate more efficiently in the future, you're going to get there a lot faster with a centralized ops model," says Harding.
Here at People.ai, we recognize it's a race to the AI-powered, data-driven, cross-functionally aware operating model. The AI-ready RevOps team of the future will have tackled the toil of manual data entry, moved from only focusing on lagging indicators to a mix of lagging and leading, and will have applied automation to core infrastructure to shift the strategic operating energy to leveraging signals provided by AI.
More importantly, as more tech and AI penetrates the business, leaders can re-allocate their time to focusing on the human element of work and unlocking every employee's potential.