The Simple Truth: Scaling is Hard
There’s a rule of thumb among investors and business leaders that scaling a B2B professional services organization beyond the $50 million revenue mark is a herculean effort. While the benchmark shows up in other industries as well (for instance, in SaaS, the path immediately beyond $50 million is affectionately known as the “valley of death”)—and is attributed to the inherent complexities and inefficiencies that businesses amass at that stage of evolution—the problem is especially acute in professional services due to the human element inherent to the model.
As professional services firms grow, they must both maintain the quality and personalized service that established their reputation in the first place, while fielding a large number of new, high-quality leaders and teams to manage the increasing number of clients and engagements spawned by that growth. Consultative, high-touch relational sales models complicate matters further, requiring robust personal connections, well-developed business diagnosis and problem-solving skills, and significant trust-building capabilities.
Ultimately, professional services revenues tend to scale linearly with the number of people in the firm, rendering both growth and margin expansion harder to come by than in other industries. When you layer in the operational excellence required to grow a company from the startup phase to $50MM in revenue, and the inherent personnel turnover that comes with that transition, these complexities make it difficult for even leading firms to reach escape velocity.
Specialization Doesn’t Seem to Help
It turns out one of the commonly pursued approaches to scaling businesses generally—narrowing focus and systematizing supporting operations through specialization—doesn’t provide as much efficiency gain in professional services. Professional services firms have historically differentiated their offerings in one of two ways, expert advice and expert execution, and each has its own distinct scalability challenges:
- The expert advice model focuses on providing strategic, customized consulting based on deep industry knowledge and tuned to the client’s context. The scaling challenge here is that this approach relies heavily on the personal expertise and reputation of individuals involved in the end-to-end set of value-creating activities associated with delivery.
- The expert execution model focuses on the delivery of services, often in a more standardized format, and includes examples like managed services, compliance monitoring, and operational support. While the offering lends itself better to standardization, execution focus still depends on high standards of quality and consistency, with a dependency on volume and a constant evolution of services provided to ensure competitive edge and growth.
AI as a Tool for Finding Opportunity in Dilemma
The foundational element of knowledge work, evident in both specialization models and traditionally limited to scalability, is at the core of professional services. Until recently, knowledge work has been inherently bound by humans’ capacity to execute. AI and digital tools, however, have begun to streamline, augment, and automate otherwise human-driven processes. These newly enabled approaches promise to scale the previously unscalable by enhancing productivity, improving accuracy, and allowing more straightforward replication of high-value tasks.
Five AI-Powered Strategies for Scaling Professional Services
- Productized Solutions: Creating repeatable processes that you can apply across multiple clients without bespoke customization. This strategy leans heavily on developing proprietary methodologies or tools to deliver consistent results. Among the areas where AI can play here is analyzing data from past projects to identify common patterns and needs among clients.
- Outcomes-Based Pricing: Aligning the firm’s success metrics and rewards with the client’s outcomes, moving away from billable hours to value-driven pricing models. AI can help develop value-based pricing models by analyzing the firm’s long history of client and delivery data to establish the relationship between services provided and outcomes achieved.
- Large-Scale Personal Touch: Leveraging technology such as CRM systems, AI-driven analytics and collaborative tools can help firms manage larger client portfolios without losing the personal touch. These technologies facilitate deeper insights into client needs, enable personalized service at scale, and enhance the ability of client managers to deliver tailored advice and solutions efficiently.
- Client Growth Intelligence: Targeting existing clients with timely data-driven retention and growth plays to strengthen the economic foundation of the business.* AI can be leveraged to monitor the countless points of client activity and contact that human teams can no longer track, drawing contextual inference and driving the highest-likelihood actions to improve client value received, retention and growth.
- Organizational Transformation: Using AI and digital transformation approaches to address operational pain points and workflow efficiency through automation and augmentation. It is estimated that 40-50% of the work of professional services businesses can be automated in the long run, and each major cost savings or role enablement success improves the revenue per dollar cost of the business.
Conclusion
For B2B professional services firms aiming to scale beyond the traditional $50 million hurdle, a new playbook is emerging. The work involves using combinations of AI, digital transformation and data science to rethink client offerings, scale high-impact delivery, stay smart real-time on client needs, and eliminate operational pain points. The work is not simple, and requires new levels of AI acumen and a commitment to innovation and improvement, but the rewards are there for those willing to invest of themselves. Done right, best practitioners will end up leaving the $50 million hurdle far in the rearview.
* Improving client retention rates by just 5% can increase profits by 25% to 95%.
