To manage enablement across 180 markets, Lenovo avoids a purely centralized or decentralized model. Instead, they focus on "harmonizing" foundational elements like customer data centrally. This creates a unified, reliable data layer that then empowers local teams to execute culturally relevant enablement programs effectively.
When product, marketing, and sales all compete for seller attention, enablement becomes highly political. The solution isn't to mediate these conflicts directly. Instead, build an objective system with clear governance and processes. This system becomes the arbiter of priority, sidelining political influence and focusing on customer-centric outcomes.
Generative AI tools are only as good as the content they're trained on. Lenovo intentionally delayed activating an AI search feature because they lacked confidence in their content governance. Without a system to ensure content is accurate and up-to-date, AI tools risk providing false information, which erodes seller trust.
Forcing reps to perform in front of the entire C-suite creates a critical, high-pressure environment that is counterproductive to learning. Successful enablement requires a phased approach with pre-training and post-event reinforcement using real-world customer calls, not just high-stakes internal role-plays.
When introducing AI to a skeptical executive, a detailed, multi-week rollout plan can be overwhelming and trigger resistance. A more effective approach is to showcase one specific AI capability within an existing tool to solve a tangible problem. This "dip your toe in the water" approach builds comfort and demonstrates immediate value.
When different departments push their own projects onto the sales team, reps get overloaded. To solve this, enablement leaders must shift the focus of every initiative away from departmental priorities and toward a shared customer outcome. This unified goal minimizes internal friction and clarifies what's truly important.