To solve these problems, leading CPG companies are adopting the three Cs as foundational elements in their promotional pricing process.
Promotional pricing plans should be agile enough to shift both strategically and tactically, while still meeting regulatory and financial requirements. Promotions planners can accomplish this by creating and curating dynamic planning processes that focus on exceptions and opportunities in real-time. This approach involves changing where, when, and how decisions are made across trade promotions teams:
- Instead of relying on monthly or quarterly planning cycles, data and plans should be managed in real-time or near real-time via daily or weekly cycles
- Management roles should change from deciding and enforcing to coaching and supporting so managers can set dynamic guidelines for enforcement and data trigger points to identify bigger picture opportunities
- Team member roles should change from a workflow and data translation orientation to a problem solving and communications orientation. This way team members have the authority to quickly solve problems and take advantage of opportunities knowing their solutions meet regulatory and financial requirements
These changes build on a foundation of RPA and AI technologies to optimize promotional pricing plans. For example, a retailer may be forced to ration a specific product, thus failing to meet the terms of a promotion agreed to months earlier to never be met, but in a dynamic, continuous world a decision can be made in near real-time to change the promotion terms to meet the new ration limit.
In a nutshell, this means no more silos of information or delays in communication. The overarching goal is a single source of truth for trade promotions, with up-to-date, accurate data the organization can rely on. This can be supported by:
- Using social media to test the effectiveness of different promotional pricing strategies
- Leveraging robotic process automation (RPA) and AI to optimize promotional tactics and pricing that meet current guidelines
- Building on a foundation of data hubs to collect and harmonize data across products, customers, promotions, and pricing
Promotion and pricing processes should be human-curated, not human-driven. This means using RPA for routine tasks like data entry and approvals and AI for jobs like promotional calendar creation and individual promotion optimization.
- AI-reinforced learnings will build resilience by quickly adapting to changes in buyer behavior and making new promotional recommendations
- RPA can quickly execute these changes and automate routine tasks that rely on simple rule-based decision trees
- Any processes that require human input should be combined with AI to suggest decision options and solutions. AI will learn from these decisions and continuously refine its suggestions through reinforced learning
Eventually, converting human and AI-supported processes to RPA plus AI processes will free up time for the team to focus on growth opportunities.