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Data Integration & Technology

Maturity level 1

Recommendations

  • Adopt a centralized CRM system to store and manage core sales data.
  • Implement basic tracking and record of account-specific sales and promotions performance.
  • Begin to establish a single source of truth for all internal sales and promotions data.

Maturity level 2

Recommendations

  • Implement a basic business intelligence (BI) platform to centralize and visualize internal sales data with limited external market data.
  • Use the BI dashboards to enable basic adjustments to sales coverage and visit cadence based on account performance.

Maturity level 3

Recommendations

  • Formalize a data integration strategy to centralize sales and relevant external market data from sources like Nielsen or IRI into a single platform.
  • Use this integrated data to prioritize sales coverage and visits.
  • Promote and facilitate data-driven decision.

Maturity level 4

Recommendations

  • Implement predictive analytics to forecast demand and enable more accurate sales planning.
  • Use automation tools to streamline sales execution, such as automated scheduling, routing and agentic solutions.
  • Leverage integrated data to optimize trade promotions with a clear view of market dynamics.

Maturity level 5

Recommendations

  • Use AI-powered predictive and prescriptive analytics to autonomously optimize sales execution and trade promotion optimization.
  • Provide sales reps with “next best action” recommendations in real time.
  • Continuously refine AI models based on field results and market changes.

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Distributon & Partner Management

Maturity level 1

Recommendations

  • Create a shared repository with sales plans, targets, and basic execution expectations.
  • Use a communication channel (email, messaging platform) for updates and feedback.
  • Establish a basic meeting cadence for partner check-ins.

Maturity level 2

Recommendations

  • Deploy a partner portal or extend CRM to provide shared visibility of sales plans and performance.
  • Implement structured partner update reports and a dashboard for tracking execution progress.
  • Introduce a standard template for joint performance reviews.

Maturity level 3

Recommendations

  • Adopt a partner relationship management (PRM) platform for co-developing plans in a shared environment.
  • Integrate partner performance data into internal systems for unified tracking.
  • Set joint KPIs and accountability measures.

Maturity level 4

Recommendations

  • Integrate internal and partner systems for real-time visibility of sales, inventory, and execution data.
  • Use analytics to jointly identify gaps and opportunities.
  • Establish a proactive joint action planning process for in-market optimization.

Maturity level 5

Recommendations

  • Build a “digital twin” of the distribution network to simulate and predict execution scenarios.
  • Use AI-driven prescriptive analytics to provide real-time improvement recommendations to both partners and internal teams.
  • Automate joint planning cycles based on predictive demand and execution potential.

Performance Measurement & Insights

Maturity level 1

Recommendations

  • Define a core set of KPIs and standardize measurement definitions across teams.
  • Track performance manually using spreadsheets or shared documents.
  • Record corrective actions and link them to identified gaps.

Maturity level 2

Recommendations

  • Centralize reporting in a BI tool with automated data refresh for standardized KPIs.
  • Configure CRM to automatically track and visualize performance data.
  • Set up automated alerts for deviations from targets.

Maturity level 3

Recommendations

  • Use an analytics platform for near-real-time performance monitoring.
  • Integrate CRM with marketing/ERP systems to enrich insights.
  • Introduce a coaching module within CRM or sales enablement tools to track corrective actions and skills development.

Maturity level 4

Recommendations

  • Leverage a revenue intelligence platform to generate predictive insights on future performance.
  • Implement forecasting for both opportunities and risks based on trend data.
  • Create a continuous strategy feedback loop from field data to corporate decision-making.

Maturity level 5

Recommendations

  • Deploy AI-driven prescriptive analytics to recommend next steps for closing performance gaps.
  • Automate measurement of leading indicators to preempt performance risks.
  • Integrate real-time measurement with compensation systems for instant recognition and rewards.

Retail Execution & Field Enablement

Maturity level 1

Recommendations

  • Deploy a basic mobile-first tool for reps to capture photos and log simple store metrics (stock levels, display presence).
  • Create a shared repository (e.g., cloud folder) with standardized planograms, merchandising guides, and campaign materials.
  • Implement a basic process for reps to report competitor activity and in-store observations during visits.

Maturity level 2

Recommendations

  • Roll out a dedicated retail execution platform to digitize daily tasks, track display compliance, and automate basic data collection.
  • Use the platform to assign clear in-store priorities and track rep accountability.
  • Develop simple dashboards to monitor KPIs like display compliance, shelf availability, and promotional execution.

Maturity level 3

Recommendations

  • Integrate the retail execution tool with CRM/ERP for pre-visit planning based on sales history and store insights.
  • Introduce guided visit workflows in the mobile app to standardize rep activities.
  • Adopt image recognition to speed up planogram compliance verification and detect execution gaps.

Maturity level 4

Recommendations

  • Apply predictive analytics to identify high-potential stores, optimize visit frequency, and improve route planning.
  • Link performance-based incentives to real-time display and sales data.
  • Establish a two-way feedback loop between field teams and headquarters for agile adjustments to in-store strategy.

Maturity level 5

Recommendations

  • Use AI-powered prescriptive analytics to deliver store-specific, real-time recommendations (e.g., product placement, cross-merchandising).
  • Integrate retail execution with a Revenue Growth Management (RGM) system to align store actions with broader business objectives.
  • Continuously refine personalized incentives using machine learning models that factor in rep performance, store type, and potential.

Sales Planning & Prioritization

Maturity level 1

Recommendations

  • Establish foundational data collection within CRM.
  • Define basic customer segmentation criteria.
  • Formalize clear, measurable goal setting processes.
  • Conduct initial manual territory review and adjustments.

Maturity level 2

Recommendations

  • Automate data capture and reporting in CRM.
  • Enhance customer segmentation using product affinity or basic behavioral data.
  • Use initial data insights for data-driven goal alignment.
  • Introduce basic BI tools for territory analytics.

Maturity level 3

Recommendations

  • Integrate sales and marketing data.
  • Implement advanced segmentation for customers and sales channels.
  • Deploy dynamic goal management systems.
  • Adopt dedicated sales planning and territory optimization software.
  • Formalize automated account prioritization reviews.

Maturity level 4

Recommendations

  • Integrate predictive analytics for segmentation and prioritization.
  • Implement automated goal cascading and real-time performance monitoring.
  • Utilize advanced analytics for scenario planning in territory and resource allocation.
  • Establish robust feedback loops for continuous planning improvement.

Maturity level 5

Recommendations

  • Explore and implement AI solutions for autonomous planning and optimization.
  • Leverage advanced AI for hyper-personalization at scale for customers and points of sale.
  • Establish continuous learning and adaptation cycles into AI models.
  • Integrate sales planning with HR systems for predictive talent management.