Revology Analytics

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Unlocking Sales Performance with Commercial Analytics Transformation in the Agricultural Chemical Industry

Discover how a leading chemical manufacturer transformed its sales analytics capabilities to drive insights-driven decision making and improve sales performance. We partnered with the client to develop a customized sales analytics platform, overcoming data silos and manual reporting processes to unlock real-time insights and enhance efficiency. Learn how interactive visualizations, advanced analytics, and comprehensive training empowered the sales team to optimize commercial strategies and unlock greater organic growth. Read the case study to see how your organization can leverage commercial analytics transformation to unlock its full potential.


SITUATION

A leading global agricultural chemical manufacturer, specializing in crop protection, sought to enhance its sales analytics capabilities to drive data-driven decision-making and improve sales performance within its North American business unit.

Despite generating significant growth through acquisitions and holding a strong market position, the company recognized a critical need to modernize its sales analytics approach. The existing reporting processes, heavily reliant on manual Excel spreadsheets, were time-consuming, prone to errors, and provided limited visibility into real-time sales performance. This hindered the sales team's ability to proactively identify trends, understand key performance drivers, and optimize sales strategies.


The company had access to a wealth of data from various internal and external sources, including sales databases, distributor networks, inventory reports, and market data.

However, this data was siloed across different systems, making it difficult to integrate and analyze effectively. This lack of a unified view limited the sales team's ability to gain a comprehensive understanding of performance and make informed decisions.

Collaborative dashboard design sessions facilitated in Miro with Sales Directors, Managers and other team members.

ACTION

To overcome these obstacles, we partnered with the company to develop and implement a customized sales analytics platform named US Crop SPIN (Sales Performance and Insights Navigator) using Microsoft Power BI. The project involved a multi-phased approach:

●       Comprehensive Data & Analytics Assessment: Before developing SPIN, we conducted a thorough data and analytics assessment involving key stakeholders across various business functions. This involved understanding the current data landscape, identifying key data sources and data quality issues, and evaluating existing analytics capabilities and processes. We also conducted workshops and interviews to understand the company's vision for becoming an insights-driven organization and identified potential roadblocks and challenges.


●       Comprehensive Data Assessment & Integration Strategy: We conducted a thorough assessment of the company's data landscape, identifying key data sources, data quality issues, and integration challenges. This formed the basis for a comprehensive data integration strategy that ensured data accuracy, consistency, and timeliness.

●       Collaborative Design & Development with Key Stakeholders: Throughout the design (using Miro) and development process, we worked closely with key stakeholders from the US Crop sales team, including sales leadership, regional managers, and sales analysts. This ensured the platform met their needs, addressed key business challenges, and aligned with existing workflows.

Advanced Analytics capability continuum.

OBSTACLES

The company faced several key obstacles in its journey to enhance sales analytics:

●     Fragmented Data & Inconsistent Data Structures: Data resided in disparate systems, making it difficult to gain a comprehensive view of pricing performance and customer behavior. Inconsistent data structures and a lack of standardization across two key banners further complicated analysis, hindering the ability to gain insights into pricing effectiveness, promotional ROI, and customer segmentation.


●       Manual Reporting Processes & Excel Dependency: The existing reporting process heavily relied on manual data extraction, manipulation, and report generation using Excel spreadsheets. This was a time-consuming and labor-intensive process taking several days each month, prone to human error and often resulting in outdated information.

●       Lack of Real-Time Visibility & Limited Actionable Insights: Existing reports provided a static, historical view of sales performance and lacked the dynamic capabilities to provide real-time insights or diagnostic analytics. This limited the sales team's ability to proactively identify emerging trends, assess the impact of sales initiatives, and make timely adjustments to strategies.

RESULTS

The implementation of the SPIN platform transformed the company's sales analytics capabilities and delivered significant benefits:

●       Enhanced Data Visibility & Real-Time Insights: The SPIN platform provided real-time visibility into sales performance across all key metrics, replacing outdated static reports with dynamic dashboards. This empowered the sales team with up-to-the-minute information to make informed decisions.


●       Improved Sales Performance Analysis & Trend Identification: Interactive visualizations and drill-down capabilities enabled in-depth analysis of sales trends, allowing the team to quickly identify areas of strength and weakness, as well as emerging opportunities and challenges across different market segments.

●       Increased Efficiency & Productivity Gains: Automating reporting processes eliminated the need for manual Excel spreadsheets, significantly reducing time spent on data manipulation and report generation. This freed up valuable time for the sales team to focus on higher-value activities, such as customer engagement and strategic planning.

●       Insights-Driven Decision-Making & Optimized Sales Strategies: Access to comprehensive, real-time data and interactive analytics empowered the sales team to make more informed, data-driven decisions, leading to more effective sales strategies and improved resource allocation.