Industry
CPG
- The dashboard offered an improved and detailed explanation of factors contributing to function and product performance across different regions and hierarchies
- Greater alignment between data originating from different business horizontals
- The data consolidation and visualization system was semi-automated for easier refresh of dashboards
- The solution saved the client a minimum 7 working days a month that was otherwise spent on manually compiling and analyzing data
- The creation of standardized data definitions and a centralized data backend enabled improved communication and decision-making across verticals and functions
The client, a CPG giant dealing in food, agriculture, financial, and industrial products and services worldwide, wanted to consolidate data across different business functions.
The lack of common data definitions had led to misalignment between functions. For instance, different regions were referred to using different terminology by the sales and marketing teams, leading to miscommunication and a poor overall understanding of business performance. This in turn led to inefficient decision-making and resource management, impacting profits negatively.
The client wanted to gain a holistic understanding of business performance through factors such as KPIs, sales, profit, and demand, to compare and analyze performance across years and geographies.
TheMathCompany examined the varied data definitions used by different functions in the business and created a standardized, ground-up, centralized data backend. Following this, dashboards were built for each business stream. By presenting detailed information on relevant KPIs, we enabled the client to reduce their reliance on traditional Excel-based data as well as better communicate, collaborate, and make decisions.
The following steps were undertaken to develop an AI-driven solution for data consolidation and visualization:
Data Processing: Raw data was periodically collated from multiple sources and extensively treated using R codes.
Consolidation: Files from different levels were effectively consolidated and information was mapped using mapper files.
Output: Relevant KPIs and metrics were displayed on multiple dashboards, which helped measure performance across verticals and regions. For instance, regional business heads were able to view data at a product, regional, sub-regional, and SKU level.
In addition, ready-to-consume data, including that on sales performance, demand forecasting, credit status, and inventory, was made available to different functions to facilitate informed and faster decision-making. The dashboards developed also had a regular refresh rate, enabling business users to gain an immediate and up-to-date understanding of their functions’ performance.
The AI solution helped provide a holistic understanding of business performance. Additionally, it aided greater collaboration between various functions and enabled the creation of common data definitions that could be used to better align internal and external initiatives.
