Identify growth opportunities across functions
The Big Picture
A global CPG company needed to be able to predict and identify potential areas of growth that would apply to future scenarios in multiple markets and product lines (e.g., household detergent and food products). Multiple, cross-functional business teams needed to understand which areas of their business would grow and which would decline ensure future, sustainable profitability.
Transformative Solution
The company chose to implement a growth driver analytics suite of the right tools to have a ‘forward-looking view’ of likely performance, and identify granular opportunities for growth. The initiative aimed to empower cross-functional business teams to preempt declines in business in specific markets, and accordingly make the corrective measures to bring back momentum in demand and sales.
A Bayesian Network approach was used to bring together all KPIs that come from across business-functions, and tie them together in a network structure, to capture the interrelationships among various dimensions and attributes. Through these models, Fractal captured the direct and indirect impact of various KPIs on business performance (sales), and hence the total impact in terms of elasticity. With the help of these network structures, Fractal could identify the set of drivers for any element in the structure and determine how to influence future incomes.
Additionally, the teams were able to capture lead-lag relationships among various KPIs so they could preempt changes in any KPI with the use of other driving KPIs.
The Change
A front-end platform for business users was enabled providing the required intelligence, empowering the cross-functional business teams to be agile and accurate in decision-making. The platform employed three core modules:
- An Early Warning System that provides a forward-looking view of likely changes to the momentum of sales in the next few weeks or months. This helped spot areas of issue or opportunities, which could require interventions.
- A Drivers Discovery Module that is used to uncover key drivers in a market and identify potential levers to pull to gain momentum. This augmented CCBT with differentiated drivers and brought out the relative importance and impact of different levers in the current environment.
- A Simulator Module that was used to run different scenarios of interventions, and predict the likely outcome, and hence enable the company to course correct the investment plan.