Retail Company Advanced Data Analytics | Case Study
A leading CPG company, provider of automotive services, and supplier of premium DIY motor oil sought lucid consumption of analytics instead of reporting. They were in a bind to compete in a price-driven industry to optimize their trade promotion spending, pricing strategies, and demand forecasting capabilities to drive top and bottom-line growth.
Challenges
With data exploding in both quantity and complexity, our client required agility in insights and decision making to respond better towards market changes. Hamstrung by lack of analytics, our client was unable to create an insights-first organization with decentralized decision-making.
- Developing insights through stand-alone BI applications is a time taking process that requires a lot of data preparation in the initial stage. That delays the consumption of insights thereby elongating the decision cycle.
- Our client faced difficulties in identifying and prioritizing high-impact analytics use cases driving business objectives and key decision making.
- Lack of consensus and coordination among business units regarding the usage of appropriate technology, governance, and processes hindered the enablement of advanced analytics tools.
- Adoption of analytics also suffered due to lack of champions for change in the senior management and unreliable reporting due to data structure/attribution challenges.
Client
Retail Company
Solution
Optimized Promotion Spending and Pricing
At a glance
The customer was seeking to compete in a price-driven industry, through better insights and decision-making agility. Applexus collaborated with the client to create an overarching strategy and digital transformation roadmap with data and analytics at the core for driving key decision-making based on data-driven insights.
Solution
Applexus engaged with the client to develop an overall vision for their data and analytics strategy and roadmap. Armed with the insights through assessment frameworks, we focussed on creating a digital transformation roadmap with analytics at the core of decision making.
- Analytics use cases were identified and segregated among Quick wins, Short Term, Long Term, and High-Value Use cases. A detailed analytics roadmap was designed, incorporating the use cases driven by business priorities.
- A unified analytics technology platform on SAP Datasphere and SAP Analytics Cloud was designed to support the analytics use cases roadmap
- To drive the technology adoption self-service consumption of analytics was enabled for business users.
- Processes, skillsets, capabilities, and training needs aligned with the overall analytics strategy were recommended to actualize an agile analytics-driven organization.
Results
The solutions implemented articulated the strategic direction of the company. They could strategize and drive key decision-making based on data-driven insights. The analytics roadmap and the uses cases defined the path to transition from reporting to analytics. Decision-makers were able to optimize trade spending and leverage accurate forecasting to drive top and bottom-line growth. A self-service platform to consume such insights with proactive alerts and recommendations on business metrics helped in making better and faster decisions. These ultimately resulted in improved agility to address the market changes.