Decision Point - A Customer Centric Sales Approach for Mapping Actionable Data Insights
With the rising emphasis on size of data within the analytics world, hype is experienced around Big Data. The rapid increase in data-driven business culture is accompanying an augmented demand for easy-to-use analytics tools. But what’s critical to understand is that the true growth of the analytics market can happen when analytics get more embedded into decision making at all levels of the organization. Headquartered in Delhi NCR, Decision Point, a Consumer Analytics & Consulting company believes that analytics technologies need to focus on “Value Extraction” from multiple data sources, by embedding the analytics solutions within the entire business process of an organisation.
Decision Point sets up an analytics center of excellence (CoE) to institutionalize high quality analytics.
Founded by Ravi Shankar along with his classmates from IIT Madras, with diverse experience across FMCG & Marketing Analytics domain, Decision Point develops analytics & big data solutions for CPG/Retail& Consumer focused industries. The firm serves a huge clientele, including several global Fortune 500 clients, in 20+ countries across emerging markets such as India, South West Asia, ASEAN, Central Asia, Middle East and Africa. “Our key success driver is the journey to make organizations see value by integrating multiple sources of data across functions rather than being analysed in silos.” affirms Ravi Shankar, CEO.
Multiple delivery models for Institutionalizing Advanced Analytics
For the clients looking for getting analytics embedded into their business process, Decision Point sets up an analytics center of excellence (CoE) to institutionalize high quality analytics. All major decisions, be it new product launch, pricing or major consumer promotions are all evaluated through CoE to maximize effectiveness of the interventions, there by generating additional incremental revenue. In order to facilitate development of best in class forecasts across sales SKUs, channels ®ions; Decision Point leverages advanced time series models such as ARIMA and other machine learning models. Decision Point further brings to the table multiple price sensitivity models based on both store level and aggregated data to assure correct management decisions in terms of pricing – volume trade-offs and developing a prioritization matrix for pricing changes across the entire portfolio based on the trade-offs.
To facilitate CPG organizations in extracting value from the customer (store) level data that is being generated within the traditional trade retail channel, Decision Point accomplishes a SaaS product- CUSTARD (CUSTomer Analytics & Response Dashboard). Developed within a big data environment to handle massive scale of data, CUSTARD furnishes various advanced analytics models to analyse the customer universe; and decompose growth within outlets based on effects of range selling, drop size and invoicing frequency. The product assists clients in deriving direct actionability for developing store level tasks and empowers organisations to track if the diagnosed actions have been taken within the stores.
“At Decision Point, we firmly believe in developing actionable insights from big data analytics and all our work is focused on ensuring that the clients derive business value from the work we do.” states the CEO. Considering CUSTARD as a key turning point for the company, Decision Point aims at using the product to embed big data analytics within the sales force processes and facilitate conversion of insights into actions seamlessly.
For the clients looking for getting analytics embedded into their business process, Decision Point sets up an analytics center of excellence (CoE) to institutionalize high quality analytics. All major decisions, be it new product launch, pricing or major consumer promotions are all evaluated through CoE to maximize effectiveness of the interventions, there by generating additional incremental revenue. In order to facilitate development of best in class forecasts across sales SKUs, channels ®ions; Decision Point leverages advanced time series models such as ARIMA and other machine learning models. Decision Point further brings to the table multiple price sensitivity models based on both store level and aggregated data to assure correct management decisions in terms of pricing – volume trade-offs and developing a prioritization matrix for pricing changes across the entire portfolio based on the trade-offs.
To facilitate CPG organizations in extracting value from the customer (store) level data that is being generated within the traditional trade retail channel, Decision Point accomplishes a SaaS product- CUSTARD (CUSTomer Analytics & Response Dashboard). Developed within a big data environment to handle massive scale of data, CUSTARD furnishes various advanced analytics models to analyse the customer universe; and decompose growth within outlets based on effects of range selling, drop size and invoicing frequency. The product assists clients in deriving direct actionability for developing store level tasks and empowers organisations to track if the diagnosed actions have been taken within the stores.
“At Decision Point, we firmly believe in developing actionable insights from big data analytics and all our work is focused on ensuring that the clients derive business value from the work we do.” states the CEO. Considering CUSTARD as a key turning point for the company, Decision Point aims at using the product to embed big data analytics within the sales force processes and facilitate conversion of insights into actions seamlessly.
