Business Intelligence - Data Analytics Simulation

Business Intelligence

Data Analytics Simulation

Methodology – A thorough assessment of the market situation was carried out prior to development of a business strategy to increase market share and revenue for our brand, Blue. Customer preferences, market size, competitors’ strengths and our existing business model were analyzed to discover opportunities for our brand.

Segmentation, targeting & positioning – Competitors’ positioning and price points were noted. Segmentation was done along the demographics of age and income. The largest segment was the low income (<40,000/yr) and younger (<35 yrs) customers and the same segment was targeted by considering their preferences in terms of product formulation (pods), price sensitivity, trade channel, media channels and the social media conversations. The data explorer tab with relevant filters was used for this purpose. In the subsequent rounds as well, the same market segment was targeted with minor changes to the pricing in each round. The ‘Geographic Demand’ tab was used for forecasting the region-wise sales in each year.

Production Levels – The production levels were decided in each round using the ‘Reports’ tab and looking at the differences between demand and production in the previous period as well as any current on-hand inventory and comparing this figure with the forecasted demand for next year.

Competition – Competitors’ response to our strategy was closely monitored at the end of each period and our own strategy was modified as per need. For instance, in 2022, the price per load was reduced from $6.75 to $5.50 in response to a competitor, Store, reducing their prices sharply to gain market share.

Outcome – By having a focused approach and targeting the low income and younger market segment through low prices and customized product offering, we were able to capture increased market share of around 20% by 2022 and cumulative operating profit of $296.8 million.

Takeaways – The advent of BI programs and access to a vast amount of data provides business managers with very real opportunities for understanding the markets they compete in and use the available data to their advantage. The managers, however, still need to use their own judgement and business acumen to turn raw data into decision support data by looking for the most relevant metrics and asking the right questions. The BI tools are thus only an aid to the decision making process for a business manager.