Data Science as an Aide in Making Manegerial Decisions

Businesses nowadays are enormously impacted by decisions, whether simple or complex, made by entrepreneurs running them. These decisions affect the business's long term success. Data science uses statistics mathematics and programming expertise to extract meaningful insights from data. The use of data in business operations and activities nowadays is indispensable. Data science plays an essential role in virtually all aspects of business operations, from inventory management to financial statistics. It feeds our need for insatiable scrolls on social media platforms to our insatiable stomachs with efficient 10-minute food delivery systems. From collecting massive data sets to analysing them data science joins the dots between massive databases and meaningful insights for entrepreneurs to make informed decisions.

Today I specifically want to focus on two areas of business namely operations and finances.

From an operational standpoint, data science initiatives can optimize supply chain management, product inventories and distribution networks. The supply chain management and by extension the delivery business is highly reliant on factors like basket size, delivery distances and costs. Zomato has recently announced plans for 10-minute delivery systems these delivery timespans can only be achieved with affordable delivery rates if Zomato figures out what a customer is likely to order and when. This data needs to be collected and analysed from consumer behaviour and spending patterns from the app that will help them cut delivery times and set up efficient food preparation points.

Similarly, BlinkIt formerly Grofers pivoted from grocery delivery to instant commerce. They now deliver groceries and other items one might find at a local general store. This move increases their basket size and gives them access to items with a low-cost supply chain than groceries that can go stale thus increasing business. This is how businesses like Zomato and BlinkIt influence their managerial decision of supply chain management using Data Science. Similarly, accurate data collection and analysis has a major impact on financial statistics for Businesses.

Traditional banks can't lend money to micro, small and medium enterprises without an instrument to measure the risk of lending money to a business. So despite merchants having a healthy balance sheet and incremental increase in their growth very few banks lend them money due to a lack of documents and collateral and this unmet credit gap is estimated to be a trillion-dollar opportunity in India.

BharatPe, a leading fintech giant, uses data science and artificial intelligence to take a note of the cash inflow, monthly inventory, spending patterns and several other parameters, every time the merchant uses the app to make and receive payments, it uses this data to estimate the projected savings, income consistency and other factors to decide the credit worthiness of a merchant. Once enough data is collected BharatPe will immediately process loans without any paper or collateral. BharatPe has already facilitated loans to over 3 lakh merchants and disbursed over 2,800 crores in loans, with a 96% repayment rate. All of this Data analysis leads to better risk assessment, better risk assessment means less bad debt which means more profitability. This is how BharatPe influences its managerial decision of risk management using Data Science.

As Carly Fiorina, former H.P. CEO remarks,

“The goal is to turn data into information and information into insight”

And data science can do exactly that by providing crucial insights detrimental to the success of a business.