How data can help reduce business expenses?

Your favorite airline is increasing “fuel surcharges” to your flight ticket. Your wholesale product supplier has increased the cost of raw material supply by 10%. Your business insurance costs increase by 10% to 20% every year on average. It is not just the large scale organizations but even small businesses are being succumbed by a constant increase in expenses. Controlling business expenses has become more important than ever. The only two ways for any business to build a strong balance sheet is to earn money or save money. A perfect balanced business strategy is to earn profits while minimizing business expenses to the minimum acceptable level. Data and analytics play a vital role in helping reduce expenses while protecting profits.

Data — A Strategic Cost Cutter

Data, or rather big data, is being hailed as a revenue generator, market developer, and a prime analyzer of consumer behavior. Now, it has also paved its way into operational cost-cutting. Research reveals that businesses that depend on data-driven strategies can glean insights faster for increasing overall revenue and cutting down on operational costs. Today, 65% of big brands are embracing data to stay ahead of the competition.

According to a report on “Big Data Use Cases 2015 — Getting Real On Data Monetization“, 40% of the companies leveraging data are enjoying diverse benefits like a better understanding of consumer behavior (52%), better strategic decisions (69%), and cost reductions (47%). Moreover, the organizations have reported an average of 10% reduction in costs and an 8% increase in revenues from analyzing data. Here’s how businesses can reduce expenses by leveraging data and improve their bottom line –

Reduce Logistic Expenses

Shipping can turn out to be a critical financial bottleneck particularly for businesses in the digital marketplace. Big data and analytics can benefit a business by reducing the staggering costs involved in getting a shipment from Point A to Point B. Real-time data vs. historical data are critical and having easy access to it helps businesses optimize processes and discover novel opportunities to cut down costs for a more cost-effective supply chain.

Take, for instance, Amazon. It offers free one day delivery for prime subscribers. With the intent to fulfill orders quickly, it links with manufacturers and keeps track of the inventory. Amazon analyses the data to choose a warehouse close to the vendor and the customer which helps the company reduce shipping costs by an average of 10% to 40%. Furthermore, using graph theory, the shipping costs are further reduced by determining the best delivery schedule, product groupings, and route.

Data also helps Amazon save on product return costs. On average, the cost of product returns is 1.5x the actual shipping cost of the product. Leveraging data analytics, Amazon assesses the probability of a product being returned so it can take appropriate measures to reduce return shipping costs. Data helps Amazon find out which cities have maximum product returns or what kind of customer segments usually exchange products. This helps Amazon adopt a proactive approach by calling customers and getting their feedback on a product and also reducing transportation and logistics costs.

Reduces Marketing Costs

Marketing is an integral aspect of business management and data has always been the indisputable king of the marketing space. Using customer profile data, marketers can make strategic business decisions and eliminate unwanted marketing costs substantially by identifying marketing strategies that are not likely to reap benefits for the business. Data helps identify the best channel for marketing that will lead customers towards a conversion or sale. Implementing data analytics is a plus point for businesses executing multi-channel marketing campaigns as it helps them go for targeted campaign execution at a lower cost. After all, the ability of a marketer to identify the right marketing channel for the right customer can save the business plenty of money.

For instance, an auto insurance company found that more than 80% of the total 100,000 households they sent marketing emails had the wrong demographics as those set of people would never buy insurance from them. After using data and analytics to identify the right demographics, the auto insurance company noticed a tenfold response rate and drastically cut down on marketing costs by conducting targeted direct email campaigns.

Reduce Fraud and Save Money for the Business

Fraud is rampant in every business domain, but data can help fight back. Depending on its type and reach, fraud can result in a costly affair for a business in any domain- retail, finance, insurance or others. Data, combined with analytics, can help organizations glean actionable insights to make fraud cases less prominent and constrict their effects.

Let’s look at an example of how data can help combat fraud in the retail sector. Most reputed retail organizations have a return policy on products purchased so as to build trust between the retailer and purchaser. For instance, if a person has proof of purchase and cites an explanation of why he/she wants to return a product, it is enough to process a product return. However, retailers are now identifying instances with the help of big data where customers might be returning products to participate in return fraud. Now if the retailer has information about what resembles the “normal” behavior of the customers who buy a specific number of products per year, they can easily identify and blacklist people participating in return fraud. Say the majority of people who buy at least 30 products from a retailer in a year return no more than four of them. So when a customer behaves in a manner that does not fit with the ideal behavior, retailers may tag them as blacklisted and ban them from shopping again. A 2018 survey found that 42% of online retailers have noticed an exorbitant increase in serial return activity. Tapping into customer data can help retailers identify and assess if a person is simply falsifying the reasons to return back a product purchase instead of blindly accepting the customer’s description of events.

Over to You

These are the most common business areas where companies can leverage the power of data and analytics to reduce expenses. It is evident from the above that data has great potential to help businesses reduce expenses and make strategic decisions. Big data and its related technologies- from data analytics and business intelligence to artificial intelligence — are all set to transform the business world. At Springboard, our focus is to help the learning community master the art of leveraging big data for competitive advantage through various comprehensive data analytics and data science programs by matching them with the specific needs of the aspirants.