You might be amazed to see how smart cars are these days. When you were growing up you just had the basics like fuel tank indicator, speedometer, and tachometer. Today, even the basic cars have everything from fuel consumption efficiency to range (how much distance you can go before you run out of fuel) wrapped in a small cockpit. What’s more interesting is the kind of intelligence that is in-built in the car to help you drive better- adaptive cruise control, rearview cameras, and collision warning systems. All these ease the decision-making process when you are behind the wheel. Similar concept extended into the operations of an organization can create a powerful impact.
According to a survey by Bloomberg Businessweek Research Services, 97% of respondents to the survey mentioned that their companies have adopted data analytics. The major drivers for analytics adoption were the ability to cut down operational costs, improve risk management, and increase profitability. The two major areas where analytics helped their organizations: improved customer service and effective resource allocation.
The goal of any business organization is to serve the maximum number of customers in the most efficient and best possible way. Data analytics is the secret sauce helping organizations accomplish this and improving business operations. The most competitive organizations today are using data analytics when making important operational decisions.
Without much ado, here’s how data analytics helps organizations scale up business operations efficiently –
Consumer Analysis to Increase Business Opportunities
Data analytics helps companies make the most out of consumer patterns. According to Mckinsey, research organizations that use consumer behavior patterns are outperforming their peers by 85% in sales growth margins and close to 25% in gross margins. Knowing who the most profitable consumers are is crucial to every business. Real-time consumer pattern demand information helps organizations identify their loyal customers, match the inventory with their orders accurately, predict seasonal spikes, depression, and trends. Consumer behavior analytics makes it more realistic for the organizations to –
- Identify new sales opportunities
- Determine customer lifetime value
- Connect and engage with more consumers
Delta Airlines, the US-based travel company, is using data analytics to tackle the pain points of customers. Delta monitors tweets from its customers on flight delays, upgrades, lost baggage, in-flight entertainment, and more. The sentiment analysis of tweets helped Delta understand that lost baggage was the biggest pain point for customers. To solve this, Delta now uses RFID generated data so that customers can track their baggage from their smartphones. Leveraging data analytics and technology, Delta became the first major airline to solve this huge pain point of customers.
Risk management is an integral part of business operations regardless of the sector. For a business to remain profitable, identifying potential risks and mitigating them before their occurrence is critical. Today, it is impossible and unthinkable to imagine a world of risk management without access to data, analysis, and reports.
Data analytics is a major contributor to the development of risk management solutions to achieve smarter risk mitigation strategies. Analytics has become an integral part of risk management strategies because of its ability to scan through large volumes of data sets to identify and detect vulnerabilities. Organizations are empowering themselves against imminent threats and risks by adding data analytics to their arsenal. Analytics is the magic wand for many Financial institutions in risk assessment and management. It powers risk assessment of loans and cash investments. For instance, a loan for a building renovation can be better assessed based on the climatic conditions of the geography, age of the building structure and other data points on the loan applicant.
Financial institutions are leading the analytical space by exploiting transactional and behavioral consumer data. Analytics helps banks identify customers with poor credit scores so that banks can avoid lending money to them. For example, Citibank invested in a data science company Feedzai that uses analytics and real-time machine learning to pinpoint fraudulent. As a result, Citibank has been able to minimize financial risk by identifying suspicious transactions and promptly notifying users of the same.
Innovation and Product Development
Gone are the days when organizations would rely on their intuition to improve the quality of their products and streamline them. Today, every service or product design process has to begin from understanding what exactly customers want. Data analytics helps organizations study customer needs through various channels to identify the best approach to capitalize on customer requirements before designing new products and redesigning the existing ones.
The popular consumer goods manufacturer Procter & Gamble (P&G) leverages analytics successfully into its new product development process by analyzing data from various brand touchpoints. For instance, P&G used various modeling and simulation tools to cut-down on prototyping expenses by determining how the molecules in a dishwashing liquid react over time, helping them refine the product.
Optimize Supply Chain and Logistics
From transport to logistics, bottlenecks can be present in any part of the business operations. Data analytics is critical in identifying and solving these bottlenecks to restore efficiency. Organizations are reaping the benefits of data analytics by optimizing operational efficiency in the supply chain and logistics. Leveraging analytics helps optimize delivery routes, time taken for delivery, and delivery methods.
With over 4 billion items shipped annually in over 100,00 vehicles, UPS uses data analytics to manage fleet optimizations. UPS invested heavily in ORION (abbreviated as On-Road Integrated Optimization and Navigation) software that does a lot of data crunching on user preferences, driver routes, and package information. ORION has helped UPS save over $300 million annually by trimming 364 million miles from drivers’ routes and saving more than 39 million gallons of fuel.
Its clear data analytics has the power to help a company make better operations decisions. Leveraging analytics by combining data from various channels can help an organization glean in-depth insights into their strengths and weaknesses. Organizations that have leveraged analytics have been successful in increasing profit margins by improving efficiency and cutting costs.
Springboard brings a comprehensive data analytics program with a unique combination of all the required analytics skills to help professionals effectively optimize business operations.