Six Real-World Business Cases for Big Data Utilization_Data Analyst Exam

Big data is changing the competitive landscape of the marketplace. And companies that are able to fully utilize big data analytics are often able to deliver products and services to the marketplace faster and better stay in tune with customer needs and desires.In 2014, a survey by research firm Gartner found that 73 percent of companies surveyed have invested in big data or plan to invest in big data projects in the next 24 months; this compares to 2013's percentage was 64 percent. Improving customer experience and process efficiencies were ranked the highest priority by respondents.

Improvements in customer experience are happening both online and offline, with data being collected from smartphones, mobile apps, POS systems and e-commerce sites, among other channels. With organizations able to collect and analyze more and richer types of data information than ever before, it's important to quantify what they're doing today and why. And, that's the most flexible means of adjusting one's business strategy to increase or maintain market share. In execution, improvements in customer experience can help increase customer loyalty and corporate revenue growth. On the other hand, if a company chooses to ignore relevant data, they are likely to lose customers and deals to competitors who are more responsive and savvy about data analytics.

Improvements in business processes continue to focus on increasing efficiency, saving money, and improving the quality of a product or service. Big data can provide deeper insights than traditional systems because it is backed by analysis of more data points and data sources.

Whether a company's goal is to drive revenue growth or speed time-to-market for a product or service, optimize the workforce, or achieve other operational improvements, the heart of the matter is with becoming more proactive and less reactive, which means using predictive analytics to shorten the learning curve.

There are many ways to use big data to enhance and improve business operations, and six typical examples are described below.

Shortening time to market

Launching a new product or service involves multiple lifecycle stages, some of which are easier to accelerate than others. Over the past few decades, drug makers have used clinical trials to simulate learning speeds, reduce costs, and minimize unnecessary burdens on patients participating in trials. With cloud computing and big data, clinical trial simulations can become even more beneficial to manufacturers and patients.

Bristol-Myers Squibb (bristol-myers squibb) reduced clinical trial simulation time by 98% by expanding its on-premises hosted grid environment to the AWS cloud. The company also further optimized dose levels, making drug products safer and requiring fewer blood samples from clinical trial patients.

Because clinical trials are highly sensitive to data, Bristol-Myers Squibb set up a dedicated, encrypted VPN tunnel linking to the Amazon gateway and configured a virtual private cloud to enable it to run its environment in isolation from public customers.

Before moving to the cloud, the scientists were using an ****-enabled on-premise environment, so it took 60 hours to run about hundreds of projects. Now, each scientist has a dedicated environment, and 2,000 projects can be processed in about 1.2 hours without causing disruption to the rest of the team.

After migrating to the AWS cloud, Bristol-Myers Squibb was able to reduce the number of subjects in clinical trials for pediatric research from 60 to 40, while also shortening the study duration by more than a year.

Optimizing the workforce

The human resources departments of some companies are using talent analytics and big data to reduce costs and thus effectively manage HR-related issues. Big data helps them to be able to effectively select new hires that will fit better into the organization, reduce employee turnover, understand skills and the current market labor output, and identify the talent needed for forward growth of the company.

Xerox used big data to reduce turnover in its call center by 20 percent. To do this, it was important to understand what was causing employees to leave and determine how to improve employee engagement.

Improving financial performance

Organizations' finance departments have moved beyond just regular reporting and BI efforts; they're already starting to leverage big data to mitigate risks and costs and look for opportunities to improve the accuracy of their forecasts. Specifically, they're using data to identify high-risk customers and suppliers to stop fraud, find revenue leaks, and uncover new or more efficient business models.

A recent partnership between The Weather Company, a weather forecasting company, and IBM will allow business users to better manage the impact of weather conditions on business performance. According to The Weather Company, each year, weather factors cause $500 billion worth of economic impact in the U.S. alone.

This weather data comes from more than 100,000 weather sensors and airplanes, as well as millions of smartphones, buildings and vehicles running on the road. This data is combined with other data sources from 2.2 billion unique forecast points to make an average of more than 10 billion real-time weather forecasts per day. Retailers, for example, can use this data information to adjust staffing and supply chain strategies. And energy companies will be able to leverage this weather data information to improve supply and forecast demand. Insurance companies will be able to warn their policyholders of severe weather conditions so they can reduce the likelihood of automobile damage during hailstorms.

Smart Selling

Slight modifications to your organization's sales and marketing strategy could have a profound impact on your business's sales performance, especially when planned modifications are made as a result of big data analytics.

Imagine a six-week direct mail campaign with a coupon return of more than 70 percent. That compares to an average direct mail return of just 3.7 percent, according to the Direct Marketing Association. And how does the grocery chain Kroger Co. do it? For one thing, they use personalized direct mail based on customers' individual shopping histories.

Kroger's customer membership card program is rated No. 1 in the food industry. More than 90% of customers use their membership cards to purchase products. While there are other factors that have ****ed together to make Kroger's financial performance so impressive, its 45 consecutive quarters of sustained growth is at least partially attributable to its customer loyalty program.

Minimizing equipment and asset failures

Organizations want to avoid unnecessary business interruption disruptions and customer anxiety. Now that sensors are embedded in everything, organizations can use this data information to determine when repairs are needed on planes, trains, cars, and other electrical equipment. Ideally, when a problem has arisen, companies want to understand what caused the issue and how it can be fixed, ideally with a specialized repair team.

Pratt & Whitney, a unit of United Technologies Corp. tries to reduce unplanned aircraft engine repairs. According to Airinsight.com, today's engines are capable of collecting about 100 parameters from multiple snapshots during an airplane's flight. By comparison, the new generation of engines is able to collect 5,000 parameters about a continuous flight. This process generates about 2 gigabytes of data. Using this data information, Pratt & Whitney and its partner IBM were able to perform proactive maintenance.

Leveraging customer lifetime value

Today's authorized customers are more demanding and fickle than ever. In order to maintain or increase market share, companies need to know as much as possible about their customers, continually improve their products and services, and be willing to adapt their business models to reflect the actual needs of their customers.

AvisBudget, an American car rental company, has been working on this. They have increased their market share and achieved hundreds of millions of dollars in additional revenue by implementing an integration strategy. Proactively engaging in determining customer value segments and providing tiered incentives to increase customer loyalty. The company's IT partner, CSC, used modeling to predict the lifetime value of AvisBudget's customer database and validated its use of multi-channel marketing campaigns and corresponding analytics.

The customer assessment data now incorporates other data, including customer rental history, service issues, service area demographics, business affiliations and customer feedback, among others.Avis Budget also collects and analyzes social media data. The company has a team of social media experts who specialize in brand marketing. The company also recently updated its website to further improve the customer experience, and they are using big data to predict regional demand for fleet placement and pricing services.

These are the six real-world business cases for big data utilization that I've shared with you, and for more information, you can follow Global Green Ivy to share more dry goods