1.4.1 Business Ramifications
Consider the following examples of companies that have implemented big data analytics:
- The global cement giant CEMEX has successfully applied analytics to its distinctive capability of optimized supply chains and delivery times.31
- Walmart relies extensively on analytics to run its entire supply chain.
- At Deere & Company, a new way of optimizing inventory saved the company $1.2 billion in inventory costs between 2000 and 2005.32
- Proctor & Gamble used operations research methods to reorganize sourcing and distribution approaches in the mid-1990s and saved the company $200 million in costs.33
- Amazon claims its latest advanced analytics can now predict purchases before they happen. Based on the pattern of customer computer searches and how long the cursor lingers over a Web site, the company plans to start bundling and shipping items to distribution centers in advance of actual purchases.34
Questions that were once based on intuition and guesswork can now be answered in objective and quantifiable terms. Big data analytics answers business questions such as the following:
- What does the future look like? What do our customers want?
- What is the reason for our success? Is our strategy working?
- What activities should we pursue in the future? Which resources should we invest in?
- What do we do to minimize our risk exposure? How do we protect ourselves from business disruptions?
1.4.2 Changing the Present and Future
The ability to answer these questions changes virtually every aspect of business. It enables understanding both the present and future. As such, it can enhance a company’s competitive position by better predicting competition and markets. It can dramatically improve operational and supply chain performance. For companies that have implemented big data analytics, it can increase productivity and improve efficiency, quality, and preventive maintenance. It can help manage suppliers and customers, as well as logistics and transportation operations. It can also better evaluate strategy, improve forecasting, help prepare for disruptions, and, overall, improve risk management.
Harnessing big data analytics has the potential to improve efficiency and effectiveness, to enable organizations to do more with less, to produce higher-quality outputs, and to increase the value-added content of their products and services. Companies can leverage their data to design products that better match customer needs. No more guessing what the customer wants. Through in-store behavior analysis and customer microsegmentation, companies can optimize market segments and know exactly what the customer is buying. In fact, analytics is moving businesses into an era of “shopper marketing”—monitoring and creating an entire shopping experience for customers no matter where they are along their shopping path: at home (online), on the go (through geolocation), and within stores (in-store monitoring).35
Data can even be leveraged to improve products as they are used. An example is a mobile phone that has learned the owner’s habits and preferences—that holds applications, photos, and data tailored to that particular user’s needs. That device will therefore become more valuable with use than a new device that has not become customized.36
1.4.3 Creating New Business Opportunities
The information potential of data is opening all kinds of new business opportunities. Consider the possibilities from the mere ability to gather data about how car parts are actually used on the road. This data can be used to improve the design of parts and is turning out to be a big competitive advantage for the firms that can obtain the information. Consider the company Intrix, which collects geolocation information. In 2012, the company ran a trial of analyzing where and when the automatic braking systems (ABS) of a car kicked in.37 The premise was that frequent triggering of the ABS on a particular stretch of road may imply that conditions there are dangerous, and that drivers should consider alternative routes. With this, Intrix developed the service offering to recommend not only the shortest route, but the safest one as well. This is an entirely novel area of business.
Big data is also helping create entirely new types of businesses, especially those that aggregate and analyze data. Data is the new asset and most organizations are unable to keep up with its rapid growth, scale, and evolution. This is not their core competency. As a result, most non-IT companies are turning to some solutions providers for help. Companies are routinely outsourcing this capability and turning to third parties. This is the rise of the third-party analytics provider (3PA). These are various analytics and IT experts, data brokers, software vendors, and solutions consultants. Similar to third-party logistics providers (3PLs) that orchestrate the movement of physical goods, these companies coordinate and make sense out of large data flows.