Data is the Lifeblood of the Digital Economy

Suresh Ramakrishnan, VP, SAP Digital
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Suresh Ramakrishnan, VP, SAP Digital

The age of digital transformation is truly upon us and going strong. Every day, we hear of a new company with an exciting business model that is set to shake up the status quo and disrupt traditional business in their industry. We are familiar with the leading examples of these transformative companies, such as Uber and Airbnb, which have disrupted their respective industries.

Digital transformation, however, is not restricted to consumer businesses. Traditional Business-to-Business (B2B) enterprises are waking up to the potential and looking for ways to tap into it to deliver new services to their customers. For example, John Deere is moving beyond simply selling farm equipment and plans to use data from sensors on its equipment along with external data on weather and soil conditions for optimizing farm output and operations. This is an excellent example of data being collected from multiple sources and analyzed to dramatically improve farm operations—from optimizing equipment maintenance schedules to minimize downtime to crop cycle planning to maximize yields. 

Another example is The Climate Corporation, which began as a start-up in Silicon Valley in 2005 (and was subsequently acquired by Monsanto in 2013) and has disrupted the U.S. crop insurance market, reducing farmers’ financial risks. The company collects information on weather patterns, local climate conditions and soil characteristics. Using these insights, it offers farmers highly customized insurance policies against damage from weather events. The ability of The Climate Corporation to monitor weather and related conditions in real-time results in timely assessments of weather-related damage, and significantly streamlines the process for farmers to file and receive payments against claims. Similar examples abound in financial services, manufacturing, supply chain, public sector and other traditional industries.

  Data is not only more available, it is more easily accessible and shareable because of the ease of cloud deployment and increasing use of APIs 

If you peer under the covers of these new services, a common theme emerges—the transformative use of data. Data from customers (e.g., both drivers and end users in the case of Uber), data from newly digitized processes and assets (e.g., tractor sensors), and, of significant importance, data from external sources (e.g., weather data).

According to Experian’s Global Data Quality Research Discussion Paper 2015, 95 percent of companies feel driven to use data to understand customer needs, find new customers or increase the value of each customer. In the U.K., 90 percent of businesses believe data is changing the way they do business.

The underlying trends fueling this growth of data-driven services are the dramatically increased availability of data from an increasing number of sources and ease of accessibility of data made possible by advancements in technology.

Increased Data Availability

With increased digitization, significantly more data is being generated, from a much wider variety of sources, and at a more frequent pace.

We used to think of data mostly from a business viewpoint, as data generated from business transactions, but almost every action now leaves a digital footprint and generates data. We have data pouring in from an increasing number of sources, including sensors and devices that form the Internet of Things (IoT), from social networks, research data, government data, and from an organization’s own systems.

Improved Data Accessibility

By some accounts, the amount of data is growing exponentially, doubling every two years. However, more data by itself does not necessarily mean more value. For data to be valuable, it needs to be curated and made easily accessible.

According to Forrester Research, 70 percent of companies that grew over 15 percent.

YOY believe external data from partners is strategic to their firms' overall business strategy, and 72 percent believe the same for third-party data.

This means that companies understand they cannot generate or own all the data they need to deliver the right services to their customers. There is significant value to be gained from data provided by partners or other external providers.

This concept of organizations obtaining data from external vendors is not new. Several institutional data vendors and providers like Dun & Bradstreet and Reuters sell curated and aggregated datasets to businesses. The important shift is happening, however, with the ease of making data available in the cloud and use of APIs significantly increases accessibility, the barrier to sharing data has been lowered dramatically. Technology is making it easier for organizations to publish valuable data and give access to customers and partners. As a result, a growing number of organizations are publishing an increasingly large number of datasets, including private companies, research institutions, educational institutions, and government agencies.

One prime example is the data.gov site from the U.S. government, which hosts more than 192,000 datasets (e.g., information on population statistics, demographics, health, agriculture, energy, education). These are made accessible through APIs, allowing developers to easily build a wide range of applications.

An example is Zillow, providers of a website in the U.S. offering detailed information on real estate, including current home values, price history, neighborhood comparisons, information on schools, and pricing trends for neighborhoods. This is based on data from Zillow’s own primary research, combined with data from public records (e.g., real-estate transactions) and external third-party data sources (e.g., maps, neighborhood stores).

Companies are thus bringing together data from multiple sources to deliver new products and experiences for their customers.

Data: The New Currency

Increasingly, companies and organizations are realizing the value that their own data may provide to their partners and others, and they’re looking at ways to share it for mutual benefit. An example is the multi-brand loyalty program Plenti that provides one common loyalty card used by several U.S. retailers, including Macy’s, Rite Aid, Exxon and Mobil. Customers can earn points by shopping at one of the participating retailers and redeem these points with several of the other companies in the group. In this case, since customer buying history gets shared across companies, it raises some consumer-privacy concerns–something to be addressed in a separate discussion.

Increasingly, businesses are also looking at ways to monetize their data by making it available at a price to other companies that can, in turn, use it to create new services for their customers.

In conclusion, data is not only more available, it is more easily accessible and shareable because of the ease of cloud deployment and increasing use of APIs. Combined with the new generation of big-data technology and infrastructure makes it possible to process, combine and create a new mash-up of services that can deliver significant competitive advantage. Organizations are more frequently using internal and external data to increase revenue by creating new offerings, sharing data with partners to create new services, or even monetizing data by selling to customers and third parties.

Data is becoming one of the most important corporate assets that can help drive revenue. It is indeed the lifeblood of the digital economy. 

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