How Do You Navigate This “Age of Data Abundance?”


In this big data era, your enterprise’s approach to mining and managing this data could lead you to starve in abundance. How do you find your path?

Many of the business obstacles and constraints organizations have dealt with over the last few decades are diminishing, if not disappearing altogether, as we enter into a new age of technology and information. One benefit of the increasingly digital environment we call Business 4.0 is that most organizations have gained access to volumes of potentially transformative data, available to them anywhere, anytime.

This age of technology is one of great abundance – an abundance of data, of connectivity and of fast-paced business decisions. But how organizations choose to move forward in this new “Age of Abundance” will be certainly a factor in their ultimate success or failure.

Exponential Growth can be an Opportunity or a Risk

Organizations are swimming in a rising tide of data. This data lives in information systems, applications, devices and platforms, and it resides in the surrounding ecosystem – shared by suppliers, supply chain and distribution partners, investors, employees, end-use customers and consumers.

But it’s not just sheer volume. The sources and available types of data also continue to grow exponentially. In fact, 90 percent of the world’s current digital data was produced in the last two years, and the U.S. alone produces upward of 2.6 million gigabytes of internet data every minute. With so much information, it’s no wonder many organizations are paralyzed with indecision – what do we do with all this data? How do we manage it, use it – extract value from it?

See also: In Business 4.0, IoT is the great enabler

Organizations that have learned how to harness and apply this abundance of data are the ones most likely to be successful in a competitive Business 4.0 world. Let’s take ABB as an example.

ABB, the $34.3 billion industrial firm that services power plants and automates industrial processes, saw an opportunity to create a new revenue stream that relies on this abundance of data and the delivery of unique, valuable business insights. The company created a way to offer a data-based service to its customers – one that could leverage extremely valuable machine and process data, connectivity and intelligent insights to improve the end customer’s business. It’s not a surprise that has been a great success for ABB.

ABB credits its ABB Ability platform of services with driving an 11 percent increase in orders for its software and services in 2017. The platform collects real-time data and analyzes and monitors conditions at industrial facilities (such as factories, oil wells, and power plants) to reduce operating costs and improve safety and maintenance. ABB estimates the platform offers the potential for $20 billion in annual sales in the future.

The Haves and the Have-Nots

ABB saw an opportunity, took a risk by creating and offering a new service to customers and found that the company’s risk paid off. But, many other organizations are not even close to having this same kind of success. Why is that?

The reason is that they are data rich but insight poor. They have not been able to move past the collection and connection phases of Business 4.0 into the innovation phase. These organizations are not getting true value from their current data nor are they preparing themselves to leverage business insights made available from all these new digital technologies, evolving partnerships, data sources and more. Additionally, leaving enterprise and external data open to interpretation can lead to organizations missing competitive advantages by overlooking or ignoring contextual patterns hidden in data.

For these organizations to succeed in the Age of Abundance, they need to understand what customers want, why they buy, what they like and don’t like about current offerings, the customer’s future potential needs, what they are willing to pay and much more. Data can help inform and generate those observations and insights — but only if the data leads to actionable insights. Raw, unfiltered data isn’t going to give these organizations the answer. They must evolve from an early enterprise into a data-mature enterprise that understands how to interpret data patterns using advanced analytics capabilities such as machine learning or artificial intelligence and solve business challenges and open up opportunities while embracing calculated risks.

Untapped Sources of Insight-Rich Data

So, how does a company transform into a data-mature enterprise? The first requirement is to have a leadership team with a data-centric statement of purpose — a team that believes analytics and data are the foundation of their company’s digital transformation.

Leaders who are committed to the end result and business goal can then determine exactly how insights from internal and external data can create new business opportunities. For example, Cummins, a global enterprise that designs, manufactures and distributes engines, filtration and power generation products, developed a business model to provide a new service that diagnoses engine issues in real time by using telematics data to remove the guesswork and provide an immediate analysis and a recommended solution. Organizations that are using data like this start by assessing their data maturity (existing data inventory and what should be captured and analyzed) and, then, map out how to reach the target state over a period.

When embarking on this journey, there are three sources of data that are often overlooked. But these data sources may be the key to innovation, so they should be part of any analysis:

1. Existing, siloed data: Think about the siloes of data at your company. Chances are they exist in a number of business functions or services such as marketing or human resources. In most cases, that siloed data is not shared with other areas of the organization that could use and gain value from it. But it has tremendous value: according to a survey of 500 IT decision makers and business application users, nearly 72 percent believe organizations miss out on opportunities because of data silos; 56 percent feel those silos are obstacles to meeting business objectives and 47 percent believe disconnected data limits innovation. To gain value from data, it needs to be available and put in digital form for anyone in the organization to use — a (sometimes) difficult but necessary task.

2. Missing internal data: Most companies capture only a small percentage of data from their own operations, while others outsource aspects of their business operations to third-party vendors. Outsourcing allows vendors to capture large volumes of data, but the risk is that this data is not always made available back to the corporate organization.

For example, airlines typically outsource wheelchair operations to service providers, who may not use connected mobility solutions to manage operations on a real-time basis. As a result, most airlines fail to collect and analyze these valuable data points, which could help them positively address customer experience initiatives or operational delays. When internal or third-party vendor data exists but isn’t analyzed or used effectively, valuable insights, innovations, and opportunities to improve revenue or customer experience are lost.

3. New kinds of external data: The data marketplace provides all sorts of information that can lead to innovation if properly identified and used. Ride-share and taxi services, for example, can identify the trending restaurants and establishments people are traveling to for meals, and the time(s) of day most popular for transportation. That data could be sold to the restaurants, who can then create offers based on insights about customers’ dining habits and locations. This creates opportunities for businesses to collaborate in a digital ecosystem — one that could enhance customer experiences and expand sales.

See also: How handling data stream can lead to immediate insights

In the Age of Data Abundance, innovation is waiting right around the corner; waiting for organizations to connect the dots and create entirely new pictures of what they can achieve.

But organizations need to open their eyes to the data they may be missing in order to develop business-driven insights and truly innovate. Look beyond your own walls and take cues from organizations already experimenting with new services or value-added data-driven offerings. Ultimately, greater access to both data and insights, and the will to use data intelligently and effectively is what sets mature, insight-rich companies apart from their competitors.

Sources: IFL Science, July 26, 2017, accessed at
ABB Ability, accessed at
ABB quarterly results press release, October 26, 2017, accessed at
ABB 2017 annual report, page 24, accessed at
Vanson Bourne, “The high cost of disconnected data,” published by Snaplogic, 2017

Dinanath Kholkar

About Dinanath Kholkar

The author is vice president and global head of Analytics & Insights, Tata Consultancy Services.

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