Trends in Big Data: Three Ways to Reap Big Rewards
As big data comes of age, we will see a shift to a new normal. Three strategies can help organizations transform their big data initiative into an enabler of continuous competitive advantage.
by Yashpaul Singh Dogra, January 2013
Tectonic technology shifts in business have been accelerating at an increasing pace. Big data is the latest to quickly become the norm for enterprises, defining new opportunities to generate revenue and improve operations. No longer just the realm of Google, Facebook, and Amazon, big data is the new norm for enterprise analytics and pervasive across many industries; drug discoveries enabled by genomic research, real-time consumer sentiment and social interaction for retail represent a smale sample of business innovation derived from big data technologies and analytics.
In the past, businesses were limited by the available structured data within the enterprise and the size of data sets that could be managed by available systems. The ability to ask questions without limitations of data size, scope, and availability is liberating. An important effect is the transformation of entire business models utilizing these capabilities. In a recent McKinsey survey, nearly 70 percent of c-level executives believe that big data will result in increasing income. Hopes for big data as a transformational force in business are high. Here are three ways leaders in your organization can transform big data initiatives from a technology adventure into a systemic enabler of continuous competitive advantage.
1. Incorporate big data into your business DNA
MIT’s Center for Digital Business finds that data-driven companies have five percent higher productivity and six percent higher profitability. Managers that use data to driving decisions lead more profitable and more efficient organizations than their counterparts. In strategic business decisions, trust in rigorous data analysis wins out over intuition. Leaders will incorporate big data into the DNA of their business. Operationalizing it will accelerate their advantage. Businesses that enjoy the benefits of big data embrace data-driven innovation, building new initiatives based on big data analysis and experimentation. And with so many data sources available, the universe of possibilities for business innovation is increasing.
But building a smarter, data-driven business is challenging. It requires business insight, leadership, and skills that are foreign to many businesses. To develop a basis for self-sustaining big data innovation, managers will need to encourage skills that connect business acumen with that of a data scientist and a technologist. In reality, all of these skills are a scarcity—so finding individuals with all three presents a significant challenge. This equates to a shortage of two million managers and analysts in the coming years.
Many companies will strive to acquire big data skills through a combination of external hiring and internal development. Increasingly, existing managers will be tapped for big data cross-training. Leaders will develop their data-driven teams to systematically use big data methodology and disperse it throughout functions and business units. Winners in the battle of business wits will build capable organizations and operationalize faster than their counterparts.
2. Experiment efficiently and effectively
Scare resources and funds will drive demand for greater efficiency of big data analysis. As big data initiatives scale, managers will increasingly scrutinize investments and the returns achieved. On average, companies will spend US$15 million annually on big data projects. Clear, hypothesis-based experimentation tied to business impact will lead the pack for funding. If this model sounds familiar, it should. This is the approach that most researchers and scientists use to prioritize funding for experimentation and research. In the big data world, business and IT are strongly tied together. To efficiently allocate resources, both will play an equal role in developing ideas, evaluating project risk, and understanding business impact. Keeping the initial projects simple and showcasing business benefits is the way to self-funding transformation.
3. Make sure your IT can keep up with business demands
By now, most understand that big data is large amounts of data in terms of volume, velocity, and variety—with more than two exabytes of data created every day and doubling every 2.5 years—and sifting, collecting, and acting on insight from the data torrent in new work for many IT leaders. With big data, normal architectures and business intelligence methodologies may not apply. The challenge in mastering big data technology is that it varies in context of the analysis. Leaders will identify repeatable patterns of technology that can be mastered for efficient scale.
An operational approach to big data will drive IT organizations to generalize capabilities in three main areas:
The ability to consume large amounts of data and manage relevant information across its useful life
The decision-making capability provided by advanced analysis and data manipulation capability for large data sets
Integration of data into business operational processes
With each completed big data project, the components necessary for scale evolve to maturity with a higher degree of reuse. The result is a lower unit cost of data experimentation and innovation.
Big data is quickly becoming a part of the enterprise fabric for many companies. In the coming years, we will see a shift to the new normal as big data comes of age. Expect to see a definitive increase in big data use cases, maturing technologies, and a data-driven culture as the forces of change. Embracing the big data shift faster and more efficiently than competitors is the path to business growth and prosperity.
Yashpaul Singh Dogra is a senior director with Oracle Insight, focused on data center technologies.