Analytics: Fueling The Digital Economy

Mala Anand

The digital economy is significantly redefining how companies manage their business. Challenged to stay ahead of the massive changes that are disrupting the marketplace, organizations are turning the vast amounts of data distributed across their enterprise into insights and outcomes to drive material ROI.

Those who view data as a strategic asset and quickly analyze the insights hidden within have a solid, quantifiable advantage. Not only is analytics a competitive differentiator, it puts the right information into the hands of decision-makers—creating a self-service, data-driven culture that stretches from the boardroom to the manufacturing floor.

Are you watching data evaporate into digital exhaust—or using it as a strategic asset?

Using analytics to energize the digital enterprise

The paradigm shift that’s creating the next-generation connected enterprise is already underway. Connectivity is moving beyond packet transport, VOIP, video, and collaboration to things, devices, and applications that coexist within a highly connected ecosystem. Collectively, they demand new business processes while creating insight-driven experiences.

Uniqueness, structure, integration, quality, access, privacy, and governance are all important elements of the data value chain. Combined with analytics, these are fundamental to gaining a competitive edge. Those who strive to succeed by leveraging analytics need to identify the data that’s unique to their organization and tap the value stored within.

Research shows that data-driven decisions are at the forefront of digital leaders’ minds. It’s not an option to adopt a data-driven culture; it’s the essential ingredient to stay alive in today’s hyper-connected market.

The following three trends illustrate how analytics have become a competitive lever in the digital enterprise:

Trend 1: Hyperconnectivity

Gartner estimated that 6.4 billion connected things would be used worldwide last year, an increase of 30 percent over the previous year. The hyperconnectivity between people, processes, data, and things is disrupting traditional data management and analytics. Data once siloed by lines of business or systems are being connected like never before, through integrated platforms that share data types across groups and devices.

Across all industries, the proliferation of Internet-connected devices has changed how businesses operate. Smartphones, laptops, tablets, and desktops that readily use the power of Big Data analytics allow businesses to automate and refine their operations. With analytics on every device, enterprises are becoming insight-driven super-engines of seismic proportion.

Organizations that leverage analytics to make real-time decisions are achieving instant value. When they add machine learning and contextual user experiences into the engagement model, the connections intensify and they’re seeing even faster responses and more favorable business outcomes.

Trend 2: Data overload

Every organization has an overabundance of data, some of which is widely distributed and/or has a short shelf life. Until recently, enterprises lacked the ability to understand how to process and analyze structured and unstructured data, and geo-spatial and sentiment information. These data sets are typically not held within a central repository, nor are they scalable, making day-to-day management extremely complex.

Organizations are at varying levels of maturity in terms of how they leverage the full potential of their data and use it as a strategic investment. Regardless of where they are in their journey, however, the common thread is the increased complexity of data, people, process, and things. This means organizations must tackle data overload with a process that analyzes all data types from a single platform.

Trend 3: Self-service and independence

Data is most valuable when it’s in the hands of line-of-business users. Rather than restricting access to IT super-users and data scientists, savvy organizations are establishing an agile self-service model where data prep and visualization are available anytime, anywhere. This model enables teams and individuals to translate their departmental information into insights and ultimately into outcomes that drive material ROI for the business.

These three analytic trends are the major contributors behind the modernization of business intelligence platforms and the creation of next-generation enterprises. Once transformed, data-driven digital enterprises fueled by analytics can:

  • Align their business strategy with their data strategy
  • View data as a strategic asset and evolve into a data-driven culture where everyone has the right level of information at their fingertips
  • Become agile, self-service organizations with independent employees who work in sync to deliver improved business outcomes

For more insight on the power of data analytics, see Next-Gen, Real-Time Data Warehouse: Bringing Analytics To Data.


Mala Anand

About Mala Anand

Mala Anand is President of SAP Leonardo & Analytics at SAP, leading the end-to-end business including go-to-market, product development and strategy. With her primary focus on product development, market acceleration and adoption in one of SAP’s core innovation areas, Mala develops and executes strategy across all markets and ensures operational excellence within the global GTM and product development teams. The core focus of the SAP Analytics business encompasses business intelligence with embedded predictive and machine learning innovations across large data sets. Formerly, Mala led the Data & Analytics | Automation Software Platforms business at Cisco Systems with a focus on innovative solutions to aggregate and analyze today’s hyper-distributed and real-time streaming data. With over 20 years of experience as a senior software executive, Mala places a deep focus on delivering innovative solutions to the market that help customers develop informed, timely insights to establish new modes of engaging their workforce and customers.