Driving Business Success through Data-Driven Strategy

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Organizations across the world are realizing the potential of data-driven business strategy and operations. They are leveraging data to unlock the understanding of their consumer behavior. And, as data-driven strategy take hold, it becomes an increasingly critical point of competitive differentiation.

Since 1995, the number of internet users has grown from 16 million to about 3.6 billion in 2016. This usage has resulted in wealth of data.1 The 3-Vs (Volume, Velocity and Variety) framework, was introduced in 2001 by Doug Laney, is now ubiquitous.2 Since then, there has been a rapid shift in data strategies based on how businesses compete in a connected world.

The worldwide IoT Market is expected to grow from $1.3 trillion in 2013 to $3.04 trillion by 2020.3 30 billion connected devices are anticipated to be in use by 2020. These smart and connected devices will in turn drive connected supply chain and smart manufacturing, retail, healthcare, automobile, energy and many other industries.

The data strategy has shifted from simple technology-focused data management capabilities to a comprehensive understanding of,

What is the right data for your company that drives the business outcomes?
What is the right tool or technology to harness data for valuable insights?
What is the right process to manage and secure the data?
Who are the right people to generate, process and consume these insights?

CHOOSE “RIGHT” DATA, TECHNOLOGY, PROCESS & PEOPLE

As the marketplace becomes increasingly competitive, businesses use data to gain a competitive advantage either by differentiating their products and services from the competition or to identify new opportunities to grow their top and bottom-line numbers.

Moreover, the data sources and types are changing rapidly as everything is becoming connected. Exhibit shows the growth of data from Embedded Systems rising faster than other categories by 2020.4 We are moving rapidly towards Smart Data.5 Smart data will further enable various connected systems and devices data to build a compelling multi-dimensional story that drives better business performance.

The worldwide data volumes will grow from 4.4ZB in 2013 to 44ZB by 2020.6 A study of 288 vendors across 9 Total Data segments revealed that The Total Data market is expected to nearly double in size – from $69.6bn in revenue in 2015 to $132.3bn by 2020.7 So, while the data volumes and variety grows at a rapid rate, it is important to, understand the right data that would influence the value drivers for the business.

Big data and storage technologies have advanced in the last decade. The business needs to determine if there is value in capturing and storing such high data volumes.8 It also needs to determine if the information captured is complete enough or if the variety is useful in deriving patterns or insights. As per CrowdFlower9, 83 percent of the data scientists feel there is shortage of data. On the contrary, every type of data and research is available on the internet. A shipping firm improved on-time performance of its fleet by using data on weather and port availability that it never knew existed.10 Ultimately, selection of the right big data technologies is important to the business.

Operational, streaming, device and machine data is usually laden with several data quality related issues. Does the business have the right tools and technology to cleanse the data? What is the extent of risk associated with bad data for the business? As per IBM, “hidden data factories” are expensive. In 2016, yearly cost of the poor data was around $3.1 trillion in the US alone.11 50 percent of the time is spent by knowledge workers in fixing the data. The global data quality tools market is expected to reach about $3.7 billion by 2021 from $1.8 billion in 2016, registering a CAGR of 14.94% during the analysis period, 2016-2021.12

Data is consumed at all levels of an organization, at varying granularities to operate, and across geographies. Does the organization have the right modern BI tool to analyze the data with ease? In 2017, we see more and more businesses are investing in cloud-capable, robust BI platforms that can handle multiple data management capabilities such as integration, storage, visualization, statistical and quantitative analysis, instead of multiple specialty tools.13 As retail omni-channels identify and understand all the sources for data, they are experiencing a data explosion. Attribute expansion in single transactions and increased data quality drive a better understanding of customer behavior and needs.

Countries are increasingly protecting its core industries with regulations. Does the business understand the data privacy implications of customer data? What processes does it have in place to protect and notify the end-user? Who is responsible for the governance and management of such data in the company? Does the business have adequate tools or technology to protect its data? For instance, businesses operating in the European Union will comply with EU’s General Data Protection Rights (GDPR) regulations that will be enforced from May 2018. These regulations provide a directive on breach notifications, right to access & portability of consumers (subject). It also identifies responsibilities for a controller and protection officers.

Finally, to define a data strategy, execute and monitor it, a data champion – Chief Data Officer and a dedicated data team is required. The rapid rise of the Chief Data Officer (CDO) role, from 400 in 2014 to 1000 in 2015, has emphasized the importance of data in organizations.14 This role is now charged with establishing and championing data strategies, governance, quality, architecture, and analytics.15 It’s important that someone in the organization takes ownership and bridges IT and operations. The role legitimizes data as a valuable asset for the organization, drives architectural and data management decisions, leverages data as a competitive advantage, and promotes a data-driven culture.16

Co-Authors:

Venkatesh Thyagarajan

Senior Director, Global Business Analytics Head

Subhendu Senapati

Architect- Product Development