RESEARCH REPORT

In brief

In brief

  • AI is impacting personal lives and fueling many businesses, enabling them to set higher expectations for what's possible.
  • What's powering AI? It’s data. Fact is: if you can see all of your data, you can build any business you wish much faster than ever before.
  • How can organizations build a business model that thrives on visible data? By taking a journey into the world of what we call DATA in 4D.


What does seeing DATA in 4D mean?

It implies:

Recognizing data is a multidimensional phenomenon—Dynamic, Dependable Distributed and Democratized—and adopting approaches, technologies, systems and cultures that will bring it into the light and make it discoverable.

These four dimensions of data have, in fact, emerged as key trends in a recent research conducted by Accenture and Everest Group, whereby 200 enterprises around the world were surveyed to gauge their approaches to data today, as well as their priorities for managing this core resource tomorrow. The good news is that most organizations recognize the importance of investing in a data-driven future: 72 percent forecasted a double-digit growth in spend on data and analytics initiatives.

DYNAMIC: Establishing a boundaryless data value chain

Traditional data value chains (built to handle enterprise data at the speed of yesterday) are collapsing. This is largely due to three reasons: internet of things (IoT) is accelerating data explosion, AI and machine learning are being used to aggregate and categorize complex data, and cloud is providing the crucial storage and compute capacity. Organizations must, therefore, rearchitect their data supply chains to be agile, adaptive and conducive for moving data at the speed of business to the point of need.

Our joint research indicates that by 2022:

42%

of enterprises plan to run most of their data algorithms and computational programs in the cloud.

47%

expect to integrate live data streams with enterprise data to derive real-time insights.

33%

will use AI and machine learning (ML) technologies for data related solutions.

DEPENDABLE: Objectivity dominates conversations around trust and value

Responsible AI rides on the belief that data is trustworthy and algorithms are unbiased. This, in turn, underpins an organization’s brand and reputation and its ability to succeed.

Trust is becoming a critical component of an organization’s data strategy and it is imperative for businesses to adopt new intelligent solutions for managing trust and reliability of their data.

Our joint research findings:

78%

enterprises believe inconsistent data quality hampers their ability to generate accurate insights.

71%

currently use or will use AI systems to automatically generate reliable business decision recommendations.

"In fact, we’d argue that to be competitive in today’s environment, enterprises need to execute a balanced strategy that prioritizes data trust at the same level as growth and profitability."

– AJAY VASAL, Strategy Lead for Data Business Group – Accenture Technology

The importance of dependability (and the impact on value and reputation when it’s compromised) extends to AI and machine learning algorithms too. As these technologies become more pervasive, they’ll be seen as indispensable members of the workforce. That will make it even more critical for enterprises to ensure their core capabilities are objective and free from bias. In this way, they’ll derive the benefits that come from collaborative human + machine models.

DISTRIBUTED: Data sharing = Data monetization

Information is no longer confined within the boundaries of an enterprise. Data sharing with peers, vendors and even competitors is key to realizing the value of data in terms of enhanced business outcomes such as increased operational efficiency, higher revenue and reduction in cost.

Organizations must, therefore, identify how data can be shared across their internal and external ecosystems in a secure and reliable environment, and in compliance with the law.

Our joint research confirmed that organization are keen to share and monetize data for specific business objectives:

80%

of enterprises want to increase operational efficiency.

82%

are looking to increase revenue.

44%

are focused on offering innovative products, services or business models.

37%

want to reduce the cost and risk of regulatory compliance.

Data sharing (or data distribution) is fast becoming the principal route to developing many innovative offerings and business models.

DEMOCRATIZED: Making business users data literate is redefining business-IT relationship

Becoming a data-powered enterprise implies going beyond providing the right reports and insights–business users need to be able to access and explore data sets, identify new opportunities and generate relevant insights. This is giving rise to a new paradigm where business users are armed with necessary skills and technologies to read, understand and work with data. In fact, in a recent Gartner survey, “poor data literacy” emerged as the second biggest challenge to the success of the office of the Chief Data Officer (CDO).1

Business users must become data literate if they are to leverage the full potential of new data for effective business outcome.

Our joint research findings:

60%

enterprises identified lack of cross-functional talent across IT and business as a major challenge to the success of their data and analytics programs.

42%

now use some kind of embedded self-service analytics tools.

44%

will be ready to use natural language capabilities to drive conversational analytics within the next three years.

Many organizations are already giving access to analytics tools to a host of stakeholders. The recent rise of data self-service technologies has been a boon for such efforts.

However, becoming data literate is not only about deploying new tools and technologies, it requires a massive cultural and talent transformation to arm users with necessary skills, incentives and supporting technologies to leverage the full potential of data for effective business outcomes.

What’s in it for you?

DATA in 4D is not about a set of point solutions to extinguish the fire burning in some corners of your business.

"Embracing DATA in 4D means you are embarking on a data-driven transformation journey so you could go from where you are in your business today to where you want to be in the near future."

– SANJEEV VOHRA, Group Technology Officer and Data Business Group Global Lead – Accenture Technology

If you leverage today’s multidimensional data that is dynamic, dependable, distributed and democratized, it can illuminate the way to new, disruptive business models and innovative offerings. It could shed light on new customer segments, new markets, new opportunities to increase productivity, streamline operations…there’s no limit to what you could imagine, build and offer globally. Wouldn’t the ability to discover the data, curate the data and consume the data in this way give you a competitive edge in your industry?

1 Christy Pettey, "3 Top Take-Aways From the Gartner Chief Data Officer Survey," January 29, 2018. Accessed June 12, 2019.

Ajay Vasal

Data Business Group Strategy Lead – Accenture Technolog​y


Sanjeev Vohra

Senior Managing Director, Lead – Group Te​​chnology Officer and Data Business Group Global, Accenture Technology

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