Skip to main content Skip to Footer

LATEST THINKING


Big success from big data

Accenture Analytics survey reveals that companies with big
data experience are satisfied with business outcomes.

Overview

Companies with big data experience are overwhelmingly satisfied with business outcomes, yet are still facing challenges to maintain competitiveness and become digital enterprises.

The Accenture Analytics Big Data Survey shows that big data is taking off. The vast majority who have completed big data projects report that they are satisfied with business outcomes and that their big data initiative is meeting their needs. According to our findings, 92 percent of companies are satisfied with the business outcomes driven by big data and nearly all (94 percent) report that their big data implementation meets their needs.

For most companies (89 percent), big data is very important to their transformation into digital. Companies are leveraging big data across a variety of activities, such as identifying new sources of revenue (54 percent) and new product/service development (50 percent). However, for most, a big data implementation comes with challenges such as locating or training skilled resources (43 percent) and technology integration (42 percent).

Companies with big data experience are overwhelmingly satisfied with business outcomes, yet are still facing challenges to maintain competitiveness and become digital enterprises.

The Accenture Analytics Big Data Survey shows that big data is taking off. The vast majority who have completed big data projects report that they are satisfied with business outcomes and that their big data initiative is meeting their needs. According to our findings, 92 percent of companies are satisfied with the business outcomes driven by big data and nearly all (94 percent) report that their big data implementation meets their needs.

For most companies (89 percent), big data is very important to their transformation into digital. Companies are leveraging big data across a variety of activities, such as identifying new sources of revenue (54 percent) and new product/service development (50 percent). However, for most, a big data implementation comes with challenges such as locating or training skilled resources (43 percent) and technology integration (42 percent).

Download PDFDownload the full report (PDF)
 

Big Success with Big Data

Big Data

Case Study

Thames Water: Using data to optimize the UK’s largest provider of water

Thames Water is responsible for supplying public water and wastewater management for much of Greater London and the Thames Valley. By using Accenture’s Smart Grid services, the company can access real-time data to improve their overall performance.

Thames Water aimed to use data to provide efficient, high-quality customer service. Accenture will help by creating a single view of the company’s operating systems and assets, such as pipe and treatment facilities. 

Between September 2013 and March 2015, Accenture will implement advanced analytics, which will enable more efficient water sourcing and remote asset monitoring. The data will help the utility giant anticipate equipment failures and respond in near real-time to critical situations, such as leaks or adverse weather events.

Background

Much has been said over the past 18-24 months about the potential of big data. The Accenture Analytics Big Data Survey takes a closer at this issue by focusing on companies that have implemented big data projects. We examined what companies are doing now with big data, the challenges they are facing and what’s next for big data analytics.

Accenture Analytics’ Big Data Survey interviewed more than 1,000 experienced users of big data from 19 countries and seven industries in March 2014. Respondents were from companies that have annual revenues between $250 million and more than $10 billion. Every respondent’s organization had already completed at least one big data installation.

Analysis

The Accenture Analytics Big Data Survey unearths several key insights, including:

There is much to learn when embarking on big data initiatives. Nearly two-thirds (62 percent) of respondents said they had no idea how difficult it would be to implement big data. Users imagine their project will be fairly easy, only to discover that there is a lot to learn about data frameworks and analytic techniques. Challenging—yet not impossible—big data implementations force users to stay flexible, adapting and learning as they grow.

Bigger companies are getting more from big data. The bigger the organization, the better the results. Larger companies have a broader conception of what big data includes, and use more types of data for a wider variety of purposes across more functions. Larger organizations start with focused initiatives in practical areas, such as customer relations, product development and operations, rather than trying to do everything at once.

Analytics talent is hard to come by. Talent is an issue for many (41 percent) and remains in short supply. The most successful users source talent wherever they can find it, leaning heavily on external, experienced resources.

Big data makes a big difference. Big data users (89 percent) believe big data will revolutionize business operations in the same way the Internet did. The consensus is clear: big data brings disruptive transformation, even if users do not always agree on precisely what “big data” includes.

Recommendations
Big data remains fertile ground for business transformation. For those just stepping foot in this territory, it is wise to start small with a proof of concept, demonstrate value and ROI quickly, build internal consensus and then grow big data programs organically.

As you grow, it’s important to be nimble and adapt and learn as new technologies—and new opportunities—evolve. An important part of growth is finding the right data science talent. Focus on building analytics skills by hiring external resources, staffing up when possible, and developing internal capabilities through training and development.

Recommendations

Big data remains fertile ground for business transformation. For those just stepping foot in this territory, it is wise to start small with a proof of concept, demonstrate value and ROI quickly, build internal consensus and then grow big data programs organically.

As you grow, it’s important to be nimble and adapt and learn as new technologies—and new opportunities—evolve. An important part of growth is finding the right data science talent. Focus on building analytics skills by hiring external resources, staffing up when possible, and developing internal capabilities through training and development.

Video Case Study: Caixa BanK

Media Help

Watch how Accenture is helping CaixaBank implement a Oracle Big Data infrastructure to create a powerful and secure data repository.