Aug 3, 2020

Accenture: maximising the return on investment for AI

Georgia Wilson
3 min
Business Chief takes a look at research conducted by Accenture on how organisations are maximising their return on investment when it comes to AI...

In research conducted by Accenture the company reports that 84% of C-suite executives believe they must leverage artificial intelligence (AI) in order to achieve their objectives when it comes to growth, in addition to most believing that AI is an enabler for their strategic priorities.

While most executives also believe that in order to achieve a positive return on AI investments, it requires scaling across the organisation, however, 76% acknowledge that they struggle when it comes to scaling, with three out of four concerned that if they don’t scale AI in the next five years they risk going out of business.

How crucial Is scaling AI?

To determine the answer, Accenture conducted a global study of 1,500 C-Suite executives from 16 industries, focusing on the extent to which AI enables the business strategy, the top characteristics required to scale AI, and the financial results when done successfully.

Emerging from the study, Accenture identified three distinct groups of companies with the capability to successfully scale AI: proof of concept factory, strategically scaling and industrialised for growth.

How to succeed at scaling

Also within its research, Accenture highlighted the three critical success factors that differentiate the proof of concept stage from a strategic scaler.

1. Drive “intentional” AI

“Strategic scalers pilot and successfully scale more initiatives than their proof of concept counterparts—at a rate of nearly 2:1—and set longer timelines,” highlights Accenture. “They are 65% more likely to report a timeline of one to two years to move from pilot to scale. And even though they achieve more, Strategic Scalers spend less.”

To scale successfully companies require structure and governance in place. With this in mind Accenture reports that nearly 71% of strategic scales have a clear defined strategy and operating model for scaling AI in place, while only half of the companies in proof of concept report the same.

“Strategic scalers are also far more likely to have defined processes and owners with clear accountability and established leadership support with dedicated AI champions,” adds Accenture. 

2. Tune out data noise

“90% of data in the world was created in just the past 10 years,” with this in mind “175 zettabytes of data will be created by 2025. Yet after years of collecting, storing, analysing, and reconfiguring troves of information, most organisations struggle with the sheer volume of data and how to cleanse, manage, maintain, and consume it.”

Accenture highlights within its research that strategic scalers are capable of ‘tuning out the noise’ when it comes to data. 

“They recognise the importance of business-critical data, identifying financial, marketing, consumer, and master data as priority domains. And Strategic Scalers are more adept at structuring and managing data.“ In addition, “they use the right AI tools—things like cloud-based data lakes, data engineering/data science workbenches, and data and analytics search—to manage the data for their applications.”

3. Treat AI as a team sport

“The effort of scaling calls for embedding multi-disciplinary teams throughout the organisation—teams with clear sponsorship from the top ensuring alignment with the C-suite vision,” notes Accenture. For strategic scalers these teams are frequently headed by a Chief AI, Data or Analytics Officer.

It’s a lesson Strategic Scalers have learned well. In fact, a full 92% of them leverage multidisciplinary teams. Embedding them across the organisation is not only a powerful signal about the strategic intent of the scaling effort, it also enables faster culture and behavior changes.

For more information on business topics in Europe, Middle East and Africa please take a look at the latest edition of Business Chief EMEA.

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Jun 18, 2021

GfK and VMware: Innovating together on hybrid cloud

3 min
VMware has been walking GfK along its path through digital transformation to the cloud for over a decade.

GfK has been the global leader in data and analytics for more than 85 years, supplying its clients with optimised decision inputs.  

In its capacity as a strategic and technical partner, VMware has been walking GfK along its digital transformation path for over a decade. 

“We are a demanding and singularly dynamic customer, which is why a close partnership with VMware is integral to the success of everyone involved,” said Joerg Hesselink, Global Head of Infrastructure, GfK IT Services.

Four years ago, the Nuremberg-based researcher expanded its on-premises infrastructure by introducing VMware vRealize Automation. In doing so, it laid a solid foundation, resulting in a self-service hybrid-cloud environment.

By expanding on the basis of VMware Cloud on AWS and VMware Cloud Foundation with vRealize Cloud Management, GfK has given itself a secure infrastructure and reliable operations by efficiently operating processes, policies, people and tools in both private and public cloud environments.

One important step for GfK involved migrating from multiple cloud providers to just a single one. The team chose VMware.

“VMware is the market leader for on-premises virtualisation and hybrid-cloud solutions, so it was only logical to tackle the next project for the future together,” says Hesselink.

Migration to the VMware-based environment was integrated into existing hardware simply and smoothly in April 2020. Going forward, GfK’s new hybrid cloud model will establish a harmonised core system complete with VMware Cloud on AWS, VMware Cloud Foundation with vRealize Cloud Management and a volume rising from an initial 500 VMs to a total of 4,000 VMs. 

“We are modernising, protecting and scaling our applications with the world’s leading hybrid cloud solution: VMware Cloud on AWS, following VMware on Google Cloud Platform,” adds Hesselink.

The hybrid cloud-based infrastructure also empowers GfK to respond to new and future projects with astonishing agility: Resources can now be shifted quickly and easily from the private to the public cloud – without modifying the nature of interaction with the environment. 

The gfknewron project is a good example – the company’s latest AI-powered product is based exclusively on public cloud technology. The consistency guaranteed by VMware Cloud on AWS eases the burden on both regular staff and the IT team. Better still, since the teams are already familiar with the VMware environment, the learning curve for upskilling is short.

One very important factor for the GfK was that VMware Cloud on AWS constituted an investment in future-proof technology that will stay relevant.

“The new cloud-based infrastructure comprising VMware Cloud on AWS and VMware Cloud Foundation forges a successful link between on-premises and cloud-based solutions,” says Hesselink. “That in turn enables GfK to efficiently develop its own modern applications and solutions.

“In market research, everything is data-driven. So, we need the best technological basis to efficiently process large volumes of data and consistently distill them into logical insights that genuinely benefit the client. 

“We transform data and information into actionable knowledge that serves as a sustainable driver of business growth. VMware Cloud on AWS is an investment in a platform that helps us be well prepared for whatever the future may hold.”

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