Introducing AI – simplifying the starting point

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When it comes to implementing AI, you need to walk before you can run.

Two stags face one another on a hillside. The younger one looks down to its left, and says, “Hey. Let’s run down to the bottom field and eat some of that fresh grass.”

The older one turns to look in the same direction, and says, “No. Let’s walk down, and eat all of it.”

Here at Capgemini, as you’d expect, we work with a lot of multinational enterprises – and everywhere we go, we find businesses are impatient to embed artificial intelligence (AI) into their organizations.

It’s understandable. The power to assimilate, assess, and perhaps even act on information as quickly as AI promises to do is sure to be attractive. Who wouldn’t want to take advantage of it as soon as possible?

We help organizations impatient for digital transformation really evaluate why they want the change. – digital can help them only if they let it. And we help them look at their processes with an effectiveness lens rather than following the trend for short-term results.

That’s why we recommend that they take stock, and that, in particular, they revisit and calibrate their starting point. One way to do this is to use our ESOAR methodology. This entails assessing current processes and determining the extent to which they can be Eliminated, Standardized, Optimized, Automated, and Robotized. After all, re-engineering the organization’s processes to drive best practices and optimize business value is a good thing to do – even if AI is not your goal.

ESOAR forms part of Capgemini’s Digital Global Enterprise Model, or D-GEM, a flexible, platform-based architecture that provides a complete overview of an organization’s people, processes, technology, and governance. D-GEM’s seven levers aim to address and improve key areas comprising workforce grades; operational locations; skills and competencies; technology; pricing; governance; and best-in-class processes, which is where ESOAR comes in.

It’s only when an organization has gained a clear picture of its current business environment, and when it’s streamlined and improved processes wherever it can, that it can then start to consider how AI can be implemented in ways that benefit the entire operation, and not just individual pinch-points. It’s at this stage, for example, that the transition to SAP S/4HANA can take place, harnessing the power of digitization to improve the way resources are managed and used. It’s at this stage, too, that process efficiencies can be brought together with artificial intelligence in order to extend and enhance the client environment. And it’s at this stage that new and higher volumes of data – from sources including the Internet of Things and digital customer channels – can be interpreted and acted upon in real time, at speeds and in quantities that simply weren’t possible before.

In a later piece in this series, I’ll take a look at how process optimization can work in practice, and at some of the benefits that might accrue. In the meantime, you might like to take a look at what I’ve contributed to the TechnoVision 2020 report, which distills much of the detail and provides examples of some of the underlying technology.

For now, though, you might like to think again about the two stags, the first looking to its left down the hill, and the second looking right, with which I opened this piece. It’s the measured, structured approach that delivers the greatest and most long-term rewards.

The second stag was wise. It was the right-eyed deer.

Want to know the simplest ways to create a digital transformation in 2020? Download the TechnoVision 2020 report  to help you through the process.

Read other blogs in this series :

Priya Ganesh  has worked for Capgemini for the last 12 years, first as a Solutions Architect and now as a Senior Director leading the solutions and transformation practice across APAC. She enables clients in their transformation journey, leveraging Capgemini’s key assets and collaboration across our Group.

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