Introducing AI – success in practice

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Fixed and inflexible business processes can be replaced by AI-driven systems. But how can process optimization work in practice?

In my previous post in this series, I advocated taking a measured, structured approach to the introduction of artificial intelligence (AI). Committing oneself at the outset to assess and streamline existing business processes will pay greater and more comprehensive dividends – and not necessarily just in the long term, either.

This time, I’m taking a look at how process optimization can work in practice and at some of the benefits that might accrue.

One approach to preparatory optimization is to take advantage of our ESOAR (Eliminate, Standardize, Optimize, Automate, Robotize) methodology, which enables organizations to take stock of current processes, and to consider the extent to which, individually or collectively, they can be eliminated, standardized, optimized, automated, and robotized. It’s part of our overall Digital Global Enterprise Model (D-GEM), which establishes a comprehensive context for an organization’s business architecture – its processes, its technology, its people, and more.

This approach provides not only general business advantages but can be of great benefit specifically in the transition to the new enterprise resource planning environment of SAP S/4HANA.

Stories from the front line

Let’s consider a few examples.

A large consumer goods company adopted this approach to set up its global finance back-office support services.

A major utilities company in Australia used SAP S/4HANA within the D-GEM architecture as a design environment, enabling it to engineer its process landscape rapidly, smoothly, and efficiently.

An AI-powered cash collection agent is available that combines the power of intelligent automation with best-practice process understanding. By making use of this automated assistant, a large retail company improved its customer satisfaction ratings, reducing wait times, and minimizing the need to engage its helpdesk agents to resolve vendor queries quickly.

A global online payment platform was able to reduce its fraud rate to just 0.32% of revenue. It did this by taking stock of current processes and by optimizing routines, before introducing a sophisticated deep learning system that analyzes transactions in real time.

AI-based case management can streamline and automate the management of customer correspondence. A transport company prepared the ground for the introduction of such a solution, leading to an 85% reduction in manual case preparation and handling effort.

Boiling it all down: make sure you’re prepared.

A few key principles are implicit in these case histories:

  • Looking up-front for opportunities to improve process efficiency will pay dividends – not only in its own terms, but as groundwork for a more successful implementation of AI
  • Optimizing platforms as part of the transformation increases the effectiveness of new tools that are introduced
  • Collaboration across business units when preparing for the transition to SAP S/4HANA enables process blueprints to be more detailed and comprehensive, increasing the likelihood of success of the new target operating model.

In short, and as with so many things, preparation is key.

You might also like to consult a page I’ve contributed to the TechnoVision report. The report as a whole addresses technology business transformation and highlights the need for simplification when embarking upon it. It’s well worth a read.

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 been working for Capgemini for the last 10 years, first as a Solutions Architect and now as Senior Manager. She has been a leader in change management, business finance transitions, and transition management. 

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