AiiA December roundup on: GBS

Thought provoking pieces on what affects you

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Seth Adler
Seth Adler
01/02/2020

We are wrapping up 2019 with this roundup of December’s best GBS resources including a webinar, a special report, and some forward-thinking solutions for 2020.

 

How to Get to Shared Services 2020: Data Analytics, Integrated Business Services and Intelligent Automation Drive a Winning Model

For the 14th year in a row, SSON gathered some of the DACH region’s leading and evolving Shared Services and Global Business Services leaders to discuss, share and project the future of the business services model.

A number of significant trends emerged, including a general preference to shift away from “Shared Services” as a moniker in favor of "Integrated Business / Technology Services” (the “Tech” part reflecting in part the critical role IT plays in automated services delivery), RPA expertise sold on a consultancy basis, and an impressive understanding of the value-driving potential of data analytics. This article also discusses:

  • Shared services ambitions fed by data
  • Rethinking sourcing models
  • Robotics and intelligent automation
  • Engaging employees
  • Looking into the future

 

How Shared Services Can Prepare For The Changing Digital Landscape – And The Role of Digital Talent

One of the most significant developments in Shared Services over the past few years has been the introduction of automated activities [a.k.a. digital workforce] into the workplace. This has been important because it supports the original value proposition of the Shared Services model: to provide business services more effectively and efficiently.

However, while continuous improvement has played its part in adjusting the Shared Services operating model, the new "wave" of automation is part of a much bigger shift towards embracing digitisation and represents a much steeper trajectory than any previous wave of progress. This article covers:

  • Preparing for the changing digital landscape
  • Developing digital talent
  • Driving digital process transformation
  • HR transformed

 

[WEBINAR] AI in Business: When and Where to use Artificial Intelligence in Your Organization

Within this rapidly changing world it’s easy to feel puzzled about AI and what it can actually do, the benefits it can provide, and how it can be best integrated into your organization.

This free, on-demand webinar outlines three common AI technologies, and provide examples for practical application in an organization. Themes covered will include:

  • Common AI techniques, how to apply them in your organization, and common pitfalls to avoid
  • How to identify and prioritize which AI projects to pursue
  • The business implications of technical decisions and how to assess the risk-reward trade-offs of different projects

 

SSON Special Report: Process Mining

The current age is characterized by high expectations and instant delivery. At the same time, productivity remains key. The only way to achieve both is to systematically remove friction from all processes – customer-facing as well as internal.

Friction is a natural outcome of siloed working, however: Most teams think in terms of their department only – and adding systems behind groups only exacerbates friction. This friction has a cost.

Process Mining is a rapid-fire solution for enterprises anxious to optimize process automation but confused about where opportunities lie in inefficient process landscapes.

Process Mining offers a visual overview but also adds an “action element,” telling a business where potential for improved process efficiency lies.

Process Mining has become irresistible to businesses that want to drive digitization and automation across their process landscape.

 

A Brief Perspective on “Retrospective Process Automation”

We all have our own business challenges which result in a framework that meets that specific environment. There is no standard way to design a use case, therefore. Process segmentation is, however, a straightforward way of categorizing the dexterity of work per the consistency of data from the source, standardized data format, and actions expected on data. Learn more about process segmentation for technology application in this article.


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