Capgemini‘s 2018 report Reshaping the Future surveyed more than 700 senior executives who are trialling automation. Although many organisations are dabbling in pilot projects, few are planning to re-imagine their core business using available technologies.

 

This first step in automation is Robotic Process Automation (RPA). RPA is an emerging technology practice that streamlines business operations to reduce costs. Using RPA tools, a company can configure software to process a transaction, manipulate data, trigger responses and communicate with other digital systems.

With RPA, businesses can automate mundane rules-based business processes, freeing employees to devote more time to higher-value work.

As with any new approach, RPA requires planning and careful implementation with a strong understanding of your strategic goals.

Start by building a road map. Identify any standardised processes that cross multiple systems. Specifically seek out situations where employees source data from one system or process and then re-enter the data into another system or process to progress a business function. This situation is ripe for automation.

Below are some Quick Wins by function, identified by Capgemini’s study:

Quick Wins

Function Tasks AI
Finance & Accounting Accounts receivable and cash management

Reconciliation

Fixed asset accounting

Order entry

Pricing calculation

Robotic Process Automation
Procurement & Supply Chain Updating vendor records

Invoice processing

PO processing

Responding to customer/supplier requests

RFP generation

Advance shipping notices

Pre-specified automation rules which trigger responses and communication.
Human Resources Onboarding

Exit and clearance

Payroll management/validation

Applicant sourcing/recruitment

Absence management

Time and attendance management

HR compliance and reporting

Performance management

Education and training

Employee service management

Robotic software for pre-screening interviews

Chatbots to manage absence notifications

Automation for onboarding

 

Sales & Marketing Lead generation Data and AI to segment customer data and re-market new products and services

 

While you are building your automation road map, remember to set measurable goals for your project. Some examples are:

  • Eliminate the need for human intervention in capturing and sorting invoices.
  • Reduce the time spent on attendance tracking by 80%.

The case for Artificial Intelligence

While rule-based technologies automate high-volume, repeatable tasks and mimic human actions, Artificial Intelligence comprises a range of technologies that learn over time as they are exposed to more data. The data points can be identified in customer journey mapping. These are opportunities where digital technology can add value to a customer’s journey with your business.

AI technologies include:

1. Speech recognition

Businesses use software such as Fonetic to automate customer service telephone interactions and to verify the identity of callers.

2. Natural Language Processing (NLP)

NLP is the ability of a computer to interpret human language and take appropriate action. Insurance companies use NLP detect fraud by monitoring social media and cross-checking against information collected by NLP software.

3. Context-aware computing

Context-aware computing seeks to anticipate the ways that computers will need support from users in specific situations. Whether indoors or outdoors, on manufacturing floors or in offices, or in any other kind of situation where a person relies on a piece of hardware to complete a task. An example is devices that change their screens and backlighting according to the amount of light in the room where they are being used.

4. Biometrics

The key benefit of Biometrics is security and safety. Fingerprint and facial recognition is favoured over multiple PIN numbers and passwords. These are the findings of VISA’s recently conducted survey.

5. Image and video analysis

Amazon Rekognition object and scene detection, customers can automatically index vast image libraries to make them searchable.

6. Machine and deep learning

Using RPA tools, a company can configure software, or a “robot,” to capture and interpret applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems. This is called machine and deep learning.

7. Swarm intelligence

Research into the behaviour of ants, bees and other social insects has resulted in novel solutions to optimise business processes. By responding to queues from their nearest neighbour, insects’ collective behaviour yields useful work despite a lack of supervision or central command. This behaviour is called swarm intelligence.

8. Chatbots or voice bots for self-service

Businesses can use Chatbots to help mobile customers navigate their online search, respond to enquiries in real-time or begin a conversation discussing their needs, in the style of a sales agent.

Building an automation roadmap begins with a vision and some quick wins. It then progresses to designing a business model that is supported by the most effective technologies available. Reducing time spent on repetitive, routine tasks will free up your team to focus on more growth generating activities.

All rights reserved Mobiddiction.