Intelligent Process Automation (IPA)
Combining RPA and AI or Machine Learning extends the automation toolbox
Intelligent automation creates operative and strategic benefits
While software robots are great in boosting efficiency in rule-based, repetitive processes, they can also be taught more complex tasks when machine learning or other AI components are added to the toolbox. Intelligence can be added by making classifications, using machine learning, OCR (Optical Character Recognition), NLP (Natural Language Processing) or NLG (Natural Language Generation).
Artificial intelligence enables new possibilities in process automation
Making recommendations and decisions
Recognizing and processing pictures
Understanding and processing documents
Understanding and processing speech
Transitioning from RPA to Intelligent automation
First a foundation with RPA must be laid where operative benefits are gained, followed by next steps with Intelligent automation, where strategic benefits can be gained
1. RPA – APPLYING TRADITIONAL SOFTWARE ROBOTICS IN RULE-BASED PROCESSES
OPERATIVE BENEFITS
Automating repetitive tasks that nobody wants to do and eliminating bottlenecks
Eliminating humane mistakes and using existing systems efficiently without integration
2. IPA – APPLYING MACHINE LEARNING AND RPA IN OPERATIVE PROCESSES THAT REQUIRE HUMAN JUDGMENT
OPERATIVE BENEFITS
Processes that require human judgement
If a process has many rules, those can also be implemented with machine learning model E.g. Risk management, Risk control, Risk reporting, Customer service email
3. IPA – APPLYING MACHINE LEARNING AND RPA IN MANAGEMENT WITH THE HELP OF PREDICTIVE ANALYTICS
STRATEGIC BENEFITS
Predicting demand, order-supply-chain
Predicting customer behaviour
Predicting and updating pricing models
Collecting budgeting information and calculating a forecast
IPA use cases can be found in all functions in organizations – they must be recognized, analysed and prioritized according to business needs
Intelligent Automation use case examples
PREPROCESSING JOB APPLICATIONS
- Prehandling job applications according to the required profile versus applicant profile
- Interview-Forget-Maybe
- ML Model based on: personal file, applications, LinkedIn
SALES RECOMMENDATIONS
- Planning sales campaigns according to customer’s buying probability
- Analyses and reports
- ML Model based on: customer data, customer history, services
HANDLING CONTRACTS
- Handling customer contracts and feeding information to ERP systems from documents
- Cross checking information
- ML Model based on: contracts, key information
EMAIL CLASSIFICATION
- Automated customer service
- Customer service emails can be handled, classified and when needed, replied to on the basis of free form content
- ML Model based on: emails, classifications, replies
PREDICTIVE PRODUCTION PLANNING
- Projects in manufacturing industries are planned according to component availability
- Precollecting
- ML Model based on: orders, stock balance, supply history
PREDICTED COST FOR A SITE
- Ability to react to a negative cost development on time
- Operative benefit from invoice handling
- ML Model based on: invoices, budget, history
What our customers have achieved with Intelligent Automation
Posti has elevated their RPA team to the next level by adding machine learning into their toolbox.
The automation solution enables faster data processing and reduces the manual workload regarding the business process.
To reduce the increased manual workload, Kekäle chose an intelligent automation solution built by Sisua Digital.
Book a free consultation with us
Want to know how intelligent automation could benefit your company? Tell us about your automation needs and let’s find the right solution for your company together.
