FROM RPA, ROBOTIC PROCESS AUTOMATION, TO COLLECTIVE INTELLIGENCE RPA

Executive Summary

CIRPA AICyberLAB

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CIRPA Collective Intelligence Robotic Process Automation: LEAN COLLECTIVE INTELLIGENCE

By COLLECTIVE INTELLIGENCE PROJECTS.

Succeeding in any digital transformation initiative requires engaged all stakeholders. With firms across geographies and industries now focused on harnessing robotic process automation and capturing its well-documented benefits, businesses recognize the need to keep all stakeholders (collective intelligence) at the core of their change efforts. Deploying Collective Intelligence Robotic Process Automation (CIRPA) is a multifaceted task that must not be taken lightly.

Ultimately, ensuring that all stakeholders (from customers, employees, providers, distributors, shareholders…) are engaged and happy enables organizations to capitalize on the transformative potential of CIRPA.

RPA Methodology

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ALIGNING ROBOTICS TO PROCESSES

Most RPA projects start with an assessment of processes to be considered for automation. This is followed by an analysis of business processes and training of the robots to execute the process. Within 6 – 8 weeks, we are usually able to create a pilot process to demonstrate the benefits of RPA.

When is RPA relevant? How do you execute an RPA Project? What are RPA’s benefits?

Highly manual / Time consuming

High volume

Discovery Assessment

Solutioning Development TestingAverage handling times reduced

No downtimes

Processing costs reduced

Payback in 3 months

Rule based/No human judgement

Low exception volume

Digital trigger & structure digital data

At least 2 different systems

Not frequent changes in process steps & rules

High like lihood of human error

Human errors eliminated

Refocus of staff on customer service

Quick implementation

Re-usable process elements

Emulates human execution of

repetitive processes with

existing applications

Robots are a virtual workforce controlled by the

business operations teams

Robots can be trained by

business users via

configuration

Sits alongside existing

infrastructure, governed and controlled by

IT

Robots work with existing IT architecture –

no complex system

integration

What is CI Robotic Process Automation (CIRPA)?TRANSITION FROM RPA ARCHITECTURE TO CIRPA PROCESSES

RPA is a feature of intelligent process automation (IPA) that describes logic driven robots executing pre-programmed rules on mostly structured data. CIRPA takes productivity optimization to the next level by redefining work and reassigning employees to execute higher-value activities. Process bots are capable of independently performing simple human-like functions such as interpreting, deciding, acting and learning.

Robots Process Robot Capabilities

are computer coded software

enable the automation of repetitive, rule-based processes

mimic interactions of users

work across functions and applications

Collective Intelligence RPA

Automated data entry

Multi-system integration

Process reconciliation

Processing simple business rules

Repetitive tasks

Data validation / Quality

Semantic understanding (facts and rules)

Multicontext integration

Process optimization

Processing complex business rules

Machine learning

Data auto-correction

Agile business creation & predictive operations

COLLECTIVE EXPERIENCESNew Business Model

Ag

ents

(stakehold

ers)

CLOUDEDWe

B2B

B2B2C B2C

B2B2C

ACI

FACTORY

MKT

PROCUREMENT

SALES

LOGISTIC

...

B2C

Customers

Employees

Shareholders

Providers

...KNOWIE AI

Collective decisions

Collective decisions

...

TOOLS “Instagram for bHsiness”

COLLECTIVE PROCESSES

AI INTERFACES

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Transformation to CIRPAHOW WE APPROACH THE TRANSFORMATION PROCESS

FACTORY

MKT

PROCUREMENT

SALES

FINANCES LOGISTIC

...

Digital CIRPA Transformation Process

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FROM “GEGACY” SYSIEMS

ENGINESINTERACTING

WITH A HUMAN

LEGACY SYSTEMS

DIGITAL SERVICES

PLATFORMS

INFRAESTRUCTURES

DATA BASES

KNOWLEDGE BASE

(FACTS & RULES)

ENGINES

INTERACTION WITH HUMANS AND MACHINES

LEGACY SYSTEMS

DIGITAL SERVICES

DIGITAL PLATFORMS

INFRAESTRUCTURES

DATA BASES

KNOWLEDGE BASE(FACTS & RULES)

TO AIC (COGNITIVE COMPUTING)

3-6 YEARS

IRANSIIION MODEG FROM “GEGACY” SYSIEMS (INSIAGGED BASE) IO AIC CIRPA SYSIEMS

Intelligent Architecture

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ENGINES

INTERACTING WITH A HUMAN

IEA INTELLIGENT ENTERPRISE ARCHITECTURES

3-6-9 YEARSTRANSITION FROM DATA-DRIVEN ARCHITECTURE TO COGNITIVE PROCESSES

E3 SEMANTIC CONTAINER

AI INTERFACES

IaaS

PaaS

SaaS

API CONNECTORS

SAP

KNOWLEDGE BASE(FACTS & RULES)

COLLECTIVE SEMANTIC BUSINESS MODEL

MODELS BASE(FACTS & RULES)

KaaS (ccIE)

IIaaS (CIE)

WaaS (WIE)

--- --- ---

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Collective Intelligent RPAsADVANTAGES I

Robotic Process Automation

Machine Learning Chatbot and NLP

Extract, Transform, Load

Rapid API Integration

Ready Bots for IT, HR & Business

RPA AI ETL API Ready Bots

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Collective Intelligent RPAsADVANTAGES II

AccuracyRight result, decision or calculation at first time.

Audit TrailMaintaining logs for essential compliance

ConsistencyIdentical process and task reducing output variation

FlexibilityInstant Ramp up/down to deal with spikes

Reliability24/7 for complete year with full availability

ProductivityFreeing manual resources for more value added task

Staff RetentionAllow focus towards

more stimulating task

Right ShoringGeographical independence

allows right shoring

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From RPA to CIRPAINCREASINGLY INTELLIGENT RPA

RPA

Data entry, extraction, aggregation and integration with

websites, portals, documents and systems

Intelligent RPA

Automatic processing of unstructured data –

acquisition, understanding and

integration

RPA+CDABPM

AIProcess Mining

CI RPA

Bioinspired collective parallelize algorithm with

an ethical improving engine, sophisticated

semantics understanding, a large and rapidly growing number of

contexts, open knowledge and big data form social

networks.

True Cognitive RPA

Deep human-like understanding and

decisioning of complex situations

Wisdom RPA

Acting

Thinking

Wisdom of the crowd: The collective

knowledge of a group of people as expressed

through their aggregated actions or opinions,

regarded as an alternative to specialist or expert knowledge.

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FACTORY OF THE FUTURE

IoT sensors for Supply Chain Management

Industrial Augmented

Reality

Predictive Machine

AnalyticsCobots

Modular Equipment

Computer Vision

Blockchain for Enterprise Resource Planning and

Supply Chain Management

Intelligent clothing and accessories

(Wearables)

Unmanned Trucks

KWS CIRPA

FACTORY

MKT

PROCUREMENT

SALES

FINANCES LOGISTIC

...

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CIRPA KWS “IKIGAI” ArchitectHreKWS LEVELS

KWS “IKIGAI”

KNOWIEUnified Collective Intelligent User Experience

KNOWLEDGEWAREUnified Collective Intelligent User Experience

KWS GROWTH MARKETING CLOUD

Market with Intelligence in the Moment

KWS AI COMMERCE CLOUDCollective Shopping

Experience

KWS TALENT CLOUD

Build Relationships & guide Customers throughout their journey

KWS 4 MEDIA

Make customers happy

KWS Cloud Platform Factory

CLOUDEDWE PLATFORMInternet of Things Machine Learning Collective Intelligence Engines Blockchain

KWS WIE KERNEL

Webservices Extensions

Built-in Artificial

Collective IntelligenceKWS AI

BPMSCollective Business Process

Management Suite

KWS AI SCM

Collective Supply Chain Management

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EXPERIENTIAL MODEL: RESEARCH OF MULTIDIMENSIONAL EXPERIENCES

Collective Experiences

Research Stakeholders in their environment (New Media)

Yesterday's Research Today's Research

QuantitativeResearch

ObservationalResearch

EmotionalResearch

TrendResearch

QualitativeResearch

Predictive Inference

CocreativeResearch

CIRPA AICyberLAB: Innovation as a driver for improvement

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CIRPA AICyberLAB

Knowdle Foundation AILABs

THE CIRPA DIVISION: LEAN INTELLIGENCE & AGILE KNOWDLEDGE

CIRPA AICyberLAB: Innovation as a driver for improvement

CIRPA AICyberLAB: Deductive + Inductive AIC Model

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• Deep Learning

Fourth generation: COMBINATION OF COLLECTIVE DEDUCTION AND COLLECTIVE INDUCTION

Third generation: NNS & MACHINE LEARNINGSecond generation: DEDUCTIVE REASONING

• ACI Technology • Interactive ACI

• Bayesian networks• Fuzzy control• Expert system

+

First generation: OPTIMIZATION TECHNIQUES

• Mathematical programming techniques

• Constrain logic

Sense

Learn

Act

KNOWLEDGE-DRIVEN

Knowledge-driven cycle

DEDUCTIVE TYPE (works by modeling expert knowledge) INDUCTIVE TYPE (works by extracting feature values from data)

OT know-how

OT: Operating technologyNN: Neutral network

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