1. How far can Business Services Automation go?
TITLE – OPTION 1
How far can Business Services Automation go?
From RPA to AI

2. About Symphony
By scale, experience and accreditation, we are the leading and largest global RPA pure play, with the only fully integrated Intelligent Automation Platform
Consulting
Implementation
Managed Services
Vision Workshops
Future of Work Accelerator
RPA COE Design & Training
Proofs of Technology
Proofs of Concept
Pilots
RPA Helpdesk
Ongoing Transformation
Monitoring & Support
Intelligent Automation Platform (The Symphony Digital Office)
RPA As-a-Service
Natural Language Processing
OCR Data Extraction
Chatbots
Virtual Hosting
Heritage in BPO
BPO dealt in people / labour arbitrage
Major shift in global demographics / labour became more expensive + technology started to evolve
A major movement was the advent of Robotic Process Automation (RPA) – the automation of highly repetitive, high volume transactional processing – which I will talk about more during this discussion.
Key to Symphony’s success was the constant focus on the way work was executed and people. Not technology.
Understanding the levers of value from a ‘future of work’ perspective enabled us to approach client challenges in interesting but familiar ways and deliver the services based on existing service structures.
This is a very different approach to say the legal tech space – lots of silicon valley youngsters building cool tech, but failing to understand the fundamentals of how a legal firm (specifically the politics / agendas of a partner-led org) operates – and thus struggling to land their solutions at scale.
Most accredited Blue Prism ‘Pure Play’ Partner
UiPath Strategic Partner & Largest Training Capability
‘Leading Service Delivery Automation (SDA) Providers
‘Cool Vendor’ in the Business Process Services category
#1 Leading Robotic Process Automation (RPA) Pure Play
Best Intelligent Automation Pure-Play 2016
Blue Prism Implementation & Best Practice Leader 2017 – US/LatAm
GSA Digital Champion of the Year 2017

3. + = Symphony Right Partner SYKES
Symphony is at the forefront of the ‘Future of Work’ and, for the past 4 years, has driven automation-led innovation amongst some well-known brands across banking and financial services, logistics, retail and healthcare.
Right Partner
The combination of Symphony's focus on improving operations through intelligent automation and SYKES focus on improving customer experience through contact centres means we can now offer clients truly innovative solutions for managing work across their organisation - from front-to-Back office. + =
In November 2018, Symphony was acquired by SYKES, a leading customer contact organization and pioneer of the ‘Intelligent Customer Experience’ (ICX).
SYKES

4. Back Office VS Front Office Benefits
Reductions in FTE are the easiest automation benefit to quantify and express monetarily, and this remains the case in the Front Office. Alternative benefits are frequently considered as mere ‘side effects’ of the automation, however when they are considered seriously, their impact on the business is often a lot larger.
Front Office
The benefits that impact the business most are NBA (increased cross sales), CSAT (increased Life Time Value), ESAT (less churn), and Training (on the job & faster = smaller % of team training).
Training
(Quicker onboarding)
Compliance
Speed
(FTE)
NBA
(Cross-Sell) $
CSAT
(proxy for LTV)
ESAT
Back Office – Reduction in Cycle Time
Front Office – Reduction in Training, Compliance, better NBA, HT,
Quality
Compliance
Speed
(Cycle Time)
Agility
(Scalability)
Insight
Cost
Middle & Back Office
The benefits that often have the biggest impact are increased scalability, and reduced cycle times.

5. Digitisation – Typical View of Work
Unstructured Data
Manual Processing
Structured Data
Analytics & Insights
Limited due to gaps between systems
Digital Inputs
Digital Inputs
Taking Unstructured data and codifying it into structured data (Swivel Chair work)
Many firms, seeking to harness many of the benefits touted by the Technology vendors (e.g. 80%+ cost savings in year 1), start their journey with RPA. However, many quickly find their automation programme starts to run out of steam about 6 months in - as either the processes were not optimised effectively, the scope of RPA was more limiting than expected or the extensibility is limited due to lack of digitisation up or downstream (i.e. cannot scale the automated components across the business)
Equally, many RPA and Machine Learning programmes fall short due to poor standardisation both in terms of data (what data is captured, how is it categorised, where it is stored) and process (how the data is captured, how it is used (human vs automation) and how it is augmented e.g. meta info)
Thus, the typical approach to digitisation is to digitise the inputs and storage aspects of the work value chain, but these approaches fail to consider how work is actually processed AND the resultant ‘dust or sediment that falls out of each activity – in which, per the above view, is often lost due to manual intervention.
Manually augmenting data / reporting

6. Digitisation – ‘Future of Work’ view
Unstructured Data
Basic Digital Tools
Structured Data
Human-in-the-Loop
Forms
a. _____ b. _____ c. _____
Advanced Digital Tools
Digital Inputs
Digital Inputs
Exception handling / Decision making
NLP
Computer vision
Speech 2 Text
RPA + RDA
If we instead take a process + data view of work – we can reimagine and redefine how that work is carried out digitally.
Tactically, the digitisation of the inputs (how data is captured and where it is stored) can be a good first step – turning unstructured data (from documents such as invoices and contracts) into structured / machine readable data. Tools such as OCR, while not a new tool, when combined with Machine Learning tools such as NLP and Image recognition can be very powerful – especially when connected into Robotic Processes – think end-to-end Procurement Helpdesk.
Additionally, bringing more self-serve technologies into areas such as customer / employee service further enables digitisation – simply by removing manual input – and again, when connected with tools such as RPA - can not only support digitisation but also enhance customer / employee experience (e.g. Automated Procurement Helpdesk)
Strategically, digitisation aims to remove manual processing and enable more informed decision making through greater access to data. If the data quality is poor, non-standard or incomplete, so too will the decision making be. Equally, understanding areas that are uniquely process related (simple, repetitive, limited judgement based decisions) vs those areas that are more data driven (complex, long tail, high judgement based decisions) – will inform how much digitisation is viable.
Horses for Sources has been using the term Digital Operations to best explain the merger between front middle and back office functions that is occurring because of Digitisation…
Analytics & Insights
All digital ‘dust’ / ‘sediment’ is captured, logged and stored for future use.

7. HfS IA & RPA Market Forecasts
Automation and AI Business Operations Spend
Source: HfS Resarch
Source: HfS Resarch

8. The Intelligent Automation Toolkit - Reimagined
UNDERSTANDING
DIGITISATION
Platforms & Cloud Services
Process
Process Discovery / Mining / Mapping
DIGITAL LABOUR
DIGITAL DECISIONING
FUTURE TECH
Receiving (Data)
Acting (Labour)
Processing
Learning
Other
Visual Recognition
Facial
Object / Character / Symbol
Handwriting
Video / Motion
Macros / scripts
Language
Emotion / Sentiment
Natural Language
Translation
Learning
Algorithms
Deep Learning
Machine Learning
Blockchain
Technology
Smart contracts
Robotic Process Automation
Environment
Augmented reality
Virtual Reality
Crowd
P2P
Mass workforce orchestration
Audio Recognition
Voice recognition
Speech / Dialog
Creation
Attended Automation
Analytics
Deterministic
Predictive
Real-time
Text
Natural language generation
Data Visualisation
Reporting
IoT
Network assets
Machine to Machine
Geo-location
KEY POINTS
The intelligent Automation landscape is complex – here, we have oversimplified the core technology categories into a single ‘Digital Operations Toolkit’.
The Intelligent Automation is not a linear progression from RPA to Machine Learning, despite what many analysts will portray rather, it is a set of specific tools to help executives solve critical issues around:
1. Digitisation (Communication and Standardisation challenges) – how to streamline the inputs and interfaces across your business to better structure information
2. Virtual Worker (Process challenges) – How to handle ‘simple’ activities, tasks and processes in a way which augments or alleviates the burden of your human workforce
3. Digital Decision Making (Data challenges) – How to leverage ‘expert systems’ to handle ‘complex’ processing – again, to augment or enhance your human workforce
SO WHAT:
At its core, Intelligent Automation is complex and ever evolving – requiring deep expertise in each of these core areas to realise maximum benefit.
With over 100+ automation projects successfully delivered, Symphony offer hands-on experience and deep expertise across all fields of Intelligent Automation.
Expertise and Experience which has been packaged up into our industry leading SAVO methodology and which permeates through each and every one of our client engagements.
NARRATIVE
The digital operations toolkit, also a great framework for looking at the complex world of Intelligent Automation, presents several core (deliberately over-simplified) solution categories.
The first pillar (receiving) contains the inputs and interfaces – from images recorded on a camera, audio streaming through a phone or documents being scanned - this pillar deals with tools for data capture.
The next pillar (acting) contains digital resources that take the inputs and from the first pillar to then initiate or manage a process – RPA being an increasingly popular tool for many starting their automation journey due to its ability to overcome legacy or complex IT systems and to enable humans to focus on more complex, judgement based decisions – however, there are of course other tools that further enhance process type work such as workflows, workflow orchestration tools and desktop automation.
The final pillar, for today’s discussion, is actually the two columns of Processing and Learning – these two columns deal with decision making and largely the fundamentals that underpin Machine Learning.
Critically, this toolkit offers various solutions each applicable for specific business problems.
The first pillar is all about solving Digitisation – Standardisation, normalisation, categorisation of data
The second pillar, is all about Virtual Worker – back office and front office processing of work without (or with minimal) human interaction
And the third, is all about Digital Decision making – leveraging machines to solve large or complex data related challenges
Virtual Agents
Behavioural
Real-time input
Outputs from learning
Haptics - Motion
Decisioning
CONTROL
Workflow / orchestration

9. The Intelligent Automation Toolkit
Platforms & Cloud Services
Process
Process Discovery / Mining / Mapping
Receiving (Data)
Acting (Labour)
Processing
Learning
Other
Visual Recognition
Facial
Object / Character / Symbol
Handwriting
Video / Motion
Macros / scripts
Language
Emotion / Sentiment
Natural Language
Translation
Learning
Algorithms
Deep Learning
Machine Learning
Blockchain
Technology
Smart contracts
Robotic Process Automation
Environment
Augmented reality
Virtual Reality
Crowd
P2P
Mass workforce orchestration
Audio Recognition
Voice recognition
Speech / Dialog
Creation
Attended Automation
Analytics
Deterministic
Predictive
Real-time
Text
Natural language generation
Data Visualisation
Reporting
IoT
Network assets
Machine to Machine
Geo-location
KEY POINTS
The intelligent Automation landscape is complex – here, we have oversimplified the core technology categories into a single ‘Digital Operations Toolkit’.
The Intelligent Automation is not a linear progression from RPA to Machine Learning, despite what many analysts will portray rather, it is a set of specific tools to help executives solve critical issues around:
1. Digitisation (Communication and Standardisation challenges) – how to streamline the inputs and interfaces across your business to better structure information
2. Virtual Worker (Process challenges) – How to handle ‘simple’ activities, tasks and processes in a way which augments or alleviates the burden of your human workforce
3. Digital Decision Making (Data challenges) – How to leverage ‘expert systems’ to handle ‘complex’ processing – again, to augment or enhance your human workforce
SO WHAT:
At its core, Intelligent Automation is complex and ever evolving – requiring deep expertise in each of these core areas to realise maximum benefit.
With over 100+ automation projects successfully delivered, Symphony offer hands-on experience and deep expertise across all fields of Intelligent Automation.
Expertise and Experience which has been packaged up into our industry leading SAVO methodology and which permeates through each and every one of our client engagements.
NARRATIVE
The digital operations toolkit, also a great framework for looking at the complex world of Intelligent Automation, presents several core (deliberately over-simplified) solution categories.
The first pillar (receiving) contains the inputs and interfaces – from images recorded on a camera, audio streaming through a phone or documents being scanned - this pillar deals with tools for data capture.
The next pillar (acting) contains digital resources that take the inputs and from the first pillar to then initiate or manage a process – RPA being an increasingly popular tool for many starting their automation journey due to its ability to overcome legacy or complex IT systems and to enable humans to focus on more complex, judgement based decisions – however, there are of course other tools that further enhance process type work such as workflows, workflow orchestration tools and desktop automation.
The final pillar, for today’s discussion, is actually the two columns of Processing and Learning – these two columns deal with decision making and largely the fundamentals that underpin Machine Learning.
Critically, this toolkit offers various solutions each applicable for specific business problems.
The first pillar is all about solving Digitisation – Standardisation, normalisation, categorisation of data
The second pillar, is all about Virtual Worker – back office and front office processing of work without (or with minimal) human interaction
And the third, is all about Digital Decision making – leveraging machines to solve large or complex data related challenges
Virtual Agents
Behavioural
Real-time input
Outputs from learning
Haptics - Motion
Decisioning
Workflow / orchestration