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Robotic process automation is winning hearts and minds, but is it good for your business in the long-run? Read this article to decide for yourself.


Robotic process automation is a type of business process automation technology based on the use of software that mimics the behaviors of humans to process and share data.The term was coined by UK software house BluePrism, previously a business that specialized in screen scraping applications for customer service departments. They realized the scope of their simple workforce technology automations could extend beyond screen-scraping use cases – and RPA was born.

What RPA is, and what it isn’t

Robots are not:

  • Walking, talking auto-bots
  • Physically existing machines processing paper
  • Artificial intelligence or voice recognition and reply software

Robots are:

  • Computer coded software (although their deployment may be codeless)
  • Programmes that replace humans performing repetitive rules-based tasks, where humans bring little value-add
  • Cross-functional and cross-application macros

Why RPA is something different to traditional business process management and workflow approaches

Robotic Process Automation describes not just a new flavor of technology but a new approach to addressing office-centric data handling and processing tasks – those that previously required manual re-keying, spreadsheets, hard-copy documents and swivel chair workers to perform.

There are several fundamental characteristics of this kind of technology-enabled solution that differ from Business Process Management (BPM) tooling and other traditional IT department dependent solutions:

  • The automation does not fundamentally change the operation of the process. Instead of a human tapping keys and building spreadsheets, a computer software application mimics the same tasks in a similar way. Stakeholders do not see a fundamental change to their operating behaviours. The same process stages will generally occur.
  • Training of robots is generally performed using code-free software, so it’s quick to do and easy to adapt.
  • IT challenges like implementing complex APIs are removed by re-keying or robotically extracting/uploading data to legacy systems.
  • Rather than being ‘a technology platform’ purchased and operated by IT – requiring a big up-front investment and lots of risk, ‘robots’ are a resource that can be outsourced in the same way as people, individually selected by departmental managers and billed monthly – with all the contractual flexibility that represents.

Not all software robots are born equal

There are essential three levels of software robot ‘intelligence’ that can be used to group the types of tasks each performs

Orchestration robots – ‘empower humans’ by fulfilling simple data processing tasks that can be generally written into algorithms supporting tasks that are:

  • One off manual, non repeatable,
  • Linear, standard and repeatable
  • Orchestrated, complex, standard and multi-scripted

Autonomic robots – fulfil more dynamic processes and work by themselves supporting tasks that are:

  • Dynamic processes, non-standard, contextual and demand an interpretation of inference

Cognitive robots – employing artificial intelligence to learn how to do something supporting tasks that are:

  • Systematic and predictive, where the robot must be capable of self learning, and self healing

Market size and players

According to [marketwatch], the Global Robotic Process Automation (RPA) Market is expected to grow to $8,781.2 million during the period 2018-2026 at a CAGR of 29.5% .
In addition to encanvas, players in the market include:

  • Automation Anywhere Inc. (U.S.)
  • Blue Prism Group Plc (UK)
  • Celaton Ltd. (UK)
  • Daythree Business Services SDN BHD (Malaysia)
  • Ipsoft, Inc. (U.S.)
  • Kofax Ltd. (U.S.)
  • Kryon Systems (Israel)
  • Redwood Software (Netherlands)
  • Pegasystems Inc. (U.S.)
  • Softomotive (UK)
  • UiPath (U.S.)
  • Verint Systems Inc. (U.S.)
  • Xerox Corporation (U.S.)

The Problem RPA was born to solve

The net gain in the productivity of manufacturing workers achieved in the 20th century, has not been matched by similar improvements to information worker productivity in the 21st century. Worker productivity in offices has stayed stubbornly untouched irrespective of innovations in communications, collaboration and automation.

Mundane tasks that resulted from a heavy use of hard-copy documents have to some extent simply been replaced with other, similar, tedious data processing tasks.

Since the 1980, productivity in the office has improved by 3% compared to a 75% productivity increase in factories over the same period.

Source: Vrije Universitet, Amsterdam – Explorative study into Information Logistics

We all know how frustrating it can be to copy data from one system to re-key it in another, because the two don’t integrate. Or the spreadsheeting activity that needs to be done to gather reporting data from multiple sources together. How about the constant malaise of emails coming into your inbox that are preventing you from getting anything done? However much we like to think knowledge working has evolved – because we don’t have as many filing clerks or secretaries anymore.

The executive perspective

The pace of digital business means that the present unhappy status quo is still far from where business leaders want it to be.

Increasing automation is the second most important strategic priority for shared services and global business services (GBS) leaders.
Process automation is seen to be more impactful than analytical software and cloud computing.
When exploring ways to improve automation 71% would expect to first try to leverage their ERP systems, 44% would plan to use bolt-on tools and 13% so far recognise the opportunity to use ‘RPA’.
Source: The robots are coming
Deloitte Client Survey of Shared Services and GBS clients, February 2016

The departmental perspective

It’s well-known that departmental managers find themselves somewhere between a rock and a hard place when it comes to getting their work done. The buck stops with them. They represent the needs of the business to the workers, and the needs of the workers to the business. When there simply isn’t enough resource in their teams to get all of the weekly work done, they’ve some obvious choices, namely:

  • To ask the Human Resources team for more resources – but they probably know that unless they’ve budgeted the spend, in all likelihood the answer is going to be no (especially if there’s a spending freeze).
  • To ask IT for an automation or application to streamline the processing workload. But IT is already ‘busy’ managing ‘keep the lights on’ IT. They are also undergoing lots of systems unifications projects these days owing to the paucity of legacy applications.
  • To outsource the work – although that might not be possible because of data security concerns, skills-set issues, or the need for access to systems and resources that only exist within the firewall of the business.
  • To hire an intern – if budgets will stretch
  • They can take on more of the work on their own shoulders, and work into the night (it does happen).

When all of these things don’t work, ‘another solution’ might be a software robot that does the work for you. This is the offer that RPA sells.

The information worker perspective

Failing to automate these light-weight data handling and processing tasks is not a victimless crime. Lots of information workers work with data. These mundane tasks put people under pressure to work late, eat at their desks, multi-task…
…and they spend less time on the things that really matter to their employer.

People today blend how they spend their time like never before… when they work, when they choose to learn, play …and socialize. They work on the move, check business emails into the evenings and on weekends. But in return they expect to access their social apps and communities during work time and be permitted to use their own mobile devices at work as at home. Similarly, they are less prepared to accept poor quality applications that burn time during the day, particularly now they know ‘there’s a robot to do that.’

Regardless of the many new social office tools and self-service apps, information workers still have to:
Fill in forms

  • Use paper forms to bridge between organizations, processes or systems
  • Create spreadsheets to gather, organize, analyze and report financial information
  • Take data from one system, to then re-key into another
  • Build self-authored apps with desktop tools as a ‘first resort’ when IT has no time
  • Aggregate content on PowerPoint slides to share information

Information workers expect business organizations to appropriately resource them, and if it comes to it, that means providing them with the right systems ‘and robots’ to make their work time productive. A long-tail of demand exists for technology-led solutions that displace the myriad of low-level manual data handling and processing tasks that employers still call on their workforce to fulfil.

According to research by McKinsey&Co., around 60% of occupations could have 30% more of their constituent activities automated. Translated proportionately in time, it means each member of your team working a 37.5 hour week could be spending as much as 45-hours a month on things they don’t really want to be doing because these tasks take time away from their primary role – and impact on their quality of life.

Source: McKinsey & Co., 2016 Report: Four fundamentals of workplace automation; a structured analysis of 200 individual work activities

The use cases of RPA

Robotic process automation is best suited to mundane clerical data handling, re-purposing, re-keying or re-publishing activities that:

  • Can be mimicked by technologies that are script-based, use if-then conditional logic or employ artificial intelligence
  • Tasks that involve small numbers of users (potentially just one) that would be uneconomic to automate with traditional IT
  • Tasks that do not vary every time they occur

In my experience, the majority of robots focus on data capture, aggregation, processing and sharing tasks that humans do, although the introduction of artificial intelligence (AI) technologies is broadening its scope. Common use cases include:

Automating hard-copy document processing

The continued use of desktop office applications and hard-copy documents remains both unproductive and wasteful.

  • The average spreadsheet or word-processed document is read less than 5-times in its life.
  • Relying on hard-copy documents to bridge between the weak points in processes increases paper waste.
  • Use of paper increases demands for storage and space – i.e. filing cabinets, rooms dedicated to archival.
  • It places further demands on resources – such as having to scan hard-copy documents to electronic files.

Swivel chair Applications

IT experts suggest that organizations have so far managed to automate between 25 to 40% of their workflows today. A large proportion of those activities yet to be automated require a human go-between to fill gaps between disjointed systems, or interface between people and systems.

These ‘swivel chair applications’ call on humans to work on several systems at the same time to complete a task (e.g. referencing multiple application windows on one screen and populating another).

Such applications have been out of reach for automation by IT – considered either too difficult or too costly to automate using traditional technologies.

Displacing shadow systems

Security of data has become a board-room issue. This has caused many IT leaders to proactively seek to eradicate the use of spreadsheets that create ‘shadow data.’

Use of office documents and self-authored applications results in a proliferation of content in mobile computing devices, memory sticks, desktop drives and intranet content management systems. Recently, this proliferation of so-called shadow data has worsened with the growth in use of mobile and software-as-a-service (SaaS) cloud based applications; many of which are used without the knowledge or consent of IT. Much of this content is invisible to IT administrators who are unaware of the applications, files or data held within them.

Cloud security developer Elastica’s vice-president Eric Andrews says the company’s threat team analyzed 63 million documents stored by its customers in 2015, when looking for shadow data threats.

What roles are affected?

It would be easy to assume that sub-optimal automation of data processing only impacts low-level clerical roles but that’s not the case. Whilst these roles typically perform more data entry and processing tasks, the impact of automation goes much further.

In fact, analysis by McKinsey & Co. suggests that even CEOs could release up to 20% of their capacity through automation.


  • Case stories suggest deploying software robots:
  • Release time to key workers – Performs mundane clerical tasks so key talent can focus on those activities that bring value to customers and stakeholders.
  • Stay in-tune with business tempo – Much faster to build and deploy than traditional solutions thanks to its light touch codeless approach (measured in days and weeks rather than months) all but displacing development and IT skills.
  • Robot keep working 24/7 – Robots can work day and night on their designated tasks to maximize the ROI available, good for online businesses working 24/7
  • Is truly agile – Solutions can be re-trained as needed must be adaptable to a variety of business needs and scalable to enterprise size. In addition, solutions must be compliance-ready and secure, storing nothing locally.
  • Eliminate human errors – Automation with RPA eliminates human error; fulfilling processes predictably every time.
  • Is a scalable solution – RPA platforms are designed for enterprise scale deployment and are typically cloud based permitting truly massive scaling at very low cost.
  • Are self-serving – Advanced solutions offer user organizations the added benefit of being able to train their own robots!
  • Are easily integrated – Complementing, rather than replacing, existing systems RPA solutions can painlessly access data from multiple, disparate sources without needing APIs or coding.

The compelling case for RPA

The idea of software robots is so compelling because, instead of buying ‘infrastructure IT’ that doesn’t directly lead to economies and improvements to processes, RPA deployments can be extremely targeted at known areas of activity that take time for workers to perform. Payroll remains the biggest expenditure items for most businesses.

Independent research by McKinsey & Co suggests that automation technologies available today, if adopted as they predict, could make a huge impact on workforce productivity. In its 2016 Report – ‘Four fundamentals of workplace automation; a structured analysis of 200 individual work activities,’ McKinsey suggests:

  • “Almost 60% of occupations could have 30% more of their constituent activities automated”
  • “Activities that consume up to 20% of a CEOs time could be automated.”
  • “Only 29% of work activities require a median human level of performance in sensing emotion.”
  • “Just 4% of work activities across the US economy require creativity at a median human level of performance.”

RPA could allegedly save Western economies around $2 trillion in annual wages and impact on over 130 million jobs.

McKinsey and Company estimates that as the use of disruptive technologies like RPA grows at the rate it is expected to, as many as 110 to 140 million FTEs could be replaced by automation tools and software by the year 2025.
Source: ‘Four fundamentals of workplace automation’ – McKinsey & Co. (A structured analysis of 200 individual work activities).

How could RPA adoption possibly be a bad choice for businesses?

Reading this article to this point, you must be scratching your head and thinking, ‘How can RPA possible be a negative force in my business?’ Well, this is why.

RPA solutions focus on automating tasks at the lowest level of the enterprise. These are the jobs that humans do in offices. Those humans work in departments that go to form an enterprise that serves up value to customers somehow that they’re prepared to pay for.

What I see when organizations invest in RPA is a myopic focus on ‘looking for automations’ to justify spend on RPA platforms. This bottom-up aproach to automation leads to the unintended consequence of resources and effort going into the minutiae of process automation, when there are normally bigger, more strategic questions to answer.

Take a step back

Before jumping into ‘RPA’ can I suggest that organizations should examine the issue of automation from another perspective.
(And see if you can follow my logic here!)

Today, business models are changing almost every year for most enterprises. That means how customer value is served up, and how organizations maximize the return to shareholders by fine-tuning their operational processes, can change dramatically within a year.

The focus on every CEO’s mind should be how to maximize customer experience, and value, along with shareholder returns.

I should say here that the impetus to think more pragmatically about business models is only being encouraged by discussions around digital transformation, and the realisation that digital technologies can transform how markets work, and how customer value is delivered.

Similarly, for organizational designers, change managers and IT teams, the challenge set before them is how to interpret those organizational ambitions by orchestrating the business model in the best possible way.

To achieve this requires a series of simple questions answered, namely:

  1. Who are the communities we need to serve and what matters most to them?
  2. What is our business model and can we write it down?
  3. What are the business capabilities and processes we need to excel at in order to achieve the business model – i.e. to deliver maximum customer value and shareholder returns.
  4. What is the best way to deliver these processes in a cost effective, high performance and reliable way? (i.e. buy, build, insource, outsource, etc.)
  5. How many of these processes are automated, partially automated or manual?
  6. What systems, resources and data are required to deliver them?

Going top-down, not bottom-up

Adopting this top-down approach is likely to demand a complete re-think of the organizational design. It will also make redundant the majority of the RPA automations on the roadmap, chiefly because many of those processes (and departments) will no longer exist.

When digital transformation makes RPA redundant

From this top-down journey of discovery, I expect that organizations will turn to no-lo code enterprise software platforms that are best-able to author the digital platforms and ecosystems that enterprises now need to deliver value to customers and other stakeholder groups through self-service provisioning (a.k.a. This kind of digital transformation erases the need for many of the tedious manual data processing tasks that are the honey tree of RPA today.

About Encanvas

Encanvas is an enterprise software company that specializes in helping businesses to create above and beyond customer experiences.

From Low Code to Codeless

Better than code-lite and low-code, we created the first no code (codeless) enterprise application platform to release creative minds from the torture of having to code or script applications.

Live Wireframe

Use Encanvas in your software development lifecycle to remove the barrier between IT and the business. Coding and scripting is the biggest reason why software development has been traditionally unpredictable, costly and unable to produce best-fit software results. Encanvas uniquely automates coding and scripting. Our live wireframing approach means that business analysts can create the apps you need in workshops, working across the desk with users and stakeholders.


When it comes to creating apps to create a data culture and orchestrate your business model, there’s no simpler way to instal and operate your enterprise software platform than AppFabric. Every application you create on AppFabric adds yet more data to your single-version-of-the-truth data insights. That’s because, we’ve designed AppFabric to create awesome enterprise apps that use a common data management substrate, so you can architect and implement an enterprise master data management plan.

Customer Data Platform

Encanvas supplies a private-cloud Customer Data Platform that equips businesses with the means to harvest their customer and commercial data from all sources, cleanse and organize it, and provide tooling to leverage its fullest value in a secure, regulated way. We provide a retrofittable solution that bridges across existing data repositories and cleanses and organizes data to present a useful data source. Then it goes on to make data available 24×7 in a regulated way to authorized internal stakeholders and third parties to ensure adherence to data protection and FCA regulatory standards.

Encanvas Secure&Live

Encanvas Secure and Live (‘Secure&Live’) is a High-Productivity application Platform-as-a-Service. It’s an enterprise applications software platform that equips businesses with the tools they need to design, deploy applications at low cost. It achieves this by removing coding and scripting tasks and the overheads of programming applications. Unlike its rivals, Encanvas Secure&Live is completely codeless (not just Low-Code), so it removes the barriers between IT and the business. Today, you just need to know that it’s the fastest (and safest) way to design, deploy and operate enterprise applications.

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The Author

Ian Tomlin is a management consultant and strategist specializing in helping organizational leadership teams to grow by telling their story, designing and orchestrating their business models, and making conversation with customers and communities. He serves on the management team of Encanvas and works as a virtual CMO and board adviser for tech companies in Europe, America and Canada. He can be contacted via his LinkedIn profile or follow him on Twitter.

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