Using cognitive tech to connect customers to business operations

Creating an engaging customer experience is more readily achieved by embedding increasingly sophisticated digital and cognitive technologies into the very fiber of an organization’s processes, from its front office right through to its back office.

Successful organizations are both strategic and nimble, leveraging the power of real-time data to reduce inefficiencies and enhance their effectiveness. Agile businesses predict their customers’ needs before their competitors do. More importantly, they have the ability to act on those predictions, which is essential for getting ahead in today’s global digital economy. Investment in cognitive technologies (those which mimic human thinking and have the capability to learn) will be required for having intelligent operations in the enterprise. An intelligent enterprise has the ability to inform and implement better business decisions by leveraging data and smarter technology.

In a study conducted in partnership with IPsoft, HfS Research interviewed 100 C-Suite executives to understand their views, expectations, and strategies, along with their investment plans for cognitive technologies. This report discusses opportunities and challenges that business leaders see for moving their organizations toward being truly intelligent—knowing their customers, using technology most effectively, and infusing cognitive technology into the fiber of their business operations.

Table of Contents

  • Smart investments in cognitive tech will help solve business problems and collapse internal barriers
  • C-Suite executives seek to align operations with business outcomes
  • Cognitive Agents are at the Forefront of Investments
  • Cognitive Tech is Driving Intelligent, Self-Learning Business Operations
  • Intelligent operations of the future: cognitive is a lever for theOneOffice core
  • OneOffice by Definition
  • Impediments to OneOffice: The Challenges of Aligning the Enterprise
  • How to track the impact?
  • Using cognitive glue to construct OneOffice

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Source: Hfs-Using cognitive tech to connect customers to business operations


Artificial Intelligence-Powered Robots Won’t Kill Banks

The elimination of millions of jobs by battalions of artificial intelligence-powered robots makes for sensational headlines. But like many stories regarding both the threat and opportunity from technological change, the real story is both more nuanced and more interesting.

A recent report from the World Economic Forum predicted that intelligent automation could eliminate five million jobs in developed countries by 2020. So, you would think a recent spate of announced job reductions in Japanese banking over the next decade – over 30,000 in total at the three major banking groups – would be a cause for concern. Instead, on a recent trip to Tokyo, I heard from a senior executive at one of those banks that automation is vital to deal with a shrinking labor force as the country ages, and that busy robots are a better alternative for the country than unfilled job vacancies.

Despite this story of long-run job displacement in Japan, it’s wrong to conclude that intelligent automation will inevitably lead to fewer jobs in the financial services industry. Indeed, recent Accenture research suggests that – for those firms who embrace intelligent automation – revenues could rise by 32% by 2022, but critically employment could also increase 9%.

Just as in every other industrial revolution, job growth will also be associated with job change and evolution. Crucially, the nature of many jobs will reflect new partnerships between man and machine. Humans will be required to teach, monitor, and maintain the automated technology, while intelligent automation will amplify and improve human skills and judgement. Of course, there will be areas in banking where machines will fully displace humans, but those roles will typically be in areas where the work is tedious and repetitive for current employees. There will also remain many roles that require creativity, empathy, and judgement, where machines will continue to play a limited role for the foreseeable future. Ultimately, if we can better understand and define the symbiotic rather than destructive relationship between man and machine, we will be able to create not only more jobs, but also more interesting and higher value-added roles in the financial services industry.

Accenture’s recent 2018 North America Banking Operations Survey finds that this transition has already begun, with many firms using data and artificial intelligence to improve all manner of processes, from customer service to employee training. 22% of North American banks are already using AI, machine learning, and natural language processing, and another 55% intend to do so within the next year. Nearly one in five banks are already using robotic process automation technology and another 63% plan to do so within a year. The research also shows that many North American banks understand the symbiotic nature of these relationships, with 54% of firms saying human-machine collaboration is important in achieving their strategic goals.

Accenture’s global Talent & Organization lead for financial services, Andrew Woolf, says the challenge for banks, insurance companies and others is to “pivot their workforce to enter an entirely new world where human ingenuity meets intelligent technology to unlock new forms of growth.” While it is easy to point to job losses from increased automation, there are also many examples of humans being augmented by technology to improve their productivity and the service they provide to customers. For example, we have seen a proliferation of robo-advisers in wealth management over the last few years. In some situations, they provide automated advice to consumers who often can’t afford to pay the fees associated with traditional financial planning. However, in other situations, rather than replacing financial advisers, AI now makes those advisers more productive. Fintechs like AdvisorEngine can support the asset allocation process, leaving advisers with more time to focus on personalizing advice for clients and doing what humans do best – building relationships. As one senior wealth management executive commented to me “A machine can put a large inheritance into the right investment portfolio, but it can’t ask you what your parents did to accumulate that wealth and express appropriate sympathy at their passing.”

AI is also helping to reduce risk and lower compliance costs. AI and natural language processing can be used to automatically produce anti-money laundering and know your customer (KYC) reports, and to gather data for regulatory stress tests. Using AI for such tasks can cut bank compliance costs by up to 30%, according to the International Banker, saving billions. This automation also spares the thousands of risk and compliance staff who have sat in large warehouses since the financial crisis the tedium of repetitive, mundane tasks and frees up their time for more rewarding work.

Even when robots are deployed in customer-facing roles, there will still be plenty of need for humans to train and maintain them, as even the best struggle with the nuances of human behavior. For example, bots struggle with recognizing such things as sarcasm, and while platforms like Alexa may be able to fake a sense of humor on demand, they are still a long way from being able to handle the full range of human emotions. So, just like a puppet, the robot will need a human to figuratively pull its strings as it learns to navigate the complex, subtle and often culturally-specific landscape of human interactions.

Similarly, humans will need to be able to explain automated decisions to make sure banks don’t fall afoul of regulators: A machine can make credit decisions about whether someone should get a credit card or an auto loan based on the factors it is programmed to look at, but there also need to be processes in place to make sure those decisions don’t discriminate based on race or geographic location. As American Banker notes, “AI has yet to prove that it is more capable than humans in avoiding both safety and soundness and consumer protection pitfalls related to credit decisions. Indeed, humans will still be involved at key steps in the process.”

Ever since the computer HAL went berserk in the 1968 movie 2001: A Space Odyssey, people have worried that humankind might be usurped by machines. The reality in banking will likely be evolution not revolution, with the machines taking on the tasks they are best suited for and the humans focusing on what they do best. However, there will also be a huge array of activities where it will be the ability to combine the humans and the machines that will separate the leading banks from those who will struggle to thrive in this new world.

Source: Forbes-Artificial Intelligence-Powered Robots Won’t Kill Banks

How Robotics Process Automation (RPA) Will Disrupt Real Estate

Digital transformation is changing the rules of business and competition in the financial industries. Established sectors, such as Real Estate, face new challenges and opportunities due to emerging technologies such as Robotics.

A lot of technological advancement is happening right now around front end retail customer experience and related applications in this space, however back office functions in the Real Estate are still deploying heavily manual processes with no automation, and currently driven by spreadsheets with no leverage on the large data sets available.

It is not surprising that many managers are pushing for a transformation to a more efficient, transparent and structured business environment. One of the big assets of the real estate industry is its richness in available data. The opportunity lays in a holistic solution of not only collecting, but also analyzing and reporting data in order to support and deliver proactive and predictive management support and decision making.

Robotics Process Automation (RPA) is one of the digital technologies that is starting to impact various processes across all players of the Real Estate sector and will unlock long existent pain points. It can help capture, validate and process financial and non-financial data in a far more efficient way.

Robotic has already impacted and is being deployed across many industries, which have been early adopters of technological advancements and is bringing in benefits such as operational efficiency, manual effort reduction, reduced error rates, improved customer satisfaction and even increasing employee engagement.

RPA technology enables a virtual workforce that works faster than a human worker, does not make mistakes, requires no monitoring and can work around the clock. The virtual worker’s activities can be logged and operational metrics can be closely tracked in order to improve or readjust the process flow.

RPA undoubtedly changes the business landscape as it eliminates the need for repetitive and highly manual labor. With increasing coverage of automated processes, a different level of skills is required, namely, the need for people who can create, maintain and define the requirements for automation, as opposed to people who actually process transactions. Preparation and re-skilling is key for both employees and employers.

As more routine tasks and activities become automated, workers can leverage RPA to perform more strategic and high value work and services. RPA also creates solutions in regards to other human labor shortages resulting from demographic trends, weak education systems and under motivated staff.

Some of the biggest benefits of RPA are:

  • Support in eliminating low value added repetitive tasks and helps process owners to focus on analysis and strategic decision making
  • Faster payback period, as by creating a robotic automated process once, it can be easily scalable, tweaked and become more productive, gaining back the investment in six months to a year
  • Better transparency and visibility into processes and the ability to capture detailed data more effectively, with greater accuracy, fewer errors, and less risk of fraud

From a back-office standpoint within the Real Estate value chain, software robots can take control over routine and manually intensive processes. This will save significant time, provide more accurate results, leave a clear audit trail and free up human capital for more value-added and judgment-based functions such as strategic analysis and decision-making. From a front office, customer-facing standpoint, system data can be paired with unstructured data from social media, blogs and other profiles to more accurately gauge the needs and preferences of the customer, allowing for more tailored experiences.

In order to evaluate the right processes that could be automated, the following criteria could be assessed:

  • Data intensive
  • Repetitive in nature
  • Rule-driven
  • Multiple- systems
  • Electronic trigger to the process
  • Involve manual calculation
  • High error rates

Applying above criteria across the RE value chain, some of the key processes, which could be potentially be a good candidates for the Robotics, includes:

In order to get started on the Robotics journey, the approach starts with the ideation stage, which identifies the activities to be automated. This process is followed by the creation of business cases. Certain processes are selected based on the business case, followed by development of the prototypes and proof of concepts. Afterwards, the roll-out phase is performed using agile methodology, with automation of processes being done in parallel to coaching of selected employees within the clients’ organization, enabling internal resources to further develop, maintain and modify the robots independently.

Real Estate Operations

  • Investor AML/KYC
  • Vendor and customer setup
  • Deal sourcing research
  • Entity & property set up
  • Common area maintenance
  • Portfolio monitoring
  • Portfolio management and reporting
  • Budgeting and forecasting
  • Partner data consolidations
  • Contract management etc.


  • Bank & Account reconciliations
  • A/P payment processing
  • A/R cash application & follow up
  • Fund accounting
  • Consolidation
  • Financial Planning
  • Standard journal entries
  • Intercompany reconciliation
  • Tax filling
  • VAT and TAX preparation, etc.

Source: Robotics Process Automation (RPA) Will Disrupt Real Estate

Fly by Wire or Fire and Forget – Augmented Versus Artificial Intelligent Automation?

This is the third and most likely final in a series of articles on the evolution of my Augmentation Intelligent Automation Theory and Practice over the last eight years. The first in the series, “Cybernetic Robotics – The Future of the Claim Processing Professional” was published in October of 2013. It was illustrated by the Giant Robot and Woman that became my Pareto Automation brand logo. It is the quintessential depiction of Intelligent Augmentation on several levels. Intelligent Augmentation is where humans supply intelligence to software robots. I am not talking about RDA. Where humans interact with desktop automation software to provide exceptions handling real time. Rather, very sophisticated RPA Digital Workers, which are detailed in the second and my most read article, “Autonomics or Cybernetic RPA?” published in July of 2016:

The two Visios that illustrated that article are now on either side of the Pareto Automation brand logo. They represent the technology of Autonomics (original definition) or Cybernetic Intelligent Augmentation Automation: a very advanced RPA Digital Worker to the left and equally advanced Rules Engine controller on the right. When combined, they provide a de facto remote-control process automation capability or as I will illustrate by analogy a very advanced “Fly by Wire” technology.

I waited a few weeks after publishing the pinnacle of my research and writing efforts: “ROC – How to Artifact” to see if I had anything further to say? This 55-page document (a free 31-page version is available at my website is the result of reviewing all my writings and related documentation over the last few of years to prepare for my speaking engagement at SSON’s 2018 Intelligent Automation World Series last month.

Last week, I woke up for the third time and realized, I had one more thing to say. 

I am convinced, that a Billion dollars of annual cost savings still resides in the five percent of Managed Health Care claim automation between 88 to 92 and 93 and 97% adjudication range. There is a four % difference in the start and end points of the five-point range depending on the type of claim system and contract complexity. Now that AI Hype is clearing (I was affected too) and the root causes of significant process automation implementation failures are increasingly traced to business model/culture change management issues. Human Centric Augmentation approaches to Process Automation are gaining the increased credibility they deserve. I am confident that Augmentation Intelligent Automation techniques can automate that 5% for perhaps a third to one half the cost of Artificial Intelligent Automation techniques.

Put simply, Rules Engine Controlled RPA Digital Workers with good OCR and perhaps NLP to access unstructured data, using an Ops Dev business model facilitated by a Culture of Trust that fully engages and empowers front line operations leaders and experts, can automate extremely complex and fluid back office processes far more economically than AI based solutions in many, perhaps most Use Cases.

This is not to challenge the wisdom of investing in AI technologies. They are the Future in many, perhaps eventually most business process automation applications, rather they are not ready yet for most demanding processes and even when they become so, may not be cost effective.

Consider the following analogy between three types of anti-tank missile technologies, which are currently used by every major military in the world: Wire, Laser and Radar Guided missiles. None are fully autonomous. They all require a human to acquire the target and make the launch decision. This corresponds to the fact that even various forms of Machine Learning, requires significant human interaction to create, monitor, validate, and fine tune. Still, decision judgment Machine Learning based AI, once sufficient accuracy levels are attained is self-directed, albeit “Fire and Forget”, which can translate into significant capability advantages over systems that require human decision intelligence.

However, Wire or even Laser guided missiles, where humans guide the missiles all the way to the target using sophisticated computer optical or laser technologies makes the guidance easy to provide and almost fool-proof in terms of reliability and accuracy compared either to the more advanced radar guided missiles or obsolete wire guided technology that required significant human skill to acquire and steer the missile all the way to the target, leaving a lot of opportunity for technical failure and human error.

Wow John, that is a great education on Anti-Tank Missiles! What the heck does that have to do with the comparative advantages and disadvantages of various Automation Technologies?

Early generation “Fly by Wire” automation like .Net Macros and first-generation RPA, while a significant efficiency improvement over various non-guided anti-tank weapons (manual processes) are now obsolete. They correspond to Robotic Process Automation or “Humans Augmented by Robots” in the Automation Continuum that follows. Second generation RPA has many enhancements, which improve efficiency and effectiveness. These can be likened to Computer Optical enhance “Fly by Wire” missiles like the ubiquitous TOW; first operational in Vietnam and alive and well in over 45 militaries on over 15 k platforms today. They correspond to Autonomics or “Robots Augmented by Humans”. A variant of the “Fly by Wire” is the laser guided Hellfire. It cost twice as much as the TOW. However, it has significant advantages like twice the range and laser illumination by a platform remote to the launcher, which greatly increases agility and survivability.  This can be compared to extending the ROI range of RPA with OCR and NLP to automate workflows that require unstructured data and Computer Vision that increases automation stability.

There is radar guided version of the Hellfire, which would correspond to Cognitive Computing or “End to End Robots, with Human Oversight”. Again, the advantages of true “Fire and Forget” technologies are manifold; however, they are notoriously hard to perfect in terms of reliability under the full range of operational contingency; something the recent death of a pedestrian by a self-driving Uber car vividly illustrates and are very expensive. The radar guided Hellfire is approximately three times the cost of the laser guided variant.

Sylvan Design Automation Continuum – Notice the resemblance of “Autonomics” or “Robots, augmented by Humans” to the Pareto Automation brand logo that illustrates the article!

Advanced “Fly by Wire” technology has been operational for close to fifty years now and “Fire and Forget” for over twenty. These technologies are all extremely effective tank killers, yet vary greatly in cost per unit. The take home point of the analogy? The older, more simple technologies can continue to have significant usefulness in certain applications long after newer technology arrives on the scene. Because it may not be superior or cost effective in every or even most applications.  Consensus is building it will be the same with Process Automation.

PS – I had a lot of hesitation writing this article. I am not sure it really offers useful information and of course uses another hard to relate to military analogy! Sorry about that really. I wrestled with this for a couple of weeks. The tipping point for me is I just had to have a reason post the illustration. Forget about the text; the picture is worth 10 thousand words!

Source: John Slagboom (Linkedin)-Fly by Wire or Fire and Forget – Augmented Versus Artificial Intelligent Automation?

Software ‘robots’ are already making business processes smarter, say enterprise leaders

A new survey shows the dramatic impact artificial intelligence technologies will make on business processes

With this announcement that the UK government is spending an estimated £327 million on research into robotics and autonomous systems, and as businesses began to realise the economic benefits of using artificial intelligence, the stage is set for Intelligent Process Automation (IPA) technologies to have a real impact on the future of work.

Senior executives across multiple industries think new software ‘robots’, utilising attributes such as machine learning, artificial intelligence, and effective use of big data, is about to unlock significant value within the next three to five years, according to a new study released by IT consultant firm Cognizant.

More than 537 senior business and technology decision-makers think that the benefits of intelligent process automation, and mining the resulting big data with automation-enabled analytics, will bring money and meaning for their businesses: faster processing with fewer errors, unlimited scalability and lower cost of ownership, along with the ability to make more timely business decisions.

Respondents estimate they are already automating, on average, 25-40% of their workflow today, indicating this automation is occurring with workflows that follow rote procedures and manual inputs, paving the way for next generation IPA technologies to drive greater cost savings and efficiency while driving richer business insights when applied to more complex workflows.

About half of the respondents saw automation as significantly improving their business processes within three to five years. However most are still in the early stages of using process automation – the study concludes there is a long tail of process systems yet to be automated, as machine learning and artificial intelligence enable a new generation of knowledge ‘robots’ that can mimic human actions whilst interacting with multiple applications.

‘The future of process work includes connecting skilled people to increasingly powerful technologies such as autonomic computing – including artificial intelligence, machine learning and deep learning – that can increase savings, enhance insights, and accelerate business. This shift is playing out in just about every industry,’ said Gajen Kandiah, executive VP, Business Process Services, Cognizant. ‘Our new study findings show that this trend will only accelerate over coming years as business leaders seek agility, better customer understanding, and cost savings.’

And businesses are taking a new approach to their organisational and business process models using automation as a key delivery model to digitise and analyse.

Charles Sutherland, Executive Vice President of Research at HfS Research, who has been closely researching developments in technology and process automation, said that by implementing software robots, service providers can ensure that work is done around the clock, eliminate human error, and ensure scalability as they save costs and drive revenue.

‘Process automation also allows clients and service providers to share benefits including enhanced compliance, reduced risk and improved job satisfaction of staff,’ said Sutherland.

Source: ‘robots’ are already making business processes smarter, say enterprise leaders

The Future of the Digital Worker – Planning and Sequencing

In digital workforce, robotic process automation, RPA, smart automation, thought leadership, The Prism, Digital Transformation, cognitive ai, artificial intelligence March 05, 2018


In the 3rd of our series on the important Intelligent Automation Skills of the future Digital Worker, we’ll focus on Planning and Sequencing – a complex yet crucial skill set needed for any software robot to be productive, efficient, and effective in the Digitally Transformed workplace.

Planning and Sequencing, which is sometimes simply referred to as “Cognitive Planning”, is classed as one of the “executive functions” of the brain. It is the skill that is involved in the formulation, evaluation, and selection of a sequence of thoughts and actions to achieve a desired goal. As humans, we do this without conscious thought every day. Even the simplest task you perform – such as making a cup of coffee – requires a carefully orchestrated sequence of tasks to achieve the end goal.

Digital Workers must be able to work within the same operational parameters as their human counterparts, which means that an Intelligent Digital Workforce should be able to cope with complex orchestration and sequencing of its tasks, with the minimum amount of human intervention as possible.

Careful Planning = High Performance and Reliability

To automate a process effectively, the process needs to be captured and optimized for execution by a Digital Worker. Recording and automating broken and inefficient processes—the “Digital Duct Tape” approach – will not generate the results you’re looking for. Neither will it move you closer towards a truly digitally transformed process, because the result will be sub-optimal and guaranteed to require unnecessary human intervention.

To achieve true digital transformation of a process, you must understand that process in its current form – including its inefficiencies – and attempt to repair them before automating. Yes, it’s true that this takes longer than simply hitting a record button (as with up-in-no-time Desktop Automation technologies), but the results are stark, when you look at the ROI delivered by some of our customers over long periods of time. A Blue Prism Digital Worker is designed to require as close to zero intervention as possible.

Take our customer Npower as an example. 2 million hrs of work are currently delivered back to the business annually, with 400 robots. These robots are managed by just 2 people. This efficiency and reliability is just not possible without a methodical approach to planning.

Of course, now there are technological advances, like Process Mining – a feature brought to the RPA industry over a year ago, through a first-of-its-kind Technology Partnership between Blue Prism and our partner MINIT – that are allowing us to simplify this process capture and planning stage.

Process Mining allows you to take unstructured data from logs and other “dark data” and build a picture of your process as it is today. This gives you some valuable indications of where you may have inefficiencies – and therefore opportunities to automate.

However, Process Mining alone is not enough. Dark data will not give you insights into the human driven decision making or intuition that went into the process. Neither will it provide you with the “WHY?” behind highlighted inefficiencies. For that, you need to dig deeper and Blue Prism is diligently researching ways to bring together dark data and human insight in such a way that addresses both aspects of this problem. Our partner DXC is beginning to tackle this problem in their APA platform, by combining customised process mining with human process annotation. Armed with this level of insight and process transparency, business leaders can automate processes in their fully optimised forms.

The Importance of Orders of Operation

While it’s important for you to properly plan the process and program your Digital Worker, all that planning would be futile if proper sequencing and orchestration weren’t in place.

Any process will involve a sequence of steps that are likely to have a very critical order of execution but will also involve many decisions and diverging paths along the way. Many of these will involve re-usable and repeated steps. The Blue Prism platform was designed from the ground up to encourage modularity and reusability. The Blue Prism designer and release manager enables a “build once, use many times” approach to process automation. Once you have programmed your resilient integration with an application, this can be easily used in many business processes with ease. Everything is designed to be parameterized, to maximise the reusability and minimise process specific customization.

Thanks to our advanced Control Room and Queue management system, Digital Workers can work in tightly co-ordinated harmony across one or many different tasks. Building a Control Room was not an afterthought for us – it is a core component of the software that has been embedded and refined for almost 10 years.

This efficient sequencing and reusability means we are able to deliver at much higher scale than other products.

Take our customer Western Union. In just 6 months, they have been able to automate more than 21 processes, realise £1m saving and reassign 48 FTEs to more valuable workload.

Where next? Our current research and product development will focus on making this orchestration fully autonomous – the Digital Workers of the future will be fully self-managing.

Data is the New Gold

It’s important to be sure that all the steps performed by your Digital Workers can be audited and explained along the way—especially because of regulatory requirements and compliance audits – but also because having a strong, built in audit trail and metrics from your processes and Digital Workers enables you to identify areas for greater cost saving and process efficiencies. The Blue Prism platform offers best in class, built in analytics and supports feeding data into an external analytics engine. Ultimately, this data will support greater insights and Machine Learning to further improve your efficiency.

Blue Prism is also the only platform that offers true, enterprise grade audit and non-repudiation. Our platform automatically logs and records every action take and changed to give you 100% visibility into your process workflows. The data collected is centrally stored in a tamper-resistant environment, making it an irrefutable piece of a compliance audit, if needs be.

Final Thought – Planning and Sequencing in an AI Enabled Future

In the world of GDPR and the digitally transformed workplace, non-repudiation and audit will begin to become even more important than ever before. Consider how you will explain to your auditors how you arrived at a decision, if that decision was fully or partially automated? Do you understand which parts of your process are driven by deterministic, rules-based decisions and which are based on non-deterministic, machine learning driven decisions? Can you guarantee that all these steps are audited BY DEFAULT, without relying on a developer to remember to program them into the process?

The Blue Prism platform is already the most prepared to support these new regulatory requirements and our latest research is focused around making it even easier for you to extract the data and create the specialized reports you need to protect your business.


Source: Blueprism( By Colin Redbond, Head of Technology Strategy for Blue Prism)-The Future of the Digital Worker – Planning and Sequencing

Practical Tips for Maximizing ROI on Robotic Process Automation (RPA) Investments

Top customer success secrets to close the time to value gap when leveraging RPA for digital transformation

With 72% of business leaders seeing process automation as an advantage and 80% of executives believing that it boosts productivity – RPA is fast becoming the technology of choice to close the time to value gap during digital transformation initiatives.

Traditionally digital transformation projects were large undertakings, utilizing big systems and projects, for which it could take years to complete and see some sort of ROI. The emergence of Robotic Process Automation has substantially reduced the time to value gap by simply leveraging the same systems that humans utilize in order to complete work. This inherently takes away the need to change an enterprise’s core systems.

Lets have a look at some powerful insights gained from some of our most successful customer RPA implementations and what they did to close the time to value gap during their digital transformation projects.

1. A Quick, But Realistic Start

In order to realize greater value in the short-term by reducing implementation challenges, it is critical to understand the nature of RPA implementations, with a realistic time expectation for completion. A key insight to consider is the difference between mapping out human tasks versus robot tasks. For example, a 15 step process flow for a human could require up to 50 steps for the robot to complete. Any workflow spec exceeding 30 steps, will typically require more time, a later start and a longer time frame to achieve outputs. Our most successful customers have discovered that selecting shorter processes, which can be delivered in two to three months, establishes momentum in their process automation journey.

2. Develop A Center of Excellence (CoE)

Creating a centralized team to build, run and maintain all of the organization’s process automations, is the first step towards formulating and regulating your process automation approach. With a well-trained team, designing, running and reporting on process automation successes and failures – the value realization and sustainability will increase. This will also create a strong framework to increase and scale up your process automations to support any key changes within the business.

3. Consider Combining Pure Robotics & Desktop Automation

NICE customers who combine pure Robotic Automation (process automation without human intervention) and desktop automation (process automation with human involvement) generally achieve the greatest value from their RPA investments. Typically, only 10%-30% of processes can be automated with pure robotics or unattended automation, leaving much scope for desktop automation to be leveraged to further optimize process efficiencies and support employee performance. This combination essentially expands the efficiency of human staff on 2 levels:

  • The pure robotics alleviates employees from the very repetitive and tedious tasks that they are expected to action on a daily basis. Replacing software robots with these mundane human tasks, is essentially taking the machine out of the human by freeing up humans to focus more energy on higher value activities that require a human touch.

Example: Human employees will have more time to consult with each and every customer, focusing on resolving more complex issues. This approach has proven to increase process efficiency and customer satisfaction scores dramatically.

  • Desktop Automation or a personal digital assistant for employees is designed to support employees during every step of a process, through real-time process guidance. In addition employees can offload certain tasks to software robots to action on their behalf. This is designed to boost employee performance and raise customer satisfaction levels.

Tip: Not only is the digital assistant guiding an employee to ensure a process is followed, each step can be captured, verified, and audited for compliance. This data is a treasure chest for process analytics teams, and is a key item for those operating in heavily regulated industries.

Only NICE has the experience and expertise to seamlessly automate more complex process scenarios by combining pure robotics and desktop automation. This powerful combination can enable greater process efficiencies. There is no need for a process automation to stop when an error occurs, instead, NICE Robotic Automation has the capabilities to seamlessly alert a human to intervene and resolve a process error or complication, in real-time. The process automation can then resume without any down time.

4. Measurability is Key

Establishing a set of metrics and then tracking and reporting on the performance of the process automations against the predetermined metrics, is essential. Some elements to report on include: time saving and volume of automations i.e. how often are the automations running? It is also advisable to have an onsite lab that mirrors the actual production, with an IT team overviewing it.

Source: Tips for Maximizing ROI on Robotic Process Automation (RPA) Investments

RPA is officially the shiny new silver bullet: 53% of the Global 2000 are planning significant RPA investments to slash costs in 2018

While we were discussing the confusing realities of the RPA hype at the HfS FORA Summit, we got a sneak preview of the interim data from the 2018 State of Operations and Outsourcing Study, conducted in conjunction with KPMG, where 250 interviews with Global 2000 operations leaders have now been completed.

We asked them where their investment priorities were currently lying when it comes to 2018 cost reduction:

Click to Enlarge

So it’s abundantly clear all the hype about rampant adoption has been warranted, and we can hang our hats on our recent enterprise robotics software and services forecast, which now appears conservative, increasing with 47% growth to $1.46bn this year (click here for full forecast):

The Bottom-line: RPA has succeeded in being positioned as the “easiest silver bullet to target that next wave of cost take-out”. Now let the real fun and games begin…

We have discussed, argued and deliberated the true value, impact and effective ways to run RPA software for many, many hours here on HfS… for over five and a half years. And you only need to read our recent work to conclude that “RPA often starts out like a teenage romance, with a lot of enthusiastic fumbling around that ends quickly, frequently leading to disappointment“. And you can also read the RPA Bible, which preaches best and worst RPA practices to such an extent, you’ll need to visit your local RPA Rabbi, Bhikkhu, Priest or Mullah to find your soul again.

The real issue, here, is that the majority of enterprises are taking the plunge and investing the dollars, with 81% actually taking RPA seriously, and 53% very seriously. So what’s going to happen in a few months when those ambitious CIOs and CFOs ask to see real, tangible demonstrations of the resultant cost takeout? Can C-Suite leaders quickly learn to love metrics that are tied to growth, value and effectiveness, as opposed to a simple reduction in operating expenses to feel rewarded for those expensive bot licenses? Are operations leaders generally going to be ready to quantify the value effectively? Can they really convince their superiors that there is true value impact beyond merely offering up headcount elimination?

What’s more, what if headcount reductions were promised to offset investments, and adopters have failed to free up the workload that can enable them? And can they reward the staff, who cooperated in the automation work, by getting them “retrained”? Is there really a plan? While the “one human to oversee every 10 bots” is becoming the latest robo-governance rule-of-thumb, how real is this? Or are we just all bull*****g ourselves about the future, and merely circling the hype to stay relevant today? Do we really care about our companies anymore, or are we more obsessed with adding big sexy initiatives to our CVs? Is this really anything different to yesteryear, where you needed to have an SAP rollout on your CV to be a credible CIO, or oversaw a 1000 FTE outsourcing deal to prove you were worth that $1.2m/ year GBS salary (yes, that’s what some get…). In this world of #fakenews, does anything really matter anymore, when we can spin our realities into whatever shiny new thing is out there?

One thing is clear is that the back office needs to be submerged into the value end of the organization. There is little more headcount elimination to be had for most companies – sure, there are still many areas that have too many people working on too few valuable tasks, and technologies like RPA are terrific tools for breathing new life into legacy systems and creating digital process flows, where before there was only spaghetti code, manual workarounds and swamps of data polluting the corporate underbelly.

One thing is clear, it’s very murky out there, and all we can really do is hatch a semi-realistic plan and try and stay on top of it as the future unravels in front of us…

Source: HFS-RPA is officially the shiny new silver bullet: 53% of the Global 2000 are planning significant RPA investments to slash costs in 2018

RPA STORM – The Strategy

“Storms make trees take deeper roots” – Dolly Parton

The storm brings changes and changes aren’t easy, but it could be the first step to a better place. This approach is an abrupt and proactive action to a new reality.

In this article, I want to show the essay of a strategy that I have been designing, called RPA Storm.The main objective is to use the ‘quick wins’ and bring a quick economy to the business through RPA. This strategy will cause immediate impact and it should be seen as a strategy of short-term, aiming at the pursuit of a specific goal.

I had this sudden insight when verifying that in many situations we need to act fast and it is necessary to have quick wins, in order to gather sponsors support for a second wave, where it is possible to adopt a more robust strategy. Although it is not the RPA Storm purpose to be a long-life strategy, the implemented code could be refactored generating a more sustainable implementation. In other words, this strategy can be adopted in order to use the first wave savings to sponsor the second wave.


Pixar has plots are an undoubtedly successful and the construction of this plots are complex projects, Emma Coats has published 22 rules of storytelling and some of those rules fit with this strategy.

One of those struck me,

#8: Finish your story, let go even if it’s not perfect. In an ideal world you have both, but move on. Do better next time. (Emma Coats)

Using the RPA Storm strategy, we know that we will not create a perfect solution and this is not the goal, but this strategy can give us the opportunity to build something really sustainable after having won the sponsors or stabilized an environment. “We will do better next time”.

Pareto Principle

Although it is a well-known concept, I would like to remind of the Pareto principle, which was one of the concepts that inspired me in this idea and which corroborates with the strategy proposal.

The Pareto Principle is also referred to as the 80-20 rule, the law of the vital few, or the principle of factor sparsity[1, 4]. It states that for many events, roughly 80% of the effects come from 20% of the causes.

The main point of the Pareto principle is to recognize that most things in life are not distributed evenly. This strategy has much of its foundation based on this concept, mainly because we want to use the least possible effort to achieve the maximum result, understanding that the effort and gain are not evenly distributed.

RPA Storm’s definition

RPA Storm was designed aiming to provide a quickly saving through the massive use of RPA, by means of automating longest manual processes committing the least possible development effort.


Thus, I have created a simple coefficient that must be used to prioritize and define what should be done:

C  = coefficient 
DT = Development Time
MT = Manual Performing Time "Annual" 

C = DT / MT

For the processing time, it is necessary to use a standard time of measurement. We will adopt into examples, yearly measurements.


'Task [X]

DT = Development Time
MT = Manual Performing Time "Annual" 

Coefficient =  DT / MT
Coefficient  =  7 / 240 
Coefficient  =  0.029167

'Task [Y]

DT = Development Time
MT = Manual Performing Time "Annual" 

Coefficient =  DT / MT
Coefficient  =  10 / 400
Coefficient  =  0.025


1) 'Task Y - 0.025
2) 'Task X - 0.029167

Setting Targets

In order to start the process we need firstly set a target, for example, let’s supposed, you have an overstaff of 10 people who work 8 hours a day, in a month you have a deficit of 1600 hours. So my target could be 1600 hours, in other words, I need to automate 1600 hours. Certainly, you may have other reasons to define your target, however, in this example, I will use overstaff. You could, for example, use this strategy to reduce the overtime or even as a proof of concept. Undoubtedly, there is a huge range of reasons and goals to use this approach, but the crucial point is to set a target to orient your effort, even more, define the target should be the first action.

Establish the target is necessary to discover, map and gather the activities that may be automated. Notice that I used the word activity, instead of process, because we will not really focus on the process as usual. A typical RPA project aims to automate a full process, however, we want to automate 1600 hours and we do not care if they are in sequence or if they are isolated activities. What we want is to use the slightest effort in order to achieve the higher return. In overstaff, after we achieve the target we will need to rebalance the activities in order to release resources.

A frequent activity that comes up to me is people spending hours to create new reports through data consolidation. These are typical cases that we can automate effortlessly. Using RPA Storm idea you will notice that in many cases we will use automation as a tool to support human activities and not as a touchless automation that seeks extinguish the job human intervention in the process.

Let’s suppose, that a person spends 1 hour a day to consolidate this information, so in a month with 20 working days we will have 20 hours and in a year we will have 240 hours. It looks like an extremely small gain. Nevertheless, imagine that to automate this we will spend only 2 hours. Well, that is the ace in the hole of this strategy.

Mapping Activities

Now, it’s time to go to the operation to gather information about the activities. The idea at this point is to reveal activities from the operation, thus, it’s interesting to do it from the operation perspective, not only based on a point of view from leader or manager. I recommend you trying talk with all the team. Try to start, gathering the requirements, from the lowest grades, because there you will find more simple activities to act and you will understand all the activities from the bottom to up. That probably will facilitate the process to you, since the complexity will increase gradually together with your knowledge about the process.

As you will be immersed in the daily work activities you probably will notice that you can make savings even without RPA. So, don’t hesitate and let the client aware about the situation because in the RPA Storm we will enter in the client to cause an impact, we need to be agents of change not only RPA providers.

Grouping Activities

Many people can repeat activities, sometimes even call them by different names but they are essentially the same thing. For this reason, we have to group these activities and calculate the time grouped to understand our real saving. Therefore, we can reuse the implementation bringing the development time, for repeated situations, to zero.

Estimating development

Once all activities have been gathered, it will be necessary to estimate the effort to develop an automation. The scopes must be limited and should only focus on specific parts of the process, it is not intended to automate all possible process flows because this is not the goal of the strategy.

These automations will have a small life cycle and for this reason, it should be borne in mind that refactoring is inevitable. Estimates must be made quickly and for this reason, we may end up having imprecise estimates. It’s important to select an experienced team to use this strategy, of course, doing it the outcome will be more accurate.

I recommend using a divide-and-conquer strategy to split your activities into smaller actions until all development tasks are less than one workday. This will help you get a clearer picture and the mistakes will be less because you will have a deeper view of what needs to be done.

Another technique that I like is to use fixed values: 30 min, 2 hours, 5 hours and 8 hours. For example, an activity that supposedly will take 1 hour and 16 minutes in accordance with the analysis, must be estimated at 2 hours.

After all, why estimate using fixed values? Let’s pretend the following situation, you have a dog and a lion. Now think which one weighs the most? The interesting thing about this though is that even though you did not know the exact weight, you know one thing is heavier than the other.

Cost-benefit Matrix

At this point we already have the two data needed to generate the cost-benefit matrix, now it is simple, we must calculate the coefficients and select the activities from the lowest coefficient to the highest until achieving the target.

An agile methodology adheres very well to this kind of environment, mainly because it fit an extremely volatile environment. Another important point is that we can have continuous deliveries of value since we have a lot of small implementations.

There is no doubt that continuous delivery of value is something that must be done in order to have an impact since the beginning of the project.

Planning the Future

After the previous steps have been completed and the automations was already delivered, it is crucial to plan the future of these processes since these automations have a short life cycle, therefore two alternatives are possible to the future: refactoring or complete replacement.

Fact is, this is an impact strategy and it does not aim to be sustainable or have completeness. What we are looking for is quick saving. It is not a strategy indicated for all situations or environments.

Therefore, is better to start a project being honest with the stakeholders. Because if your client wants a quick saving and you cannot guarantee a scalable, robust and sustainable structure, still, you can provide a strategy to achieve the client expectation and preparing the environment to the next steps. Thus, RPA Storm allows you to deliver value and increase gradually your automation’s environment, assuming that we are creating something valuable, but temporary.


Source: Robson Fernando Veiga (linkedin) – RPA STORM – The Strategy