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What is your first thought when you hear RPA? Do you think about machines taking our jobs? Or maybe dream how much nicer your life could be if you did not have to do dull and repetitive tasks?
I must admit that not so long ago I thought that RPA is just another hype. But then I decided to learn more about it from the experts and today I am pretty excited about it.
Give me my PDF. Stefan Andreasen is a passionate entrepreneur, innovator and net-worker with solid background in both technology and business. In he started Kapow as the largest European marketplace for cars, real estate and boats for sale. The items for sale was collected from thousands of dealer websites and made searchable on the www.
In the marketplace was sold to the largest bank in Denmark and Kapow became a pure-play software company — Kapow Software. Today Stefan is back in Denmark where he serves as investor, adviser and board member for a number of technology startups while looking for the next big thing.
What would you suggest to a company that wants to start using Robotic Process Automation? Be sure to get an RPA platform which supports both front-office employee invoked and back-office taken from a queue or on schedule automation. At first focus on automating the simplest processes with the highest value of automation.
Later more complex processes can be automated. Have experienced IT staff involved in setting up the right architecture, security rules and logic for audit trails before starting. Not involving IT staff and security staff.
This will almost for sure create RPA scripts which are not build on a solid framework for the figure. As COO, David has built, and now continues to lead, the global consulting, implementation and managed services teams within Symphony Ventures, ensuring flawless solution design and execution on every engagement. LI company profile Twitter: Over the last couple of years, we have been approached by numerous organisations, the world over, to advise on taking the right first few steps on their RPA journey.
Many come with a pre-conception that the first necessary step is to perform a Proof of Concept PoC. This is an exercise where we install the RPA software and perform some basic tasks, connecting to the line of business applications. Usually these projects are delayed because of access to systems, InfoSec reviews, procurement, and legal discussions. The end-point is always the same: At the end, all that is proven is what the industry already knew.
Yes, you can connect to the application and yes, you can perform a few tasks far simpler than you would see in any real deployment project. After all what would make that business that different to the hundreds or thousands that have gone before; with the same ERP, the same mainframes, legacy applications, SAAS apps, and custom apps developed in the same programming languages?
Most commonly, issues come about from not understanding the business processes in enough detail, and therefore not catering for every eventuality. We typically approach implementations with a third of the time spent on capture and design, a third on implementation, and a third on testing. Two thirds of the project is therefore focused on ensuring the business process and business rules are truly understood and the solution is fit for purpose.
The other common challenge is in resourcing a project. The ideal RPA consultant is someone with a very logical mindset, programming experience, and an interest in solving business challenges. It is not a developer, nor is it an experienced member of the operations team, although the insight from your process subject matter expertise is essential in any project.
Whilst developers do have the right skills, they often find the simplification of the configuration of RPA tools less interesting than building code from scratch, so retention of these resources is a challenge. My advice to any organization embarking on RPA is to consider engaging with a specialist firm to leverage their experience, even if that engagement is to train up your team to be more effective. Ying comes to Pega with more than 10 years of software product management experience leading Fortune organizations and VC-backed startups with varying software development methodologies to deliver award winning product solutions and enabling enterprises to make the leap from water fall to Agile.
The challenge today is that many organizations still approach their automation efforts in a siloed fashion — they start by looking at specific tasks and or processes within departments or functional areas, rather than getting aligned around the outcome for the enterprise. What is the enterprise outcome you are driving towards? Rather than a functional or department specific goal on productivity or cost savings, an outcome could be simplification of experience for employees and customers.
Look for opportunities for automation that has the broadest reach and meaningful impact. Projects such as shifting the manual copy and pasting of customer information by your highly-valued knowledge worker to robots during the customer onboarding process would be a great place to start.
Make sure your technology supports your use cases now and beyond. You might already be thinking about the role of RPA bots for the back office or perhaps quick wins via RPA assistant bots to support your knowledge workers — make sure the RPA technology you choose is flexible to support attended and unattended use cases.
Starting too big rather than MVP — example: The fraud team was divided into three departments FTEs: Each team played a very different investigative role in their respective fraud transaction but all were focused on a common outcome, minimizing fraud exposure for the bank and their customers. The assessment team focused on identifying a single task that is performed most frequently across all three departments and focused on that one task as the starting point and was able demonstrate the value and the impact across the departments in less than 8 weeks.
When companies approach RPA as a stand-alone tool instead of a key capability part of supporting a broader Enterprise Automation framework. This Franken-stack approach has rapidly created the new shadow IT and makes it even more challenging for those who are accountable for technology to ensure governance and support.
While all those benefits are true, what is missing from this binary approach is what Enterprises really need out of an Enterprise Automation framework that supports outcomes and agility. Therefore, we see organizations that continue to hold this binary view end up with a Franken-stack of technologies that makes it a challenge to achieve continuous quick wins that scale and get to transformation. The answer is not RPA vs. BPM but Enterprise Automation. Enterprise Automation with capabilities in: Intelligence that can be applied at the work level — not just at the bot — to guide the actor s working independently as well as together, and more importantly, get to your outcomes such as customer engagement and productivity.
Lastly choice and flexibility to pull in these capabilities as your organization evolves across your transformation journey so that you can deliver rapid value along the way. Pierre joined Contextor in , in charge of Marketing and Communication.
We firmly believe that RPA is complementary to BPM, to whom it provides agility, helping enterprise to engage its digital transformation. We are convinced that it is paramount to exhaustively look all business processes to clearly identify where the most repetitive tasks are happening, even if they are simple tasks covering a small part of a global process.
By starting there with attended RPA, you will succeed in quick wins by increasing employees comfort at work with more guidance, guaranteeing compliance to company policy or regulatory rules and bringing more agility to the IS. It will take a few weeks from the proof of concept to the running robots, and attended RPA will gain adhesion from clients and employees and provide fast ROI.
One of the most common error is to see too big: Then do not start your RPA journey with a strategic and complicated process you would like to automatize from end to end. It would be the shortest path to disappointment, if not failure.
Another common error is to consider RPA as a technology more than a business tool: From the operations point of view, it is crucial to know how the employees are working with the processes, sometimes adapting them, and to un-zoom to detect from which processes automation will provide the more benefits. From the IS point of view, it is important to know the capabilities, and the limitations, of RPA tools towards the specificities of enterprise IS, especially regarding legacy applications.
Culliton has over 30 years of experience in the technology sector and over 20 years of experience providing enterprise software solutions to Fortune companies. He is currently working with current and future OpenConnect customers to provide the next generation of analytics and automation solutions for back-office operations. Are you cutting head count? Are you trying to increase productivity by simplifying your processes?
Then, determine whether the processes you want to automate are complex — that is, something that a human might take some time to master — or simple. For example, the processing of insurance claims involves more complexity than most RPA tools can handle. So, if you want to automate complex tasks, this will help you considerably narrow down the choices of RPA tools and providers. By far, the most common is the failure to have, and stick to, an automation strategy from the beginning.
I wrote a blog post http: Beyond that error — and it covers a lot of ground — companies also run into the trap of what a former U.
Adam leads market development, product and brand marketing, and strategic partnerships. He began his career in management consulting in the Financial Institutions Group at BearingPoint and has spent the past 14 years in tech product marketing and advertising. He was most recently director of strategy at i.
Adam holds a bachelor degree from the University of Vermont. Before selecting an RPA product, first determine what exactly you want to accomplish. Do you want to simply automate the operation of a legacy system e.
There are many products on the market at this point, and they have different capabilities. RPA alone if-then-else programmable bots is like building a house of sticks, in that it delivers quick wins.
However, RPA alone creates exceptions and ignores the simple judgment work that weighs down an operation and can be automated with machine learning powered cognitive automation.
Businesses looking for both quick wins and long-term value select products that combine both RPA and cognitive. Three key beginning steps are: The champion is essential for enterprise-wide visibility, credibility, and funding; the operational evangelist is needed to fill a beginning pipeline and create a team with the technology and methodology to automate the qualified opportunities; IT must made aware of the technology and how it will be used. Being entirely too casual about their RPA implementation is the greatest and most common error.
The technology of a few RPA vendors has advanced dramatically — but many customers fall into the trap of viewing all robotic solutions as the being essentially the same.
By not selecting the best technology, their implementations are crippled by issues with product usability; extensibility, scalability and virtual environments. Another error is rushing past the building blocks of governance and methodology to show a quick success — typically on a very simple process.
Which makes sense to a degree, but then RPA stumbles when the more difficult processes in the pipeline are automated, creating an environment for pushback and discouragement. He is responsible for worldwide marketing of the Kofax Kapow robotic process automation software platform. He has fifteen years product marketing and product management experience managing various software products and solutions. Take the time to look at the big picture business challenges you are trying to solve, so that you fully understand how best to solve, and the benefits that can be achieved.
Robotic Process Automation RPA is a great fit for automating a lot of different tasks or activities within a business process where gaps exist and work is still done manually.
I always start with making clear that the process itself is useful. Cheap useless processes are still useless. And then I go deeper; do we still need all that data to execute or manage the process? You are probably familiar with those kind of process analysis questions. And I know, that also costs time and money. But as a human, the social consequences worry me the most. As told, as a process owner, I would love to execute my processes cheaper. Unfortunately that often mean people lose their job.
And these days many people still have those administrative data processing types of jobs. I hope companies will take that into consideration. On the other side; the cool thing is in my opinion that administrative jobs will become less popular in the future.
This hopefully leads to the fact that kids learn a real craft again. Jobs where they make things. Maybe digital things like robots or AI algorithms, but also real stuff. I always have too laugh when I am in a big building where everybody can program software, but nobody knows how to fix a broken coffee machine or a clogged toilet. She has also founded and run three companies — a systems integration services company, a software product company, and current consulting company — with responsibility for corporate and financial governance, strategic direction, team hiring and management, and day-to-day technical contributions.
Sandy blogs about BPM, enterprise architecture and other intersections of business and technology at www. This was necessary because the mainframe applications typically did not have APIs or any other callable interfaces, so the only way to interact with them was to emulate a user by sending keystrokes and reading the results from the terminal window. This type of integration could be used to hide the text screens from the user and replace them with more functional user interfaces, and to automate actions on the text screens by sending keystrokes to the screen in order to assist the user in their tasks.
Eventually, screen-scraping made way for RPA, and workflow evolved into BPM, with opportunities for these technologies to be used together effectively.
RPA is a fast way to automate user tasks with a minimum of effort and disruption for both the users and IT. A long time before joining Redwood, Neil began his management career at Xerox where he worked for 14 years. The RPA market is full of overblown vendor claims, and lots of hype about cognitive and artificial intelligence. Cut through that and ask to see and speak to references who have deployed this at industrial scale, or who can confirm that they got what the vendor promised, and as a result are pushing on from the initial pilot.
Ask to look at the total cost of ownership, not the acquisition cost of the robot which can be as low as free. As in most aspects of life, there is no such thing as a free lunch.
The most common mistake is simply making the robot emulate tasks that a human would do, and investing time money and energy and refining that emulation with diminishing returns in productivity.
The reality is with that approach you end up with a tipping point when the effort to manage the robots outweighs the benefit in productivity. You end up replacing low cost effort, with expensive robot supervisors that are never called out in the business case or by the vendors. What you really want is your people available to do the things that they are good at and that add value, rather than having them in place to catch the things the robot is bad at. You can only achieve that if you look at the process and the desired outcomes, not the individual tasks themselves.
As with every other technology which should be introduced in an organisation, select pilot processes to apply RPA technology. These pilot processes should be of reasonable size not to small, not to large and should allow to test the potential of RPA.
As RPA is about automating tasks of human-machine interaction, the as-is process analysis should be mapped down to task level, not only subprocess level. The tasks should be categorised based on their IT coverage, i. Besides gathering experiences using RPA technology itself, also HR-relasted aspects should be covered in the pilot project to prepare for process-related as well as people-related changes.
One of the most common errors we see in the context of RPA is to start with too complex pilot processes and based on this, to have problems to deliver tangible results within a reasonable time. Another problem we identified is not representing both business and IT within the RPA pilot project in a balanced way. RPA advocates that it is for business, but IT should be involved as well with a special focus on governance topics.
John Mancini is an author and speaker on technology and digital transformation trends and a respected leader in the content and information management community. He believes that in the next 5 years, a wave Digital Transformation will sweep through businesses and organizations, and organizations now face a fundamental choice between Information Opportunity and Information Chaos. As a frequent keynote speaker, John offers his expertise on Digital Transformation and the struggle to overcome Information Chaos.
He blogs under the title Digital Landfill, has almost 10, Twitter followers and a Klout score in the 60s. I have a fair amount of experience with terms that industry marketers and analysts apply to market segments.
We had in mind a set of disciplines and strategies by which organizations attempted to capture, manage, store, preserve, and deliver content and information critical to business processes. Looking back, this created two sets of problems. But not everyone shared this expansive definition. The early days of process automation were all about getting core processes to scale. ECM and BPM solutions focused on creating new efficiencies by automating high-value, mission-critical, and document-intensive processes.
The focus was on a small number of direct process-stakeholders and users. Solutions were expensive and custom and took a long time to implement. But in an era of technology disruption, efficiency is a necessary but not sufficient condition for success. Success requires agility as well as efficiency.
Being an agile enterprise means that process change must occur dynamically and in small increments. It means that accountability and responsibility for process innovation must be decentralized and driven as close to the customer as possible. It means that the tools and platforms upon which process innovation occurs must be accessible to the business and easily usable by the business with a minimum of IT intervention.
Being an agile enterprise means that the era of complex BPM customizations must end and transition to low-code and no-code platforms. Co-Founder and Chief Everything Officer Asheesh is an outsourcing veteran with over 20 years of cross-industry experience. Under his tutelage, Infosys BPO grew its business through both organic and acquisitive routes and managed the region with two delivery centres in the Philippines and three in China. Sebastien Meunier is an expert in Innovation in Finance, with 15 years of experience in managing business and technology transformations in Financial Services, and among the top 10 Fintech influencers on social media.
I would advise them to spend time upfront to really understand what is RPA compared to other automation techniques, organizing awareness sessions and workshops to identify relevant use-cases before jumping into experimentation. Then I would recommend to go step by step: And always keep a business perspective: Derek Miers focuses on the methods, approaches, frameworks, techniques, and technologies around BPM and business transformation programmes—workflow, case management, robotic process automation, decision management; alongside the methods associated with business architecture, and target operating models.
Think big, start small … iterate been saying that about BPM and workflow for the last 20 years. Trying to treat it as just a quick fix … a way of downsizing the organization … leads to all sorts of political problems. Does nothing for the value proposition of the organization.
Since co-founding the company, Gabby has advanced his thought leadership in IT automation and been dedicated to setting the company on a path to strong growth and validation. The Ayehu platform continues to earn accolades from customers, partners and industry experts including Gartner, Red Herring and Deloitte. Prior to founding Ayehu, Gabby held various operational and management positions at successful Israeli technology enterprises including Infogate Online Ltd, Webmaster and Walla Communications Ltd.
When it comes to choosing RPA software for your organization, the choices certainly are many. It starts with an internal audit to determine your present and future goals and needs. From there, establish some specific guidelines that will help you to avoid becoming overwhelmed by all of your available options.
Consider these factors as you begin the evaluation process:. Integration creates a more robust and highly functional platform that effectively carries out workflows. Likewise, if the tool cannot be rolled out broadly to the entire organization due to the need for extensive training and in-depth knowledge, the overall benefits will no longer outweigh the time, money and efforts invested in the process. The goal should be, over time, to be able to reuse certain parts of existing workflows to facilitate faster, easier and more efficient creation of new workflows.
Outside IT, reports are also essential as they demonstrate the overall value of the work being done. Because RPA technology is relatively new, there are certain pitfalls that IT professionals should be aware of so they can avoid any negative impact on the department and company as a whole.
Here are four of these common drawbacks:. However, problems can arise when and if any part of a particular process is changed. If a process change is not properly communicated, documented and applied, the RPA will inevitably fail.
That means that unless it is properly programmed, it will not necessarily work without issue right out of the gate. Still, many of the duties that were once handled by people will no longer exist as part of the day to day activities. As this shift occurs, be prepared to adapt and transition employees into new roles within the company. He frequently tops the lists of the most recognized names in his field, and was the first individual named as Laureate in Workflow.
Start with repetitive human tasks, where users are bogged down performing tedious work, repetitive steps, or otherwise without requiring any meaningful analysis. Also look for where users are shifting back and forth between different application interfaces as part of the task or process step.
These scenarios are where the low hanging fruit will be found and offer the logical starting point for RPA. Understand that BPM was never designed to fully replace the work done by human beings, but rather to facilitate that work by assigning tasks, sequencing steps, enforcing rules, and other means of work management.
In contrast, RPA in fact is purpose-built specifically to replace work otherwise less efficient and effective when performed by humans. There is not today an established standard or methodology which prescribes the ideal interplay between BPM and RPA, and indeed some of the greatest pitfalls lay in the poorly defined separation of concern between the two.
For example, one of the common mistakes is to create too complex of rules, and miss the opportunity for separately managing decision logic business policies and rules separate from the procedural rules necessary to the automated task. No RPA platform is designed for decision management, yet a well-architected approach can and should leverage best of breed capabilities. Lastly, perhaps the most common mistake is aiming too low and underestimating the potential of RPA.
This is every bit as powerful, with an equivalent potential for disruption, as adding physical robots into the enterprise workforce. It is far more powerful than that. RPA is something entirely new, and as part of a broader BPM strategy enables levels of efficiency and digitalization previously out of reach.
Gabriel Pana has been working for the past 5 years in IT and Operations with a high knowledge of processes, business analysis and improvement. He joined UiPath in to work and grow the business in all areas with a main focus on channels, alliances and the manufacturing vertical. We would suggest to look at all internal and outsourced processes and decide on some that can be automated into a pilot.
By involving all departments you are to achieve a better ROI within the company and so you will be able to transform your full business. While the pilot focuses on showing the capabilities, the initial assessment of all Company groups and department will allow a fast scale up and growth. Although we all pride that RPA is a business solution, IT should always be involved from the start — to help with the development, implementation, infrastructure and architecture.
This will allow, eventually, a higher ROI and a fast deployment — with less bottlenecks. He manages product marketing strategy, competitive intelligence, technical alliance marketing and the customer advisory group. Bart enjoys boating, hiking and music with his family in Austin, Texas.
Company LI profile Twitter: There are several critical considerations for organizations deploying RPA. First, they have to define their automation strategy, begin building a robust operating model and ensure cultural adoption from the business and employees. RPA should be easily applied to automate repetitive processes of administrative work without interfering with work ethic or moral.
A good RPA deployment enables employees to make higher value contributions to the business by automating the repetitive tasks. Human and robot need to work together in harmony. Next, organizations should ensure that their RPA solution is built, managed and owned by an accredited operational team or Center of Excellence spanning operations and technology.
This ensures not only the highest quality, but also compliance by having the robotic process adhere to all IT policies and regulatory governance. Overall, the RPA platform must have the functionality to meet the strictest standards of security, control, data integrity, change management and scalability. They deploy an RDA solution across disparate desktops throughout a business unit without consulting IT which has several negative implications.
First, since it is not centrally managed, there is susceptibility to fraud as one individual controls the robot and whatever process it runs, such as financial account management. There are some use cases with small business and outsourcers that are ideal for RDA.
Another mistake we see is the other extreme, that is when IT tries to build the Robotic Processes from the ground up with a vendor. We encourage organizations to go with an RPA solution that is controlled by the business, but governed by IT.
Thierry is specialized in setting up, incubating and growing successful projects for customer service organizations by creating an ecosystem of People, Processes and Technology. His tour of duty includes working for some of the largest system integrators, 2 of the Big 5 Customer Service Providers, and setting up customer service operations for large accounts in Banking, Telecom, and Automotive sectors.
RPA is only making processes faster and with no data error, but it does not make them efficient. So every Automation project should have an initial phase of Lean process analysis. The major error is to not do a real benchmark on solutions, via a POC or a Pilot. And second, not implying business and compliance into the selection and the design.
He is a member of the executive committee of Science Olympiad Foundation, the largest Olympiad in the world. He is the CEO and Founder of a software product company called Epiance, which has clients all over the world, clients who vouch for the product line which he created.
He has 30 years of experience in the corporate arena. Ravi has been a pioneer of knowledge management and business process modeling.
He was one of the founders and early evangelizers of Electronic Performance Support. R Ravi was one the of the early creators of the foundations for automation. In fact the first automation product that he created in was well ahead of its time. Many of the these ideas form the basis for the Robotic Automation product that is becoming very popular today.
He has multiple patents patent pending to his name. Just like with any new technology, organizations tend to get carried away by the hype of RPA and tend to build intense internal pressure to adopt this technology.
It is amazing how human beings repeat the same mistake again and again. The most commonsensical approach is abandoned and replaced either by a very aggressive unidimensional strategy or a very conservative wait and watch attitude.
An organization should consider the following aspects very carefully before they embark on RPA strategy. Understand the internal dynamics. Are the key stakeholders supportive? Is the operational leadership willing to embrace this technology? Much of the operational leadership is still steeped in the mindset of more people, more power.
The resistance to change can therefore be intense. This is a key component that needs to be considered. Instead of delving directly into automation and getting carried away by the hype of RPA- go deeper.
The key aspect that organization really want to focus on is improvement in performance or improving productivity. Automation is just one piece of the puzzle. There are many other complementary technologies which along with automation can yield dramatic benefits. How can onecCombine this with automation and arrive at a holistic approach.
If you are a part of the executive leadership shield your team from excessive pressure to deliver results quickly. Excessive speed makes a system commit more errors. Theoretical understanding or feedback from analysts can only go so far. I would definitely recommend organizations to do live implementations of Performance improvement in diverse processes. Based on the actual experience strategize the organizational approach.
Answer questions such as what kind of processes should I automate? High visibility can increase speed , but can also create unnecessary resistance to future projects if some hitches develop. Take all softer aspects, humane aspects, technology aspects, political dynamics, customer expectations before crafting a strategy for improvement.
Diving immediately into RPA without any experience. Aiming for complete automation at the first go. Being disappointed with small productivity gains.
Incremental approach is the best when it comes to any new technology. IN a large organization , increasing visibility to the project. This sometime backfires because the project is over managed and small mistakes are amplified. Implementation managers spend most of their time with unnecessary escalations. Sometimes it might be advisable to underplay the project and gradually increase visibility to various stakeholders. The approach will vary based on an individual organizational dynamics.
Losing track of the objective of performance improvement and focusing narrowly on just automation. Being driven by multiple stakeholders. It is always advisable for a single individual to drive the pace and strategy of automation. Managing external pressures is critical. It cannot affect the core aspects of RPA implementation strategy.
Picking up the moist challenging , toughest and most aggressive processes. Ignoring the low hanging fruits. Ignoring alternatives to RPA. Sometimes implementing a new technology may be a superior solution.
One has to remember that RPA is a patchwork solution and is not necessarily the most elegant one. However there have been cases where a grounds up development could be superior to RPA. Adrian Reed is a true advocate of the analysis profession. In his day job, he acts as Principal Consultant and Director at Blackmetric Business Solutions where he provides business analysis consultancy and training solutions to a range of clients in varying industries.
It might be that an organisation is looking to reduce cost, reduce backlogs, increase speed—but knowing this in advance will help shape and frame the initiative. If we automate a bad process, we can end up with more waste and failure demand! So understanding the work, and the end-to-end process and how it impacts the customer and other stakeholders is crucial.
This is just one specific example, of course—and I am certainly not arguing against RPA when used in the appropriate contexts! Finally, I think buy-in is important. We need to accept that as with any change the concept of automating work may be disruptive and even scary to some. Appreciating that this is not just a technology and process change, but also a people and human change is crucial.
We must engage, and engage with empathy. This includes increasingly the intersections of unstructured data, analytics, and Cognitive Automation while mobilizing the HfS analysts to research Intelligent Automation dynamics across specific industries and business functions.
A central theme for all his research is the increasing linkages between technological evolution and evolution in the delivery of business processes. Intelligent Automation in general and RPA are in the eye of the beholder as the market lacks a common understanding or even robust definitions.
This stems both from the nascent phase of market development as well as from the reluctance of the large service providers to educate the market. While nothing is defined in the context of automation, the common denominator in all the approaches is decoupling routine service delivery from labor arbitrage. Against this background, buyers need to be clear that RPA is about service delivery, but not about individual tools or technologies.
Therefore, buyers should invest significant time in evaluating the appropriate processes for RPA. The most important question is, what form of enterprise transformation you are trying to enable and achieve? Everything else will follow from there. Thus, buyers should avoid short-term focused, tool centric approach. Think about service orchestration. Governance, security and testing should be central considerations not afterthoughts.
Last but not least think about the implications on talent. The talent understanding not only those innovative technologies but their impact on process chains and workflows is scarce. They are the key educators in the market. Much information is on their websites, but we can also do introductions. But also consider the impact on your own workforce. Change management is the crucial conduit for successful deployments. Most mistakes and consequently failed projects result from ignoring the points we have raised above.
Many look for the next short cut or silver bullet to achieve cost savings. Yet, most of these savings are on sub-process levels and deployments are not scalable. Thus, for many RPA is like drug to satisfy those desires for guaranteed cost take out.
As automation and RPA should be about service delivery, buyers need to think about end-to-end processes and transformation. Notions of data curation should be a starting but not a by-product. What we are seeing is that buyers, often confused by the marketing of a market that is not defined, are jumping onto projects without co-ordination or change management.
Within larger organizations we are seeing multiple RPA projects often without the knowledge of the process owner. Similarly, IT is often not part of the decision-making process, yet critical to success of the deployments. And lastly, buyers are confused what RPA really is as the use of the moniker across the industry is inflationary. The difference of RPA vs. RDA, the implications on front and back-office, the need to integrate broader automation capabilities all too often gets lost not least as the large service providers are shying away from educating market.
Pedro has more than 24 years of professional experience in Enterprise Software Market with a complete background and skills in sales, marketing and business development, focused on the company strategy, lead generation and oriented to objectives with the commitment and consecution to results.
He is one of the most influential Spanish thought leader in BPM, as for 10 years has been dedicated to promote industry awareness of Business Process Management in Spain and Latin America — also as a Professor. RPA technology plays and will play an important role in BPM, from the automation of repetitive human tasks that can be replaced by a robot either software, hardware or both.
RPA is based on notions of software robots that replicate the actions of a human interacting with a user interface with a computer, which can benefit BPM when optimizing a transversal process of the organization, taking the orchestration of all Robots involved in a process. The analyst Grand View Research, Inc. And another important driver is that it is estimated that RPA is expected to cost as one-third of the least expensive offshore labor.
When any company model a process using Business Process Analysis can identify processes or sub-processes with high daily volumes of repetitive tasks and low added value that are performed by employees, as these tasks should be replaced by the execution of RPA technology, to get security and responsiveness, to reduce errors, and to save time and money.
And now the use of Artificial Intelligence machine learning in RPA allows you to adapt to different circumstances and make decisions on the automated process allowing more adaptability. Many of the problems in implementing BPM are common in implementing RPA, but RPA has many problems when the implementation does not follow a continuous improvement cycle, as it is required to control the impacts of any change in a process, and even any change in the strategy of the company that it requires a modification of processes, systems, applications… that it could be controlled by Enterprise Architecture tools.
In the implementation of RPA, there are important dependencies between systems, data and applications, so we should be sure that any change in one system, on data table or the release of any application can create a problem in the automated process.
The phase of creation is very critical, and it requires to make enough tests with all possible scenarios to check that the automated process works fine, because if the process itself is flawed the RPA does is formalize the flaws. Please, run a pilot project first and clearly demonstrate the right execution and right performance it is important to control metrics before the automation and after.
Another common error is about documentation similar problem than application programming , if the RPA is not well documented with all process definition and mapping in detail it will be difficult to make changes and to ask how it works.
So all have to be rigidly documented and recorded requirements, process definition, change requests, metrics, bugs, releases, exceptions…. He also develops relations with the process mining academic community and evangelizes process mining benefits to enterprises worldwide. Robotic Process Automation speeds up business processes and eliminates repeating manual tasks handled by human resources, by assigning them to robots. RPA vendors around the world offer sophisticated solutions that make RPA implementation projects easy and fast to execute.
I would also suggest not to leave out post implementation evaluation. Addressing these points early and based on data is a key to successful RPA. Minit as an analytical tool working on the principles of process mining offers technological support for making the right and data-based decisions. It might seem obvious, that RPA brings benefits to the enterprise, speeds up the process and cuts costs, but it also gives rise to further questions: A Is it possible to quantify the benefits of RPA optimized process to the original?
B As robots perform their tasks faster and in much larger scale, what is the impact: When deployed, robots of most vendors are precisely logging all the activities performed, thus offering a data source for post-implementation evaluation of process performance.
Minit can use that information to carry out a regular process analysis and based on it, compare the processes among themselves. This approach helps to quantify the added value of RPA and identify further potential problems, leading the enterprise on the path to continuous improvement.
In the pre-implementation phase, based on our experience, there are in general two approaches to process analysis:. This approach is time and resource consuming and often related to potential issues of subjectivity, limitation of view and exception related problems.
The disadvantage of this method might occur in cases where information systems and lack of regulations or rules let employees perform tasks in various order.
In such as cases, identifying the right individual is mostly based on feeling or approximation. Typically resulting in the same issues as mentioned before — subjectivity, limitation of view and exception related problems.
The process discovery is automated and eliminates the subjectivity and view limitations at the same time it includes all the exceptions no matter how often they occur. There are multiple possibilities to filter the process data based on various criteria — timeframe, metrics, variants, attributes of process instances and cut the process model by different dimensions, hence drilling down into those parts of the process that are of the interest to the customer.
The RPA related decisions are thus data centric and objective, the canvas is filled with the reality based process model, and bottlenecks and inefficiency points are easily spotted.
Using the interaction recording allows the analyst to monitor work of all individuals performing the analyzed tasks and combining them to a single process map automatically. The analyst can then drill down into single process variants, explore different behavioral patterns and quickly pick the right person to base the RPA project on. Mathias is the technical Founder of a9t9 and Kantu.
He is also the original author of iMacros, a popular web automation software with hundreds of thousands of users. Before starting out on his own, he worked for the business software giant SAP, where he was responsible for the design of HR-specific databases.
He is the main author of five patents. When not working on Kantu, he is figuring out methods to make his remote controlled Quadcopter fly by itself. Clearly describe the processes that you want to automate, ideally with screenshots of each step. This will give you the best of both worlds: You are flexible because you use a real scripting language AND you save time because you use RPA for the tricky parts.
Alexander Samarin is an architect for achieving the synergy between strategy, good business practices and disruptive digital technologies in various digital systems: Because those robots are, actually, programmable containerised microservices then application architecture enables agility and reliability. And, beware of automation pitfalls see http: Over the last 14 years, Mohit has acquired strong experience in managing and leading process improvement, strategic change management, transformation shared services, onshore and offshore and risk management projects within large diversified Australian and global financial services companies.
We have been part of the biggest deployment of Robotic workforce in the world. For starters It is very important to understand standard definition of RPA from end user perspective.
Currently, they are advise by consultants or RPA software providers. Most of them they modify the definition of RPA to match to their service offerings. They can view our Independent and comprehensive report http: They need to create and develop internal capabilities for RPA in medium and long term.
We are training clients to do automation by themselves. First phase should cover maximum 10 process with not expensive tool with no frill consulting firm. Automate them with trial versions…experience the difference before selection. Train your own resources and do not have high expectations in first phase. RPA should be led by enterprise wide strategy. Clients need to identify and segment their drivers for automation into 3 buckets i.
New starters need to be lean and learn from mistakes from other organisations who have already in mature stage of their RPA journey. They should not have high expectations in the initial phase. Automation should be treated as first step of the journey not a destination. Mihir is a visionary in the automation space, having helped define a new, 3 billion dollar market category for business process automation BPA. With the aim of constantly producing and innovating on automation software that is easy to use, and utilizes enterprise social collaboration and mobility platforms, Mihir leads the charge in driving billions of dollars in savings to millions of businesses, transforming the way they operate.
An engineer at heart, Mihir focuses Automation Anywhere as a whole on creating groundbreaking technology that changes the way businesses think about automation.
His previous experience includes leadership roles in internet, e-commerce, and wireless market leaders at the forefront of innovation like E2Open, Kiva, ISN, Netscape, Infoseek, and Omnisky. There is nothing holding you back. We provide both speed and scale. These are some of the reasons companies both large and small are deploying anywhere from 50 bots to thousands of bots. This is not a trend. It is a dramatic shift in the way people and machines will work together.
Once you have automated a few processes which can be automated, you will find hundreds more which must be automated. People will sometimes imagine that RPA is not only difficult to adopt but that it will somehow be rejected by employees. In truth, employees embrace the promise of RPA taking the mundane things off their plates, liberating them to do the things human beings prefer to do. No one, at any job level, wants to do a repetitive task again and again. It automates routine, repetitive tasks instantly.
It frees human workers to use their brains, their talent and their imaginations. What bigger mistake could there be than suppressing the real potential of human workers? Prior to joining Aragon, Mr. Sinur spent 20 years at Gartner, where he was critical in creating the first Hype Cycle and Maturity Model, which have become a hallmark of Gartner analysis, along with the Magic Quadrant. Prior to Gartner, Mr. It was not so much because he was a programmer that Facebook seemed a good idea to Mark Zuckerberg as because he used computers so much.
If you'd asked most 40 year olds in whether they'd like to publish their lives semi-publicly on the Internet, they'd have been horrified at the idea. But Mark already lived online; to him it seemed natural. Paul Buchheit says that people at the leading edge of a rapidly changing field "live in the future. Live in the future, then build what's missing. That describes the way many if not most of the biggest startups got started. Neither Apple nor Yahoo nor Google nor Facebook were even supposed to be companies at first.
They grew out of things their founders built because there seemed a gap in the world. If you look at the way successful founders have had their ideas, it's generally the result of some external stimulus hitting a prepared mind.
Lots forgot USB sticks. The reason those stimuli caused those founders to start companies was that their experiences had prepared them to notice the opportunities they represented. The verb you want to be using with respect to startup ideas is not "think up" but "notice. The most successful startups almost all begin this way. That may not have been what you wanted to hear. You may have expected recipes for coming up with startup ideas, and instead I'm telling you that the key is to have a mind that's prepared in the right way.
But disappointing though it may be, this is the truth. And it is a recipe of a sort, just one that in the worst case takes a year rather than a weekend.
If you're not at the leading edge of some rapidly changing field, you can get to one. For example, anyone reasonably smart can probably get to an edge of programming e. Since a successful startup will consume at least years of your life, a year's preparation would be a reasonable investment.
Especially if you're also looking for a cofounder. Other domains change fast. But while learning to hack is not necessary, it is for the forseeable future sufficient. As Marc Andreessen put it, software is eating the world, and this trend has decades left to run.
Knowing how to hack also means that when you have ideas, you'll be able to implement them. That's not absolutely necessary Jeff Bezos couldn't but it's an advantage.
It's a big advantage, when you're considering an idea like putting a college facebook online, if instead of merely thinking "That's an interesting idea," you can think instead "That's an interesting idea. I'll try building an initial version tonight.
Noticing Once you're living in the future in some respect, the way to notice startup ideas is to look for things that seem to be missing. If you're really at the leading edge of a rapidly changing field, there will be things that are obviously missing.
What won't be obvious is that they're startup ideas. So if you want to find startup ideas, don't merely turn on the filter "What's missing? But if you're thinking about that initially, it may not only filter out lots of good ideas, but also cause you to focus on bad ones. Most things that are missing will take some time to see. You almost have to trick yourself into seeing the ideas around you. But you know the ideas are out there. This is not one of those problems where there might not be an answer.
It's impossibly unlikely that this is the exact moment when technological progress stops. You can be sure people are going to build things in the next few years that will make you think "What did I do before x?
What you need to do is turn off the filters that usually prevent you from seeing them. The most powerful is simply taking the current state of the world for granted. Even the most radically open-minded of us mostly do that. You couldn't get from your bed to the front door if you stopped to question everything.
But if you're looking for startup ideas you can sacrifice some of the efficiency of taking the status quo for granted and start to question things. Why is your inbox overflowing? Because you get a lot of email, or because it's hard to get email out of your inbox? Why do you get so much email? What problems are people trying to solve by sending you email? Are there better ways to solve them? And why is it hard to get emails out of your inbox?
Why do you keep emails around after you've read them? Is an inbox the optimal tool for that? Pay particular attention to things that chafe you. The advantage of taking the status quo for granted is not just that it makes life locally more efficient, but also that it makes life more tolerable. If you knew about all the things we'll get in the next 50 years but don't have yet, you'd find present day life pretty constraining, just as someone from the present would if they were sent back 50 years in a time machine.
When something annoys you, it could be because you're living in the future. When you find the right sort of problem, you should probably be able to describe it as obvious , at least to you. When we started Viaweb, all the online stores were built by hand, by web designers making individual HTML pages.
It was obvious to us as programmers that these sites would have to be generated by software. That suggests how weird this process is: Since what you need to do here is loosen up your own mind, it may be best not to make too much of a direct frontal attack on the problem — i. The best plan may be just to keep a background process running, looking for things that seem to be missing.
Work on hard problems, driven mainly by curiosity, but have a second self watching over your shoulder, taking note of gaps and anomalies. You have a lot of control over the rate at which you turn yours into a prepared mind, but you have less control over the stimuli that spark ideas when they hit it.
If Bill Gates and Paul Allen had constrained themselves to come up with a startup idea in one month, what if they'd chosen a month before the Altair appeared? They probably would have worked on a less promising idea. Drew Houston did work on a less promising idea before Dropbox: But Dropbox was a much better idea, both in the absolute sense and also as a match for his skills.
If you do that, you'll naturally tend to build things that are missing. It wouldn't seem as interesting to build something that already existed. Just as trying to think up startup ideas tends to produce bad ones, working on things that could be dismissed as "toys" often produces good ones.
When something is described as a toy, that means it has everything an idea needs except being important. It's cool; users love it; it just doesn't matter. But if you're living in the future and you build something cool that users love, it may matter more than outsiders think. Microcomputers seemed like toys when Apple and Microsoft started working on them. I'm old enough to remember that era; the usual term for people with their own microcomputers was "hobbyists. The Facebook was just a way for undergrads to stalk one another.
At YC we're excited when we meet startups working on things that we could imagine know-it-alls on forums dismissing as toys. To us that's positive evidence an idea is good.
If you can afford to take a long view and arguably you can't afford not to , you can turn "Live in the future and build what's missing" into something even better: Live in the future and build what seems interesting. School That's what I'd advise college students to do, rather than trying to learn about "entrepreneurship. The examples of the most successful founders make that clear.
What you should be spending your time on in college is ratcheting yourself into the future. College is an incomparable opportunity to do that. What a waste to sacrifice an opportunity to solve the hard part of starting a startup — becoming the sort of person who can have organic startup ideas — by spending time learning about the easy part.
Especially since you won't even really learn about it, any more than you'd learn about sex in a class.
All you'll learn is the words for things. The clash of domains is a particularly fruitful source of ideas. If you know a lot about programming and you start learning about some other field, you'll probably see problems that software could solve.
In fact, you're doubly likely to find good problems in another domain: So if you're a CS major and you want to start a startup, instead of taking a class on entrepreneurship you're better off taking a class on, say, genetics.
Or better still, go work for a biotech company. CS majors normally get summer jobs at computer hardware or software companies. But if you want to find startup ideas, you might do better to get a summer job in some unrelated field. It's no coincidence that Microsoft and Facebook both got started in January. At Harvard that is or was Reading Period, when students have no classes to attend because they're supposed to be studying for finals. Preferably with other students. It's not just the classes that make a university such a good place to crank oneself into the future.
You're also surrounded by other people trying to do the same thing. If you work together with them on projects, you'll end up producing not just organic ideas, but organic ideas with organic founding teams — and that, empirically, is the best combination.
If an undergrad writes something all his friends start using, it's quite likely to represent a good startup idea. Whereas a PhD dissertation is extremely unlikely to. For some reason, the more a project has to count as research, the less likely it is to be something that could be turned into a startup. Whereas when students or professors build something as a side-project, they automatically gravitate toward solving users' problems — perhaps even with an additional energy that comes from being freed from the constraints of research.
Competition Because a good idea should seem obvious, when you have one you'll tend to feel that you're late. Don't let that deter you. Worrying that you're late is one of the signs of a good idea. Ten minutes of searching the web will usually settle the question.
Even if you find someone else working on the same thing, you're probably not too late. It's exceptionally rare for startups to be killed by competitors — so rare that you can almost discount the possibility. So unless you discover a competitor with the sort of lock-in that would prevent users from choosing you, don't discard the idea. If you're uncertain, ask users. The question of whether you're too late is subsumed by the question of whether anyone urgently needs what you plan to make.
If you have something that no competitor does and that some subset of users urgently need, you have a beachhead. Or more importantly, who's in it: For example, if you're building something differentiated from competitors by the fact that it works on phones, but it only works on the newest phones, that's probably a big enough beachhead.
Err on the side of doing things where you'll face competitors. Inexperienced founders usually give competitors more credit than they deserve. Whether you succeed depends far more on you than on your competitors. So better a good idea with competitors than a bad one without. You don't need to worry about entering a "crowded market" so long as you have a thesis about what everyone else in it is overlooking.
In fact that's a very promising starting point. Google was that type of idea. Your thesis has to be more precise than "we're going to make an x that doesn't suck" though.
You have to be able to phrase it in terms of something the incumbents are overlooking. Best of all is when you can say that they didn't have the courage of their convictions, and that your plan is what they'd have done if they'd followed through on their own insights. Google was that type of idea too. The search engines that preceded them shied away from the most radical implications of what they were doing — particularly that the better a job they did, the faster users would leave.
A crowded market is actually a good sign, because it means both that there's demand and that none of the existing solutions are good enough. A startup can't hope to enter a market that's obviously big and yet in which they have no competitors. So any startup that succeeds is either going to be entering a market with existing competitors, but armed with some secret weapon that will get them all the users like Google , or entering a market that looks small but which will turn out to be big like Microsoft.
Most programmers wish they could start a startup by just writing some brilliant code, pushing it to a server, and having users pay them lots of money. They'd prefer not to deal with tedious problems or get involved in messy ways with the real world. Which is a reasonable preference, because such things slow you down.
But this preference is so widespread that the space of convenient startup ideas has been stripped pretty clean. If you let your mind wander a few blocks down the street to the messy, tedious ideas, you'll find valuable ones just sitting there waiting to be implemented.
The schlep filter is so dangerous that I wrote a separate essay about the condition it induces, which I called schlep blindness. I gave Stripe as an example of a startup that benefited from turning off this filter, and a pretty striking example it is. Thousands of programmers were in a position to see this idea; thousands of programmers knew how painful it was to process payments before Stripe. But when they looked for startup ideas they didn't see this one, because unconsciously they shrank from having to deal with payments.
And dealing with payments is a schlep for Stripe, but not an intolerable one. In fact they might have had net less pain; because the fear of dealing with payments kept most people away from this idea, Stripe has had comparatively smooth sailing in other areas that are sometimes painful, like user acquisition. They didn't have to try very hard to make themselves heard by users, because users were desperately waiting for what they were building.
The unsexy filter is similar to the schlep filter, except it keeps you from working on problems you despise rather than ones you fear. We overcame this one to work on Viaweb.
There were interesting things about the architecture of our software, but we weren't interested in ecommerce per se. We could see the problem was one that needed to be solved though.
Turning off the schlep filter is more important than turning off the unsexy filter, because the schlep filter is more likely to be an illusion. And even to the degree it isn't, it's a worse form of self-indulgence. Starting a successful startup is going to be fairly laborious no matter what. Even if the product doesn't entail a lot of schleps, you'll still have plenty dealing with investors, hiring and firing people, and so on. So if there's some idea you think would be cool but you're kept away from by fear of the schleps involved, don't worry: The unsexy filter, while still a source of error, is not as entirely useless as the schlep filter.
If you're at the leading edge of a field that's changing rapidly, your ideas about what's sexy will be somewhat correlated with what's valuable in practice. Particularly as you get older and more experienced. Plus if you find an idea sexy, you'll work on it more enthusiastically. Sometimes you need an idea now. For example, if you're working on a startup and your initial idea turns out to be bad.
For the rest of this essay I'll talk about tricks for coming up with startup ideas on demand. Although empirically you're better off using the organic strategy, you could succeed this way. You just have to be more disciplined. When you use the organic method, you don't even notice an idea unless it's evidence that something is truly missing. But when you make a conscious effort to think of startup ideas, you have to replace this natural constraint with self-discipline. You'll see a lot more ideas, most of them bad, so you need to be able to filter them.
One of the biggest dangers of not using the organic method is the example of the organic method. Organic ideas feel like inspirations.
There are a lot of stories about successful startups that began when the founders had what seemed a crazy idea but "just knew" it was promising. When you feel that about an idea you've had while trying to come up with startup ideas, you're probably mistaken. When searching for ideas, look in areas where you have some expertise. If you're a database expert, don't build a chat app for teenagers unless you're also a teenager. Maybe it's a good idea, but you can't trust your judgment about that, so ignore it.
There have to be other ideas that involve databases, and whose quality you can judge. Do you find it hard to come up with good ideas involving databases? That's because your expertise raises your standards. Your ideas about chat apps are just as bad, but you're giving yourself a Dunning-Kruger pass in that domain.
The place to start looking for ideas is things you need. There must be things you need. If someone made x we'd buy it in a second.
You know there's demand, and people don't say that about things that are impossible to build.
With Robotic Process Automation, you can easily automate such repetitive tasks in a given business process. Referring to the example of Invoice Processing, RPA can read emails, download and read PDF’s, maintain data in Excel sheets, update backend ERP systems, while approvals and quality checks remain manual as they need specialized skills, judgement and knowledge. Lone Star College was founded in and offers Associate Degrees, Workforce Certificates and Transfer Credits. November The way to get startup ideas is not to try to think of startup ideas. It's to look for problems, preferably problems you have yourself.