Automation, Robots and Autonomics – Know Your Terminology – Thoughtonomy

Some concepts to deal with Robotics Process Automation and Artificial Intelligence.

Automation Software

Automation is the use of machinery, control systems or technology to manage the execution of activity which would otherwise require human input and/or intervention. While it is arguable, given this classification, that all computer software is delivering automation, the term automation software typically refers to solutions designed specifically for the purpose of automating a defined task, activity or process. In its simplest form automation includes techniques such as macro-routines and scripting, while in other cases automation software is designed to automate a highly specific task, activity or function. The most advanced and flexible manifestations of automation software will include those which deliver the orchestration and execution of a variety of activities and the management of their relationships and inter-dependencies.

Robotic Process Automation

Robotic Process Automation (RPA) refers to an approach to removal of human activity whereby automation software carries out tasks and activities in other applications and systems by interacting with them in the same way as a human – hence the use of the term “Robotic”. Typically this involves the use of automation routines or “software robots” interacting with these applications via an application GUI (graphical user interface) or CLI (command line interface) though can also include other methods of “driving” an application such as calling web services or scripted routines.

The key difference between RPA and other automation methods is that due to the approach of emulating humans in utilising other applications via a standard interface, the software can be deployed without modification to the applications or systems being automated.

Desktop Automation

Desktop Automation is a form of RPA software deployed locally on a user’s desktop or laptop machine whereby the software is initiated on demand or against a schedule to carry out an automated action. The software executes tasks by emulating the human user, and by having the software execute the “grunt work” within a task or process, operators can manage a significantly increased workload. Desktop Automation is simple to deploy at relatively low cost, and can be a very simple way to deliver efficiency improvements where human workers can call automated routines on demand. However, given the distributed nature of a desktop RPA deployment, attention should be given to the implications on security and management control, on the change and release management of automated processes, and the auditability and reporting of activities.

Enterprise RPA

Unlike desktop automation, Enterprise RPA is not installed locally onto a user’s environment. Instead, virtual environments are created where an automated process is executed by a pseudo-user (the “robot”) emulating the human worker, in a completely hands-off fashion. The virtualised user environment is typically implemented into a datacentre environment with consideration given to factors such as availability, security, management and control which are not addressed in desktop automation. Typical deployments are into business users for high-volume transaction based activities and processes, and execution of processes, rather than initiated locally by an operator, are provided against a defined schedule or through existing task queues and case management applications. An Enterprise RPA deployment is generally configured to operate 24×7 as it does not rely on the presence of a user or their desktop environment in order to execute.

Intelligent Process Automation

Intelligent Process Automation (IPA) is becoming an increasingly common phrase, and attempts to draw a distinction between the more static, rules based approaches of a typical RPA use case, and the use of similar approaches coupled with a level of machine learning or artificial intelligence (see below), such that the automation is operating in a more dynamic environment where multiple factors, data sources and contextual differences might define the action to be taken.

As with much of the current terminology, there is no clear definition of when a process is “robotic” versus “intelligent” and some implementations of RPA technology are in fact using multiple, complex and dynamic sources of information to define the execution of activities. (See Adaptive Automation)

Software Robot

There is no standard definition of what entity constitutes a “robot”. Some providers use the term to describe each time an automated process runs, others refer to each unique automated procedure or scripted action as an individual ‘bot, some consider each desktop agent a robot, and yet more (such as Enterprise RPA vendors) use the same term to describe a runtime resource capable of operating many different processes as a pseudo FTE – the software equivalent of a human operator and their computer virtualised as a single entity.

While there are arguments for each classification, and standardisation of taxonomy is unlikely, the differences can lead to some considerable confusion in pricing and scoping against RPA requirements. Prospective buyers should avoid inaccurate comparisons on a “per-robot” basis and instead seek to relate the costs of an RPA solution to a business case based on the scope of automation possible and the scale or volume of work a solution can deliver.


Autonomics in IT refers to a self-managing computing model named after, and patterned on, the human body’s autonomic nervous system. An autonomic computing system is designed to control the functioning of applications and systems without input from the user, in the same way that the autonomic nervous system regulates body systems without conscious input from the individual. The goal of autonomic computing is to create systems that run themselves, capable of high-level functioning while keeping the system’s complexity invisible to the user.

The term is often used to describe the deployment of automation into IT management scenarios, whereby the automated management and resolution of conditions, events and failures, and/or automated response to demand or context based conditions (e.g. auto-regulating performance by scaling and adapting available resources based on demand) effectively delivers self-managing – or autonomic – systems capable of operating and adapting to circumstances independently of human input.


Heuristics is the application of experience-derived knowledge to a problem or task. Using a basic form of machine learning, heuristics will use historical data (experience) to inform an action or activity. One example of heuristic software is mail quarantine applications which screen and filter out messages likely to contain a computer virus or other undesirable content, based on data from previous activity. Heuristics can be very effective at filtering or processing information based on probability as defined by previous experience, and by definition should become increasingly accurate over time, though is unlikely to be 100% accurate and can result in “false positives” such as incorrectly filtering.

Adaptive Automation

The term Adaptive Automation is used to describe the use of Heuristics in an automated process such that the automation routine or process will be defined based on previous experiences and executions. Examples of adaptive automation are event management processes in system and application support, or automated security management systems which, over time, learn an ever more accurate pattern of “normal” behaviour and will deliver a different automated response based on deviations from that normal pattern.

Unlike AI (see Artificial Intelligence), Adaptive and Heuristic automation remains rules based and, within those rules, actions and outcomes can be modeled and/or predicted.

Artificial Intelligence

In its pure sense, artificial intelligence (AI) refers to systems which are self-aware, and capable of rational thought. However in recent years, the term has been used more broadly to encapsulate the simulation of human intelligence processes by machines, especially IT systems. These processes include learning (the acquisition of information and rules for using that information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction (identifying that a course of action is proving or likely to prove unsuccessful and modifying that course). Particular applications of AI include expert systems, speech recognition, and machine vision.

Considerations in deploying truly artificially intelligent systems to automate work include the potential inability of a user to completely and accurately predict how the system will respond to a situation or given set of circumstances.

Machine Learning

Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. This area of AI focuses on the development of computer programs that can teach themselves to adapt and change when exposed to new data. Unlike heuristics, which uses historical data to inform decisions, machine learning can include experimentation – testing various approaches via trial and error in order to “learn” what will deliver a successful outcome or the timeliest solution to a problem.

Virtual Workforce

The Thoughtonomy Virtual Workforce® is an Enterprise automation solution encompassing many of the principles covered in this overview. It is an as-a-service software solution which provides a platform for clients to automate a wide variety of IT and business support processes and activities. It is focused on delivering high levels of resilience, security and scalability and a commercial approach which allows users to relate the cost of the solution directly to the benefits being realised. The Virtual Workforce utilises RPA approaches, adding advanced load balancing, workload management, multi-tasking and auto-scaling algorithms to provide a highly flexible platform which can deliver rapid and non-disruptive automation.

It’s integrated web portal provides a custom interface to allow users to interact with automated processes and vice versa, providing a single platform for both back-office and front-office or self-service automation. Thus a single solution can offer both zero-touch automation more typically targeted by RPA, and self-service automation more usually delivered with desktop automation, but with the security and management controls not possible with distributed desktop alternatives.

Typical deployments are into service providers, IT and business process outsourcers and Enterprise IT functions for use against a wide range of both high-volume/low-complexity and low-volume/high-complexity IT and business support processes.


Source:, Robots and Autonomics – Know Your Terminology – Thoughtonomy


Five things to know to land a cloud architect job


Demand for cloud architects is growing in the enterprise, but competition for jobs is tough. Here are five questions to help you ace a cloud architect interview.

Cloud computing is becoming a key way for businesses to deploy new applications, which is rapidly changing the IT job market. And demand for cloud architects is especially high.
In fact, roughly 11,100 cloud architect jobs are currently listed on career website, with salaries ranging from $75,000 to more than $150,000 annually. But before landing that dream cloud architect job, you have to wow potential employers during the interview process.

Here are five key questions you can expect an employer to ask during a cloud architect interview, along with advice for how to respond.

1. How do a cloud architect’s responsibilities differ from those of other data center professionals?

A cloud architect focuses more on the meta, or big-picture, view of the data center and less on an individual server’s configuration and throughput. For instance, cloud architects examine how an organization’s central authentication system ensures that only authorized employees access system resources. By comparison, a system analyst is tasked with tying the authentication system to a specific application, such as

2. Where do you see technology in one year? How about three years?

Rather than get caught up in the daily grind of data center and cloud operations, cloud architects must think ahead. They need to be blue-sky, big-picture thinkers. Cloud architects determine how emerging technologies, like biometrics and the Internet of Things, will impact enterprise systems and cloud infrastructure. They also need to craft a roadmap that shows where the business’ systems are today and where they need to be in a few years.

3. How do containers fit into a company’s cloud architecture?

Businesses are constantly trying to make software more portable, and containers are the latest variation on that theme — which makes them a critical technology for cloud architects to know. First, cloud architects must understand the capabilities containers offer. Containers work at a layer above the OS and virtualization software. Theoretically, they offer more portability, but they pay a price for that easy movement: decreased security. The software running in the containers does not include the inherent security checks found at the OS or virtualization layer. Consequently, running containers within a firm’s data center and behind its security perimeter makes sense, while putting the software onto a public cloud is a bit risky.

4. What standard interfaces should a company use?

OpenStack has emerged as a key platform, enabling companies to tie different cloud applications together. Businesses primarily use free, open source software as an IaaS platform. OpenStack, which is available under an Apache license, consists of a group of interrelated components that control pools of processing, storage and networking resources.

5. What cloud architect certifications do you have, or are pursuing?

Cloud architect certification programs come from two different sources. Independent training and certification companies, like Arcitura Education, CompTIA and EXIN, offer vendor-neutral certifications. In addition, the industry’s biggest vendors, such as EMC, Hewlett-Packard, IBM and Microsoft, have cloud architect certifications geared toward their particular products.

Cloud architects are becoming more popular. By knowing answers to key questions, IT pros can position themselves to land a high-paying cloud architect job.

Source: Techtarget-Five things to know to land a cloud architect job by Paul Korzeniowski

Top 5 predictions for project management in 2016

As a discipline, I see project management as being fairly static. Still, there are changes and movements happening. Here are my top five for 2016.

What’s going to happen with project management in 2016? Since project management as a discipline is fairly static, I liken this concept of predicting changes in project management to a conversation two fictional characters had on one of my favorite shows, “The Big Bang Theory,” a few years ago. Leonard Hofstadter is an experimental physicist and his future girlfriend and wife, Penny, is asking questions about his job while they are out to dinner together.

Penny: “So, what’s new in the world of physics?”

Leonard: “Nothing.”

Penny: “Really, nothing?”

Leonard: “Well, with the exception of string theory, not much has happened since the 1930’s, and you can’t prove string theory, at best you can say “hey, look, my idea has an internal logical consistency.”

Penny: “Ah. Well I’m sure things will pick up.”

I think of project management changes when I think of this conversation about experimental physics. Still, I believe there are slow changes happening and some shifts in focus and management about to happen.
Here are my top five predictions for project management I 2016.

1. Emergence of CPOs. I think 2016 is the year of that the CPO position – or Chief Project Officer – begins to get real traction. In the late 1980’s many technical experts and business leaders were suggesting that Chief Information Officers (CIOs) would be the next critical C-level position in organizations. It happened. We’ve also seen the emergence of CFOs in the last decade and now CMOs (Chief Marketing Officers). My prediction for the next big C-level position to emerge is the CPO. It may mean the end of PMO directors and/or centralized project management offices (PMOs)…we will have to see how that plays out.

2. Decrease in PMOs. Project management offices are still failing or at least not serving many organizations very well. Sometimes it’s due to a lack of strong leadership at the top of the PMO, sometimes it’s putting a great project manager in charge who ends up spending too much of this time managing projects rather than managing the PMO, and sometimes it’s just a disorganized mess led by whatever resource manager needs a position of responsibility this week. Not enough are formed around the principles of strong leadership, executive buy-in, and established practices, policies and templates. Executives in the organization can only stand so many restarts before they move in the direction of a decentralized project management infrastructure.

3. Shift away from PM certification focus. While many organizations and job postings will still list certification as a “nice to have” or “preferred”, fewer will focus on that aspect of a candidates background or experience. In 2015, I consulted with two organizations where they were looking for someone who was an experienced project manager and the consulting search listed several key responsibilities and qualifications and PMP certification was listed as “preferred.” However, it was never even discussed during any of the proceedings leading up to the engagements. I’m seeing it listed, I’m not hearing about it being discussed.
4. Decentralized project management in all but the largest of organizations. I realize this may seem to contradict the “emergence of CPOs” that I discussed above, but not really. I think we will still see the CPO position start to mean something in the PM community, but we will also see the increased use of project managers and consultants throughout the organization in individual business units and departments or just more of an independent pool of professionals.

5. Increasing reliance on remote project managers and consultants – growth of virtual team situations. It only makes sense. Professional service organizations who base most of their business on seeking out and providing project solutions are moving more and more to geographically dispersed teams, project managers and teams that may never meet face to face, and offshore development teams who provide great development services at a fraction of the price of high priced co-located project teams. Let’s face it, project teams rarely need to sit at the same table and by allowing your PM’s and project teams to work remotely mean you can always find and obtain – at least on a contractual basis – the best of the best by not making them relocate just for the privilege of having them take up space at your company headquarters.

Summary / call for input

I see project management, in general, as a being fairly static. Important – often critical – in organizations who rely on steady and strong project management to bring home profitable and successful customer implementations in order to succeed as a company. But still, fairly static. There are always new project management software tools and templates available for organizations looking for a change or improvement, but many offer fairly similar capabilities.

But for 2016, I’m going to predict this five things I’ve mentioned above. How about our readers – what changes do you see coming for project management and PM infrastructures or methodologies in the coming year. Please share and let’s discuss.

Source: CIO-Top 5 predictions for project management in 2016 By Brad Egeland

CIOs: Acquire new skills for technology management

CIOs should be seen as enablers and leaders of change in their business.

CIOs should be seen as enablers and leaders of change in their business. In this buyer’s guide, Computer Weekly looks at how the age of the customer requires IT leaders to
focus on both the business technology and IT agendas; why IT leaders need to use blogging and social media to raise their profile and build influence in their organisations; and how IT leaders can roll out projects ever more quickly without running unacceptable risks.

In this 14-page buyer’s guide, Computer Weekly explores:

  • Ways of acquiring new technology management skills
  • Lessons and literature for CIOs
  • How to role out IT projects faster, without running unacceptable risks
  • Case Study: How Atkins ramps up IT speed

Download the guide from: Computerweekly-Acquire new skills for technology management