3 Ways Intelligent Automation Can Save Your Legacy Systems

There are few things an IT executive dreads more than having to replace an outdated legacy system. You know…those ancient programs that hold some of (if not all of) the organization’s critical, “can’t survive without it” data. The reality for many companies is that these legacy systems remain the foundation from which all business processes function. Unfortunately, as these systems become increasingly challenging to manage and are no longer capable of meeting the changing demands of customers, they become a much bigger concern. Thankfully, with intelligent automation, replacing them entirely is no longer the only option.

Depending on the overall scale of an organization’s legacy systems, replacing outdated technology with newer, better systems can take months or sometimes even years. Add to this the increasing pressure to ensure a seamless and error-free data migration. Finally, and perhaps most importantly, customers and employees alike must be able to access the systems they need just as they normally would even while the replacement is occurring. One IT executive in the banking industry likened the replacement of legacy systems to “changing the engine on a Boeing 747 while still in flight.” In other words, it’s incredibly difficult and a monumental task to say the least.

In the past, replacing entire legacy systems could be avoided (along with the astronomical costs associated with such a feat) by offshoring or outsourcing. Unfortunately, this is not always feasible, especially for companies that have a significant number of users. Intelligent automation provides the ideal solution to legacy problems, regardless of business size or industry. Here’s why.

Intelligent Automation is FAST

Let’s say a competitor of yours has come out with a new and improved feature to serve customers that your legacy systems unfortunately do not have the capacity to support. Rather than scramble to find a solution and waste valuable time in the interim, intelligent automation can help bridge the gap, either temporarily or as a long-term solution. Considering the fact that the legacy replacement process typically takes years to complete, automation powered by AI provides a much faster solution, allowing your company to remain competitive at all times.

Intelligent Automation is SECURE and SCALABLE

One of the biggest downsides to outsourcing is the loss of control and subsequent increased data security risk associated with giving up that control. Because intelligent automation is an in-house solution, all of your sensitive data remains in the full possession of your IT department. This makes it an inherently more secure option. Additionally, unlike offshoring, with intelligent automation you can easily scale up or down at a moment’s notice based on need.

Intelligent Automation is AFFORDABLE

The reality is, many organizations have been built upon old systems that date back to the 70s and 80s. For many, these ancient relics are simply too expensive to replace. Intelligent automation provides an affordable alternative, allowing businesses with any budget to break the chains that once bound them to their outdated systems. This opens up the doors to virtually limitless possibilities.

Obviously there are certain limits to how much intelligent automation can revitalize legacy systems. For instance, this type of technology cannot actually alter outdated systems. It can, however, serve as an interim solution unless and until a full replacement becomes necessary. For many organizations – particularly those that do not have the means or resources to completely dismantle and replace their existing infrastructure, intelligent automation is well worth considering.

Experience it for yourself with a live product demo.

4 Steps for Winning the Battle for AI Talent

A recent survey revealed that 42% of employers admit they are concerned that they won’t be able to access the talent they need to run their businesses. This worry is compounded for those in IT, a sector notorious for its ongoing staffing shortage. And with the rise of artificial intelligence technology, the demand for top-tier AI talent is far outweighing the supply. The good news is, with the right approach, even smaller organizations can compete for today’s most sought-after candidates.

Create a Purpose Statement

Employee engagement has dipped to a measly 34% in recent years. One way to boost morale is to provide employees with a sense of purpose. Simply put, today’s top AI talent doesn’t want to spend the majority of their time crunching numbers or working on projects that don’t challenge and empower them. They want meaningful work. You can address this desire by developing a compelling AI purpose statement. Ideally, your statement should highlight the unique and exciting opportunities that await candidates.

Focus on “Citizens”

We’re not talking about citizens of a particular locale, but rather the emerging role of citizen data scientists. Unlike data scientists, who focus on wrangling and cleansing data, Gartner defines these individuals as “power users” who are capable of performing both simple as well as moderately sophisticated analytical tasks that would have previously required more expertise. Forward-thinking organizations are already focusing their attention on citizen AI talent as a means to bridge the gap between AI specialists and the rest of the enterprise.

Tap into Universities

Thankfully there has been a recent shift in how much emphasis colleges and universities are placing on equipping students with applicable, employment-ready skills. This includes prepping those studying AI for entering the workplace. A great way to get ahead of the game in terms of recruiting this up-and-coming AI talent is to forge strong relationships with educational institutions, in particular, with academic departments that specialize in artificial intelligence and other related functions.

Reskill / Upskill Existing Staff

It’s been proven time and again that it’s far more cost-effective to retain existing staff than it is to recruit externally. Organizations may be sitting on a gold mine of available AI talent without even realizing it. For instance, the right training can help IT professionals comprehend and cultivate practical skills and gain the fundamental understanding they need to develop into marketable AI talent in the future.

According to a recent Ernst & Young poll, 56% of senior AI professionals said they believed the lack of qualified AI professionals was the single biggest barrier to AI implementation across business operations. You can win this war for AI talent by implementing the four strategies above and implementing the right tools. Experience the Next Generation of intelligent automation and orchestration with your free 30 day trial of Ayehu. Click here to claim yours.

Episode #31: Could Implementing New Learning Models Be Key To Sustaining Competitive Advantages Generated By Digital Transformation? – Cognizant’s Caroline Styr

December 15 2019    Episodes

Episode #31:  Could Implementing New Learning Models Be Key To Sustaining Competitive Advantages Generated By Digital Transformation? 

In today’s episode of Ayehu’s podcast we interview Caroline Styr – Senior Executive at Cognizant’s Center for the Future of Work. 

Traditionally, learning & work have been viewed as mutually exclusive domains in our lives. Each took place in its own chronologically segregated time, often sequentially, but occasionally overlapping each other.  However, organizational digital transformation obliges us to re-examine that approach, as perpetual reskilling & upskilling become prominent fixtures in the future of work.  Is it time to integrate learning & work to the point they’re indistinguishably co-mingled in one’s job description?  Will doing so bolster a digitally transformed organization’s competitiveness, particularly in attracting & retaining talent? And how should responsibility for continuously refreshing people’s skills be allotted between individuals, organizations, academia, & government? 

At the dawn of the 4th Industrial Revolution, & against a backdrop of ever-lengthening lifespans, these questions have begun taking center stage. Those entering today’s workforce can expect to be employed for 6 decades.  Or more.  Given the recent pace of technological change, it’s a sure bet the skills they inaugurated their careers with won’t be the same ones they’ll need to maintain, much less, advance them.  For insight on how people & organizations should realign their expectations of and bearings towards this new paradigm, we consult with Caroline Styr, Sr. Executive at the Center for the Future of Work.  Caroline’s recently published study “Cycling Through the 21st Century Career, Putting Learning in its Rightful Place”, highlights this critical, yet lamentably under-discussed issue.  We’ll learn about some startling findings her study uncovered, her prescription for how organizations can initiate the shift towards a modern career model, and the one surprising thing she believes individuals should focus on in order to adopt a continuous learning mindset. 

 Guy Nadivi:  Welcome everyone. My name is Guy Nadivi and I’m the host of Intelligent Automation Radio. Our guest on today’s episode is Caroline Styr, Senior Executive at Cognizant’s Center for the Future of Work. Caroline recently published a paper which got our attention. It’s titled “Cycling Through the 21st Century Career, Putting Learning in its Rightful Place”. Now the reason this paper got our attention is because on this podcast, we often talk about how automation, AI, and machine learning will create amazing new opportunities not only for forward thinking organizations, but also for forward thinking professionals.

  However, the key for people wanting to take advantage of these amazing new opportunities, will be to up-skill and/or re-skill themselves, and that will require adopting a new mindset of continuous lifelong learning. So we wanted to devote an episode of the podcast to that topic, and in order to really sink our teeth into the subject, we invited Caroline to come onto the show. She’s here with us today to share some of the really intriguing findings published in her paper, and what the implications are for people and organizations looking to succeed in this era of digital transformation. Caroline, welcome to Intelligent Automation Radio. 

   Caroline Styr:  Thank you so much for having me, Guy. Looking forward to the conversation. 

   Guy Nadivi:  Caroline, I want to provide some context for everyone by quoting or paraphrasing some really eye-opening figures and statements published in your paper.   Careers are extending as expected lifespans rise resulting in an even greater need for a continuous skills refresh over 60 plus years of learning and work.  “The digital age is creating demand for continuously emerging new skills. While not every employee will need to build advanced algorithms, most jobs, 75% of them, according to your recent research, will be augmented by automation and AI, and 13% of new jobs in the future will be created by these technologies. So it’s vital that workers gain at least a high level understanding of these new technologies and how to work alongside them.  Despite this, workers are struggling to find a connection between learning and work, making it very easy for them to deprioritize learning.43% of your respondents believe their learning has only a moderate impact on their work, and 34% go so far as to say there’s limited impact or none at all on work. Therefore, not surprisingly, most workers approach learning as a must do, not a want to do.  Here’s perhaps your most astonishing finding. Most respondents to your survey think they’re exempt from up-skilling, with 65% expressing confidence that their current skillset will sustain them throughout their career. Wow! This confidence actually increases with the length of the career ahead, with millennials scoring above average results for “very” or “extremely” confident. Caroline, there’s clearly a major disconnect going on right now in the workforce.  A cursory glance at the better paying job ads on Monster.com, ZipRecruiter, or any job board, reveals that there’s obviously a growing need for emerging new skills. All of us, or most of us anyway, know people who are working well past traditional ages of retirement, usually because they have to due to a variety of often unforeseen reasons.  It should be plainly evident, especially when so many people had difficulty finding jobs during the great recession not too long ago, that you really shouldn’t allow your skills to grow stagnant. Yet despite all this empirical evidence, you still uncovered what I think can fairly be called some abysmal findings. How do you explain this? 

   Caroline Styr:  Absolutely, Guy. The findings were incredibly surprising. We surveyed over a thousand knowledge workers and as you mentioned, 65% believe their skill sets would last, that they’re exempt from up-skilling. I think it’s unsurprising then that this translates into a pretty serious disinterest with learning.  So we categorized over half of these learners, over half of those that we surveyed as compliant, which means that people who learn because they have to, because it’s mandated for compliance reasons, or to meet annual appraisal targets. This really isn’t a finger pointing exercise. This isn’t blaming the workforce and saying, “Oh, they just can’t be bothered to learn”. You have to ask yourself the question, “Why would the workforce focus on learning if the majority don’t think there’s a significant impact on the work that they do?”  As you highlighted, Guy, over 1/3 say there’s limited impact or none at all on work. So I think it’s far too easy to shrug and say, well, this won’t impact me and carrying on doing the same old, same old. Of course, this has to change. Organizations and individuals alike have some serious work to do to get out of this learning funk. In order to answer the question, “Why should you adopt a continuous learning mindset?”, I really believe that business leaders need to focus on better integrating learning and work. 

   Guy Nadivi:  Caroline, in your paper you write something that I think all our listeners will immediately recognize as intrinsically true, and I’m going to quote here. “Traditional career models promote a learn-work-retire cadence, encouraging workers to give up any meaningful learning as soon as they step through the office door. This might’ve made sense when the pace of change was slow enough for one set of skills to last a lifetime, but that’s not the case today.”  You then proceed to talk about an alternative approach you call the “Modern Career Model”, which seems to be based at least somewhat on Agile methodology, which will be very familiar to our listeners in IT. Can you please break down for us how the Modern Career Model works and why it might be better than what most organizations are currently doing? 

   Caroline Styr:   Absolutely. So nice to be quoted, Guy, makes me feel so special. So, at the Modern Career Model, this model that we put forward focuses above all else on integrating learning and work. It focuses on reprioritizing learning so that each worker considers his or her career not as a series of projects on the one hand and learning goals on the other, but as a series of cycles in which the two are intertwined and interrelated.  So the cyclical relationship between learning and work really signals that the impact of learning on work is just as important and demands just as much attention as the impact that new types of work have on learning. So if we just think about that for a second and break that down for a second. I think most of us learn in the workplace because something comes up, a task, something that we have to do and we have to work out how to do it really quickly.  That kind of classic case of quick – How do I do a pivot table in my Excel spreadsheet? and then quick – Google and you get it done. But maintaining a curious and creative mindset in the work place, putting learning and growth first and making it part of the daily routine, whether that’s a tricky task, whether that’s for a tricky task on the horizon or not, reaps huge rewards. You’re far more likely to say mentally fit, focused, and engaged with every task at hand.  But employees have to be empowered to prioritize learning by their organizations. The top reason for not learning, according to our research is that workers simply don’t have enough time. There’s a shedload more research out there that confirms this and that’s why we’re reimagining the career module, rethinking it so that there’s more time baked in, and there’s more focus on what’s important in the digital age. If you’ll allow me to talk on this thread for a little bit longer, Guy.  Another reason why I find this idea of reinventing career models so urgent, is that our current traditional career models, they don’t just deprioritize learning. They’re not built for 60 plus year careers like you pointed out in your introduction, and they’re not even built with half of the workforce in mind. What I mean by this is that our traditional career model was built over a hundred years ago by and for men.  In fact, in the early 1900s men made up about 72% of the workforce, and so it’s not really surprising that the career model was invented without considering traditionally female duties, especially a hundred years ago like childcare. But the impact of this is still being felt today. So women, especially in the US and Europe, are far more likely to choose self-employment or part-time employment rather than full-time employment because of these restricted, outdated career models that just don’t fit. So it’s just another little reason to consider modern current model fit for the 21st century. 

   Guy Nadivi:  An excellent point I don’t think a lot of people would normally think about. It reminds me that my wife is a product manager for a mid-sized global firm of about a thousand employees. Her firm is undergoing a digital transformation. At the start of this year, virtually everyone in her company underwent Agile training. So I’m curious, Caroline, would you advocate organization-wide Agile training as a first step for enterprises implementing a Modern Career Model approach or is there a better way to initiate this paradigm shift? 

   Caroline Styr:  There are certainly principles from Agile methodology that are well reflected in the cyclical approach to careers in the Modern Career Model.  Managing progress, sustainable development, delivering frequent new things like that. I think the way in the paper that we suggest organizations initiate the shift is through a framework that we refer to as the “Three M Methodology”. Three M’s being Measurements, Motivation, and Mobility. So I’ll rattle through these really quickly.  Measurement is to think about how we measure learning in the workplace. So when business leaders effectively collect and process employee performance data, learning can be measured in terms of how it impacts work outcomes. Instead of this kind of obsessive focus on how many hours have you spent learning or how many courses have you completed, which is the most common way of measuring learning today. Actually, the most common way of measuring learning today is to not measure it at all, according to our research.  So I think organizations need to really get into a place where they’re measuring learning effectively by looking at things like how is it making you do your work more efficiently or faster? The ultimate goal really is to create real time employee profiles encompassing skills, work performance, and engagement.  The second is motivation. That’s all about personalizing the career experience for the individual. So what does a worker want out of their career and how can continuous learning support that? So it goes back to that really grim statistic about 51% of people learning because they have to. By connecting learning to career growth transparently and emphatically, employers can convert those compliant learners into the achievers who are learning for the sake of job growth and job performance. Then those people are far more better prepared to survive and thrive in the digital age.  The final M being mobility. In this new career model, we talk a lot about fluidity and flexibility and movement across the organization, across job roles, departments and teams. About 45% of those surveyed said that their organization doesn’t support internal mobility. Or if it did, it wasn’t well understood by employees. But internal mobility really opens up opportunities for workers to find work that’s better suited for them, that it’s more satisfying and that really promotes learning.  So instead of being stuck in the same career silo, executing the same old tasks, workers are motivated to learn to make sure that they make that move into a new role. So yes, three M’s, measurement, motivation, and mobility to nail the Modern Career Model. 

   Guy Nadivi:  Let’s talk dollars and cents. I’m the CEO of a company undergoing a digital transformation. I know that I need to start up-skilling and re-skilling my workforce. Tell me in broad terms, what’s it going to cost me to implement a Modern Career Model that gets my people to learn and adapt versus outsourcing parts of their work or even replacing my staff altogether with people who have the skills and experience I need. 

   Caroline Styr:  Yeah, absolutely, Guy. An important question. Instead of talking about what this is going to cost, let’s talk about what the cost is if you don’t do this. So as I alluded to earlier, organizations are missing out on top talent by sticking to these outdated career models.  By sticking to these models that were built by and for men that, for example, are encouraging women to favor different types of employment.  So first off, you’ve got an issue with attracting talent. If organizations don’t do this, they aren’t cultivating the talent that they need for the digital age. They will lose their competitive edge because the talent will be stuck five, 10 years behind the curve, unable to keep up with the pace of change. Then you’ve got a big issue with delivering products and services that meet the needs of the consumer in the digital age.  Thirdly, if organizations think that they can simply hire in and retain talent with the skills that they need, they’re sorely mistaken because that talent is committed to up-skilling. They’re not going to stick around at an employer who can’t offer them the infrastructure that they need to continue up-skilling. So the majority of workers in our survey said, well, it’s about 73%, said that they depend on their employer for support in preparing for the future of work.  But despite that fact, over half are concerned about their employer’s ability to do so. So then you’ve got this huge issue with retention because people are simply going to walk if you can’t help prepare them for the future of their work. So it’s my firm belief that it’s going to cost organizations a lot more to not rethink career modules for the 21st century than it will to actually implement that new career model. Because the question of having the right talent quite frankly, is a question of surviving the digital age or getting wiped out. 

   Guy Nadivi:  Okay, that’s compelling. So let me ask you this – inevitably some IT executives hearing today’s discussion might wonder if making the investment in the kind of learning shift you’re advocating might just end up making their personnel more appealing to competitors seeking to poach staff. What would you say to convince them otherwise? 

   Caroline Styr:  Yeah, I mean not to be really contrary, but I’m going to invert again and say instead of worrying about whether your talent is appealing to others, you should be worrying about whether your organization is appealing to talent. So it’s the same message, if you don’t do this, you’re not going to attract and retain modern talent and your company won’t be fit and agile enough to compete in the digital age. 

   Guy Nadivi:  Okay. Point well taken. So as vital as adapting may be to staying competitive in the fourth industrial revolution that we’re undergoing here in the 21st century, the fact remains that not all organizations will be able to adapt due to resource constraints. So with that in mind, Caroline, what role do you think government should play in helping all people and organizations adopt a continuous learning mindset? Or should that all stay in private hands? 

   Caroline Styr:  It’s a great question, Guy. I absolutely don’t think that it should all stay in private hands. I think the crucial player in this game is academic institutions. After all, they’re responsible for that first stage of this outdated, learn, work, retire cadence that we’re talking about that we’re a bit stuck in. So, in another paper that we’ve published at the Center, it’s called “Relearning How We Learn, From the Campus to the Workplace”.  We interviewed and surveyed academic leaders and business leaders to understand who they think is responsible for up-skilling the workforce. About 84% of higher education institutions expressed concern about meeting the challenge of preparing the future workforce, compared to about 58% of business respondents. So there’s a lot of work to be done in this space as well. So one little, innovative idea that we put forward in our paper at “21 More Jobs of the Future” was this idea of a uni for life coordinator.  I think that’s my British-ism a little bit, making it university for life, but you get the picture. This is a job for someone who will support graduates and alumni to continue up-skilling throughout their career with the help of university resources. So it’s kind of like a learning professional, but coming out of the academic institution as opposed to the work, as opposed to the organizational institution or the private institution. This way we’re starting to, by doing things like this, we’re starting to break down that learn, work, retire model from the very beginning, not just in the middle in the work portion. 

   Guy Nadivi:  There’s a famous Chinese proverb that you’re no doubt familiar with, a journey of a thousand miles begins with a single step. For career-minded listeners embracing the message you’re advocating, what do you think should be the first step in their thousand mile journey of continuous lifelong learning to remain relevant and further their career? 

   Caroline Styr:  Yeah, I can talk about that stuff forever. So it’s going to be good to focus on one thing. It’s a big challenge. So one thing – our Chief Learning Officer at Cognizant says something a lot about continuous learning that I completely agree with. It’s the idea that to adopt a continuous learning mindset, you have to focus on self-reflection, which I think means that you have to take assess an amount of responsibility for your learning.  So one way to do this that we talk about in the paper is to think about your current list of tasks. This is just a short way to rethink your attitude towards learning. So think about your current list of tasks and whether you’re doing any learning to support those tasks. So it’s not just thinking about learning for learning’s sake, but baking it into the work that you’re already doing. So it doesn’t matter if you’ve been doing these tasks for years and years and years, there’s always something new to learn.  So for example, I had to write a certain amount of articles a month, and despite the fact that I’ve been doing that for years and it’s a very dependable part of my routine, I still try to match learning to it on a regular basis. So how are people consuming content on LinkedIn in 2019 for example? What can I learn there? How can I adjust my writing style to meet their needs? How can I perfect that punchy little tweet that brings people to my article? How can I integrate more multimedia into my articles to engage the reader?  These are all things that are new, that I can learn, that I can be learning day in, day out, even though they’re related to a task that I’ve been doing for years and years and years. I think devoting time to reflecting on your learning like that, means that you’re taking responsibility for baking learning as best as you can into the day to day of your career. 

   Guy Nadivi:  One final question, Caroline. For the corporate presidents, CEOs, or any IT executives listening in, what is the one big, must have piece of advice you’d like them to take away from our discussion with regards to improving their competitiveness by facilitating continuous learning for their staff? 

   Caroline Styr:  So I think the one really key message here is that a new career model isn’t a nice to have. It’s a must have. What worked a hundred years ago does not work today. If you want to get the best out of your talent in the 21st century, then you have to ensure that they’re ready to pivot with the next new thing, you have to ingratiate a mindset of continuous learning.  I really think, and I think the research shows this as well, that you’re not going to do this by pouring your money into new learning platforms or solutions if the structure at the end of the day, if the structure of the career doesn’t empower the workforce to learn, doesn’t integrate learning into work. That’s why this career model is an absolute must have. I think to get there, to get to that new career model, start with measurements, make sure that you’re measuring the impact of learning your work, and then I think you’ll be well on your way. 

   Guy Nadivi:  We’re in a new age and that definitely requires new thinking. I’m going to give your excellent paper another quick plug here for those listeners who want to get their hands on it. Caroline Styr’s paper is titled “Cycling Through the 21st Century Career, Putting Learning in its Rightful Place”. You can download it from www.cognizant.com/futureofwork, and I highly recommend it for the valuable insights it provides about continuous learning both for organizations and individuals.  All right. Looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Caroline, it’s been great having you on the podcast and helping us gain your perspectives about how continuous learning will impact the future of work. Thank you so much for joining us today. 

   Caroline Styr:  Guy, it’s been an absolute pleasure. Thank you so much for having me. 

   Guy Nadivi:  Caroline Styr, Senior Executive at Cognizant’s Center for the Future of Work. Thank you for listening, everyone, and remember – don’t hesitate, automate! 


Caroline Styr 

Senior Executive at Cognizant’s Center for the Future of Work

Caroline is a thought-leader and speaker in Cognizant's Center for the Future of Work. The Center has a charter to examine how work is changing, and will change, in response to the emergence of new technologies, new business practices, and new workers.  

In this role, Caroline develops cutting-edge thought leadership to challenge perceptions of the Future of Work, in collaboration with leading technology and business thinkers, academics and policy makers. Above all, she is dedicated to demystifying what the individual needs to succeed in the modern organization. She has also written extensively about Diversity and Inclusion in the Future of Work.  

Prior to joining the CFoW, Caroline worked in international digital services and transformation across the retail and healthcare industries. She has a BA (Hons.) in German from the University of Bristol, alongside which she certified in Theatre and Performance from Bristol Old Vic Theatre School. 

Caroline can be reached at: 

LinkedIn:                         www.linkedin.com/in/caroline-styr-3a137b103/

Twitter:                          https://twitter.com/carolinestyr


“Organizations and individuals alike have some serious work to do to get out of this learning funk. In order to answer the question, ‘Why should you adopt a continuous learning mindset?’, I really believe that business leaders need to focus on better integrating learning and work.” 

"… the cyclical relationship between learning and work really signals that the impact of learning on work is just as important and demands just as much attention as the impact that new types of work have on learning. " 

“…maintaining a curious and creative mindset in the work place, putting learning and growth first and making it part of the daily routine, whether that's a tricky task, whether that's for a tricky task on the horizon or not, reaps huge rewards.” 

“Another reason why I find this idea of reinventing career models so urgent, is that our current traditional career models, they don't just deprioritize learning. They're not built for 60 plus year careers like you pointed out in your introduction, and they're not even built with half of the workforce in mind.” 

“…I think organizations need to really get into a place where they're measuring learning effectively by looking at things like how is it making you do your work more efficiently or faster? The ultimate goal really is to create real time employee profiles encompassing skills, work performance, and engagement.” 

“…instead of worrying about whether your talent is appealing to others, you should be worrying about whether your organization is appealing to talent.” 

“…the one really key message here is that a new career model isn't a nice to have. It's a must have. What worked a hundred years ago does not work today. If you want to get the best out of your talent in the 21st century, then you have to ensure that they're ready to pivot with the next new thing, you have to ingratiate a mindset of continuous learning.” 

About Ayehu

Ayehu’s IT automation and orchestration platform powered by AI is a force multiplier for IT and security operations, helping enterprises save time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure. Trusted by hundreds of major enterprises and leading technology solution and service partners, Ayehu supports thousands of automated processes across the globe.



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Episode #1: Automation and the Future of Work
Episode #2: Applying Agility to an Entire Enterprise
Episode #3: Enabling Positive Disruption with AI, Automation and the Future of Work
Episode #4: How to Manage the Increasingly Complicated Nature of IT Operations
Episode #5: Why your organization should aim to become a Digital Master (DTI) report
Episode #6: Insights from IBM: Digital Workforce and a Software-Based Labor Model
Episode #7: Developments Influencing the Automation Standards of the Future
Episode #8: A Critical Analysis of AI’s Future Potential & Current Breakthroughs
Episode #9: How Automation and AI are Disrupting Healthcare Information Technology
Episode #10: Key Findings From Researching the AI Market & How They Impact IT
Episode #11: Key Metrics that Justify Automation Projects & Win Budget Approvals
Episode #12: How Cognitive Digital Twins May Soon Impact Everything
Episode #13: The Gold Rush Being Created By Conversational AI
Episode #14: How Automation Can Reduce the Risks of Cyber Security Threats
Episode #15: Leveraging Predictive Analytics to Transform IT from Reactive to Proactive
Episode #16: How the Coming Tsunami of AI & Automation Will Impact Every Aspect of Enterprise Operations
Episode #17: Back to the Future of AI & Machine Learning
Episode #18: Implementing Automation From A Small Company Perspective
Episode #19: Why Embracing Consumerization is Key To Delivering Enterprise-Scale Automation
Episode #20: Applying Ancient Greek Wisdom to 21st Century Emerging Technologies
Episode #21: Powering Up Energy & Utilities Providers’ Digital Transformation with Intelligent Automation & Ai
Episode #22: A Prominent VC’s Advice for AI & Automation Entrepreneurs
Episode #23: How Automation Digitally Transformed British Law Enforcement
Episode #24: Should Enterprises Use AI & Machine Learning Just Because They Can?
Episode #25: Why Being A Better Human Is The Best Skill to Have in the Age of AI & Automation
Episode #26: How To Run A Successful Digital Transformation
Episode #27: Why Enterprises Should Have A Chief Automation Officer
Episode #28: How AIOps Tames Systems Complexity & Overcomes Talent Shortages
Episode #29: How Applying Darwin’s Theories To Ai Could Give Enterprises The Ultimate Competitive Advantage
Episode #30: How AIOps Will Hasten The Digital Transformation Of Data Centers

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Neither the Intelligent Automation Radio Podcast, Ayehu, nor the guest interviewed on the podcast are making any recommendations as to investing in this or any other automation technology. The information in this podcast is for informational and entertainment purposes only. Please do you own due diligence and consult with a professional adviser before making any investment

Automation-Driven Employee Onboarding – From Days to Seconds

Author: Guy Nadivi

It’s really true. Automation-driven employee onboarding can reduce the time that process takes from days to seconds. Actually, in some cases, we’ve heard that at some organizations, onboarding is measured in weeks, not just days.

I was at a VMworld conference in San Francisco a few years ago, and struck up a conversation with someone visiting our booth who said that prior to automating their employee onboarding process, it took them 2 weeks to get new hires fully integrated into their company!

When you calculate the cost of the people involved in onboarding that new hire, as well as the productivity time that new hire lost by not being fully onboarded faster, you quickly realize how expensive this process can be. The phrase “time is money” really applies to the onboarding process, which is why automating it frequently turns out to be such a big win for organizations.

According to the Society for Human Resources Management, more commonly referred to as SHRM, the average cost of onboarding an employee is $4,129. Of course, this is an average figure taken from a broad cross-section of companies and industries. Your mileage may vary. Maybe it’s lower. Or maybe it’s higher. MUCH higher.

That $4,129 figure is taken from a 2016 report published by SHRM, and was the most recent number we could find about the cost of onboarding from an independent, reputable source. One thing you can be almost 100% certain of though is that now, towards the end of 2019, that number has likely gone up even higher. How high is hard to say, but there’s no reason to believe that the cost of onboarding employees has gotten any cheaper the last 3 years.

If you’d like to calculate what the cost of onboarding an employee is for your organization, I encourage you to Google “employee onboarding calculator“, and you’ll find numerous websites that can help you determine what your cost is.

There’s probably a pretty good chance that no two organizations have identical onboarding processes. Everyone’s is just a little bit different. Or perhaps A LOT different.

Despite that, there are some aspects to onboarding that are probably universal across most, if not all organizations.

  • First off, onboarding is typically laborious. Many different things need to be done in order to successfully onboard a new hire, and often times these things are primarily manual processes.
  • Onboarding often touches many different things across multiple departments – HR, IT, Facilities Management, etc. The more things your onboarding process touches, the more things that can go wrong, especially if they’re done manually where the potential for human error is always lurking in the background. That’s just a basic application of Murphy’s Law.
  • The process of onboarding can be very time consuming, particularly when some or even all of it is manual. This is true not just for the new hire being onboarded, but also for the people involved in the new hire’s onboarding.

And what are these laborious, error-prone, time-consuming processes I’m referring to? Here’s a list of some, but by no means all, of the tasks involved in many typical onboardings:

  1. Order new employee’s IT equipment
  2. Create new employee’s Active Directory account and  email
  3. Add new employee to calendar and  mailing lists
  4. Create new employee’s logins for primary systems they’ll use
  5. Provision new employee’s virtual machine(s)
  6. Email new employee all new hire documents from HR, including I-9 and W-4 tax forms
  7. Order new employee’s business cards
  8. Submit request for new employee’s office key and/or ID badge
  9. Create new employee’s IP phone (using API calls to Cisco Unified Comm. Manager, for example)

Guess what? In general, all of these tasks can be automated, saving a lot of work, a lot of time, and a lot of mistakes.

Doing so has some surprising benefits for an organization.

According to SHRM, 69% of employees who experienced great onboarding were still with the company after 3 years!

Now think back to the average cost of an onboarding, and ask yourself – how long would a new hire need to stay at my organization in order for us to break even on them? Hopefully it’s become a little clearer why the better the onboarding experience for your new hires, the more positive financial impact it can have on your organization.

That’s particularly true when it comes to onboarding executives and other high-pay employees.

According to a Harvard Business Review that polled global executives worldwide about their onboarding experience, nearly one third (32%) said their onboarding experience was POOR.

Why does that matter?

It matters because the cost to an organization of replacing a failed executive as a percentage of his or her salary is 213%, according to the Center for American Progress.

If your organization is hiring a highly-paid employee, you really want to make sure that it’s not only the right person, but someone who’s going to stick around long enough to justify the investment in hiring them. Otherwise, it might be much more expensive to lose them.

Now specifically with regards to automating your employee onboarding, here are probably the top 3 benefits:

  1. You’re going to save time, and when it comes to onboarding, the savings often will not be measured in hours but in days or weeks! BTW – I recently learned from Lee Coulter, the Chair of the IEEE Working Group on Standards in Intelligent Process Automation, that a better way to describe time saved by automation is “Hours Returned to the Business”. I think that’s very applicable to automating the onboarding process.
  2. You’re going to save money, that’s not only a result of saving time, but a product of longer retention for new hires.
  3. Finally, you’re going to reduce errors. The more things you do manually, the more opportunities you have for errors. Plain and simple.

Collectively, all these benefits contribute to a KPI that’s become increasingly important to how your department is graded, and in many cases compensated, at least bonus-wise.

I’m talking of course about customer satisfaction ratings. At a lot of organizations, this has become the central metric, or at the very least an extremely important one, for rating performance.

Automating the onboarding process will undoubtedly improve your customer satisfaction ratings.

Here’s something else to consider.

For many organizations out there these days, a good chunk of their new hires are younger employees. I’m talking about the millennial generation, of course, but also early members of the next demographic wave, often referred to as Gen Z.

You probably know that these generations have been raised on Facebook and mobile apps, and generally prefer interfacing with technology rather than people. We know that empirically because we see it for ourselves just about anywhere we look.

A 23-year old young lady in my own family told me that she and her friends consider books to be weird. Books apparently are weird because why would you read something written on processed dead trees when you could just use a smartphone and pull it down from the cloud?

So automating the onboarding process for this demographic is likely to be a bigger factor than you might realize in retention of younger employees. If their first impression as new hires at your organization is that you’re having them do things manually, you’re likely to persuade them that your organization may not be the kind of digitally transformed, progressive environment they want to be working at for 8+ hours a day.

Finally, it’s also worth mentioning that if everything discussed up till now applies to onboarding, then it also applies to offboarding, which is basically the same process in reverse.

This is especially true in the case of layoffs when you have a large volume of people who all basically have to be offboarded simultaneously. That’s a recipe for chaos when done manually, but a routine garden-variety process when it’s automated.

Automating the offboarding process also ensures you’ll have properly documented audit logs for compliance and internal review.

Both the onboarding and offboarding processes tend to be low-hanging fruit at most organizations, when it comes to automating procedures that yield big benefits quickly.




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