How AI is Revolutionizing the IT Support Role

Over the past several decades, the role of IT support has evolved from basic plug-and-play transactions to handling much more complex tasks and workflows. Unfortunately, the pace of technological change and demand for faster, more accurate and more seamless service has also evolved – in many cases, beyond what human agents are capable of. Furthermore, support teams are being hindered by antiquated processes and technology silos, preventing them from realizing their true value.

That’s why more and more organizations are turning to emerging capabilities, like machine learning and artificial intelligence, to help supplement and enhance the IT support role. AI tools, like intelligent chatbots and virtual support agents, have already proven highly effective in facilitating greater efficiency and superior end-user service.

IT Support’s Greatest Challenges

To truly recognize the impact AI can have, it’s important to understand just what today’s IT support agents are up against. Research has shown that L1 and L2 IT support personnel waste hundreds or even thousands of man hours each year simply due to time-consuming manual labor and inefficient infrastructures. Often times, agents find themselves having to switch between multiple systems and platforms just to accomplish a simple end-user support request.

Another major hurdle modern IT support teams face today is a lack of adequate access to data. Or, perhaps we should clarify this to lack of access to quality, usable data. Agents (and their managers) need access to insights like this in order to analyze and improve performance. Unfortunately, these insights are not always readily available in many organizations, crippling the support desk and ultimately impacting service levels.

When these issues occur, either individually or compounded, not only does the end-user become frustrated, but so do the IT support desk agents. And if they’re feeling unhappy, overworked and unfulfilled, they’re far more likely to churn, leaving organizations with the burden and cost of recruiting and training. It’s a never-ending cycle.

How AI Can Help

How AI is Revolutionizing the IT Support Role

To answer the call of these costly and frustrating challenges, organizations across the globe are turning to AI technologies. In particular, they are leveraging the power of intelligent chatbots to handle lower-level support needs. Imagine how much more valuable your skilled IT workers could be if they weren’t wasting half their day resetting passwords or restarting systems. Not only do virtual support agents resolve issues faster and improve customer satisfaction, but they free up the IT team to focus their efforts and skills on more value-added business initiatives. This is good for everyone involved.

Artificial intelligence can also assist with building out additional content resources, helping higher level agents resolve issues faster and providing invaluable insight to management to facilitate data-driven decision-making. Machine learning algorithms can automatically and continuously analyze past cases to provide real-time guidance for best next steps as well as identify and make suggestions on areas of potential improvement. It’s like having a consulting firm working on your behalf, 24/7/365, only without the hefty price tag.

When IT support agents have access to the most up-to-date tools and innovative capabilities like AI, they’re jobs will be made infinitely easier. Trained workers will be able to apply their skills to more meaningful work, end-users will receive faster and better service, while at the same time, organizations will realize improved satisfaction levels, higher productivity and efficiency, and lower costs overall. That’s what we call a win-win-win!

Want to experience this kind of breakthrough for your IT support team? It’s as easy as downloading Ayehu NG. Click here to try it free for 30 days and put the power of AI to work in your organization.

Slash MTTR with Intelligent Automation for AIOps

Author: Guy Nadivi

There seems to be confusion in the marketplace about the term “AIOps” as far as what it means exactly, but there’s much less confusion about what it can do – Improve IT’s customer satisfaction scores by reducing noise, lowering call volume to the service desk, and slashing MTTR.

These are the types of benefits every IT organization is demanding, and the good news is they’re attainable right now.

Ayehu has partnered with Edge Technologies to show you a vision of what that looks like, and give you a glimpse at the promise that AIOps can bring to your IT organization.

Many of you have worked for years in the IT Operations and Systems Management space. Some of you may recall that in the mid-‘90s, Enterprise Systems Management and Business Service Management (or BSM for short) emerged as new disciplines that would bring together distributed systems and mainframes into a single pane of glass to solve problems. As you may know, Gartner killed off the BSM category in 2016 because vendors failed to deliver on these promised benefits.

In many large enterprises, the picture today still remains the same. Does this scene look familiar to you?

The CIO is still asking “why has customer experience dropped for our core service?.  The IT Ops Manager is unsure what the cause might be as everything looks good thanks to fantastic ”monitoring”.  And the SRE can’t make sense of any of the screens because he/she is suffering from information overload and isn’t sure where to look. No wonder MTTR is high!

Even with today’s AIOps vendors, and a market where new ones seem to be entering the space every week, the promise of universal views into your operations remains elusive.  Nevertheless, it’s still a highly sought-after goal.

So the question is, what is preventing progress towards that goal?

Today, we still continue seeing knowledge and visibility silos across the enterprise from business units, support, operations, and engineering functions all the way through to 3rd-party service providers.

This is one of the main challenges to overcome if AIOps is going to succeed. Internal politics, tool proliferation, and un-integrated workflows continue contributing to the slow adoption of AIOps.

Sound familiar?

The promise of a “single pane of glass” never materialized leaving teams to use point products with limited integration and different data formats. The result?  A huge and costly inventory of tools to manage and operate leading to more frustration.

It’s widely accepted across the industry that most monitoring dashboards today fail to provide required operational views that business needs.

AIOps aims to fully automate IT Operations workflows, but the reality today is that enterprises still struggle with tool sprawl resulting in the “swivel chair” effect. Your triage and remediation workflows are still very much reactive in nature, but the goal is to prevent incidents from happening in the first place as much as possible, right?

Also, in our experience over the years, the tools used today are more than likely to be replaced at some point, so the best approach is to have a vendor agnostic data visualization and integration solution for your dashboarding needs. The tools supplying the dashboard data feeds will come and go.  Replacing them is a simple configuration change in Edge.

In order to break the knowledge and visibility silo challenges and create intelligent operations dashboards for increased AIOps adoption, think of the process in three parts:

Part 1:   Integrate all required data sources ranging from customer experience and your enterprise IT domains to give business and service health views by role. For example, executive, manager, and analyst views.

Part 2:   Integrate your existing event management, monitoring, and IT service management tools at the data and web layers to maximize your existing tool investments, skills, and standard operating procedures to become more proactive than ever before.

Part 3:   Integrate your process automation tools (such as Ayehu) to create convenient and frictionless workflows that can be executed in either attended or unattended mode.

Now that we better understand the problems and obstacles in the way of making progress, let’s walk through the process of creating ideal intelligent operations dashboards for your AIOps initiatives by uniquely combining your data and tools into role-based views of your business and services.

When we think about digital transformation and the outcomes businesses are looking for, one of the goals CIOs have longed to achieve is ensuring that business and enterprise IT are completely aligned. This has been a goal for as long as most of us can remember!

To reflect that in our intelligent operations dashboards, let’s start from the top-level (see graphic below),which is a set of first-level business, customer, and end-user experience (EUE) dashboards that appeal to all levels of the organization.

The second level is a triage dashboard, designed to allow teams to quickly identify whether the server, network or application layer is the source of an outage or service health issue.

The third level is a dependency-mapping dashboard that links application, network, and server infrastructure together in topology views to understand the business impact.

The fourth level is individualized dashboards specifically designed for teams and dedicated roles — application, infrastructure, and network monitoring dashboards.This level of dashboard is where SMEs can directly access your existing best-in-class tools using Edge’s unique web UI proxying capability.

The fifth level gives you access to your raw data including logs, events, packet traces, and call stack traces for example —so that detailed analysis can be performed in context to the issue being investigated.

By combining your data sources and tools into universal views using a single platform like Edge, you can provide appropriate dashboards to your executives, management, and SMEs that provide them access to the content they need and tasks they need to perform to be successful in their daily jobs.

By combining business and related service health metrics along with the power of integration with your data and tools, you can rapidly identify root cause, fix the problem for good, and slash your key performance indicators such as MTTR. Many Edge customers report having happier customers, greater alignment between business and IT, eradication of visibility silos, and overall better decision making and outcomes from their deployment.

Not least of all, their most valuable assets (people) are more successful in meeting their goals and performing their job tasks.

Now let’s talk a bit about automation.

Digital Transformation is a buzzword you hear a lot about these days.  It doesn’t have one standard definition but can basically be understood to mean the collection of technology, process, and even cultural disruptions an organization adopts to maximize its competitiveness in the 4th industrial revolution.

Those technology disruptions can include things like cloud computing, artificial intelligence, chatbots, and of course automation.

The process disruptions include things like Agile or Six Sigma, and a cultural disruption might be something like repositioning the organization’s focus to be better aligned with the customer journey.

For IT departments, digital transformation ultimately boils down to optimizing and accelerating delivery of computing services, regardless of whether the customer is external or internal.

When it comes to incident monitoring, one thing an IT department can do as part of its digital transformation, is to consolidate the visualization of all their various monitoring tools into a single pane of glass, as Edge Technologies enables.  A unified dashboard providing a 360° view of operations, can also provide an extraordinary opportunity to not only centralize incident monitoring but also to automate incident remediation.  That represents a big step forward in the digital transformation of data centers, and a perfect example of how 1 plus 1 can sometimes equal 3.

A recent paper published by Gartner (ID G00390283 – October 9, 2019) advised its readers that an ideal performance monitoring dashboard framework must aim to “Provide for the rapid triage and remediation of performance issues…”.

No argument there. Ayehu and Edge Technologies agree that combining automation with performance monitoring is central to an ideal dashboard framework.  But perhaps the most important word to emphasize in Gartner’s recommendation is “rapid”.

Unfortunately, “rapid” is not an adjective that the vast majority of service desks can use to describe their MTTR today.

MetricNet, the IT consulting firm that publishes benchmarks, performance metrics, and scorecards for a variety of IT-related activities, claims that the average incident MTTR is 8.40 business hours.  If you’re an end user in an organization who just submitted a ticket to the help desk, you do NOT want to hear that it will take an average of 8.40 business hours to remediate your issue.  On the contrary, you want to know that your IT department is doing everything it can to expedite a resolution for your incident, before it starts hampering your personal productivity.

When it comes to MTTR, your mileage may vary of course, depending on your IT organization’s ticket backlog, user population density, and complexity of tickets handled.

Regardless though, one universal factor that’s slowing down almost all IT organizations is the ever-increasing user demand for IT services, which often leads to growing system complexity in your environment to accommodate that growth, and ultimately results in ever increasing pressure on your staff to keep up. 

However, people don’t scale very well.  Even the very best data center workers can only do so much.  At some point, and that point is pretty much right now, automation has got to do more and more of the repetitive, tedious, laborious tasks all this growth in demand for services and increased system complexity is creating.

That’s why consolidating visualization of all your monitoring tools into a single pane of glass and incorporating automated incident remediation into that dashboard, can give your IT department the critical boost it needs to overcome the lack of human scalability.

If you’re interested in test driving Ayehu NG v1.6 with all its cool new features, download your very own free 30-day trial version from the link below:

https://info.ayehu.com/download-free-30-day-trial-ng

How to Future-Proof Your Business with Intelligent Automation

How to Future-Proof Your Business with Intelligent AutomationAutomation has become a staple in IT operations. Yet, despite its prevalence, many of the automated processes currently being used are antiquated. The fact is, IT infrastructures have evolved substantially over the past decade or so, and continue to do so at a rapid pace. In order to maintain a high degree of integrity, automated processes must also adapt. Adopting more intelligent automation will not only dramatically improve internal operations, but it will position your organization leaps and bounds ahead of your competitors.

What is “intelligent automation?”

Unlike conventional automation tools of the past which were capable only of executing simple, manual and easily defined processes, intelligent automation and orchestration platforms are able to undertake tasks and workflows that are far more complex. Not only is intelligent automation capable of making decisions without the need for human input, but it can also evolve and improve itself over time.

Why is intelligent automation beneficial to IT operations?

IT ops has long been tasked with the overwhelming duty of doing more with less. Today’s IT teams, however, are also being depended on to drive innovation, and at a much more rapid pace than ever before. Intelligent automation facilitates both of these things by streamlining operations and freeing up skilled staff to apply their expertise to more innovative business initiatives. Furthermore, automation is dramatically improving the delivery and integrity of information, which paints IT ops in a positive light.

What are some of the biggest challenges IT ops face today?

Among the many challenges IT operations face in the digital age is the need to increase agility while maintaining as little disruption to existing processes as possible. IT teams must continue to meet (and in many instances exceed) business demand while also looking toward the future and finding newer, better opportunities to grab onto. It’s a delicate balance between meeting the needs of today and anticipating what the needs of tomorrow will be.

Why aren’t more organizations adopting intelligent automation?

Automation in its traditional form has worked well for IT ops, mainly because it can be leveraged on an ad hoc basis, such as with custom scripts and job scheduling. These days, however, things are becoming far more complex, with many different layers of virtualization and applications stacks of varying ages, along with combinations of public and private cloud solutions, all of which must be aggregated to deliver a single, streamlined IT service. In this environment, the concept of integrating intelligent automation can seem overwhelming. The good news is, it’s not nearly as complicated as it may seem.

What’s a good way to get started with intelligent automation?

A great way to introduce intelligent automation into the mix is to start small. Identify the big wins – or those routine, manual and time consuming tasks and workflows that when automated will produce the greatest return on investment quickly. Figure out what your IT operations team is wasting precious time and resources on, and then start deploying robots to do the dirty work. Keep in mind, however, that in order for intelligent automation to truly be beneficial, it must eventually become an integral part of the entire infrastructure. It’s ok to smart small, but make sure you’re working toward the big picture.

Without question, adding intelligence to automation will facilitate far greater productivity and innovation, while simultaneously setting the bar higher in terms of speed and agility for IT operations. Organizations that successfully deploy intelligent automation will easily surpass their competitors who do not, ultimately positioning themselves at the head of the pack.

Where do you want your company to be? Get a jump on the competition and future-proof your business with intelligent automation. Experience it for yourself by taking Ayehu for a test drive today.

Free eBook! Get Your Own Copy Today

Episode #35: The Critical Steps You Must Take To Avoid The High Failure Rates Endemic To Digital Transformation – Pink Elephant’s Troy DuMoulin

February 18, 2020    Episodes

Episode #35: The Critical Steps You Must Take To Avoid The High Failure Rates Endemic To Digital Transformation

In today’s episode of Ayehu’s podcast we interview Troy DuMoulin – VP Research & Development at Pink Elephant. 

In response to the growing balkanization of IT management practices among its various government branches in the 1980’s, the United Kingdom developed a set of standardized practices that all their agencies & vendors were expected to follow.  These standardized practices eventually evolved into a widely adopted framework for administration of information technology commonly known as ITIL.  Worldwide, 47% of surveyed organizations use at least some form of ITIL, making it the most popular IT framework, according to a 2017 Forbes Insight survey. 

Given the accelerating drive by organizations to digitally transform their operations, ITIL has gained even greater prominence as an enabling factor in their success….or failure.  To better understand the promise & perils of organizational transformations, and what role automation, AI, and machine learning will play, we turn to Troy DuMoulin, VP – Research and Development at Pink Elephant.  Troy shares his thoughts with us about what he believes is the “gift of ITIL”, the 5 questions CIOs & IT leaders must answer before an organization considers using a shared tool chain, and why process and tool projects are really people change projects in disguise. 



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 Troy DuMoulin, Vice President of Research and Development at Pink Elephant, a premier global training, consulting, and conference service provider. Now, I have no doubt that many members of our audience have either taken Pink Elephant training or attended a Pink Elephant event. And Troy is a leading ITIL, IT governance, and Lean IT authority with a solid and rich background in executive IT management consulting. He was also one of the 12 architects on ITIL 4, and given his extensive expertise with business process re-engineering in organizational transformation, we thought our listeners would enjoy hearing his thoughts on these issues from an ITSM practitioner’s standpoint. So we’ve invited Troy to come on the show because we’re eager to get his insights about the intersection between ITIL and automation, AI, and other transformative technologies. Troy, welcome to Intelligent Automation Radio.

Troy DuMoulin: Thank you, Guy. It’s definitely a pleasure to be here today. Guy Nadivi:Troy, our show is very focused on an IT executive demographic, all of whom I’m sure have heard of ITIL and ITSM, but I wonder if you’d indulge us a little bit and define these from your perspective.

Troy DuMoulin: Absolutely. It’s always an interesting question. I’m asked what is ITIL because it really is what we’ve always done. In my role, Guy, I often get asked to come and speak to senior leadership teams and describe to them the goings on in the ITIL and ITSM worlds. And I ask them a few questions before I even start. I say, “Tell me, guys. Today do you have practices and management capabilities for sitting down with your customers and sitting down and asking and figuring out where they’re going and how you can help them?” “Yes, of course we do. Obviously.” Okay. All right great. Then you take those conversations and you capture those requirements somehow in a meaningful way that you can verify you’ve heard what has been said and is shared back. “Yes, that’s what we do.”

Troy DuMoulin: “All right, then you hand those over to someone else to kind of figure out how we’re going to blueprint it and then we’re going to actually get ‘er done, whether it’s a project or not a project. We have to get it acquired or built, and then we’ve got to somehow, again, validate before we move it into production this thing called ‘the requirements’ that we first gathered on the front end.” “Yes, your point?”

Troy DuMoulin: “Hold on a second. Then we move those things into production once we verify that it won’t blow up upon arrival, and of course then you get the honor to support and run and deliver value that you’ve initially helped develop and co-created with your customer.” He said, “What’s your point?” I said, “Congratulations, folks. You’re doing ITIL.” Because all that ITIL has ever been, IT Service Management, and that’s what we talk about, is a set of organizational capabilities for taking requirements or demand and translating those through a complex value chain to the other side until we get value on the other end. Basically, it’s a value chain. And the recent version of ITIL 4 is very much oriented and visualized that way.

Troy DuMoulin: The interesting thing is people often think that’s service management over here and that’s architecture over there and that’s project management over there and that’s software development over there as if somehow these things are all separate, distinct, and independent. Well, they are different organizational capabilities. I’ll grant you that, Guy. But here’s what ITIL has always done. It’s the gift of ITIL, I like to call it. 3-step process. Every single major version, iteration, whatever you’d like to call it. It figures out what we’re all talking about, so it aggregates, it pulls in. Aggregates is the key word here. All of the different topics du jour. Things we’re talking about.

Troy DuMoulin: And then it integrates what seemingly was independent but is not, because these things all work together, or they should. And then it republishes a new picture, codifying the new holistic view of the IT management workspace. And this new picture becomes the new version. So it’s always a lag indicator. It doesn’t lead, it doesn’t invent anything. ITIL has never invented anything, and service management is just another way without using the word ITIL to talk about just the general organizational capabilities, AKA things we wish to be good at, to take, demand and produce value.

Troy DuMoulin: I chuckle. The conversation is usually starting, “Can you tell us about this new thing that you’re trying to introduce to us and prove to use why we should do it?” And in essence, because I’ve just asked them these questions, I say, “Congratulations, folks. You’re doing everything ITIL talks about now. Not one thing that ITIL covers doesn’t already exist in your organization. It’s not whether it exists or not, it’s whether you have it under intentional governance and management and whether you understand how it all connects in the bigger ecosphere of value generation.”

Troy DuMoulin: And so that’s the initial going in conversation is congratulations, you’re already doing it, but are you focused on it? Because typically they’re not. They’ll be focused on technology, maybe on structure, but very, very, very infrequently on an operating model of IT management practices. That’s service management. So what is service management? Yes, anything your organization does in the soft skills people side process area we could call ‘service management’. I’m not sure if that was the answer you were looking for, but that is in essence what is service management today.

Guy Nadivi: It’s interesting that you define service management that way because in a recent article on Pink Elephant’s blog, you make a provocative statement that, quote, “Service management process and tool projects are really organizational change projects in disguise”. In your experience, Troy, what percentage of ITSM projects successfully transform an organization? And what factors do the successful ones share in common?

Troy DuMoulin: Yeah, so let me unpack that statement a little bit. You know what they say; hindsight is 20/20, or wisdom is a cumulative experience. So after 20 plus years in the industry of seeing many projects not succeed, I had to do a little insight here in thinking about the basis of what you just asked me.

Troy DuMoulin: The reality is, most organizations don’t recognize that the true problem we’re trying to solve here is to gain agreement and alignment of the organizations, plural, inside our value chain so that we can agree to agree what we’re going to do, how we’re going to do it, and do it hopefully in a consistent, coherent and high velocity way.

Troy DuMoulin: In essence, it’s an organizational change project. The process and the tool are very important but they’re not the goal, they’re enablers to the goal. I sit down and I hammer out through this dialogue all of these discussions with folks around “how are we going to get stuff done”? We finally, through negotiation, horse trading, all of that, agree to agree what it is, but then we’ve got to actually codify it quickly before we forget and leave the room, otherwise we leave the room and it’s open to subjective debate. So we’ve got to write it down and constitutionalize it. We the people find it self-evident and true and we have signed here. Documents are important, but more as a constitutional aspect of agreement.

Troy DuMoulin: And then you’ve got to have this tool. You’ve got to make it visible. The principle of Jidoka in Lean says you cannot govern or manage what you cannot see so putting it in a tool makes it visible, makes it measurable, makes it even automated in the sense of flow of work and the visibility of the flow of work or lack thereof.

Troy DuMoulin: The tool’s really critical as well. We’ll call it a critical success factor and enabler, but it’s not the goal. The goal is agreement. We have all these diverse organizations which want to have the right to independent thought and practice. The document was simply to document agreement that we finally hammered out. The tool was to make it visible. But here’s the problem; the goal or the deliverable of the project was the agreement, not the document nor the tool. And so they’re enablers, you can’t work without them, but most organizations who don’t recognize that what they’re really up against is a people change project, which is supported by processing tools, will invariably fail because they focus on the wrong stuff.

Troy DuMoulin: Guy, think about this; how many times in your professional career have you seen people spend hundreds of thousands of dollars, if not more, on process documentation and tool implementation, go live and the very next day nobody does anything different. Right? It completely fails to deliver the value after a six month to a year project. Have you ever seen this?

Guy Nadivi: More times than I care to recount, actually.

Troy DuMoulin: So what’s the definition of insanity?

Guy Nadivi: Doing the same thing over and over and expecting a different result.

Troy DuMoulin: But this time it’s going to work. We’re going to slap the easy button. So here’s your answer; most organizations fail miserably when they think there’s a tool or a process project and this is what I’m not proposing. I speak a lot about DevOps and I talk about the DevOps tool chain. It’s obviously a great thing if I could find a way to automate code flow from the point of code commit all the way to deployment without stopping and I’ve got all these things verifying, production assurance, verification of test result, et cetera and I can deploy in a high velocity way, this would be awesome. This tool chain sounds wonderful.

Troy DuMoulin: But, there are five questions that I’ve been able to articulate, and I’ve written it on my blog. Maybe we can link to it, but the reality is these are the five questions that CIOs and leaders would have to be able to answer before their organization could ever use a shared tool or tool chain like I’ve described. The first question I’ve kind of already articulated. Can we agree that we need to agree across silos on anything? Agree to agree. That’s the first question. Second question; can we agree, please, on one way to do it? Because unless it provides strategic differentiated value, variation in Lean actually has an impact on quality, costs, and speed. Can we agree on one way, please? One way? OMG, as long as it’s my way. No. One way.

Troy DuMoulin: Okay, third question; can we agree that we’ve got one way and we keep it simple? Because we’re engineers, we’ll over engineer everything to the point of almost un-usability. Question four; can we agree if we’re going to do it one way, can we do it with one tool? Unless it’s a strategic differentiated tool. Again, a system of parity means it doesn’t give us more money to have multiple variability here or get us more market share, it just costs us more in impact speed. So can we reduce variability and come up with one tool to do the one way? And the final question is can we agree that that one tool isn’t a point solution or best of breed, it’s an integrated tool system. Folks, it’s a tool chain. The output of one tool becomes the input of another which is the output, et cetera, et cetera.

Troy DuMoulin: And this is interesting because these five questions you would have to be able to answer as a leadership team before that organization would ever use a shared tool chain. Because where I work and how I often see this play out, Guy, is that people can’t even get past question one. And none of those questions are actually process or tool questions, really. They’re organizational, culture, leadership, and organizational will. And what I typically see is not one shared platform is a service technology being used in a multi-tenancy way by product teams. Each product team develops their own tool chain. And nowhere in any DevOps literature have I read that’s the actual intent.

Guy Nadivi: You just touched upon the fact that, to begin with, people just need to agree to agree. And Tony Saldanha is a former Vice President of Proctor & Gamble that recently appeared as a guest on our show. He published a book in 2019 called Why Digital Transformations Fail, which claims that the failure rate for these projects is as high as 84%. And Tony attributes that high rate of failure to basically two things; lack of leadership and lack of creativity, which you’ve kind of touched upon. But I’m curious, Troy, from an ITIL/ITSM perspective, what are the primary factors you see derailing organizational change projects?

Troy DuMoulin: I completely agree with Tony’s premise. Let’s take it from this angle. Two things. Again, as you mentioned, I’m a Lean advocate and Lean leadership is a big part of the philosophy of how Toyota succeeds year over year and is still one of the highest brands. And they talk about persistent adaptation towards truth north values in a direction. This is the premise, though; true north means we have a shared outlook and a shared view of where we’re all going. Andy Stanley was once quoted to say, “We all end up somewhere. Some of us actually get there on purpose.” So action or movement in its own right is not value necessarily. It’s a perception, perhaps a value, but it’s not necessarily unless we are getting somewhere we plan to go.

Troy DuMoulin: That being said, that means that leadership in this question, in this situation, has to basically deliver two things, and this is a principle out of the Shingo Institute connected to Utah State. That leaders create systems thinking, we the people include all of these different stakeholder groups both our brand and all those embedded now 3rd-party vendors we call partners. We the system, right? Systems thinking. And then the other is once we have a system identity, constancy of purpose. We’re all going there. Where are we going? We’re going there. We’re going there because velocity is speed with direction over there. And we’re going to do it the same way. We’re going to share the same values, beliefs, practices, and the same basis for prioritization of work. And this is what leadership is. It’s called alignment. Pulling everybody together pulling in the same direction. And then we get velocity which is speed with direction.

Troy DuMoulin: So this principle of failure is key because we lack systems thinking. Or if we think systems, we only think technology systems, because let’s take the word systems integration. So I have this vision in my head of a systems integration approach to technology. Data layer, infrastructure, all of that, application layer in an integrated system. Well, to use that integrated system, systems integration, I would have to have an integrative set of management practices because that’s what it’s automating. Which would mean I have an integrative organizational context. We, all the people, work together in a cross-functional product team like this. Think of it in your mind like a three layer stack. Yes, I have an automation layer, but I have a practice layer and on top of that an organizational layer, or if you want to flip them, organizational layer comes first as the basis and you go up this way when we don’t think systems thinking, we only think technology.

Troy DuMoulin: But again, that’s a means to the end. Systems thinking, if you’re going to use that premise – because we can have a management system, a technology system, an organizational system – is to have this much more holistic view. Because with integrative tech, it doesn’t mean I’ve got people to agree.

Guy Nadivi: Speaking of principles, Troy, principle seven of ITIL 4, the last principle of the latest ITIL framework is, “optimize and automate”. I’ve read that this principle’s considered by many to be a first step towards acknowledging the need for more AI and automation in ITSM. From your considerable ITSM practitioner perspective, where do AI and automation add the most value to ITSM?

Troy DuMoulin: Well, it’s our business, first of all. We are in the business of automation and technology so we should be good at doing that. And what do we typically automate? First of all, if we can standardize a practice, we can all agree that this is what we’re doing, and then stabilize it, then we should automate it because we should get onto higher value heuristic versus algorithmic work. But that would be dependent on us agreeing to stabilize and have standards, which by the way is a dependency for all of this. And if we can actually do that then awesome. We should automate it because machine learning and artificial intelligence are excellent at detecting patterns that we the people can’t see because we have inability to see massive data correlation.

Troy DuMoulin: This is data analytics, machine language – excuse me – machine learning, data science. This is the whole basis of what information technology is as compared to operational technology. Information technology is to manage the information and data in such a way we can make decisions based on the automation of data correlation. So we the people, can be learning from machine learning and pattern recognition, AIOps, et cetera. I have an event. If I see so many events of a certain nature within a certain timeframe, maybe that might predict a failure, let’s avoid it. Or can I see this event so many times within a certain timeframe? Show me there’s a pattern with an unstable environmental component, I should remove, AKA problem management. So machine learning, artificial intelligence, the automation of all of that helps we, the people, make better decisions which is the premise of information technology versus operations technology is machine teaches machine. Do this, change this because this condition is met for the purpose of machine automation.

Troy DuMoulin: So this is critical for us to make better decisions. But take a page out of Google’s SRE. They say 50% of what we do we’ll call toil. That’s the stuff the manual administration kind of standard operations, and we’d like to reduce that as much as possible through automation because the other 50% of assisted men’s time should be on innovation, it should be on finding ways to automate the thing we called toil so that we could get up and start working on higher value, more heuristic work. We can’t do that well without knowing what the data says and that is the value and the blessing of machine learning and artificial intelligence.

Guy Nadivi: Troy, for the CIOs, CTOs and other 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 organizational transformation?

Troy DuMoulin: Yeah. We need to go back to your first observation that when we realize that transformation really is a people change project, that really process and tool projects are people change projects in disguise, and that process and tools, while critically enabling, are valuable, they’re not the goal. They’re the enablers. They’re not the goal themselves. And if we can focus on first principles in this way, understanding the organizational alignment is the predictor of systems alignment, then we’re going to get somewhere but not until we realize that that is the goal.

Guy Nadivi: All right. Looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Troy, I can say with confidence that you’re the most distinguished ITIL/ITSM expert we’ve ever had on this podcast. And I’m sure I speak for our listeners when I say it’s been very educational tapping into your insights to gain a better understanding about this space. Thank you so much for sharing your perspective with us today.

Troy DuMoulin: Thank you, Guy, for inviting me.

Guy Nadivi: Troy DuMoulin, vice president of research and development at Pink Elephant, a premier global training, consulting, and conference service provider. Thank you for listening, everyone, and remember; Don’t hesitate. Automate.



Troy DuMoulin 

VP Research & Development at Pink Elephant.

Troy is considered by many to be one of the world’s foremost ITIL® and ITSM experts; he is currently working on the ITIL 4 update as a member of the Lead Architect Team. As a leading IT governance and service management authority, Troy has exceptional expertise and experience in Lean IT and DevOps as well as an extensive background in executive IT management training and consulting – with more than 20 years’ experience. He is also a published and contributing author for multiple books on topics such as Lean IT, the service catalog, and official ITIL® publications for editions (2, 3, and 4). A frequent speaker at IT management events, Troy was recently named one of the “Top 25 Industry Influencers in Tech Support and Service Management" by HDI. 

Troy can be reached at:

LinkedIn:            www.linkedin.com/in/troy-dumoulin-148235 

Blog:                   https://blog.pinkelephant.com/author/6 

Article:               Is Your Technology or Framework  A Solution Looking For A Problem? 

Website:            www.pinkelephant.com 

Quotes

“…all that ITIL has ever been, IT Service Management, and that's what we talk about, is a set of organizational capabilities for taking requirements or demand and translating those through a complex value chain to the other side until we get value on the other end. Basically, it's a value chain. And the recent version of ITIL 4 is very much oriented and visualized that way.” 

"Not one thing that ITIL covers doesn't already exist in your organization. It's not whether it exists or not, it's whether you have it under intentional governance and management and whether you understand how it all connects in the bigger ecosphere of value generation." 

“The reality is, most organizations don't recognize that the true problem we're trying to solve here is to gain agreement and alignment of the organizations, plural, inside our value chain so that we can agree to agree what we're going to do, how we're going to do it, and do it hopefully in a consistent, coherent and high velocity way.” 

“Andy Stanley was once quoted to say, ‘We all end up somewhere. Some of us actually get there on purpose.’ So action or movement in its own right is not value necessarily. It's a perception, perhaps a value, but it's not necessarily unless we are getting somewhere we plan to go.” 

“First of all, if we can standardize a practice, we can all agree that this is what we're doing, and then stabilize it, then we should automate it because we should get onto higher value heuristic versus algorithmic work. But that would be dependent on us agreeing to stabilize and have standards, which by the way is a dependency for all of this. And if we can actually do that then awesome. We should automate it because machine learning and artificial intelligence are excellent at detecting patterns that we the people can't see because we have inability to see massive data correlation.” 

“…machine learning, artificial intelligence, the automation of all of that helps we, the people, make better decisions which is the premise of information technology versus operations technology…” 

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.

GET STARTED WITH AYEHU INTELLIGENT AUTOMATION & ORCHESTRATION  PLATFORM:

News

Ayehu NG Trial is Now Available
SRI International and Ayehu Team Up on Artificial Intelligence Innovation to Deliver Enterprise Intelligent Process Automation
Ayehu Launches Global Partner Program to Support Increasing Demand for Intelligent Automation
Ayehu wins Stevie award in 2018 international Business Award
Ayehu Automation Academy is Now Available

Links

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
Episode #31: Could Implementing New Learning Models Be Key To Sustaining Competitive Advantages Generated By Digital Transformation?
Episode #32: How To Upscale Automation, And Leave Your Competition Behind
Episode #33: How To Upscale Automation, And Leave Your Competition Behind
Episode #34: What Large Enterprises Can Learn From Automation In SMB’s

Follow us on social media

Twitter: twitter.com/ayehu_eyeshare

LinkedIn: linkedin.com/company/ayehu-software-technologies-ltd-/

Facebook: facebook.com/ayehu

YouTube: https://www.youtube.com/user/ayehusoftware

Disclaimer Note

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

7 Tips to Win the IT Talent War

7 Tips to Win the IT Talent WarAs any IT leader will acknowledge, attracting top talent is only half the battle. It’s keeping them on that’s the real challenge. And with an average employee tenure of only about 3 years, it’s a serious concern for many organizations across the globe. Add in the complex, fast paced and highly stressful role of IT support and you’ve got quite the conundrum. So, what’s the secret? How can you do things differently so that your company remains as safe as possible from cyber-attacks while your talented employees stay on for the long haul? Here are 7 tips to point you in the right direction.

Keep them challenged. The last thing you want is for your IT support personnel to become bored and stagnant in their current positions. Avoid this by investing in ongoing training, setting up mentoring programs, and offering opportunities to learn about and master new strategies and technologies. The more you keep your IT employees engaged and involved, the less likely they’ll be to look elsewhere.

Rotate project time. Being stuck on the same project day in and day out can lead to fatigue and frustration. Consider rotating employees onto various IT projects so that they don’t feel stuck. This will provide exposure to and the opportunity to learn about new skills and also open up the door to be able to approach long-term projects from differing perspectives – both of which can benefit your organization.

Give them the tools they need. These days, keeping up with the onslaught of cyber-attacks is nothing short of exhausting. Don’t leave your IT personnel out to dry by making them handle this monumental task manually. Arm them with the technology they need to do their jobs better, faster, more efficiently and more effectively, such as intelligent automation.

Provide a safe place to vent. Without question, the job of keeping an entire organization safe from breaches and outages can be incredibly stressful. Additionally, IT security personal often feel tense due to the amount of classified and confidential information they are entrusted with. Provide an opportunity and a secure avenue for these employees to vent their feelings.

Encourage time off. Everybody needs a little down time, but given the fast-paced and highly stressful field of IT, these employees could probably use some time off more than anyone else in your organization. This is where technology can help. By automating a good portion of tasks and leveraging the cloud to embrace more flexibility, your team can take the much needed time off they deserve without the company feeling any negative impact.

Use realistic metrics to measure success. One of the biggest reasons IT professionals find themselves dissatisfied at work is because they feel they aren’t being adequately recognized. This is often due to a lack of clear and specific metrics for success. Management should set realistic expectations, communicate openly and routinely measure progress. Good work should be rewarded and areas of improvement identified and addressed in a positive, productive way.

Empower them. If your employees feel that their only option is to come in every day and put in 8-10 hours of labor, they’re not going to develop any kind of connection or loyalty to your organization. On the other hand, if they know that the work they do plays a direct role in the “big picture” and that their achievements are tied into the company’s overall success, they’ll be much more plugged in, which means they’re more likely to stay on for the long haul. Empower them by inviting ideas and encouraging autonomy.

Are you doing enough to keep your IT personnel satisfied, engaged and plugged in? If not, you could be facing higher turnover, which can negatively impact your company’s bottom line and also leave you more vulnerable to things like outages and cyber-attacks. By implementing the above tips, you’ll create a more positive work environment that fosters longevity. Happy employees will work harder to ensure that your organization remains strong, secure and successful.

eBook: 10 time consuming tasks you should automate

4 Steps to Intelligent Process Automation Breakthrough

Intelligent process automation is rapidly transforming the global economy, delivering momentous gains to enterprises that adopt it at scale. One recent article by McKinsey revealed that some organizations have been able to automate 50 to 70 percent of their workflows, generating ROI that reaches into the triple-digits. In addition to cutting costs, intelligent process automation can also deliver precision, speed and enhanced customer experience.

In order for organizations to enjoy the full value of intelligent process automation, IT leaders must be willing to take a guiding role. Unfortunately, many IT executives find this challenging, whether due to the increased complexity of IT processes, lack of understanding and/or clarity, inconsistent or fragmented tools that hinder scaling, or the misconception that intelligent process automation cannot be adopted without major re-engineering of existing processes.

How can these challenges be overcome? And how can IT leaders succeed in their automation initiatives? The answer to these questions lies in the following four key steps along the intelligent automation journey.

Step 1: Evaluate the high-level potential value

The first step in becoming an intelligent process automation leader starts with the development of a clear business case. This involves assessing the potential high-level value of the company’s main IT activities. Some examples of what these areas of value might look like include:

Incident Response – A significant number of IT incidents are initiated through support desk requests. These typically result in tickets being created and assigned to Level 1 support agents. While these are the obvious candidates for automation, the portion of tickets that are escalated to specialized L2 and L3 agents are also ripe for the picking, thanks to the advanced technology behind intelligent process automation. And since these activities are generally well-documented, categorizing and prioritizing them by automation potential should be relatively straightforward.

Planned Activities – In addition to the one-offs and unexpected support tickets that crop up, IT is also responsible for performing a number of planned activities on a regular basis. These activities typically include things like backups, upgrades and patching. They may also involve more complex security audits. The amount of time and resources required to perform these duties can collectively add up to around 20 percent of the IT budget. Calculating this figure can help determine the potential savings intelligent process automation can deliver.

Introducing New Applications – From a business perspective, this activity is often viewed as the one that produces the most significant value. It can also account for an additional 20 to 40 percent of the time and resources put forth by IT. These activities are not exclusive of application development, either. They also include such tasks as testing and hosting. This places increasing demand on both the application team as well as the infrastructure group.

Step 2: Dig deeper to identify which specific use cases are best suited for intelligent automation.

Determining how to effectively implement intelligent process automation requires a deep dive to uncover the root causes of issues. It may also involve the untangling of complex systems and the development of an accurate picture of how to leverage automation to extract the greatest value. In other words, the process is a complicated one and requires a certain degree of commitment. Let’s take the three potential use cases above as an example.

Incident Response

Automating IR begins with identifying which incidents are the best candidates, which can be challenging. The goal should always be digging deep enough to uncover the “why” of documented incidents. Without this information, efforts are futile. Text-mining can help by automatically reading ticket descriptions and extracting the necessary insights to sort them into three categories:

  • Automatable
  • Requires machine learning
  • Highly cognitive/manual

This analysis should leave you with a prioritized list of incidents to automate and the type of automation best suited for the job.

Planned Activities

Most enterprise-grade IT departments rely on industry-standard tools to manage their infrastructures. Unfortunately, due to factors such as advanced customization, adjustments due to mergers and specific user requirements, managing these systems often requires a significant amount of manual effort, diminishing the overall value.

For instance, despite the widespread adoption of infrastructure and application monitoring tools, support teams are often unable to respond effectively to the logs being generated, either because there are too many of them or because of the many reasons why they are being generated in the first place. As a result, IT leaders are often unclear on how to approach intelligent automation implementation.

In situations such as this, machine learning technology can be “trained’ to identify the reasons behind alerts and then either recommend or autonomously make better decisions on which action to take. This eliminates much of the complexity for the IT team.

Introducing New Applications

Many IT executives fall into the trap of focusing solely on the reduction of manual labor. As a result, they fail to see and achieve the full value potential of intelligent process automation. Faster and more accurate delivery of applications requires the development and design of a new operating model, with an emphasis on DevOps and agile.

Reviewing this entire process to gain an understanding of how to make the most use of this new operating model can result in entirely new approaches to work. Intelligent process automation can facilitate some of these new ways of working. For instance, automating the testing process will enable applications teams to iterate more quickly. Likewise, developing a self-service model for things like automated server provisioning allows the operations team to become more responsive. The list goes on.

Step 3: Execute your proof of concept

In order to demonstrate the true value and validate your case for intelligent process automation, the next critical step is executing a proof of concept. A great place to start with this is incident management. Organizations that have successfully deployed intelligent process automation for incident management have been able to achieve substantial cost savings in a relatively short period of time.

Thankfully, there are many different incidents that can quickly and easily be automated to support your proof of concept, including such tasks as password resets and employee onboarding. In its most basic form, a proof of concept requires the following:

  • Collaboration with subject matter experts to identify where automation can best be applied and understand all the steps and systems involved in a particular process or workflow.
  • Careful selection of an intelligent process automation platform. Look specifically for products that can be integrated with existing systems and applications and offers pre-packaged, no-code options. (This will enable rapid adoption and time-to-value.)
  • Obtaining necessary IT and overall business approvals with regard to regulatory constraints, security guidelines and access limitations.
  • Ongoing testing and monitoring to capture results and document value

This phase is also an ideal time to consider building stronger internal intelligent automation capabilities; for example, developing a team to spearhead a future automation center of excellence (CoE). This team will ultimately become the foundation and engine that drives all IPA initiatives.

Step 4: Build intelligent automation capabilities to scale

Achieving the full benefits of intelligent process automation requires the development and nurturing of certain skills and capabilities, in addition to rolling out an entirely new company-wide culture. This is essential as successful adoption of IPA requires that automation become embedded into the very heart of the organization itself. There are plenty of ways to accomplish this, but generally speaking, companies that have been successful have done the following three things:

Build on success to expand into new areas of IT (and beyond).

Once the basic tasks and workflows have been automated, it’s time to move on to more advanced level-2 and level-3 activities. The IT team should be expanding beyond incidents to begin leveraging the AI and machine learning technologies to assist with things like analytics and decision support. The goal is to eventually roll out intelligent process automation to as many routine and complex processes as possible.

Spread the word.

With a strong foundation of capabilities and experience, IT leaders can begin to position themselves as subject matter experts for the rest of the organization. This process involves continued outreach, such as connecting with other leaders across the enterprise to advise them of the specific benefits IPA can have for them. This outreach also provides the opportunity to identify additional areas where automation might be beneficial.

Explore the advanced elements of intelligent process automation.

While the majority of organizations have thus far only focused primarily on simple process automation, the future belongs to those with an eye toward artificial intelligence and cognitive learning. These solutions are already making an impact on companies with forward-thinking leaders. The best way to break into this arena is to start working on small AI initiatives. From there, just like basic automation, you can continue to build, expand and grow.

Intelligent process automation is maturing rapidly and quickly becoming a core component of the IT landscape. IT professionals who recognize the importance and understand how to develop their automation capabilities have the potential to become respected leaders in the process – a title that will serve them well throughout their careers.

Free eBook 10 time-consuming IT tasks you should automate

3 New Roles AI Will Create for Humans

What if we were to tell you that robots are not coming to steal your job, but instead, they’re coming to give you a promotion? Would that change your perception of artificial intelligence? Probably. Thankfully, in most cases anyway, it’s the truth. While AI will, inevitably, make some roles obsolete, it will simultaneously be creating newer and even more lucrative opportunities for humans. In fact, we’ve pinpointed at least three distinct job categories intelligent automation will open the door for. Let’s explore each of these below.

Trainers

Artificial intelligence is just that – artificial. Yes, it is capable of improving autonomously, but someone still has to be there to tell the program what to do and ensure that everything is moving along as it should be.

For example, before you can tell your virtual assistant Amazon Alexa that you want her to call your spouse, you first have to “teach” her who your spouse is and what phone number should be used. Once AI tools and platforms have the basic understanding of what’s expected of them, they can then continue to self-learn, but just like any student, they need to be taught those basics first.

Evangelists

Like it or not, artificial intelligence isn’t going anywhere. In fact, according to Gartner, 70% of organizations will assist their employees’ productivity by integrating AI in the workplace by as early as next year.

Yet, despite this looming proliferation, not everyone is quite comfortable with the concept of AI. Fear of the unknown is still a very real problem for many organizations. That’s where AI evangelists come in. These are human experts whose role, at least in part, is to explain computer behavior to others.

Having champions of intelligent automation will enable the enterprise to overcome fear and resistance, clearing the pathway to successful digital transformation.

Managers

As smart as AI is, it’s not necessarily something you can simply set and forget. To the contrary, human oversight is still very much needed to ensure that systems are working properly, securely and responsibly.

The fact is, while chatbots have the capability of learning and communicating, they lack many of the characteristics that are innate to humans. One need only look back to the Microsoft Tweetbot debacle of a few years ago to understand this.

In March of 2016, the computer mega-giant introduced its interactive chatbot named Tay to the world of Twitter, with the goal of engaging 18-24 year olds with the concept of machine learning. The chatbot was taught to interact with other users like a real human through reading and processing actual tweets.

Unfortunately, within hours, savvy Twitter users had transformed the formerly innocent bot into something vile and offensive. Simply put, AI has the potential to run amok without adequate human oversight.

How Humans Can Prepare

Within these three categories there will be numerous positions and opportunities for human workers to future-proof their careers. The best place to start is through education. Learning new skills and gaining a fundamental understanding of intelligent automation technology can make you an invaluable asset and catapult your career possibilities.

Ayehu’s Automation Academy is designed to provide individuals of every level with the up-to-the-minute knowledge, experience and tools necessary to develop and expand their automation knowledge. Best of all, it’s available completely free of charge. Develop your skills today to become a trainer, evangelist or manager of tomorrow. Enroll for free today!

Introducing Ayehu NG v1.6 – New Advanced Features

Author: Guy Nadivi

If you’re an existing user of Ayehu NG, or even if you’re just thinking about trying us on for size, you probably know that one of the core strengths of our solution is how easily and quickly you can plug Ayehu into various ITSM platforms, cyber security tools, operating systems, messaging and notification solutions, and increasingly chatbots and AI services.  Almost all of these integrations can be activated seamlessly without writing a single line of code. 

And the purpose of providing you with all these pre-built integrations and connectors that make up our ever-expanding ecosystem, is to simplify your ability to orchestrate automation across any platform in your environment.  All from a single pane of glass!

We add new integrations and their accompanying activities to Ayehu on an on-going basis, but sometimes, that hasn’t been quick enough for some of our customers and prospects. 

In our last release of NG, v1.5, we introduced you to its new Activity Designer.

This new functionality allowed you to build your own activities from scratch, in Python, C#, or .NET.  Many of our customers use the Activity Designer to create activities for actions against external systems that we don’t currently connect to. For example, you can use it to connect to Dropbox, Google, or any other third-party system that has accessible APIs.

SDK

In this new version 1.6 of NG, we’ve added a software development kit.  This new SDK means that now, in addition to being able to build custom activities, you can build entire custom integrations!  So if you’d like to integrate Ayehu with a platform we don’t currently have an integration with, you can do it yourself.  This might be especially helpful if you’ve got a homegrown application that’s the only one of its kind, and you want to automate certain tasks for it.  You can do that with the new SDK, and orchestrate the workflows from right inside Ayehu NG, just like you do for your other platforms.

NG-to-NG Migration Tool

In the past, migrating an NG workflow from a pre-production environment like DEV or TEST was a bit challenging.

In release 1.6 though it becomes a breeze with our new NG-to-NG Migration Tool.  This tool makes moving workflows from a DEV or TEST environment much simpler because it brings over almost all the entities associated with that workflow into your PRODUCTION environment.

BTW – this comprehensive migration can be done on a single workflow or an entire folder of workflows.

Slack Bot

Many of you have been taking advantage of Ayehu’s integration with Slack to build intelligent bots which provide your end users with powerful self-service remediation capabilities, that have eased the strain on your service desks.

In version 1.6, we’ve greatly simplified the process of configuring a Slack bot to just one click.  On top of that, we’ve also activated an “Add to Slack” button on our Slack Integration page so you can easily register your bot with Slack.

Configurable Password Policy

Ayehu NG v1.6 now has enhanced security for configuring default password policy. This means that passwords for all new accounts will be much stronger.  You can now set your own default password strength and parameters based on your organization’s security needs.

So if your password standard requires 12 characters, two special characters, and a number, you can now set this as default and it will be enforced across all local accounts in your environment. If you prefer synching accounts from your Active Directory, then NG will default instead to the password policies you’ve established in AD.

Updated Installer

Another improvement NG v1.6 introduces is an updated installer, which simplifies installation while also providing greater visibility into the process.

In the image seen here, you can review all the components to be installed on a component selection tree.  The most popular components are selected by default, but you can easily toggle the ones you don’t want. We’ve also added a pre-requisite screen check to ensure that the installation will complete successfully, and to let you know if any minimum installation requirements are lacking.

Refreshed Login Page

This new feature is more about aesthetics than anything else, but we’ve refreshed the login page with a bit more of a dynamic look and feel to it.

image001

BMC Helix Remedyforce Integration

Finally this newest release of NG includes an integration for BMC’s Helix Remedyforce.  It’s basically a duplicate of the existing BMC Remedyforce integration capabilities but on BMC’s Helix platform. This new integration allows you to Create, Update, and Get records from Helix Remedyforce, as well as execute SOQL queries.

If you’re interested in test driving NG v1.6 with all its cool new features, download your very own free 30-day trial version here.

To watch a replay of the live webinar and see these new features in action, click the image below.

5 Biggest Blunders Organizations Make with AI

According to Gartner, implementation of artificial intelligence has skyrocketed by 270% over the last four years, with spending on AI software and hardware anticipated to soar from the present amount of $37.5 billion to a whopping $97.9 billion by the year 2023. There’s no argument. AI is here to stay, and it’s going to become a truly integral part of our everyday lives. As such, business leaders in every industry are wondering what AI means for their organizations and, more importantly, how they can capitalize on the tremendous opportunities this innovative technology presents.

In order to be successful with AI, however, it’s imperative that leaders not move forward too quickly without adequate awareness of the many obstacles that could delay, limit or even completely destroy their efforts. Specifically, here are five common traps many organizations have already fallen into that you can hopefully avoid with your own AI initiative.

Being misled.

Sorry to be the bearer of bad news, but not every AI product on the market is what it’s presented to be. In fact, many less-than-forthcoming and often downright dishonest service providers are selling what amounts to glorified automation tools. Automation is great, but the true value of AI lies in its ability to become smarter and more autonomous over time. Don’t be led astray. Do your homework and, if possible, take potential platforms for a test-drive before you invest. Trust us – you’ll know the difference.

Putting the cart before the horse.

Once you’ve got a true AI platform at your disposal, it’s easy to get so excited about the potential artificial intelligence presents for your company that you end up getting ahead of yourself. Keep in mind that AI isn’t an end, but a means to that end. Achieving big-picture goals often requires accomplishing smaller milestones along the way. Focus first on identifying specific business issues, pain points and areas of the business where AI can provide fast, measurable wins and then scale from there. Slow and steady wins the race.

Forgetting data.

The fact is, the outcome of an artificial intelligence engine is only as good as the quantity and quality of the data it is able to ingest. You can’t expect an AI platform to start churning out valuable insights or begin learning and improving contextually if you don’t adequate data to begin with. It’ll work to a degree, but it’ll produce substandard results, so what’s the point? Start by determining whether or not you have the right architecture in place, and if not, focus your efforts there first.

Leaving silos.

If you’re looking to store grain, silos are great. If you’re trying to implement an organization-wide AI initiative, not so much. Why? Because an effective, end-to-end AI strategy inherently depends on integration of data and collaboration of teams. You may have mapped out areas within your organization where AI might help, but if you don’t break down the roadblocks that exist within your infrastructure, don’t expect good results. Data gathered from one team that isn’t shared with the data scientists managing AI models is useless without seamless collaboration.

Failing to invest in skills.

Sure, the beauty of artificial intelligence is, well, that it’s artificial. Implemented properly, AI can run circles around human employees, performing work faster and eliminating error. That said, humans are still very much needed. In fact, some would argue even more-so now than ever before. Without the right team to ensure everything is running smoothly, you’ll quickly lose ground. Thankfully, fighting the war for external talent isn’t necessary. Oftentimes, reskilling in-house employees is not only sufficient, but a much better approach. In either case, an intentional investment in skills is equally as important as choosing the right AI platform.

Artificial intelligence presents tremendous opportunity for organizations of every size and industry. But in order to be successful with AI, leaders must apply their own human intelligence to the process. By knowing which common blunders to steer clear of, like the five listed above, successful implementation and the business value that follows will be well within your reach.  

Episode #34: What Large Enterprises Can Learn From Automation in SMB’s – DataAutomation’s Will Christensen

February 3, 2020    Episodes

Episode #34:  What Large Enterprises Can Learn From Automation in SMB’s

In today’s episode of Ayehu’s podcast we interview Will Christensen – Co-Founder of DataAutomation. 

The renowned business management guru Tom Peters once wrote that “Business is about people. It’s about passion. It’s about bold ideas, bold small ideas or bold large ideas.”  Automation, arguably, is a bold large idea that’s taken root in large enterprises.  Less well known is the fact that it’s pretty popular among smaller businesses as well, where it’s become no less of a bold large idea.  That may come as a surprise to some who only think of automation as a tool for roboticizing complex, large-scale processes in big organizations.  Nevertheless, automation’s diffusion has made it readily accessible at all levels, just as computers went from being once rare machines of the privileged to ubiquitous tools of the masses. 

The democratization of automation is creating a bonanza for service providers who can accelerate the benefits an organization realizes from its deployment.  One such provider is DataAutomation, whose cofounder Will Christensen has gained a unique perspective on this trend through his extensive experience helping SMB’s automate a broad diversity of processes.  Will joins us to share the surprising #1 driver for automation among SMB’s, the 4 basic questions to answer before automating any SMB’s manual process, and the litmus test SMB’s should go through before deciding whether or not to even automate a manual process. 



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 Will Christensen, cofounder of DataAutomation, an automation service provider. Will spends a lot of time helping organizations deploy automation in the SMB space, and that caught our attention, because you really don’t hear as much about automation for SMBs as you do for large enterprises. Yet despite the difference in their respective scales, the desired outcome for both enterprises and SMBs is the same: Improving performance, reducing costs, and gaining competitive advantage. So we’ve invited Will to come on the show and shed some light for us on automation for SMBs, and in the process we may learn some new perspectives that could also be applicable at the enterprise level. Will, welcome to Intelligent Automation Radio.

Will Christensen: Thanks. It’s good to be here. I’m excited to chat with you a little bit about this other perspective.

Guy Nadivi: So let’s start, Will, by you telling us a little bit about your background and how you got into automation.

Will Christensen: Absolutely. It’s actually a pretty good story. I’m a little bit of a superhero nerd, so I totally call this the origin story, so to speak. So I was the low man on the totem pole at an advertising agency, and I walked in, and being the low man on the totem pole, you get the really awesome opportunity to get essentially all the grunt work. And so I was handed 16 hours of copying and pasting things manually, and the 16 hours was happening once a week. So almost half of my life was dedicated to literally putting together these manual reports. And I thought, “You know, there’s got to be a better way.” Somebody sat me down at that point, this is several years ago, and said, “Hey, Will, this is called a VLOOKUP.” They showed me how to connect one spreadsheet to another, and my mind was blown. “Holy crap. You can actually move things from one spreadsheet to another automatically? No need to manually go look up each one of those items?” And I said, “Okay, if you can do that, what else can you do?” And so technically, DataAutomation started with a VLOOKUP, and I then spent probably close to 180 to 200 hours teaching myself how to do different pieces of automation. Did a bunch of macros in Excel, then I got underneath that and understood all of the Visual Basic, taught myself to code. I even taught the Excel program to open up web browsers and download all of the data sources, so I got it to the point where this 16 hour process, I cut it down to two hours. And so my computer would wake up in the middle of the night and I’d come in in the morning and check the work, and then send out the reports. And I just got so … I loved it. I loved the process, and I thought, “You know, I’ve learned a lot of new skills here. I wonder if I could take this out and give it to other people.” And sure enough, that’s exactly what happened. I was able to take that skill set, I became the resident person in the office who would solve anything related to Excel, and pretty quickly I started to translate that into using other SaaS platforms that allow for automation, and went to work for a tech incubator on the east coast called RoundSphere, and pitched them on the idea of creating a company, a systems integrator, an automation-focused company that basically just helped other companies automate, and they bought off on it. That was three and a half, four years ago. So ever since, we’ve been neck deep. We graduated pretty quickly from Excel to Google Sheets, and then quickly moved from Google Sheets into using things like Zapier, which is a platform we’ll talk a little bit more about, that’s pretty heavy in the SMB space for automation, and you know, dived in head first to APIs, and becoming API experts to help with data transformation and data movement back and forth between different platforms.

Guy Nadivi: Will, on this show we tend to focus on the impact of intelligent automation on enterprise IT, as I stated in my intro, and these are organizations with large scale operations that are digitally transforming their information infrastructure through automation. Your focus, though, being targeted a bit more on the SMB market, I’m curious, at that level, what drivers are used to justify automation projects?

Will Christensen: That’s a great question. The number one thing that I find, it’s kind of interesting, because you’d think that it was all about money and time, and, “What can we get there?” But I find that the number one thing is actually boredom. So the clients will come to me and say, “I am doing this thing and it is totally driving me insane.” And so there’s a lot of value they place on doing something that’s boring versus doing something that’s a little easier to understand. I’d say the second thing that I often see is the amount of impact that it can have on the bottom line of the business. So if it’s a report that they are preparing, and there’s a bunch of data sources, and it’s only happening once a month, they’ll look at it and say, “Okay, well if we had this report at our fingertips every day, what could that mean for the business?” And so that’s an exciting piece of what we do, and what gets it to that next level, because we’re able to make it so that that report that was taking three or four hours is now completely automated, and they can get access to that data in more realtime. So boredom, I see access to realtime information that gives them a competitive edge or allows them to make better business decisions, and then it gets into the more normal things you’d see like, “Okay, well how much time is this currently taking me? If I delegated this to an employee, it would take them X, Y, Z amount of time, and then they’re going to cost X, Y, Z. So what would it take to automate it?” And that’s where it goes. So it depends on the individual that I’m talking to and where they stand in the company, but I often see, especially if it’s a smaller business where it’s the owner of the company that’s actually handling whatever it is, the lower the level of the project, the higher the value they see in pushing it off their plate. I hope that answers your question a little bit.

Guy Nadivi: Yeah. That actually speaks to one of the universal drivers for automation, which is there are tasks people are doing that they shouldn’t be doing, that machines should do to free them up to do other things. And I think since the general perception out there is that automation is primarily taking place at the enterprise level, there are probably going to be a lot of people surprised to hear about its growing popularity for smaller organizations as well, even if it’s just to alleviate boredom. The SMB space, though, is not as resource rich as the enterprise. So how do smaller organizations tackle automation deployments differently than large enterprises?

Will Christensen: That’s a great question. So this is a good opportunity for me to describe a platform that we use a lot. It’s called Zapier. If you get to their website, zapier.com, “Zapier makes you happier.” That’s how you say it, so if you see that is that “Zapier,” that a lot of people will mix up the name, but Zapier’s entire goal was to create something that users large and small of organizations could get in and basically tackle their own automation. And so they tried to take it out of the hands of the developers and put it in the hands of the average individual who’s actually doing that work. And so inside a larger organization, you’ve got different individuals who are kind of that evangelist for automation, and those same individuals exist in the SMB companies, and given tools that take APIs or code and turn them into a visual language, something that someone who’s not a coder can handle, is really what puts it in the playbook for them. So just a dumb example, but if you’re getting emails, and they have attachments on them, and the attachments have different keywords, and you need to funnel those into different Dropbox folders or different Google Drive folders, that is a very simple task, using Zapier. So automation can be handled on a smaller scale because it’s very inexpensive to get involved and understand some of those things. And it’s creating new businesses like DataAutomation who focus on helping those companies take off and do what they need to.

Guy Nadivi: Okay. So tell us about some of the more interesting automation use cases you’ve worked on, and the quantitative impacts they’ve had.

Will Christensen: So it’s totally crazy in terms of some of the different things that we’ve done for different individuals. One company we worked on, they are a freelance network, so they’re called FreeeUp, and they help individuals get to kind of understanding how to get to the right freelancer in the Philippines. A great company to work with. They do a great job filtering. With FreeeUp, they had a process where they were cleaning out some old contacts, and we built a 32-step zap inside Zapier that literally sends an email to the individuals that are out there and says, “Hey, would you like to be on the freelance network? We’ve noticed you haven’t worked in a while.” And so Zapier was totally capable of not only integrating with their internal time tracking system with a little bit of help, we integrated with their internal API, Zapier can run code steps in JavaScript or Python, no problem, right in the middle of everything that’s there, and so we would trigger this off and send out this email, and based on what they clicked, basically we built an entire flow that just cleaned out that list of people, and that process was taking individuals there 20 to 30 hours a week, and we automated essentially the entire process. So really, really powerful in terms of what we were capable of doing there. We worked with another company called Nelbud. They’re a grease hood cleaning company. They do kitchen exhausts and restaurants. They’re out of Indiana, and they came to us with several different reports. They really made a focus the past several years trying to do better with their reporting, and the reason they wanted to report, do better with reporting, is they had several people who they’d mix something up or they’d do something wrong, and they didn’t know why they’d done something wrong. And so because of that, they were having pretty high turnover, because they’d get in and try to help people understand what they were doing wrong, but it wasn’t clear. Overall the quality of the jobs would go down, and that kind of thing. And so we developed a series of reports that would go in and allow them to grade different systems. We developed a Chrome extension that sits on top of their CRM, essentially, and we allowed them to grade all of their jobs. So that wasn’t something that’s built into the CRM, we needed to automate that process and allow them to put structured data around it, and it had some significant impacts. We started working with them back in 2016, and their turnover rate dropped more than 10 points over the course of those four years, because a lot, in part, because of the automations that we put in place that allowed the different individuals in the company to measure their performance. So when they did certain things inside the CRM, we built a dashboard or we facilitated the data transfer so that the dashboard could be created so they could track and see what was happening. They also had a report, this is just a standard example of hours saved. They had a report that was taking three to four hours once a week for essentially the right-hand person to the CEO, and he needed this report done once a week so that he could project revenue and understand where growth was happening, and it was just taking a ton of time. That’s actually how they found us, is they were trying to automate some of that using Zapier and some other systems, and we built them a script that’s still running today that goes in and extracts this information from their CRM, puts it in a digestible format that works really well for their business, and pushes it into Domo. And so three to four hours a week in perpetuity is what that thing was worth in terms of the money or dollars saved. And so that individual is pretty high level in their company, and you know, thousands of dollars a year that they’ve saved. And not to mention all of the uptick in their ability to do that. So those are just some examples that I’ve come across of different things that I’ve helped automate in the SMB space.

Guy Nadivi: When you’re tackling the automation of manual processes, like the ones you just described, what kind of questions do you start with when you’re talking to your customers? And what if those are questions that they can’t answer?

Will Christensen: Yup. That’s a fantastic question. I always ask them three basic questions, and I say three, and then I always add a fourth one on there. So let me go with four. Four basic questions. “Where is the data now? Where does the data need to go? And what needs to happen to the data in between?” Okay, so we understand the process, and you could insert whatever word you want. When I say “data,” you could say, “Where’s the report now?” Or, “Okay, the output here is a report. Where is the data from the report now? Where does it need to go?” “It needs to go into this report.” “What needs to happen to it in between?” And then the last question I ask is, “What triggers the process to start?” And some people, they haven’t done enough thinking about this piece or what’s going on there, that they’ve even realized what’s there. So if they can’t answer those questions, I often will throw out and say, “You know what? If you could wave a magic wand,” I don’t know what it is about that statement or that phrase, but people get really excited about magic wands. And I ask them, “If you could wave a magic wand, what would be the outcome here?” And generally speaking, if I can get them to answer that question, then I can start to work backwards to understand, “Okay, magic wand equaled this. That means the data’s here,” and you can kind of start getting at some of those deeper, finer points.

Guy Nadivi: I’m curious, listening to you talk about those things, about what single metric other than ROI best captures the effectiveness of the kind of automation you deploy for those organizations?

Will Christensen: So the best metric that I’ve found is generally the hours saved, and they can generally times that by the number of times the automation runs. So for example, I work with an e-commerce company, and they are able to submit an invoice to their manufacturer in exchange for a reimbursement on everything they sell. It’s like a manufacturer discount program, and that invoice was not something they had automatically. In fact, they were copying and pasting that into an Excel template, creating a PDF, and then sending it out. We created a link between their ERP system that brought in all of their order data, and then formulas that would create a PDF or a template, and then we’d automatically spit that out. And then we upgraded that a step further, and we just gave the code access to generate that PDF on the fly and input it into the system. And so that one, the way that … To go back to your question, “What is that metric?” When we were evaluating, “Should we automate this? Is this worth the amount of time and investment?” The thing that he looked at was time. All about time, for putting it there. Does that answer the question?

Guy Nadivi: Yeah. Yeah, absolutely. Time is money, so that’s a big driver for a lot of automation projects in general. Now, you spoke about the impact of the phrase “magic wand” on your customers, and sometimes the term “automation” can have an interesting impact on people’s expectations. So I’m wondering, Will, what are some of the more unrealistic expectations you’ve encountered in the SMB space about deploying automation?

Will Christensen: So I would say most of the time … It’s interesting that you talk about unrealistic expectations, because in the SMB space, what I’ve discovered is that most people have tried to automate already. They heard from their brothers, sisters, boss, or whatever, they heard through the grapevine that you could do this automatically, and they do the first thing everyone thinks to do, and they go to Google and start Googling around to figure out what they can automate. And a lot of times they actually get pretty disgruntled, and so their expectations are very low already in terms of what they’re tackling, because they’ve tried. They’ve spent an afternoon trying to push that data back and forth and failed because they didn’t have the right resources. And so they get really frustrated. And so oftentimes in the SMB space, I have to help them bring those expectations back to reality, which is that, “This is possible with a little bit of extra automation muscle.” So in the SMB space, I find the expectations are actually lower, not higher. I have run across a couple where they come up and they’ll ask something like, “Okay, I need to be able to get my proposal to go through the system, and when it gets down here, I need the system to analyze whether or not this is a good deal or not.” And then you start to ask them questions about, “Well, what is a good deal?” And they start to talk about like, “Well, first I have to look at the client and decide whether or not they’ve paid me in the past,” which I can totally automate that. I can look up to see if they’ve paid in the past. And then they’re like, “And if they’ve been rude to me on a phone call, I’d probably up the bid a little bit. And if they’ve done this …” And there’s all sorts of data that’s just, it’s not gathered in a place that’s easy to extract, and that becomes unrealistic, right? If you’re starting to put things on conjecture or human intuition, really, really difficult to put that in there. Now, obviously there’s AI and things like that that are coming out, that are handling more and more of that, but there’s a lot of things that are difficult there. Last thing I’ll mention in unrealistic expectations is I often get people that want to automate things that are inside a closed system, so like on a desktop, not in the cloud. And anytime you’re trying to automate something on a desktop, there’s a lot of good programs out there that can do mouse clicks and things like that. That can be very difficult. So I encounter that a lot and have to either advise them to move to an online system … Very rarely are we able to make something work that’s on a closed system like that. It has to be more of an online thing.

Guy Nadivi: Interesting. Will, you gave a presentation at an Amazon sellers trade show last year about how to decide if a process should be automated or not, and I’m curious if you can share with our audience some of the finer points of your litmus test.

Will Christensen: Yup, absolutely. So this is something that I’ve developed over the past three or four years as we’ve taken on different projects, and we’ve done our fair share of, “Oops, we shouldn’t have automated that,” and our fair share of, “Wow, that was very effective for the client and for us.” And so as we’ve gone in and pushed on that, we’ve discovered this litmus test that I shared at that Amazon sellers show, at the Prosper show last year, and the first piece of the litmus test is, make sure you’ve done that thing five times manually. And I don’t even know if I shared that at the Prosper show, because I think that’s something that’s come up since then, but make sure that you’ve done your manual process 5 times manually, and 5 times is the bare minimum. Do it 10 times, do it 20 times manually. It depends on how long it takes that process to take, right? But do it manually first before you attempt to automate, because you’re going to discover what fields you need, what the data needs to look like, what the end goal is, the finer points of what’s there. There’s some real power in doing it manually a couple of times, at least five times, before you start automating. Then the second thing that I tell people is, after you’ve done that, you have to kind of identify or figure out what should be automated and what shouldn’t be automated. And so I’ve broken that down into a couple of time tests. So what I tell people is, “Hey, get out a sticky note and anything that matches this, write it down on a sticky note, and start putting a ticker next to that sticky note to see what’s going on.” So if it takes you more than 15 minutes a day, more than an hour a week, or more than an hour a month, you should be writing it down on that sticky note and putting a tally mark next to it for every time it happens, and give yourself some massaging on how long that thing takes. So if it’s a 15 minute task, you put that ticker next to it, and you’re going to pretty quickly find out how much time you’re putting into it. And then the last piece of the litmus test, after you’ve done it five times manually, after you’ve written it down and it’s made it to that sticky note and it’s equaling more time than that, I say if you have an intern, someone who’s just out of college who has a basic understanding of Google Sheets or Excel, a basic understanding, so not crazy in formulas, maybe they know how to write a VLOOKUP, maybe not, but at least they know how to move things around in different sheets, they’re not completely inept there. A basic understanding of email, right? So somebody who can make their way around email, and then a Word document. So just a basic intern. If you could teach a basic intern how to do this task in less than 15 minutes, or in less time than it takes you to actually do it yourself, it’s probably time to consider automation. I had to find a litmus test that wasn’t so technical that people couldn’t do it, but was also indicative of the simplicity needed to hand something to a robot. And so that’s kind of the process or litmus test that I give to my clients to decide whether or not it’s time to automate.

Guy Nadivi: Now, speaking of robots, “robophobia” is the term we use at Intelligent Automation Radio to describe people’s fear of automation, and particularly as it pertains to the impact it might have on the nature of their job or even their employment. How do you assuage the robophobia concerns at your SMB customers?

Will Christensen: So that’s a fantastic question. It’s something that comes up often. So what I’ve discovered is that from the top of the organization, automation is a must. Yeah, we definitely need to do that. But if you go all the way to the bottom of the totem pole, remember where I started, right? I was at the bottom of that totem pole, doing that 16 hours a week, and I was automating my own process. At the time, I didn’t even consider the fact that I might be automating away 16 hours of my job. What was I going to do next? I mean, I’m a very forward person and so I was like, “Well, I’ll just figure something else out to do that helps the company.” For those individuals that are in those roles, you kind of have to help them recognize that if they can take pieces of the work they’re doing and automate them to the point where they’re no longer pulling a lever for 15 hours a day or pulling a lever for 20% of their day, they get some real opportunity to take that to the next level and give back to the company. And when they give back to the company, the company can grow, and there are going to be new opportunities for them to automate. And so this is where I have to do some culture shifting. I do a process where I call it “automation interviews”. It starts with an automation audit, where I come out to a company and they look at everything that’s going on in the company. I document processes, I point out things that I think could be automated first. And after I do that audit, I recommend doing automation interviews where I actually get on the phone with individuals who are actually doing the work. So my audit was focusing more on leadership, and I do interview some of the individuals who are doing the work, but it’s more focused on the leadership aspect to kind of show overall impact that’s going to happen. Then I get in and I meet with the individuals who are actually doing the work, and my goal in that interview is to make a culture shift. So the first thing I do is open their mind to what’s possible, but first I have to gain their trust. So I gain their trust and help them recognize, “I’ve done manual things too. I don’t like it either. It’s difficult, but we’re going to do this together. We’re going to figure this out.” Then after I’ve gained their trust, I open their mind and show them, “Hey, the world of automation is real. You’ve tried to automate. You’ve failed. It was frustrating. Let me show you how we can get around that.” And then after I’ve started to get their hopes up in terms of what’s possible, I actually roll up my sleeves and we automate something. I’m looking for an easy win of some kind to actually open up their mind and automate some piece of work. And sometimes I save people 15 minutes a week. Sometimes I save people two or three hours a week in that half an hour process of automating. But after they’ve tasted robophobia, after they’ve actually eaten some of the pie, it’s so much easier to move forward, because they’re like, “Oh man, this is way better than doing it manually. I was so scared of this. Why was I scared of this?” So that’s kind of the process that I go through to assuage robophobia and help them through that. Help them through the concern, and once they see that, and taste the pie and look at it, they’re like, “Oh, cool. This opens me up to do X, Y, Z, and is a good opportunity for me to go and ask for a raise.”

Guy Nadivi: I think that’ll be very interesting for some of the enterprise executives listening to the show, to hear your perspective on how to change the culture in that regard and assuage that fear. And so, Will, to close out, for the CIOs, CTOs and other IT executives listening in, what is the one big must-have piece of advice that you’d like them to take away from our discussion with regards to deploying automation at their organizations?

Will Christensen: Absolutely. The number one thing, #1 piece of advice that I would give to a CIO or a CTO or IT executive that’s listening to this podcast would be, when you’re considering automation for your employees, remember that although they fill a function inside your business that feels like a cog in the machine, they’re emotional, and because they’re emotional, they are going to react to the way that automation is presented very differently than obviously a computer would. And so because of that, you kind of have to win them over first. I’ve seen a lot of automation start at the top and die at the bottom, and the individuals who take it on and do what needs to be done, and actually can successfully get there, are the ones who are able to help those guys who are actually doing the work get in there, and that includes sit down and interview. Go do some of that work. If you haven’t been the one to copy and paste for a couple of hours in a while, roll up your sleeves, get down there, sit down with the interns and do what they’re doing. And once you’ve done it 5 times manually, you’re going to start to understand that some of the automation that you’re feeding from the top down is totally ineffective. It doesn’t handle all of the use cases that are there. So that’s probably the number one piece of advice I would give, is when you’re automating, make sure to go to the bottom of the totem pole and have some one-on-ones, if not sessions where you actually do some of the manual work, to understand what it’s like to be in those shoes so that your automation is something that’s viable and can be used and will actually shift culture and change in the long term.

Guy Nadivi: Excellent advice. All right. It looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Will, we’ve really enjoyed speaking with you. It’s been great having you on the podcast to learn about a whole ‘nother market for automation that much of our audience might not know much about. Thank you so much for joining us today.

Will Christensen: Yep. Glad to be here. Excited to share a little bit of a different perspective with you and your listeners.

Guy Nadivi: Will Christensen, cofounder of DataAutomation, an automation service provider. Thank you for listening everyone, and remember: Don’t hesitate, automate.



Will Christensen

Co-Founder of DataAutomation. 

With over a decade of business development experience, it’s safe to say Will Christensen has an elevated passion for fulfilling what the end user desires and efficiently working towards faster iterations. Considered by some to be the “Tony Stark of Software,” he enjoys tinkering with cutting-edge technology, apps and systems, and loves to create innovative solutions for businesses and individual clients.He is the co-founder of DataAutomation, which customizes both automation and integration processes for e-commerce sellers. Will also heads up business development for RoundSphere, a tech incubator dedicated to developing new opportunities through software. Prior to his present endeavors Will has garnered extensive proficiency in advertising, media management, and product development.  

Will can be reached at:

LinkedIn:                       https://www.linkedin.com/in/william-christensen-91074a11/  

DataAutomation:        https://dataautomation.com/  

Quotes

“It's interesting that you talk about unrealistic expectations, because in the SMB space, what I've discovered is that most people have tried to automate already. They heard from their brothers, sisters, boss, or whatever, they heard through the grapevine that you could do this automatically, and they do the first thing everyone thinks to do, and they go to Google and start Googling around to figure out what they can automate.” 

"There's some real power in doing it manually a couple of times, at least five times, before you start automating." 

“I've seen a lot of automation start at the top and die at the bottom, and the individuals who take it on and do what needs to be done, and actually can successfully get there, are the ones who are able to help those guys who are actually doing the work get in there, and that includes sit down and interview. Go do some of that work. If you haven't been the one to copy and paste for a couple of hours in a while, roll up your sleeves, get down there, sit down with the interns and do what they're doing.” 

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.

GET STARTED WITH AYEHU INTELLIGENT AUTOMATION & ORCHESTRATION  PLATFORM:

News

Ayehu NG Trial is Now Available
SRI International and Ayehu Team Up on Artificial Intelligence Innovation to Deliver Enterprise Intelligent Process Automation
Ayehu Launches Global Partner Program to Support Increasing Demand for Intelligent Automation
Ayehu wins Stevie award in 2018 international Business Award
Ayehu Automation Academy is Now Available

Links

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
Episode #31: Could Implementing New Learning Models Be Key To Sustaining Competitive Advantages Generated By Digital Transformation?
Episode #32: How To Upscale Automation, And Leave Your Competition Behind
Episode #33: How To Upscale Automation, And Leave Your Competition Behind

Follow us on social media

Twitter: twitter.com/ayehu_eyeshare

LinkedIn: linkedin.com/company/ayehu-software-technologies-ltd-/

Facebook: facebook.com/ayehu

YouTube: https://www.youtube.com/user/ayehusoftware

Disclaimer Note

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