ITOps: Best practices to improve performance and service quality

ITOps best practicesThere’s no doubt about it. Intelligent automation is the biggest driver for increasing the overall performance of ITOps and service quality for businesses today. It allows IT management and personnel to streamline their workflows by automating the time consuming day to day tasks that bog them down, allowing technology to do the heavy lifting so they can focus on more important business-critical issues.

Intelligent automation can be applied to almost any pain point your organization may face, from frequent password resets to service restarts to disk space cleanups and much, much more. The key is to begin with a few small things so that the value can be easily identified and then work up to include more complex projects and workflows to utilize automation to its fullest potential.

Best Practices for Systems and IT Operations Managers:

As with anything else in business, there are certain “best practices” that have been established and should be implemented to achieve optimum results with automation. Here is a brief list of guidelines for system and ITOps managers to follow:

  • Pick one or two pain points with value. What simple processes or small tasks are important to your organization but are bogging your team down? Pick points that you can quickly and easily measure the value of once you’re up and running.
  • Once you’ve got your list of pain points, it’s time to sell the value of your automation project to the key decision makers within the organization. Go over the benefits in detail and be prepared to counter any objections and show evidence of projected ROI (try our free ROI calculator). The more prepared you are ahead of time, the better your chances of winning over the “powers that be”.
  • Carefully evaluate available intelligent automation tools to help you choose the right product and then learn as much as you can about the one you choose so that you can truly convey the benefits that it will have for your business operations.
  • Foster IT automation skills within your team. Make it clear to IT personnel that automation isn’t something to fear. That it’s not there to eliminate their jobs, but rather to make them more efficient and productive, and to provide the opportunity to enhance their skills, become more marketable and achieve more growth in their careers.
  • Encourage communication between IT teams and business people. Devops and automation go hand in hand, with the shared goal of bridging the gap between IT personnel and those on the operational end of the technology. For optimum results, a solid relationship built on trust and open communication should be developed and fostered.
  • Develop key performance indicators and measure results. Once you’re up and running with automation, it’s critical that progress is continuously monitored, measured, analyzed and modified accordingly. Develop a list of which performance indicators are most important to your organization and then measure regularly to ensure optimum results.

In summary, organizations that follow these practices will not only increase agility and reliability, but they will also have a more productive, happier staff. ITOps teams that know how to utilize these tools will have more opportunities for growth, both within the workplace and beyond, as demand for these skills continues to grow.

In the end, it’s a triple win: employees, your business and your customers all benefit in multiple ways through automation. So, the question then becomes not “should you automate”, but rather, “why haven’t you started yet?”

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The Rise of Artificially Intelligent Service Management (AISM)

It’s been said that the best way to serve customers is to anticipate their needs, whether it’s a restaurant concierge offering to walk patrons to their vehicles with an umbrella overhead on rainy evenings or rolling out an update on a software product. The same concept can be applied in the IT realm, specifically in IT service management (ITSM).

The fact is, with today’s technology, it’s entirely possible to predict that certain situations will occur, from simple password reset requests to servers crashing. It’s not really a matter of if these things will happen, but rather when. And if you know what’s coming, you can be prepared to respond and, in many cases, even head problems off at the pass.

That’s where artificial intelligence comes into play. Thanks to AI and machine learning technologies, ITSM professionals can now predict potential problems faster and with a much higher degree of accuracy. As a result, the end user (or “customer”) enjoys a much more positive experience. In other words, everybody wins.

What is Artificially Intelligent Service Management?

The core principles of ITSM remain sound. The introduction of AI into the mix doesn’t change this. Instead, it enhances it. AISM simply takes the fundamental concepts and processes of ITSM – incident response, service request management, etc. – and leverages newer and better technologies to make them even more effective. In the context of IT service management, AI can be applied to improve, simulate and/or replace the work of a human agent.

You may be asking yourself, “Isn’t this really just automation?” The answer isn’t necessarily cut and dry. The truth is, we’ve been automating processes and workflows for decades, and ITSM is no stranger to this technology. The difference is that with AI, these processes and workflows become more intelligent and independent. Rather than just carrying out predefined or scripted instructions, AI is capable of identifying and carrying out required actions all on its own.

How does AISM work?

Now, let’s take a look at how AI can enhance the execution of ITSM activities.

Support Request Management

The basics of ITSM: an end user needs assistance. They either pick up the phone to call the help desk, send an email request, submit a support ticket or browse the self-service options (if available). The steps necessary to fulfill that incoming request are then followed and the user receives his or her desired outcome. The problem is, that outcome could potentially take hours, days, weeks or even longer.

Now, let’s look at that scenario with AISM at the helm. The end user initiates contact and immediately receives two-way support from an intelligent bot. They request what they need and the bot – relying on underlying technologies of machine learning, deep learning, neural networks and natural language processing – understands the request and responds accordingly. Rather than waiting for a human to take action, AISM can produce results for the end user within seconds.

Incident Management

The ability to react, respond to and correct an incident is one of the most basic components of ITSM. Traditionally, a form would be filled out. Perhaps the analyst might do a little research. Ultimately, the task is assigned to a team. There it might sit untouched for a while before it is either rejected, resolved or possibly even assigned to another team altogether. In the end, the incident is resolved, but after much back and forth and passing of the torch.

Enter AISM. The end user reports a problem via his or her self-service portal and an incident is immediately created. Thanks to artificial intelligence, however, that same end user may instantly be prompted with various suggestions that are pulled from the underlying knowledge base. This may result in resolution right away.

If not, it is turned over to a support analyst who is automatically provided with suggested resolution methods. The AI can even advise who the incident should be assigned to, what relevant implications may exist, the scope of the situation and more.

Problem Management

In a traditional ITSM setting, problem management would often involve a person taking the time to review prior incident patterns and trends and develop possible resolutions. Along the way, however, many twists, turns, delays and bottlenecks exist. For instance, let’s say a support agent grows weary of addressing the same incidents over and over. The problem may be investigated further. Perhaps some knowledge may be created and a change is even identified. But, given the chaotic nature of the ITSM environment, time passes and nothing really gets done.

Now, take that same scenario in the context of AISM. Instead of a frustrated human agent taking the initiative to identify and resolve problems, machine learning technology continuously scans patterns of data to pinpoint and present potential issues that should be investigated. What’s more, thanks to data processing and learning across multiple patterns of work, AI is even capable of proposing a solution, backed by data-driven risk and impact analyses. In other words, it takes the guess-work out of decisions.

AISM – From Reactive to Proactive and Beyond

Getting back to our original point – that the best customer experiences are anticipatory in nature – AISM enhances service management by facilitating the shift from reactive (meeting needs when they occur) to proactive (predicting and preventing issues from happening in the first place). There are three key ways AISM can do this:

  • Guidance – The end user has a need and AISM uses a connection with endpoint tools to identify and make suggestions based on that need.
  • Learning – Building a knowledge base used to be a hassle. Not with AISM. Thanks to machine learning and AI tracking systems, the knowledge base can naturally grow based on issues encountered over time.
  • Strategy – AISM is capable of identifying and recommending both changes to existing core services as well as new innovations to improve for the future.

Conclusion

As you can see, AISM follows many of the same principles, processes and best practices of ITSM. It’s just faster and more accurate. And with AI being leveraged to intelligently automate complex tasks at just about every operations level, IT professionals will be freed up to spend more time innovating and evolving to help achieve business goals.

Buckle up folks, because AISM is poised to be a true game-changer.

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The real secret to success for modern businesses

Intelligent automation has become one of the most talked about areas of enterprise technology over the past several years. The virtual workforce which was once just a concept has quickly become an integral component of modern business structure.

The technologies behind intelligent automation – AI and machine learning – have already begun delivering significant returns on investment for forward-thinking organizations that have taken a chance and chosen machine over outsourcing. Instead, those companies that want to remain a step ahead of the competition, operating efficiently and at maximum productivity, have found a way to complement and augment their human workforce with a virtual one.

On the flip side, employees that are wise enough to recognize the value that intelligent automation brings to their lives and to the success of their organization are thriving in this melting pot environment. They are freed up to focus their expertise on more complex and challenging projects while their robotic counterparts handle the day-to-day menial work and repetitive, manual administrative tasks on their behalf.

Widespread adoption of intelligent automation is also bringing to fruition an entire new class of jobs, just as experts predicted it would. Those roles that are being eliminated are making way for newer opportunities to reskill existing workers. After all, someone has to oversee the automation, not to mention identify additional entry points, plan for future deployments, etc. There’s plenty of room for robots and humans to work side by side in the enterprise of the future.

For organizations still on the fence, it’s important to realize that intelligent automation is the fastest and easiest way to digitize, something that’s going to be inevitable for success in tomorrow’s landscape. And automation is no longer something that is simply governed by IT. Today, this technology is capable of assisting with everything from employee onboarding to compliance and cybersecurity. To be fully utilized, automation must be viewed not as software, but as a capability across the entire organization.

Just as the industrial revolution redefined the way businesses operated a hundred years ago, the digital revolution is now upon us, offering a similar transformation. In many ways, this is a defining moment for business leaders and key decision makers. The way humans and technology interact is evolving yet again, facilitating far more than just quick wins, but sustainable and highly scalable success. In some instances, intelligent automation is enabling firms to bring offshore resources back in-house.

The key is striking the right balance between the human and virtual workforce with the goal of maximizing the use of technology while also focusing on retraining and redeployment of human resources. Once that balance is achieved, the sky is the limit for the organization.

If you’d like to see what intelligent automation can do for your business, simply request a free product demo and we’ll show you around! Or better yet, experience it for yourself with a free 30-day trial.

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7 Steps for Getting Started with AIOps

Today’s IT teams are dealing with a growing mountain of data. What’s more, they’re finding themselves having to use a multitude of tools in order to monitor and manage that data. In situations of technical outages, this can make it incredibly difficult and time-intensive to identify and resolve underlying issues. Anyone in business knows that even just a tiny amount of down-time can have a serious and costly impact on the bottom line. And it’s the IT team that bears the brunt of the burden.

Take, for example, the two largest supermarket chains in Australia. Last year, both experienced severe technical issues which forced them to shut down several stores while they worked on fixing the problem. Not only did those companies lose revenue during the shutdown, but they also suffered a serious blow to their reputation. In other words, customers were not happy.

To better and more quickly identify, resolve and prevent outages and other problems, organizations are turning to artificial intelligence for IT operations (AIOps) – the long-term impact of which will be nothing short of transformational.

What is AIOps

In simplest of terms, AIOps combines data science and machine learning functionality to enhance and/or replace the majority of IT operations functions. This includes performance and availability monitoring, event analysis and correlation, ITSM and automation. To put it even more simply, AIOps platforms gather and analyze all of the data produced by IT to extract what’s of value and present meaningful insights.

How to Get Started with AIOps

Step 1: Don’t put it on the back burner.

If you really want to reap the benefits of AI for your IT operations, the time to jump on the AIOps bandwagon is now. Don’t make this an afterthought or push it out as some far-off future initiative. Even if the actual deployment isn’t imminent, start preparing yourself and others within your organization by becoming familiar with artificial intelligence and machine learning capabilities today. This way, in the event that priorities shift and you need to implement sooner, you’ll already be a few steps ahead of the game.

Step 2: Be careful when choosing your initial test case.

The concept of AIOps at scale may seem overwhelming, but keep in mind that truly transformative initiatives almost always start small. Focus first on capturing knowledge, testing frequently and iterating as needed. You don’t need to be an expert right out of the gate, and not every project you spearhead will be a resounding success. Just be mindful of what you’re starting with and work your way up from there.

Step 3: Work on developing and demonstrating your proficiency.

If you are leading the AIOps charge in your organization, you’ll inevitably be the go-to subject matter expert, at least initially. It will be up to you to communicate and convey the value of the technology to your colleagues and others in leadership. Wear your role with pride and start assembling a team of others who can champion the cause alongside you. Start by identifying gaps that exist in skills and experience, and then create a plan to address those gaps together.

Step 4: Don’t be afraid to experiment.

There are already many AIOps platforms on the market that are incredibly complex and subsequently cost-prohibitive. As with any tech product or solution, it’s wise do experiment and test the waters. Keep in mind that more features doesn’t necessarily equate to a better product. Your organization may not need all those bells and whistles. If possible, take advantage of product demos and free trials. This will enable you to evaluate AIOps uses and applications specific to your business needs without having to invest too heavily or commit to one particular solution.  

Step 5: Expand your vision beyond the IT department.

Data management is a massive component of AIOps. Take a step back and examine your organization. Chances are very high that your existing teams are already skilled in this area and that there are data and analytics tools already present within your organization. Resist the urge to reinvent the wheel and be willing to expand your vision to look beyond the IT department. It could save you tremendous time, effort and money.

Step 6: Standardize whenever possible and modernize wherever it makes sense.

You can prepare your existing infrastructure so that it is capable of supporting an AIOps implementation in the future by developing a consistent automation architecture, immutable infrastructure patterns and infrastructure as code (IaC).

Step 7: Consider build-vs-buy.

Understand that there are a number of variables involved in making a shift to AIOps. Likewise, the platforms available on the market today will continue to evolve, as will the infrastructure and applications for which you are responsible currently. Be mindful of this as you weigh whether to purchase a solution or build one of your own. Ideally, the best answer will likely be a combination of the two, so be prepared to figure out which approach best applies where and by how much.

Over the past few years, AIOps has developed from an emerging category to an IT necessity. Successful companies are beginning to leverage AIOps to automate and improve IT operations by applying machine learning to their data. Furthermore, forward-thinking organizations will use AIOps to draw valuable insights from their IT data that will help drive strategic business decisions.

If AIOps is on your to-do list (and it certainly should be), the steps outlined above should help you to, at the very least, lay the groundwork so that when the time comes to implement, the process will go faster and much more smoothly.

Why wait? Experience the next generation of IT automation, powered by machine learning and artificial intelligence and get started on the fast track to successful AIOps deployment. Start your free 30 day trial of Ayehu today!

The 7 Secrets of Effective Digital Transformation

If you’ve ever read the book The 7 Habits of Highly Effective People by Stephen Covey, you’re familiar with the concept of “beginning with the end in mind.” Putting that into context in terms of digital transformation means organizations must determine what their goals are before they begin adopting a ton of shiny new technologies. Unfortunately, many otherwise intelligent business leaders make the mistake of focusing so much on technological innovation that they miss the mark altogether.

This is not to say that technology isn’t a key driver of digital transformation. The problem often lies in a misunderstanding of what digital transformation actually is. According to a recent report by Altimeter, despite the fact that a growing number of enterprises are investing in innovative technologies, the majority of them are still lacking in terms of meeting customer expectations due in large part to a lack of digital literacy. The report also concludes that the main obstacles to achieving the solidarity and collaboration necessary for true, effective and lasting digital change are ego, politics and fear.

When an organization begins with a tech-first approach, it risks missing the point about what digital transformation is truly all about. In many instances, company leaders – CIOs in particular – fall into the trap of attempting to build new technology atop an old and crumbling legacy foundation. There’s an erroneous belief that all it takes to keep up with disruption is continuously adopting the latest and greatest apps and programs. New tech is great, but it must be adopted as a component of the digital transformation process, rather than its fundamental basis.

To demystify the whole digital transformation concept and improve your chances of success, here are a few expert tips to keep in mind.

The human element should be front and center.

Yes, the term is “digital” transformation, but in reality, it’s more about human transformation than anything else. That’s really what’s at the heart of any successful change. Technology is essential, yes, but it’s equally, if not more important that your people are all on the same page and moving together at the right speed. One of the biggest challenges to transforming a business is bringing its workforce up to speed, in particular, getting them current with the skills needed to facilitate change.

Experts unilaterally agree that the key to achieving true digital transformation is having a team of individuals who are curious, motivated by and passionate about the mission. Only then can you successfully usher in the innovative technologies you need to move forward.

A great example of this is Pitney Bowes. Several years ago, the company began initiating a shift to align itself with the changing world of tech. Specifically, they focused on evolving in 10 key areas such as machine learning, analytics, mobile, SaaS and APIs. But while leadership recognized the critical need for a strong technical strategy, they also prioritized the development and implementation of a solid people strategy as well.

The company organized curriculum for each of the 10 key areas of disruption and every one of the 1,200 employees was tasked with immersing themselves in one of those 10 topic areas for a period of one full year. The results have been beneficial to both sides – the company, by enhancing its workforce, and the employees, who have enriched their skills and improved their personal value proposition. Additionally, with staffers becoming subject matter experts in their chosen topics and subsequently collaborating together, many new and valuable relationships have been forged. This is advantageous to everyone involved.

Take the time to really understand your customers.

Ask any business leader what they believe the biggest driver of digital transformation is and they’ll probably cite the evolving behaviors and preferences of their clientele. Yet, according to the Altimeter report, a remarkable few (less than half) actually bother to truly understand their digital customers.

The few that are actually getting it right have done so by taking an outside-in approach. In other words, they take the time to determine what’s missing or broken that can solve a need and then focus their efforts on doing just that, tying in key performance indicators (KPIs) and ROI to demonstrate success. Rather than looking at internal processes, these innovators examine the customer experience first to identify opportunities to add value.

The key takeaway? If you aren’t meeting what your customers want or need, your efforts to achieve digital transformation will inevitably fall short and you will risk being left behind. The best technology, the best policies and procedures, the best laid plans – none of that will matter if the end result doesn’t make the lives of your clientele easier. That’s the end result that should be your focus from day one.

Establish new teams.

Spearheading digital transformation shouldn’t be a side project. If you want it done right, you need to have a team of individuals who are 100% dedicated to the cause. Teams should be made up of various people with different strengths and diverse backgrounds. For instance, you might have a project manager, a lead developer and someone who is focused on the customer experience. You could then supplement this with members from other roles, such as QA, development, ops and finance.

When an idea for a new initiative arises, the team’s job should be bringing it to fruition – at least to some degree – as quickly as possible. It’s not about achieving perfection right away. Digital transformation involves evolution, which means your team should be ready to go through a cycle of development – try things out, assess how they work and then adapt and improve accordingly. This agile methodology may require a paradigm shift, which is why it’s so important to have a dedicated team.

Cultivate collaboration as you deploy technology.

As mentioned, digital transformation isn’t entirely about technology. Yes, technology is a critical component, but it takes people to really achieve successful change, and that requires ongoing collaboration. Trailblazing ideas, sharing best practices, building a community – these things drive innovation and continuous improvement.

Use Pitney Bowes as an example once again. While they were designing their curricula around their 10 targeted technology areas, leadership also hosted global innovation roundtables to enhance collaboration efforts. As a result, they were able to identify cases in which there were common problems with their integration, delivery and operational practices. This enabled a fast and effective resolution across the board. Furthermore, because of the improved collaboration, workers acknowledged feeling much more engaged, as opposed to being just another “cog in the wheel.”

Don’t give in to the resistance.

It’s human nature to fear change, and that fear often manifests itself as resistance amongst workers. Logically speaking, the larger the enterprise, the greater the push back is likely to be. If you want to successfully shift to a digital ecosystem, you simply cannot let the naysayers get you down.

That’s not to say you should steamroll over them and ignore their concern. It’s more about your approach. Over communication and clear articulation, not just about what is happening, but how and most importantly, why, is key. It’s also important to develop a group of early adopters and innovators – those who embrace the proposed changes, as they can become your champions.

At the end of the day, digital transformation is really about people transformation.

Think like a startup.

As organizations become larger, greater divides between various groups and departments begin to occur. This results in silos of information, which can hinder communication and the ability to collaborate effectively.

To avoid this, try to adopt more of a startup mentality – one that focuses on operating nimbly and making sure that projects are being carried out in the correct way. Be cognizant of any walls and barriers that exist and focus on eliminating those and encouraging unilateral communication across the board. Encourage teams, departments and divisions to work closely together with a goal of making strategic decisions more quickly and rolling out smaller changes faster.

Take a bottoms up approach.

According to the aforementioned Altimeter survey, only 40% of the companies polled say their digital transformation initiative is overseen by an executive-mandated steering committee. Getting buy-in from the C-suite is certainly important, but how you go about doing so can make all the difference in the world.

Many organizations have had tremendous success by flipping the typical top-down narrative to more of a bottoms up approach. In other words, they focus on obtaining buy-in from all levels of hierarchy within, bringing together a diverse group of workers to collaborate together to create a digital transformation strategy.

This provides the opportunity to go through checks and balances to determine what makes the most sense and is directionally appropriate. Only when every ‘I’ is dotted and every ‘T’ crossed is the strategy presented to the C-suite for approval.

Conclusion

Is technology an important part of digital transformation? Of course. But if that’s all you’re focused on, you will inevitably come up short. Instead, focus on the people and policies that matter most, get all your ducks in a row and start with the end in mind. Do so and your organization can be counted among the success stories.

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5 Tips for Managing the Changes of Digital Transformation

Today’s business leaders are focused on digital transformation. What they often fail to consider is how much transformations like these alter the very essence of their organization. In some instances, a company might modify its entire business offering after going through a successful transformation. This may require a complete realignment of how you approach the market, how you use technology, how you engage your customers and how your employees see their roles as well as the business as a whole.

At the end of the day, change is about speed. It’s about competitiveness. It’s about innovation. To be successful in today’s digital environment, organizations must be agile and ever-evolving. The problem is, change isn’t always easy – especially when it comes to people. Getting your employees on board requires strong, deliberate leadership. This is where change management comes into play. To follow are five truths that change leaders must embrace in order to be successful.

Start with a vision.

You cannot drive change unless and until you have a clear and accurate picture of what you’re trying to achieve. When you develop a vision of the end-state, it becomes easier to understand the ‘why’ of what you’re doing, and when you can get others to appreciate this ‘why,’ you’ll get buy-in. Just be careful not to be too rigid with your vision. Make sure you leave room for adjustments along the way. 

Involve the stakeholders.

Remember, change management is really about people, and these people will either resist or embrace the proposed changes. To mitigate detractors and maximize drivers, identify who will be most affected by the changes you are proposing and then get them involved in the process as early as possible. If you can make them feel a sense of control over what’s happening, they’re more likely to become advocates for your cause.

Listen.

The nature of digital transformation is that it is fluid. You will inevitably reach points at which you must pivot in order to progress. There may also be a number of tradeoffs or roadblocks you haven’t yet considered. Listening to those most closely affected can provide insight as to what courses may need to be corrected. Additionally, giving people a voice can help get them on board. Invite people to share their questions, concerns and feedback.

Communicate, communicate, communicate.

Having a clear vision of your digital transformation won’t do much good unless you share that vision with everyone else. Being honest, forthcoming and transparent right from the start can do wonders for overcoming employees’ fear of change. Use as many tools as are available to you, from email and newsletters to intranet sites, videoconferencing, town halls and more. Do everything you can to instill that vision in your employees.

Learn as you go.

The fifth rule for change leaders is to recognize that as you push forward toward your goal, new and unexpected challenges can and will arise. Your success in achieving digital transformation will depend largely on your ability to adjust to those challenges. Be prepared to regularly reevaluate to make sure you’re still on the right track and course-correct as needed. Being agile is what will ultimately get you to your end game.

Of course, having the right tools in your corner can also help make managing change easier. Ayehu supports digital transformation through seamless integrations, rapid adoption and even faster time-to-value. Click here to take Ayehu for a test drive for 30 days.  

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Smart CIOs know AIOps is the key to maximizing efficiency

In today’s volatile marketplace, businesses in every industry are focusing on cutting costs. Unfortunately, some folks still view IT as an expense and an area in which the metaphorical belt can be tightened. What they don’t realize, and what an increasing number of CIO’s are embracing, is that implementing AIOps can actually result in reduced expenditure overall.

CIO’s that are concentrating on IT as a force of operational automation, integration and control are losing ground to executives who see technology as a business amplifier and a source of innovation. Ongoing advances in technology are now providing forward-thinking CIO’s with a much broader spectrum with which to work in terms of cutting costs across the entire organizational platform.

It has nothing to do with cutting IT capability, but rather finding ways to make IT operations more efficient. This is primarily achieved through intelligent automation, which significantly reduces the time and resources needed to run both routine tasks as well as complex workflows. When these tasks and workflows are automated, IT personnel are freed up to focus on other, more critical matters, thereby improving the overall performance of the department and subsequently the company as a whole.

Another way that CIO’s are leveraging AIOps for the benefit of their organizations is through improvement of incident management and mean time to resolution (MTTR). Critical system errors are costly and can have a significant impact on an organization’s bottom line. AI-powered intelligent automation is allowing businesses to manage incidents and downtime scenarios more efficiently and in a much timelier manner, which means less risk of negative impact, both on the business and on the end user.

AIOps isn’t just becoming a tool for cutting costs, either. It’s also significantly improving business performance, which plays a key role in increasing revenue. According to a recent survey conducted by Gartner, the main focus of CIO’s in the current climate is growth. They want to attract new customers and effectively retain their current ones. Intelligent automation helps to improve service levels, thereby improving the customer experience.

In a time when budgets are at the forefront of every manager’s mind, from the top down to those on the front line, finding areas to improve service and lower expenditure has become a necessity. The concept of AIOps has opened up a number of opportunities for streamlining operations and improving efficiency, which ultimately achieves the goal of reducing costs and boosting enterprise growth. By applying technology as an amplifier to business operations, rather than as simply an individual component, organizations that are embracing artificial intelligence and automation are already reaping the benefits and are poised for ongoing success as we move toward the future.

Ready to join these forward-thinking business leaders? Download your free trial of Ayehu and start building your AIOps strategy today.
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Making the Case for Artificial Intelligence in Your Organization

Recent statistics published in Forbes revealed that while 82% of IT and business decision makers agree that company-wide strategies to invest in AI-driven technologies would offer significant competitive advantages, only 29% said their companies have those strategies in place.

Why such a big divide? In many situations, it’s a simple lack of buy-in. In fact, Forbes Insights research also revealed that while 45% of IT stakeholders express “extreme urgency” regarding the application of AI within their organizations, only 29% see that same sense of urgency among their C-suite. Among the board of directors, that percentage drops down to just 10%.

Leaders who want to reap these benefits and advance AI within their organizations must overcome these odds by making a strong, solid business case around how artificial intelligence will deliver in terms of business benefits, such as operational efficiency, competitive advantage and revenue growth. Here are a few recommendations on how to accomplish this goal.

Illustrate success through real-life case studies.

There’s nothing more powerfully persuasive than a real-life story. C-suite executives and board members don’t want to hear about hypotheticals. They want to see numbers – quantifiable proof of ROI – before they’ll be willing to sign on the dotted line and invest in AI. After all, it’s pretty hard to argue against benefits like lowered costs, improved service levels and other key business advantages.

Demonstrate AI’s decision-making support.

One of the hardest parts of an executive’s job is making critical business decisions. If you can show them how artificial intelligence can address and resolve this major pain point, you’ll make believers out of even the biggest skeptics. Simply put, AI provides the ability to digest, process and analyze data to unlock invaluable insight and boosting confidence through data-driven decision support.

Position AI as the cornerstone to successful digital transformation.

These days, everybody’s talking about digital transformation. In fact, it’s widely believed that moving to digital operations and offering digital services will be absolutely essential in order to remain competitive in the modern economy. If you can position AI as the catalyst for making this happen, you’ll get emphatic yesses across the board. And since analytics is the core to what drives digital experiences, the connection to AI shouldn’t be too difficult.

Link AI with the power to innovate.

40% of IT leaders list driving innovation and implementing new tech as one of their top concerns. In today’s rapidly changing landscape, staying in-step is no longer enough. To remain competitive and achieve sustainable success, organizations must find a way to stay a few steps ahead. Easier said than done? Not when you have artificial intelligence in your corner. AI offers business leaders the opportunity to garner engagement from all levels of the organization, creating a truly collaborative environment where ideation and innovation thrive.

Reinforce the power of AI for optimizing client experience.

In business, you’re only successful if your customers are happy. Leveraging machine learning and artificial intelligence can help businesses to become far more responsive to their clients, ultimately delivering a better experience overall. And it’s a win-win, because not only do customers receive a higher level of service, but because AI frees up employees to focus more on high-value initiatives, the organization benefits from greater productivity. Happier clients + more efficiency = a better bottom line.  

It’s important to point out that AI, just as with any technology, shouldn’t just be implemented for the sake of it. It should be leveraged because it’s the best and most effective solution to a specific business problem or opportunity. When presenting your case, be sure to tie the technology and its capabilities directly to these problems and/or opportunities, and demonstrate exactly who will benefit and how. This will make your case far more compelling and improve your chances of success.

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EBOOK: HOW TO MEASURE IT PROCESS AUTOMATION RETURN ON INVESTMENT (ROI)

4 steps to minimize MTTR

Any seasoned IT professional will tell you that one of the biggest challenges they face in their day to day job is reducing mean time to resolution (MTTR), or the amount of time it takes to get key systems back up and running after an incident. Down time in any industry can have a significant impact on both internal operations and external service levels. And the longer it takes to get things resolved, the worse the problems can become. Intelligent automation can make minimizing MTTR even easier and more effective.

Managing mean time to resolution involves 4 main steps:

  • Identifying the problem
  • Uncovering the root cause of the problem
  • Correcting the problem
  • Testing to verify that the problem as successfully been resolved

How quickly you can achieve the first step will ultimately depend on the quality of the monitoring system you have in place. Having a basic system can only get you so far and leaves a lot of room for costly error. Depending on how many incoming alerts your organization fields, staying on top of them can be too much for a small IT department. That means serious issues could slip through the cracks and cause major problems down the road. Enhancing your system with intelligent automation can create a highly effective, closed-loop solution, ensuring that all critical incidents requiring attention are prioritized and addressed accordingly.

Once an incident is identified, the next step is determining its root cause. This is the costliest part of the MTTR equation because it takes time, resources and manpower. Obviously, the more serious the issue, the more quickly it needs to be addressed. It may require “all hands on deck” to help uncover the cause so it can be corrected. It’s also important to maintain visibility and accountability at all times throughout the process. Who is handling the problem? What steps have been taken so far to get to the bottom of it? Has anything been missed? Again, automation can address this by providing real-time status of incidents, ownership, severity and priority in one central dashboard.

As soon as the problem has been properly diagnosed, the third step is taking the necessary actions to resolve it as quickly and effectively as possible. With most incidents, time is of the essence, so developing a solution is critical. One of the biggest benefits of integrating intelligent automation into your incident management process is that it can actually predict MTTR based on historic events. This can provide a guideline for the resolution process and alleviate some of the stress that naturally arises during a downtime. The IT team will be able to work quickly and efficiently to implement a solution that will get systems back up and running fast, limiting the negative effects on the company.

The final step in the MTTR process is testing to ensure that the problem is, indeed, resolved. It’s also important to assess each process to identify areas that can be improved. Being proactive and leveraging artificial intelligence can help to determine the best way to deal with similar incidents and can even help to avoid them completely.

In conclusion, managing the mean time to resolution process involves careful monitoring and the right tools, specifically intelligent automation. This can provide the most timely and effective response and a faster overall turnaround, thereby reducing or even eliminating impact on the business.

If your current incident response strategy isn’t producing these results or you’d like to learn more about how IA can dramatically reduce your MTTR, take Ayehu for a test drive or download a free 30 day trial.

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3 Ways Virtual Assistants are Transforming the Service Desk

A few years ago, the chatbot phenomenon swept the consumer world. Today, people are becoming more and more at ease using conversational AI and virtual assistants to do everything from set their doctor appointments to planning travel. Yet, despite this consumer-driven craze, one area that seems to have been left largely in the dark is the IT help desk. Surprisingly (and frustratingly) enough, for many organizations, even something as basic as requesting more storage and resetting your password still requires opening and waiting for a ticket to be serviced.

The truth is, what once began as an innovative service to help employees has somehow evolved into more of a costly distraction. Budget-conscious executives have come to view the IT service desk, not as a core component of the business, but as an expensive necessity. As such, the help desk has long been the target of cost-cutting reductions. Yet, despite these efforts, one recent report indicates that the expenses surrounding service desks are actually on the rise. Today, a typical help desk is massively overloaded and majorly underfunded.

Enter the virtual assistant. Unlike the many other “solutions” CIOs tried in the past, chatbot technology has the potential to dramatically disrupt and ultimately transform the modern service desk in a way that is both positive and sustainable. This will happen in three distinct ways, as follows.

Automating the humdrum.

According to Gartner, password resets account for 40% of all service desk requests. In this way, help desk support agents can feel like mere robots, repeatedly responding to the same requests over and over (and over) again. Why not transition these mundane, repetitive tasks to actual robots? AI-driven virtual assistants can handle everything from simple tasks to complex workflows. This frees up human agents to focus on higher-level initiatives.

The best part? Chatbots are available 24 hours a day, 7 days a week, 365 days a year. They work weekends and holidays and they don’t require overtime. This means not only can you offer round-the-clock support, but scaling to higher volumes will not require an increase in headcount. The tremendous value this promises has led many large, global enterprises to begin deploying virtual assistants.

Removing the human from intuitive tasks.

Under normal circumstances, a typical service order can take more than a full business day to resolve. This process generally includes several interactions between support analysts and often requires escalation to subject matter experts. Next generation chatbot technology is now capable of using historical interactions – such as voice transcripts, prior transactions and other preexisting data – to learn, engage, suggest and recommend resolutions. Even complex troubleshooting can be handled almost, if not entirely by virtual assistants.

Revamping the user experience.

The IT industry has spent a fortune in an attempt to improve employee self-service. Yesterday’s setup was centered on the creation and maintenance of an institutional knowledge base where users could log in and search for answers to their questions in lieu of opening a help desk ticket. The results of these queries were often mixed. Today, thanks to advances in artificial intelligence technology, a user can type, text or even speak their question and a virtual assistant can engage in a meaningful exchange to resolve the issue.

Despite getting off to a markedly slow start, large enterprises around the globe are beginning to recognize the value that conversational AI brings to the table. As such, we are seeing a rapidly growing number of organizations “hiring” virtual assistants to help transform their service desks into the highly effective, cost-efficient and innovative business benefits they’ve always dreamed of being.

Get started with virtual assistant technology and see how it can revolutionize your help desk by downloading your free 30 day trial of Ayehu today.