AIOps (Artificial Intelligence for IT Operations) has helped businesses to induce automation in their essential business processes. From monitoring software systems to providing actionable insights for incident resolutions, AIOps has proved to be a boon for organizations. However, you cannot just add an AIOps based analytics platform to your IT infrastructure. For AIOps transformation, you need to have a predefined strategy along with addressing the challenges with AIOps adoption. If you do not have a predefined strategy, your AIOps transformation could fail and leave an impact on the service availability. Read on to know five reasons your AIOps transformation could fail and how to avoid them.
Non-compatibility with existing tools
Are your software systems able to exchange information and data seamlessly? An AIOps based analytics platform will require information from other software systems to generate meaningful insights. Interoperability with existing software systems can lead to the failure of your AIOps transformation. If your software systems do not allow you to work with other products or systems, it is time to consider an IT transformation first.
What’s the point of using a digital service desk AI software when the tickets generated by the service desk are ignored by your legacy tools? Make sure that your legacy tools are forwarding the tickets that are generated by the services desk for further analysis. If your legacy tools are compatible with an AIOps based analytics platform, it will automatically consume IT incidents from the service desk and generate actionable insights.
Not knowing the problematic areas
You are not undergoing AIOps transformation just for the sake of adopting a new-age technology. The main purpose of using AI in operations management services is to increase the productivity of your IT operations. Besides focusing on the latest trends in the AI industry, you should focus on the problematic areas for which an AIOps transformation is needed. Some of your IT operations might already be efficient and not require the support of an AIOps based analytics platform.
AIOps adoption can be costly and it is better to find the main problem areas that are decreasing the ROI (Return on Investment). Even the best AIOps tools and products have fixed use cases and can’t help you with something out of the box. AIOps transformation can be costly but will be profitable in the long run if used appropriately.
Lack of training data
An AIOps based analytics platform will require training data to be more efficient with time. Data is like fuel to AI/ML algorithms which helps them to learn about the IT processes. Organizations lack at providing training data to AIOps based analytics platforms which eventually leads to the failure of AIOps transformation. Even the big organizations fail to provide training data to AI/ML algorithms to make them better.
If your training data is messy and contains many outliers, your AIOps based analytics platform will not produce meaningful insights. The organizational data is always scattered across various software systems and is unstructured. Without getting a complete view of the organizational data, AIOps based analytics platforms cannot perform to their fullest.
Not knowing about performance metrics
How would you know that your AIOps transformation is going wrong? Well, one way is to wait and let the failed AIOps transformation impact your ROI. Another way is to use performance metrics to know the benefit of AIOps adoption. If you get to know about inefficient AI DevOps platform management services in time, perhaps you could switch to another transformation strategy. Some of the major performance metrics that can help in determining the impact of AIOps transformation are as follows:
- MTTD: MTTD (Mean Time to Detect) is the time invested in finding out an IT incident. If you have adopted AI for application monitoring, the MTTD should decrease.
- MTTR: MTTR (Mean Time to Detect) is the time taken to fix an IT incident. AI in operations management service should always reduce MTTR significantly.
- Service availability: AIOps platforms will always boost your service availability and reliability. If your service availability is not improving, you need a change in your AIOps strategy.
Failing to embrace the change in IT culture
Your IT culture will go through a major change due to AIOps adoption. At first, it would be hard for your employees to trust the decisions of AI data analytics monitoring tools. However, you can create awareness among your employees regarding the pros of AIOps adoption. You can use open box AI/ML tools that can be customized according to the current IT culture in your organization.
In a nutshell
Just like AIOps platforms offer enhanced observability into software systems, you should have observability into AIOps platforms. You can use various performance metrics for measuring the impact of AIOps on your organization. The global AIOps industry has a CAGR of more than 20% indicating the rise of AI in operations management services.
In 2017, Gartner predicted that the use of Artificial Intelligence for IT Operations or AIOps would increase by 40% in 2021. This has held up, as according to industry reports, the AIOps market value was $13.51 billion last year and is expected to grow to an impressive $40.91 billion in the next five years. The reason behind this is that AIOps finds applications in various fields. AIOps has particularly emerged as a key driver in the Fintech landscape.
In the financial sector, the use of AIOps enables quick monitoring, security, and efficient management of data. The financial sector handles a huge volume of sensitive data and IT Automation with AI can help reduce human error and workload. The automation of manual processes through AIOps will enable more efficient Fintech solutions. In this article, we explore the impact of AIOps in the finance sector.
Fintech or Financial Technology is the application of technological tools to automate and enhance all financial services. Fintech includes the use of IT operations management software, algorithms, and even the development and use of cryptocurrency. Initially, Fintech was just focused on transactions, bookkeeping, and digital currency. However, in the past few years, Fintech has evolved to include the use of mobile devices for transactions, applications for credit, investment management, and other such financial activities which are performed without the help of an actual person.
The migration of financial data centers with the help of data center migration planning tools is also a part of Fintech. Such AIOps tools are used by large community banks and such financial institutions that have outgrown existing data centers and need one that can adapt to rapid growth and has sufficient bandwidth and infrastructure to accommodate all financial data.
Since financial institutions make use of various databases and networks, data center consolidation initiative services are also included under Fintech. These services help to manage servers, systems, and locations to improve efficiency for a low cost. Let’s understand how AIOps can help Fintech in the current fintech landscape.
The financial sector is often at risk of data breaches and other such security threats. The use of some of the best AIOps platforms and software can not only prevent this but also greatly improve the quality of financial services and products that are offered to clients.
In 2021, AIOps possesses the power to enhance the financial sector through the following methods:
- Efficient day-to-day operations – The primary use of AIOps in Fintech involves improving efficiency. The combination of machine learning and data analytics drastically cut down on errors and improved the quality of the financial services being provided. AIOps digital transformation solutions analyze the demands and preferences of the customer base and help to create accessible digital products and services. This also reduces downtime which helps companies save thousands of dollars.
- Analyze and improve performance – AIOps in Fintech helps to analyze available data to understand problems and act against them. Financial institutions also make use of digital transformation services and solutions to predict what clients want in terms of financial service and improve engagement according to the analytics.
- Identification and prevention of fraud – One of the major use cases of AIOps in Fintech is in the detection of frauds and anomalies. When relying on old technology and manual processes, it can take approximately 6 months to figure out a data breach. But AIOps can do it in a few seconds. Financial institutions often use different tools to predict risks, identify third parties trying to log in, and illegal transfers of large sums. AIOps brings all these together. The AIOps dashboard constantly monitors data and all activities to make sure that no information is compromised.
- Monitoring and improving compliance – Compliance in banking or financial service businesses is the act of adhering to a set of rules or requests. AIOps can strengthen compliance and make sure that all work practices and standards are being followed and maintained. AIOps tools in Fintech can be used to identify issues before they become actual risks so that business does not suffer from loss of revenue or lose clients. Financial institutions are also using digital service desk AI software to improve overall work and client engagement.
- Reducing drawbacks – For a long time, financial institutions kept on-site servers to prevent security breaches. But this affects the speed of services and makes them unstable and less scalable. It also does not completely do away with risks and when the system is affected, it takes a long time for the support staff to solve the issue. However, AIOps algorithms continuously look for risks, bots, and DDOS attacks. Fintech makes use of the best AI auto-discovery tools to analyze server conditions. This reduces drawbacks significantly.
The financial sector deals with data at every minute of the day. It can often prove to be a challenge for IT operations if a large volume of data must be processed at once. This is where AIOps comes in. In 2018, Gartner suggested that the use of AIOps in the form of monitoring tools for infrastructure and various applications would increase from 5% to 30% by 2023. The impact of AIOps, especially through tools like IT infrastructure managed services, is not only efficient but also transformative for Fintech.
The advancement of Fintech in recent years has led to the rapid digitization of services in the financial sector. Financial institutions are now using AIOps tools like the cloud migration assessment tool for businesses to shift data and optimize the services offered. Such solutions ensure security and better performance. For financial firms planning to invest in AIOps platforms for their unique needs, the time has never been better. With the advent of new technologies in AIOps, fintech is going to scale new heights.
Organizations across the world saw their business processes become severely constrained due to the COVID-19 pandemic. Since physical workplaces were shut down, businesses found it hard to maintain business continuity. Organizations quickly started adopting the WFH (Work from Home) culture to maintain business continuity. This culture brought its challenges and organizations had to cope with them. One such challenge was to manage security & compliance remotely.
Challenges of remote working
The coronavirus outbreak brought unprecedented challenges. While most companies struggled with maintaining team coordination, communication, and performance standards, technical challenge further prevented business leaders from managing productivity. Most organizations did not have a dedicated IT infrastructure to handle remote IT operations. Hyper-automation and a dedicated remote working IT infrastructure became the most sought-after transformation and companies were quick to embrace newer technologies. AI tools in IT operations management were the best solution for managing remote working.
How AIOps helps remote working
AIOps platforms use AI/ML algorithms to support IT operations and automate them. AIOps focuses on decreasing the need for human labor. The COVID-19 pandemic increased the demand for AIOps based analytics platforms. These platforms are seamlessly helping organizations adapt to the WFH culture by offering distinct features:
1. Remote monitoring
The biggest challenge with remote working was to monitor the performance of software systems responsible for IT operations. CIO/CTOs would not be able to access the workplace IT infrastructure to monitor the performance of software systems. System monitoring can help identify the incidents within the IT infrastructure. AIOps platforms can implement rigorous monitoring of software systems without the need for human intervention.
AIOps can collect data from multiple and remote sources. The temporal data will then be analyzed to find any outliers or anomalies. You can identify incidents within your remote IT infrastructure and can resolve them to maintain business continuity. Real-time user monitoring tools can help in solving incidents faster.
2. Incident resolution
With AIOps, you can find the root cause of an incident easily. Even if the devices connected to your IT infrastructure are at remote locations, AIOps will still identify the incidents. An AIOps based analytics platform utilizes temporal data to identify incidents.
Upon the discovery of an incident, an AIOps platform will inform you about the IT team responsible for resolving it and provide actionable insights to resolve an incident faster.
If an event occurs twice within the remote IT infrastructure, AIOps platforms can remember it. Remembering an incident means they also recall the steps needed to solve it.
Hyper automation for ITOps is automating all the processes except for those that can only be managed manually. You cannot invest in installing high-cost servers at each employee’s home to achieve better results. Firms are looking to automate IT operations to maintain business continuity in such times. AIOps platforms can help in automating several IT operations with their intelligent AI and ML algorithms. The costs for automating numerous IT processes may seem high in the beginning but will be beneficial in the long run.
Besides monitoring the user experience, you also must monitor the performance of systems used by the employees to perform essential business operations. AIOps platforms help in enhancing the observability in user experience and the internal states of the software systems. Since your employees are working remotely, you must make sure that their software systems provide high performance. Low-performing software systems can result in lower productivity and higher downtime.
If an issue arises with any essential software system, AIOps can identify it even before an employee reports it. Enhanced observability with AIOps helps in digital experience monitoring. Firms use various digital platforms to connect with their customers. If an issue occurs with the user experience on digital platforms, AIOps can find it for you in advance.
5. Enhanced collaboration
Communication has been a key challenge amidst the COVID-19 pandemic. DevOps teams are not able to remove the communication gap between the operations and development teams. AIOps platforms not only reduce the communication gap between IT teams but also allows east collaboration. Processes like feedback collection can be automated using AIOps. You can collect feedback from your employees and customers at regular intervals to understand issues with the IT infrastructure.
6. Security & Compliance
Security & compliance is an indispensable business process for organizations. Firms are producing large volumes of sensitive data that need to be protected. Cybersecurity experts cannot visit the workplace to access security platforms. Remote work culture lets employees work from multiple devices and thus, safeguarding the business data gets even more difficult. If any data breach occurs, one cannot rush to the workplace for accessing the resources needed to solve it.
AIOps based analytics platforms identify the potential risks within the IT infrastructure in advance. You can automate the basic steps to follow if a data breach occurs with a reliable AIOps platform.
7. VDI (Virtual Desktop Infrastructure)
Virtual desktop infrastructure solutions are in demand due to the COVID pandemic. VDI enables employees to work remotely and can access IT resources. Organizations can deploy computing capacity, enterprise applications, and other IT components on the devices of employees via VDI.
If there is a VDI desktop virtualization software system, its performance must be monitored. Data about the performance of virtual desktops has also to be analyzed. AIOps can help in managing your VDI and making sure the employees are provided with the computing capacity that they need. AIOps can monitor the user experience of virtual desktops to identify any issues. You can also eliminate any potential risks within the VDI with a reliable AIOps platform.
45% of businesses have already started using AIOps to ensure business continuity and remote monitoring of software systems. Even if firms cannot access workplace resources, they are able to maintain business continuity with AIOps.
In today’s competitive and software-driven era, businesses must make better decisions to stay ahead in the market. The IT infrastructure of a business is responsible for essential business processes. Businesses invest more in the management and security of their IT framework so that their essential operations do not stop. However, with the growing business data and customer needs, managing IT infrastructure has been tougher than ever.
AI tools in IT operations management offer enterprises a way to achieve better results.
The need for a responsible AI framework
The traditional IT framework is not able to match the huge volumes of business data produced every day. Business data needs to be analyzed and protected from intruders. Traditional software systems cannot upscale themselves automatically with the growing need. You will have to restructure your IT framework frequently as per growing demands.
A framework is a foundation on which business applications and other components of IT infrastructure are built. An AI framework is scalable and requires less human intervention to operate. IT automation with AI tools will also enhance the productivity of an organization.
Things to know before building a robust AI framework
1. Building a dependable AI framework isn’t easy
AI adoption can be complicated as its impact is tricky to measure. An organization can go for hyper-automation, but that will involve high investment. Implementing a complete AI framework for each of your business processes will help you achieve hyper-automation. It is important to note that firms that achieved hyper-automation also started small.
Analyze which IT operations are most vulnerable and demand a scalable solution. Once you have identified them, apply AI only to those IT operations. There is no point in exhausting your funds at once by going for a full-fledged AI solution. Once AI is successful for initial test cases, you can start building your AI framework piece by piece.
2. Leverage the power of AIOps platforms
AIOps (Artificial Intelligence for IT Operations) is a scalable solution to automate and enhance the productivity of your IT operations. AIOps platforms are also helping organizations monitor remote work extensively. The recent COVID-19 pandemic has forced organizations to look for automated IT operations. The main benefits of using AIOps for your business are as follows:
- AIOps managed infrastructure services help reduce the need for human intervention.
- With a reliable AIOps based analytics platform, you can identify the incidents within the IT infrastructure easily.
- AIOps platforms use AI/ML algorithms to provide actionable insights for solving an incident within the IT framework.
- You can use AI for application monitoring amidst the remote work culture. AIOps platforms offer enhanced observability into software systems to monitor their performance. Virtual desktop infrastructure solutions powered by AIOps are also available in the market to adapt to the WFH (Work from Home) culture.
- With AIOps, you can identify vulnerabilities associated with the software systems like exhaustive capacity, outage prediction, and much more.
- AIOps platforms for your IT framework will help the IT teams collaborate quickly. The disorientation among the IT teams will be drastically reduced by adopting AIOps.
- AIOps platforms can offer real-time information about cyber-attacks to boost cybersecurity.
You can identify the skill gaps within your organization and implement AIOps to fill them. System administrators, CIOs, or CTOs always aim to monitor the performance of software systems end-to-end. With AIOps, not only can you monitor the software systems rigorously, but also resolve incidents faster within the IT framework.
3. Decide your performance metrics
Benchmarking is critical for identifying the impact of AI on a business. While designing an AI framework for an organization, IT leaders should decide on performance metrics to be used. Some of the best performance metrics for measuring the impact of AI on an organization are as follows:
- Service availability: The availability of your applications and systems to provide essential services to customers translates into business reliability. With AI adoption, you can significantly enhance your service availability.
- MTTD: MTTD (Mean Time to Detect) is the average time taken to identify the root cause of an incident within the IT framework. With AI adoption, you can decrease the MTTD.
- MTTR: MTTR (Mean Time to Resolve) is the time taken to fix an issue within the IT framework. A reduction in MTTR will denote the positive impact of AI on your organization.
- MTBF: MTBF (Mean Time Between Failures) is the average time between IT outages. For example, if the software systems of an organization fail three times after operating 300 hours, we can say the MTBF is 100 hours.
Some other metrics for measuring the performance of AI-powered systems are service reliability, MTTA, the ticket to incident ratio, automated versus manual workload, and many others. Deciding the metrics for measuring the performance of AI-powered systems should be done while implementing an AI-led IT infrastructure.
4. Look for a responsive and reputed AI firm
There is a skill gap in the industry when it comes to AI experts. Organizations find it hard to ensure ethical use of intelligent AI algorithms and high-end analytics. Organizations are already using traditional monitoring systems and are not sure about the algorithmic fairness of AI platforms.
You should use AI monitoring tools provided by reliable AI firms. Pre-made AI solutions are designed according to industry standards. With premade AI solutions, you can decide the extent of automation to be induced in the IT framework.
In a nutshell
More than 50% of businesses have reported that adopting AI has boosted their productivity. Implementing a responsible AI framework for your company will help you cut costs in the long run. Start exploring AI-based platforms for your company now!
The IT operations, the lifeline of a company or a business, is where the active response system of the firm is centered. Constant innovation has led to significant changes in the operational infrastructure over the last few years and brought new-age challenges to the fore that continue to test the limitations of the existing structure. Especially with the digital revolution that is increasingly transforming the way businesses function and manifest themselves, the ITOps struggle to cope with the mounting data volume and in leveraging inputs from core systems.
This is prompting businesses to push their boundaries and resort to Artificial Intelligence (AI) solutions with greater bandwidth. AIOps or Artificial Intelligence for IT operations is the way traditional IT services and management can be reassessed by integrating machine-based learning and abilities into the existing database and launching it in a broader spectrum. This involves functions like automation, availability, event correlation alerts, and delivery at par with the rising complexities of the business.
AIOps as evolving platforms
The penetration of AIOps in modern job design has been slow but steady. Big business enterprises are now looking at AIOps as an advanced tool to single-handedly manage extensive data monitoring and analysis while processing burgeoning data and information load at a remarkably fast pace. AIOps are programmed for tackling a diversity of output for exact and efficient error spotting in real-time situations followed by critical problem-solving and addressing high-risk outages. Besides, the predictability of AIOps provide a clear sense of the shortcomings and be prepared for unforeseen disruptions in the workflow.
According to reports by the world’s leading research and advisory company and IT management specialist Gartner, the use of AIOps may rise exponentially in the next 3-5 years at a rate of up to 30% that can help catapult business statuses remarkably. However, harnessing this technology requires a solid investment which is why the businesses are interested in a model that is reliable and can prove to be beneficial to the clients and profitable to these ventures at large.
The roadmap for AIOps
Launching and incorporating a versatile technology like AIOps with the current business machinery can seem daunting initially. However, before proceeding with the AI setup, it is essential to consider both the immediate and long-term implications of such an arrangement. Most often, organizing pre-existing records is the key to implement AIOps to the best of capacity.
Here are a few pointers a business can follow to launch its own AIOps interface:
- It’s always wise to understand the technology before applying it.
AI is no rocket science but requires a focused approach to make sense of its terminology. Persistent engagement with the AI tools can result in a better grasp of the subject matter and an assured involvement with related projects and other stakeholders.
- Start small and simple and demonstrate the power of AIOps to your team in the most convincing manner possible. Highlight the specific problems that you expect your AIOps to fix including the anomalies that escape human surveillance. This could imply automatic troubleshooting and recovery responses if the system reports any malfunction. In a larger picture, this will helps mobilize isolated IT entries and integrate the work ecosystem with a more robust yet feasible strategy.
- Allow room for experiments to evaluate the true potential of an AIOps application. Even if the whole initiative is cost-intensive, there are resources available at a reasonable rate that can be used to expand knowledge and tap into its wide range of functionality.
- Be well-versed with digital analytics and statistical figures to enable the management of big data and helps track and monitor performance updates. This gives a direct insight into the positioning of your business and measures that can be taken to upscale possibilities.
- Equip your infrastructure with State-of-the-art facilities that can shoulder the AIOps network and fully support the system upgrades that may emerge in the process.
- When it comes to monetization of the business, the AIOps capitalize on the Return on Investment factor and help the company earn big bucks and invest in furthering the threshold. This can give a fair sense of how to fund AI-driven businesses at every stage.
The partnership between IT and AIOps is the new currency for optimizing the digital operations of a company. AI could very well be the gamechanger but it requires the informed use of this feature to take any enterprise to the next level. AIOps are also ‘guardians of security’ of confidential data owing to their prompt detecting abilities that minimize the risk of breach, leaks, cloning, and other potential threats that may hamper its credibility.
Therefore, embrace this top-notch, persuasive technology without fear or hesitation as it not only beats the operational status quo in theory but also sets revolutionary but achievable standards for your business. As a result, your project becomes more ambitious and future-oriented and the tech more approachable and ubiquitous with each passing day.
With technological advancement and reliance on IT-centric infrastructure, it is essential to analyze lots of data daily. This process becomes challenging and often overwhelming for an enterprise. To ensure the IT performance of your business is on par with the industry, Artificial Intelligence for IT operations (AIOps) can help structure and monitor large scores of data at a faster pace.
What are AIOps?
It is the application of artificial intelligence, machine learning, and data science to monitor, automate and analyze data generated by IT in an organization. It replaces the traditional IT service management functions and improves the efficiency and performance of IT in your business.
AIOps eliminates the necessity of hiring more IT experts to monitor, manage and analyze the ever-evolving complexities in IT operations. AIOps are faster, efficient, error-free, and reliable in providing solutions to issues and challenges involved in IT.
Top 6 Things AIOps can do for your IT Performance
By moving to AIOps you save a lot of time and money involved in monitoring and analyzing using the traditional methods. You can also eliminate the risk of faulty data or outdated reports by opting for AIOps. Here are six reasons to choose AIOps and how they can enhance your IT performance.
- Resource Allocation and Utilization
AIOps make it easy for an enterprise to plan its resources. Real-time analytics provides data on the infrastructure necessary for a seamless experience be it the bandwidth, servers, memory, and more details.
AI-based analytics also helps an enterprise plan out the capacity required for their IT teams and reduce operational costs. With AI-driven analytics, the enterprise knows the number of people required to address and resolve events and incidents. It can also plan the work shifts and allocate resources based on the number of incidents during any given time.
- Real-time Notification and Quick Remediation
Real-time analytics has made it easy to make quick business decisions. With AIOps, businesses can create triggers for incidents and can also narrow down business-critical notifications.
According to a study, about 40% of businesses deal with over a million events daily. Assessing priority events becomes an issue in such cases. AIOps help businesses prioritize and effect quick remedies for anomalies. The priority incidents can then be assigned to the IT team to resolve on priority.
- Automated Event and Incident Management
Using data collected by AIOps, both historical and real-time, businesses can plan for different events and incidents. Thus, offer automated remedies for such incidences.
Traditionally, detection and resolution of such events took a long time and required larger incident management teams. It also meant that the data collected would not be real-time.
Using AI-based automation reduces the workload and ensures that an enterprise is equipped to handle current incidents and planned events. It also requires less manpower to deal with such incidents saving a business from hiring costs.
- Dependency Mapping
AIOps help understand the dependencies across various domains like systems, services, and applications. Operators can monitor and collect data to mark the dependencies which are even hidden due to the complexities involved.
AIOps even analyze interdependencies that might be missed unless there is thorough monitoring of data. It helps enterprises in the process of configuration management, cross-domain management, and change management.
Businesses can collect real-time data to map the dependencies and create a database to use in change management decisions like when, how, and where to affect system changes.
- Root-cause Analysis
For improved IT efficiency and performance, understanding the root cause of anomalies and correlating them with incidents is important. Early detection will help affect quicker remedies.
AIOps let IT teams in a business have visibility on anomalies and their relation to abnormal incidents. Thus, they can respond quickly with efficient resolutions for a smooth experience.
The root-cause analysis also helps in improving the domain and ensuring that the business runs efficiently with less exposure to unknown anomalies. Businesses are equipped to investigate and remedy the issue with better diagnoses.
- Manage IoT
With many Internet of Things devices used widely, the necessity to manage data and the device complexity is of utmost importance. AIOps sees a wide application in this field and help manage several devices at the same time. The sheer volume of devices can make it overwhelming to manage IT operations.
IoT devices have several variables in play and operators require AIOps to manage them with ease. Machine learning helps leverage IoT and monitor, manage and run this complex system.
AIOps ensure that the IT performance thrives with consistent efficiency. It not just helps monitor large data in real-time but also detects issues, analyzes correlation, and ensures quick resolutions. Automated resolutions and management can eliminate downtime and save time and money for any business.
In a nutshell, AIOps aid in the consolidation of data from various IT streams and ensures you receive the highest benefit out of it. Whether it results in automation, resolving incidents at a quick pace, or finding anomalies and making data-driven decisions, AIOps help an organization while ensuring the IT performance is efficient.
Have you hired a CIO (Chief Information Officer) for your organization? A CIO in an organization is responsible for managing the computer technologies used by the employees. However, sometimes CIOs find it hard to analyze the technological standard of an organization due to lower visibility. Read on to know more about the lack of visibility into the user experience.
What is a CIO?
A CIO monitors the technologies used by an organization and the usability of the information produced within the organization. Since more and more firms are working on a digital platform, the roles of CIOs have significantly increased over the years. CIOs find out the benefits of technologies used within the organization. A CIO makes sure that each technology is being used for any particular business process.
A CIO also analyses the technologies offered by a firm to its users. It makes sure that the information and technologies within an organization are used for the betterment of the organization. CIOs help a firm to adapt to the changes and use the latest technologies that can make the business processes less tedious.
Digital experience monitoring
DEM (Digital Experience Monitoring) is one of the main job responsibilities of a CIO. DEM is monitoring the way a customer or internal employee interacts with the digital interface of the firm. DEM analyses the user behavior within an enterprise application or digital interface. It focuses on checking the availability of enterprise applications. DEM helps us in knowing the user’s experience with any particular application and how to improve it.
DEM is done for both customers as well as internal employees. The DEM for internal employees is often referred to as EUEM (End User Experience Management). Digital interfaces can be any technology used by the firm to connect with customers. It can be the firm’s website used by customers to access the offered services or, it can be a management system accessed by the internal employees. You can provide a better customer experience with the help of DEM. Sometimes CIOs face hassles while improving the user experience as they have very little visibility into applications and system software(s).
What does poor visibility mean?
Good visibility signifies how well you can view and access the offered services. Every firm has its services that are visible to the users. If a user cannot find/interact with your offerings easily, it implies that your firm offers poor visibility. Visibility is talked about in the context of the user applications that work as a substrate between the firm and the user. For example, an e-commerce website contains a link to check the real-time availability of products in the warehouses. It is an example of enhanced visibility that can help the customers know about the availability of services in their geographical location.
Enhanced visibility implies a better user experience and also better marketing. When customers can know about the availability of your services easily, the conversion rate will also be high. CIOs aim at offering greater visibility to customers when they interact with enterprise applications or software(s). Poor visibility will not only hamper the user experience but will also drive away potential customers.
Challenges with poor visibility
Poor visibility leads to various issues that hamper the user experience. The challenges with poor visibility are as follows:
- A wide range of applications and systems are being used by a firm. With poor visibility, your employees may not be able to complete the business processes effectively. Maybe your particular business process is lacking due to a bad user experience. You may not be able to visualize the shortcoming of your user experience due to poor visibility.
- When you have poor visibility into user experience, you cannot determine the source of any problem. Your IT teams may blame each other as there is no dedicated communication pipeline.
- As users do not get a better user experience, they might deviate to services offered by your competitors.
Possible reasons for poor visibility into user experience
There can be many possible reasons for poor visibility into the user experience that are as follows:
- Your organization does not have a single view of performance metrics for different IT systems. Your administrators have to view the performance metrics of each IT system separately. It is not only time-taking but also lacks accuracy.
- The existing business metrics for digital experience monitoring are not up to the standards. You need to choose the correct business metrics for gaining visibility into the user experience.
- Your employees are not able to realize the cost impacts of poor user experience on your business. You may not even be aware of the problems arising due to poor visibility into the user experience.
- Your employees may not have access to real-time performance metrics. You may not know about bad user experience until someone has reported it.
Pros of better visibility into user experience
The benefits of greater visibility into user experience are as follows:
- You not only monitor the performance of digital interfaces for your customers but also for your employees.
- With better visibility, you can decrease MTTD (Mean Time to Detect) and MTTR (Mean Time to Resolve) drastically.
- You can solve issues with the digital experience immediately if your engineers have better visibility.
- It is easy to track the root cause of an IT issue with enhanced visibility. You can significantly increase the uptime of your digital interfaces.
- With better visibility, a CIO can understand the issues faced by customers/employees and can provide a personalized digital experience to them.
What’s the solution?
Many businesses are choosing AI-based platforms for better monitoring of IT infrastructure. AIOps platforms help in gaining more visibility into the user experience. With AIOps, you can automate the DEM process and can monitor user experience in real-time.
In a nutshell
The global AIOps market size will be more than USD 20 billion by 2026. You can use an AIOps platform for better visibility into the user experience. A CIO can automate steps for digital experience monitoring and can save time and effort. Enhance visibility into the user experience for better results!