The enterprise software market consistently demonstrates impressive growth, often surpassing 10 percent year on year, making it the most rapidly expanding segment within the broader IT industry, according to Statista. In 2022, global IT spending on enterprise software reached approximately 783 billion U.S. dollars, reflecting a 7.1 percent increase from the previous year.

This trend will continue as global sectors adapt to the macroeconomic changes of the Next Normal and geopolitical tensions between Russia and Ukraine escalate. Business and IT decision-makers may take a head-first approach to tech procurement without first establishing a well-defined buying process.

In their quest to gain a competitive advantage, this can lead to hasty decision-making on behalf of business leaders and investments in technology that may not provide value to the company or align with their prospects.

Discerning the most impactful solutions can be challenging and exhilarating, with many emerging technologies vying for attention. As such, IT decision-makers must deploy solutions for successfully navigating the intricate maze of the tech buying process. 

In this article, we navigate the tech buying process, providing business and IT decision-makers with an essential guide for informing technology procurement. 

We discuss aligning business goals with the tech-buying process, outline key steps to establish an effective approach, and identify vital stakeholders to involve. Additionally, we touch on the typical duration of the buying process and offer practical tips for choosing the right tech vendors, ensuring successful partnerships that drive innovation and growth.

A summary of the article’s key points includes the following:

• Aligning business goals with the technology buying process
• Steps for establishing the tech-buying process
• Who should be involved in the buying process?
• How long is the tech buying process?
• How to choose the right tech vendors?

Aligning business goals with the technology buying process

In the era of digitalization, organizations must ensure their technology acquisition process remains in harmony with wider business goals. This alignment ensures that the chosen solutions address immediate needs and support long-term growth and adaptability.

To achieve this, it is essential to cultivate a tailored purchasing strategy that enables executive and IT decision-makers to champion the broader technology adoption lifecycle. According to Gartner, 87% of senior business leaders say digitalization is a priority, and 91% of businesses are engaged in some form of digital initiative.

By embracing a culture of cross-functional collaboration among key stakeholders and continuously evaluating the effectiveness of technology investments, organizations can optimize their resources and capitalize on emerging opportunities.

Streamlining technology adoption and procurement processes becomes even more pertinent when contrasted with research revealing that 93% of organizations have adopted or plan to adopt a digital-first business strategy.

Steps for establishing the tech-buying process 

1. Start Planning: To ensure a smooth and efficient tech-buying journey, it’s essential to begin with a well-thought-out planning process that sets the stage for success. This foundation involves identifying pain points, assembling a diverse buying team, setting a realistic budget, defining clear timelines, and aligning business objectives.
2. Research and Identify Potential Solutions: Investigate various technology options that align with the organization’s needs and objectives. Look for industry trends, expert recommendations, and user reviews to gather valuable insights.
3. Evaluate and Compare Vendors: Assess the strengths and weaknesses of each potential vendor based on factors such as product features, pricing, customer support, and integration capabilities. Create a shortlist of the most suitable options.
4. Request Proposals and Conduct Demos: Reach out to the shortlisted vendors for detailed proposals and schedule product demonstrations to better understand their offerings. Encourage stakeholders to provide feedback and ask questions during the demos.
5. Make a Decision and Negotiate Terms: Select the best-fit solution for the organization based on the feedback and evaluation. Negotiate contract terms, pricing, and support arrangements to ensure a mutually beneficial agreement
6. Implement and Monitor: Roll out the chosen technology solution, providing necessary training and resources to facilitate a smooth adoption process. Continuously monitor performance and address issues, ensuring the solution delivers the desired outcomes.

Who should be involved in the buying process?

A successful technology buying process requires collaboration and input from various organizational stakeholders. 

Involving the right individuals ensures that multiple perspectives are considered, fostering a comprehensive understanding of the organization’s needs and promoting buy-in from all parties involved. 

Here are the key stakeholders who should be involved in the technology buying process:

1. Executive Decision-Makers: C-suite executives, such as the CEO and COO, play a pivotal role in setting the strategic direction for technology investments. Their insights and understanding of overall business objectives are crucial in ensuring technology decisions align with the organization’s goals.
2. Chief Information Officer (CIO) or IT Director: As the individuals responsible for overseeing the organization’s technology infrastructure, CIOs or IT Directors are instrumental in evaluating potential solutions, assessing compatibility with existing systems, and advocating for the necessary resources to support implementation.
3. IT Professionals: Technical staff, such as network administrators, system analysts, and software developers, can provide valuable input on the feasibility, functionality, and integration of potential technology solutions. Their hands-on experience and expertise ensure the chosen technology is effective and efficient.
4. End-Users: The individuals who will ultimately use the technology – employees or customers – should also be involved in the buying process. Their feedback and opinions can help identify specific requirements, uncover potential challenges, and ensure that the selected solution meets their needs and expectations.
5. Finance and Procurement Teams: These stakeholders play a crucial role in assessing the financial viability of technology investments, negotiating contracts, and managing budgets. Their involvement ensures that technology decisions are fiscally responsible and adhere to organizational procurement policies.
6. External Consultants and Vendors: Engaging with industry experts, consultants, and technology vendors can offer valuable insights into market trends, emerging technologies, and best practices. Their input can help organizations make informed decisions and select the most suitable vendor management solutions for their unique requirements.

Organizations can ensure a more holistic and collaborative approach to acquiring technology by involving these key stakeholders in the technology-buying process.

How long is the tech buying process?

The duration of the tech buying process varies significantly depending on several factors, such as the size and complexity of the organization, the technology being acquired, and the level of customization required. 

Typically, smaller businesses with specific needs can complete the process within a few weeks to a few months. On the other hand, larger enterprises or those requiring highly specialized solutions may take several months or even over a year to navigate the process successfully.

It’s essential to remember that a well-executed tech buying process involves thorough research, evaluation, negotiation, and implementation. Rushing through these steps could lead to suboptimal decisions that may not align with the organization’s long-term goals. 

Therefore, it is crucial to allocate sufficient time and resources to ensure a successful outcome, regardless of the specific timeline for each organization.

How to choose the right tech vendors?

Selecting the ideal tech vendors is a critical aspect of the tech-buying process, as it can significantly impact an organization’s performance and growth. To make informed decisions, consider the following strategies:

1. Research and Shortlist: Conduct thorough research on various tech vendors in the market, exploring their reputation, product offerings, and customer feedback. Create a vendor shortlist that aligns with your organization’s goals and requirements.
2. Evaluate Vendor Expertise: Assess each vendor’s industry expertise and experience working with similar organizations. Consider their knowledge of industry trends, best practices, and any unique challenges your organization might face.
3. Analyze Product Features and Functionality: Compare the features and functionality of each vendor’s solution, ensuring they align with your organization’s needs. Pay close attention to scalability, integration capabilities, and user-friendliness.
4. Consider Customer Support and Service: Evaluate each vendor’s commitment to customer support and service. Look for vendors that offer personalized assistance, prompt response times, and ongoing support for successfully implementing and maintaining their technology solutions.
5. Weigh Pricing and Contract Terms: Analyze each vendor’s pricing structure and contract terms. Ensure they align with your organization’s budget and expectations for long-term value.
6. Request Proposals and Demos: Engage with the shortlisted vendors to request detailed proposals and demonstrations of their solutions. Encourage stakeholders to participate and provide feedback during this stage.
7. Check References: Reach out to existing clients of the shortlisted vendors to gather insights about their experiences and satisfaction levels. This step can help validate your decision and identify potential red flags.

Mastering the tech-buying process

In conclusion, navigating the tech buying process is crucial as it directly influences modern business operations, significantly impacting an organization’s performance and bottom line. 

According to Oomnitza’s 2023 Snapshot Survey on SaaS and Cloud Spend Optimization & Automation, enterprises face challenges managing their software and cloud resources effectively. The survey reveals that 50% of enterprises waste a minimum of 10% of their yearly spending on underutilized software and SaaS applications. The survey also indicates that 53% of respondents spend over 10% of their budget on poorly managed or untracked cloud resources.

By highlighting the intricacies involved in this journey, this article aims to provide valuable insights to help businesses better navigate the tech buying process and make more informed decisions when procuring new technology.

Making better-informed technology investments ensures businesses remain at the forefront of innovation — ultimately contributing to their success in the long run.

The post Navigating the Tech Buying Process appeared first on Digital Adoption.

Gartner reports that organizations need to prioritize smart budget trade-offs, savvy talent strategies, and optimal digital investments to achieve success this year. By leveraging these trends, businesses can drive margin improvement, reduce operating expenditure, improve operational resilience, and capitalize on new growth opportunities of an efficient IT operation.

To meet these expectations, CIOs and IT leaders must establish trust through the delivery of transparent, reliable, and responsive technology.

According to the 2023 State of IT from SWZD, despite the widespread belief that a recession is imminent, most organizations plan to increase their technology spending in 2023.

One key aspect of IT efficiency is leveraging new technologies to optimize business processes and drive innovation. This includes investing in tools and systems that automate tasks, improve data analysis, enhance collaboration, and provide real-time insights into performance.

Just like a computer that runs smoothly with efficient management of hardware and software resources, IT efficiency aims to ensure optimal utilization of resources to achieve better outcomes.

Efficient IT is critical for businesses undergoing digital transformation. Organizations moving away from more traditional operating models require more agile IT systems and processes to keep up with modern business demands.

This article will discuss the importance of IT efficiency and how it can benefit your organization’s bottom line. We’ll also provide tips on achieving greater IT efficiency for your business by leveraging automation, virtualization, and other cost-saving measures.

By focusing on IT efficiency, organizations can achieve greater agility, responsiveness, and competitiveness in the ever-disruptive world of technology.

What is IT efficiency?

IT efficiency can be described as the ability of an IT organization to deliver optimal IT services to a company while minimizing costs. It involves identifying ways to streamline operations and improve productivity, while still maintaining or enhancing the quality of services provided.

IT efficiency can be achieved in several ways, such as adopting automation, leveraging cloud computing and analytics, or optimizing resource utilization. Technology solutions for specific business functions can help organizations streamline processes and optimize costs and resources for maximum performance and efficiency. 

Automation tools can also reduce manual labor by automating mundane tasks. Cloud computing provides access to large amounts of data and analytics on demand, allowing organizations to make decisions that can drive growth and profitability quickly. 

Optimizing resource utilization can also help reduce expenditure by using existing resources more effectively. This could involve reducing redundant processes or reallocating resources from one project to another. 

Why is IT efficiency important?

IT efficiency helps organizations reduce costs while improving their IT processes and services. This makes it an important part of any digital adoption strategy as businesses move away from more traditional operating models.

IT leaders aim for efficiency by optimizing available resources. However, achieving efficiency is challenging, even with careful planning. Often, efforts to enhance efficiency fail to reach expected goals, and vital operations continue to perform poorly.

Improving IT efficiency starts with understanding the current state of IT operations and identifying areas for improvement. Reviewing existing technology investments and ensuring that processes are streamlined and efficient is also essential.

What are the benefits of IT Efficiency?

The benefits of IT efficiency are many. We’ve outlined some of the main advantages below:

Reduce costs – By streamlining IT processes and using automation and virtualization, organizations can reduce their IT costs significantly.

Increase productivity – Organizations can increase their productivity by taking advantage of new technologies and cutting operational inefficiencies.

Generate more revenue – By cutting costs and increasing productivity, businesses can generate more revenue.

Remain competitive – Businesses can remain competitive in an ever-changing market by improving their IT efficiency.

Enhance security – By reducing the number of unnecessary IT components and streamlining processes, organizations can improve their security levels.

Improve customer satisfaction – Businesses can improve customer satisfaction by delivering better services and faster response times.

How does IT efficiency affect the bottom line?

IT efficiency can have a significant impact on an organization’s bottom line. It’s an often overlooked factor in digital transformation strategies, but ensuring businesses remain competitive and profitable is essential.

The broader term of IT efficiency covers a range of processes and technologies, including automation, virtualization, cloud computing, and more. When businesses dig deeper and review their IT processes, they can identify areas where efficiency improvements can be made.

For example, automation can help reduce labor costs, while virtualization reduces the need for hardware and associated costs. These savings can be significant, helping businesses remain competitive in an ever-changing market.

Increasing the bottom line is simple but requires careful consideration and planning. IT efficiency is an important part of any digital transformation strategy, and businesses should look for ways to optimize their operations to maximize profit.

How To Make IT Operations More Efficient

Make sure to prioritize your business needs over technology.

Sometimes we get caught up in the excitement of new technology and want to implement it immediately to reap the rewards. However, it’s important to proceed cautiously and not rush into the latest trend without consideration.

Increased IT efficiency is achieved by selecting tools that aid in the company’s success. For instance, introducing a new ERP system is recommended by IT to improve productivity across the company. This system automates internal processes, freeing employees to concentrate on other projects.

If you overlook business needs and get too excited about technology, IT efficiency can be decreased. The technology may not be used as originally planned or may have glitches because it is new or too expensive for the long-term needs of the business.

Carefully choose your IT vendors and partners.

The efficiency of your IT depends on your IT vendors and partners. It is tempting to make impulsive purchases based on convincing offers, cheap deals, advertising, and reviews. 

However, your business’s most suitable product or service should be chosen to avoid long-term issues.

Establishing a solid relationship with your primary IT partners is crucial as they play a critical role in your business’s smooth functioning. These partners are considered strategic allies allowing open communication to convey your business goals and expectations. Collaborating with your IT partners can lead to exploring innovative technologies, processes, and frameworks that benefit your business.

Create documentation to establish clear processes

Although documentation and processes may seem like tedious admin tasks, they are vital to the success of your business. Although it might seem like your productivity is decreasing initially, establishing clear procedures and comprehensive documentation can enhance the speed at which you deal with IT infrastructure problems.

This will lead to increased efficiency in IT operations in the long run. With straightforward documentation and simplified procedures, you can diagnose and fix issues faster, resulting in less downtime.

Consider various IT stakeholders, including technical leads, operators, and end-users. Each group requires specific documentation tailored to their needs. For instance, end-users need documentation on using an application correctly, while configuration and troubleshooting processes are unnecessary.

Here’s a straightforward method for categorizing your employees:

• Technical leads need detailed technical information about systems and applications and their interrelationships. Language Code for Output: EN-US
• IT operators need an administration guide. It should document installation, configuration, and troubleshooting procedures.
• Applications should come with manuals for end-users that explain how to use them to perform tasks related to their job responsibilities.

Automate, Automate, Automate

You may already be aware that automation is crucial for boosting efficiency. IT departments often spend significant time on administrative tasks, hindering progress on bigger projects. Automating such tasks saves time and ensures consistency.

By implementing it, your IT department can deploy new applications and services faster, mitigate security and compliance risks, reduce operating expenses, and free up your IT staff to concentrate on strategic priorities that align with business objectives. 

This leads to an increase in IT efficiency, helping you get more value from your IT department. It is important to be aware that automation can malfunction. To avoid issues in the future, make sure to implement checks and documentation. You should also establish a process that identifies and resolves errors quickly.

These are the four essential tips to increase your IT efficiency. By investing in the right technologies and vendors, creating comprehensive documentation, automating tasks when possible, and establishing an efficient process to diagnose and fix issues quickly, you can improve the efficiency of your IT operations.

Doing so will ultimately lead to a better user experience and improved business results.

IT Efficiency: Getting It Right

The key to increasing your IT efficiency lies in understanding your business goals and developing a strategy that aligns with them.

Consider investing in technologies that can help you automate tasks and set up efficient and sustainable processes for long-term success. Additionally, partner with good vendors who can provide essential services, such as data storage and cloud services, allowing your team to work more flexibly.

Finally, create comprehensive documentation and processes to help your IT team diagnose and fix problems quickly. Investing in the right technologies, vendors, and processes can significantly improve the efficiency of your IT operations and lead to increased business results.

The post How IT Efficiency Affects Your Bottom Line appeared first on Digital Adoption.

But bubbling under the surface is a phenomenon that threatens to undo all that good work.

A 2022 report by Airtable and Forrester found that knowledge workers spend nearly 29% of their time searching for the data needed to do their jobs.

In this article, we’re shining a light on that lurking beast. That’s right. We’re talking about data silos.

The trickiest thing about data silos is that, in some ways, they can prove useful— for organizing certain processes within an organization. However, they can be a major impediment to successful decision-making if left unchecked.

They hinder digital transformation and cost organizations millions of dollars in lost data, inefficient operations,  and customer dissatisfaction. Organizations must adopt a modern data architecture to break down the barriers between their various departments or teams. This way, they can access all the information they need quickly and efficiently without going through manual processes.

Worse, data silos can form even if you have a robust data lifecycle management process.

We will explore the downsides of relying on data silos and the strategies you can use to eliminate them and create a more streamlined environment in your organization.

What is Data Silos, and Why Do They Occur?

Data silos refer to the isolation of data within different departments or systems in a business, leading to a lack of shared understanding and collaboration. 

Simply put, different teams get accustomed to working only within their data environment, leading to a situation where data is stored in inconsistent formats and accessed through different applications. 

This disconnect hinders efficient decision-making and restricts access to information, ultimately complicating business operations. 

Data silos occur for various reasons, including departmental budgeting, incompatible data platforms, and a lack of a unified approach to data management. 

To maximize business performance, breaking down data silos and establishing a systematic approach to managing and sharing data throughout your organization is essential.

The Dark Side of Data Silos: Pitfalls to Watch Out For

We live in a world where data is king, and every business seeks ways to make sense of everything.

As businesses grow, so does their data, and they often turn to data silos to help manage the influx. Sometimes this is intentional. Sometimes it’s not.

While data silos can be a valuable tool, there is a dark side to these information kingdoms. 

One pitfall to watch out for is the lack of collaboration between departments and teams, often arising from silos. Organizations can become echo chambers, where each unit is focused solely on its own data without considering the bigger picture. 

This can lead to missed opportunities, duplicated efforts, and a lack of innovation. 

To avoid these pitfalls, it’s important to break down data silos and encourage cross-functional collaboration. 

By doing so, your business can reap the full benefits of its data and unlock new insights and opportunities. 

How to Identify Data Silos

Before you can combat data silos, you need to master the knack of identifying them within your organization.

There are several warning signs to look out for when identifying data silos. These include: 

• Multiple teams use different software and systems to store similar types of data.
• Different departments have access to different versions of the same data set.
• Teams face difficulties sharing information, leading to a lack of visibility into the data.
• Data is stored in separate formats and locations, making integrating difficult.
• Duplication of efforts due to a lack of synchrony between departments.

The trick to identifying data silos is simple but not easy.

You need to talk to your teams, audit their data, and understand what data they use for what purposes. In larger organizations, identifying data silos and strategizing solutions would fall to the Chief Data Officer or Chief Data Analytics Officer.

Overcoming Data Silos: Tools, Tips, and Emerging Technologies

Data silos aren’t a new problem. Rather, we think that the inability of humans to share information has been a difficult problem to overcome for many centuries.

But in a way, that’s good news because it means there are plenty of tools, tips, and emerging technologies to help you deal with the problems caused by data silos.

We’ve listed some of our top solutions and broken them down to explain how they can help you overcome data silos for good.

Preventing Data Silo Issues With a Unified Platform

Data silos can be frustrating obstacles in any organization. 

Data can become scattered across multiple systems and departments, making it difficult to retrieve and analyze. Not only can this cause delays in decision-making, but it can also lead to inaccurate data and missed opportunities. 

Fortunately, there is a solution to these challenges: a unified platform. 

You can easily access and analyze information in real-time by integrating all your data sources into one system. 

This lets you make more informed and data-driven decisions, ultimately helping your organization thrive. 

Building a Culture of Collaboration to Reduce the Risk of Data Silos

Building a culture of collaboration can be a game-changer in breaking down data silos and ensuring that important data is shared across your organization. 

By promoting teamwork and communication, organizations can foster an environment where data is shared seamlessly and decision-making becomes more inclusive and effective. 

Collaboration is key to the success of any organization looking to reduce the risk of data silos.

Leveraging Cloud Technology to Support Data Sharing and Access Control

Cloud technology has revolutionized the way we handle data sharing and access control. 

With cloud technology, you can easily store and share large amounts of data with other people or devices. This means you can access your data from anywhere and anytime, as long as you have an internet connection. 

Cloud technology also provides an added layer of security, ensuring that access to your data is only granted to authorized users— but giving users access to data is simpler than ever.

Leveraging cloud technology is not only user-friendly but also saves time and resources that could have been spent on maintaining data servers. 

By utilizing cloud technology to support data sharing and access control, you are taking a step forward in securing your data and making it more efficiently accessible— which goes a long way towards fighting data silos.

Deploying Ai-Driven Tools and Automation to Simplify Data Management Tasks

As businesses accumulate vast amounts of data, managing and making sense of it becomes increasingly complicated. 

Enter AI-driven tools, which allow for efficient data management through automation. 

With these tools, tasks such as data categorization, cleaning, and analysis are simplified, saving businesses valuable time and resources. 

The beauty of AI-driven tools is that they can learn and adapt to new situations, making them an essential part of any data management strategy. 

By embracing this technology, you can move away from manual data management methods and focus on using your data to drive growth and success.

Don’t Work For Your Data: Make Your Data Work For You

Overcoming data silos takes time and more than a little elbow grease, but successful business leaders know that the long-term rewards are worth the short-term costs.

The same 2022 report by Airtable and Forrester found that 80% of business leaders consider “reducing data silos” a top priority for their organizations.

By understanding why data silos occur and what the common pitfalls are, you can proactively build strategies to minimize their risk. 

Collaboration is key in fostering an environment where data silos cannot easily find a foothold. Cloud technology and AI-driven tools offer accessibility, convenience, and scalability, enabling seamless sharing and access control. 

In today’s highly competitive business landscape, data can be an anchor that eats up work hours and drains your resources. Or it can be your most powerful tool for honing your competitive edge.

The post The Dark Side of Data Silos and How to Overcome Them appeared first on Digital Adoption.

Applied observability helps a company make sure their software works well by using information in a smart and connected way. It can help a company in many different areas by turning the information they get from watching their systems into useful outcomes.

According to Gartner’s research, by 2026, organizations that have successfully applied observability will be able to make decisions faster and gain a competitive edge over their competition. This is expected to account for 70% of all businesses.

With the integration of applied observability practices into a company’s data lifecycle management (DLM) approaches, organizations and software engineers can use their insights to create an all-encompassing view of operations. 

Nonetheless, this requires utilizing sophisticated tactics for analyzing business operations information to accurately decipher available facts. This equips decision-makers with the knowledge they need immediately to make wise decisions more quickly and effectively.

To reap the full benefits, businesses must ensure that their data is up-to-date and accurate. By utilizing AI-driven automation and machine learning, applied observability can yield greater accuracy and reliability in data capture while ensuring that the generated results apply to the specific needs of each enterprise.

In this segment of our Digital Adoption Trend Report 2023, we’ll share how CIOs and IT leaders can leverage applied observability to fortify operational processes and increase business velocity. From identifying emerging trends in data capturing to uncovering new applications of AI-driven automation, the report will explore what drives businesses toward digital transformation and provide key insights into how this technology can be used for improved efficiency and greater results.

At the end of this report, readers will clearly understand what applied observability is, how to use it effectively, and why businesses must leverage it for better decision-making. The report will also provide detailed, actionable recommendations on implementing this technology within their organization.

What Is Applied Observability?

Applied observability can be defined as the ability to track the state and performance of software applications over time. It is a comprehensive approach for collecting data on software systems that can then be used to gain insights into system health, observability problems, and potential improvements.

This data can include logs, metrics, and events from all components of a software system, including the application and its underlying infrastructure. This data can then be used to generate real-time observability charts, reports, and insights that can help organizations quickly identify and resolve application and infrastructure observability issues. 

Applied observability offers a holistic and coordinated approach to utilizing observable data across multiple business areas. It shortens the lead time between stakeholder activities and organizational responses by providing a way for businesses to proactively plan decisions.

By combining the data they collect and analyzing it with AI-driven automation, applied observability helps businesses make better decisions faster. In addition, distributed systems, such as microservices and cloud computing, make storing and analyzing data within the organization easier to create more targeted insights.

Why Is Applied Observability Important?

Applied observability is dedicated to the notion that a business’s success relies on forecasting what lies ahead and crafting plans based on factual data. This aspiration serves as applied observability’s main compass for progress and growth. Through the diligent application of applied observability, businesses can reduce their response times to customer inquiries and bolster the efficacy of their daily operations.

To realize the advantages of observability, it is essential to be proactive instead of reactive. For example, IT professionals who leverage stakeholders’ actual behaviors and activities rather than merely relying on guesses or assumptions will have a significant edge over their competition. Analyzing observable data makes it possible to look for improvements in customer service, operational efficiency, and speed. 

Applied observability also enables organizations to uncover hidden patterns in their data that can help them identify operational issues, recognize trends, improve process optimization, increase customer satisfaction, make informed decisions regarding product launches, and realize cost savings.

Software engineering teams can reap tremendous benefits by employing observability as well. Testing various hypotheses and making data-driven decisions can minimize the risk of system failure and reduce development time. Observability solutions provide a comprehensive view of what’s going on within a system. This helps engineers quickly detect and diagnose issues and identify areas of improvement for system reliability.

The Three Verticals of Applied Observability

Most observability tools deal with the three pillars of observability: logs, metrics, and traces. This means they can collect and analyze data from these sources and provide a unified view of system performance. Logs give information on system events, metrics are numerical measurements of resource utilization and performance, and traces track the flow of a system request through its components. Let’s explore these three pillars in depth.

Logs

Logs are a record of events that occur in the system over time. They can provide details about errors, application performance, and more. Applied observability tools can aggregate log data, analyze it for patterns and anomalies, and provide alerts when something unexpected occurs.

Metrics 

Metrics are numerical measurements that can be used to monitor a system’s health. Applied observability solutions can collect metrics from various sources, such as log files, application performance management tools, and system resources. These metrics can then be analyzed to determine trends, identify correlations between different events, and even detect problems in the system before they become serious.

Traces 

Traces can be used to track a request’s flow through the system from start to finish, including all the components it touches. Applied observability solutions can capture traces as they happen and use them to detect bottlenecks, latency problems, and other performance issues. This helps teams diagnose and resolve problems quickly, reducing system downtime and improving user experience.

By understanding the three pillars of applied observability, teams can use the right tools to gain valuable insights into their systems and identify potential problems before they become serious.

Components Of Applied Observability

In addition, other components of applied observability include data acquisition, analysis, automation, and visualization. It’s important to understand each component and its role in applied observability so that organizations can optimize their use of this powerful technology.

Let’s take a more in-depth look at four major components of applied observability:

Data Acquisition

Data acquisition is gathering data from different sources for further analysis and use. Data acquisition is a critical step in any applied observability initiatives, as it provides the basis for all other activities, such as modeling, forecasting, and decision-making. It involves collecting data from various sources, including databases, files, and other external sources such as surveys or interviews.

Data acquisition is accomplished through various methods, including manual entry of data into a database or program, automated collection from Internet resources, and web scraping. In addition, machine learning and artificial intelligence tools can be used for automation in data acquisition. The goal of data acquisition is to obtain the most accurate, complete, and consistent data set that will allow the organization to make better decisions.

Data acquisition processes are typically customized to fit the needs of the project and organization. Depending on the nature of the data, it may require different collection methods, including manual entry, automated harvesting from websites or web scraping, and machine learning algorithms.

Once the data has been collected, it must be stored in a secure manner to protect its integrity. Data can then be analyzed using various techniques such as descriptive statistics or AI and ML algorithms. Observability tools can collect, analyze, monitor, and visualize metrics and traces. This gives users valuable insights into system performance, errors, usage patterns, and more.

Analysis

Analysis of the gathered data is then used to make decisions, conclusions, and predictions. It can also detect patterns, trends, and correlations in the data. Data analysis allows organizations to better understand their customers, products, services, and operations.

Careful consideration must be taken when collecting data from various sources, as this will affect how accurate the results are of any analysis. The right tools and processes should be in place to ensure the accuracy, completeness, and consistency of the data acquired.

Data analysis allows organizations to gain valuable insights from the data that can lead to better decisions and improved performance.

Visualization

Data visualization is an important part of any applied observability process. Visualizing data helps organizations gain insights more quickly and easily. Using visualizations, data can be presented in a way that is easier to interpret, aiding decision-making processes. Visualizing data also provides an easy way to share information with stakeholders, helping them make better decisions based on the data collected.

Applied observability is an important tool for any organization looking to make informed decisions based on data. By leveraging the right tools and processes, organizations can maximize the value of their data and gain insights that will help them take advantage of opportunities while also avoiding potential pitfalls.

Visualization is crucial in applied observability, helping organizations quickly detect issues and better understand customer behavior. Organizations can make better decisions and improve their performance with applied observability.

Automation

Digital transformation efforts continue to accelerate as organizations seek ways to leverage the digital disruption of recent years and maximize business outcomes. Adopting and acquiring new technology means that IT leaders become increasingly responsible for monitoring various complex and dynamic systems. 

This can include capturing, storing, analyzing, and presenting data using manual human processes. Using outdated monitoring procedures may be suitable for overseeing basic, static systems but quickly prove inadequate for maintaining the complex and ubiquitous IT ecosystems found today.

This can lead to IT teams feeling inundated with an overwhelming number of metrics. The majority of data generated by companies remains both unseen and unused, despite its potential to deliver meaningful insights. By switching strategic approaches and opting for observability over monitoring, IT teams can gain greater visibility over vast continuous data sets and distributed environments.

As such, automation has become a crucial component of applied observability, allowing organizations to detect issues quickly and take necessary action in a timely manner. Automation also increases the accuracy of the data collected, helps reduce manual errors, and enables faster processing of large amounts of data. 

Automation of data acquisition is also possible through deep learning technologies like artificial intelligence (AI) and machine learning (ML). The emergence of artificial intelligence for IT operations (AIOps) means that organizations now have access to disruptive bleeding-edge technologies that provide them with more efficient ways to extract data value.

This could include automating issue detection, automatically determining root cause analysis, or even automating remediation. AI-augmented automation compliments observability initiatives by delivering insights on a much larger scale and at higher accuracy.

Measuring The Impact of Applied Observability

To accurately measure the impact of applied observability, businesses must track and monitor multiple KPIs related to customer experience, efficiency gains, cost optimization, risk management, and process development.

By monitoring these metrics over time and comparing the results to past performance levels, companies can identify opportunities for improvement and begin to understand how their data-driven decisions influence overall business performance.

It’s crucial to measure the impact of applied observability over a period of time, as it can take weeks or even months before an organization begins to reap the benefits of AI-driven automation. However, with continuous monitoring, businesses can identify problems early on and adjust accordingly.

Identifying The Demand Criterion For Applied Observability Solutions

The need for an observability solution is propelled by various forces, ranging from the ever-growing demand for digital services to the urgency of dealing with complex IT systems and applications.

To make an informed decision, it is essential to consider the following factors:

• The demand for applications to manage ever-increasing corporate activities is greater than it has ever been before.
• The demands of users have reached their peak, and they will not hesitate to switch tools if they experience unfavorable interactions.
• Development teams constantly innovate and refine applications and software systems to reduce release cycles and keep up-to-date with the latest technology.
• In the modern era, IT teams manage both traditional and cloud-native applications.
• Distributed system architectures, especially those built with microservices and cloud-native technologies, have become increasingly complex. As a result, it’s necessary to use observability tools to help debug systems and improve their performance.
• The use of cloud-based services and third-party APIs is rapidly increasing as organizations recognize their immense potential to benefit businesses at all levels.

Due to these factors, the complexity, dependencies, and points of failure in a distributed architecture have skyrocketed. A Cisco poll of more than 1000 worldwide IT decision-makers revealed that the quick rate of modernization and digital transformation during the pandemic has drastically magnified this issue even further.

Consequently, massive amounts of operational data are generated throughout the technical chain – from applications to infrastructure and networks. It’s become increasingly difficult for organizations to manage this complexity due to a lack of visibility and an inability to prioritize their strategies.

How To Use Applied Observability In Your Organization

Applied observability provides businesses with real-time, actionable data to gain an understanding of their systems and operations. Companies can then use this data for a number of purposes, such as improving system performance, gaining insights into customer behavior, and optimizing processes to increase efficiency. This can be achieved by monitoring the system’s performance and integrating applied observability into the existing analytics infrastructure, giving businesses a holistic view of their operations.

Here are some additional tips for using applied observability in your organization:

• Automate data acquisition process as much as possible to ensure the data’s accuracy, completeness, consistency, and timeliness
• Use AI and machine learning tools to automate anomaly detection and forecasting processes
• Leverage visualization techniques to interpret data quickly and easily.
• Take advantage of predictive analytics to anticipate customer needs and develop strategies accordingly
• Monitor the performance of your business operations through dashboards or alerts so you can take action when necessary
• Analyze customer feedback or other structured sources to gain insights into customer behavior
• Leverage automation to help scale the applied observability processes

• Utilize site reliability engineers (SREs) to ensure the proper functioning of all systems
• Use actionable insights to optimize the end-user experience
• Integrate insights from analytics to measure and improve marketing campaigns
• Develop predictive models to anticipate changes in customer demand or market trends

Preparing For The Future: Applied Observability

As data collection and analysis become increasingly instrumental in forecasting the future state of IT operations, organizations will need to invest in the right tools and processes to maximize the value of their data. Observability is not a single technique or definite market, it’s an interconnected collection of organizational layers and business processes that leverage tools for collecting data to be observed.

Gartner predicts that in the next five years most companies that apply observability will experience a reduction in decision-making latency, thus giving them an edge over their competition.

By applying the best practices outlined in this article, businesses can easily prepare for the future by incorporating applied observability into their operations. The goal of this practice is to gain an in-depth grasp of how a system works, ultimately enabling teams to make sound judgments about enhancing its capabilities.

The post Applied Observability appeared first on Digital Adoption.

But the excitement of digital transformation does not stop there. Every year, innovations, approaches, and applications all help businesses take their digital transformation journey in unpredictable ways. Applications of an old technological framework are not enough, and flexibility around technology is now crucial to driving business growth. 

For years, global organizations have been making plans for digital implementation strategies. In 2023, those large-scale digital transformations will become more visible than ever. For example: 

• The 2020 UN roadmap for digital cooperation plans for integration across countries using new technology 
• In 2022, the UK government revealed its three-year plan for wide-ranging digital transformation 
• At the end of 2022, The EU program “A Europe Fit for the Digital Age” was planning dozens of specific legislative changes to accelerate digital transformation journeys across the continent.

Meanwhile, more industry-wide digital adoption changes will become clear. By 2025, the UK’s traditional copper phone lines will be switched off in favor of internet-based protocols. 

This article will take stock of the current situation. It will remind us that digital transformation is an essential and functional concept and explain how it will look in 2023. We’ll explain ten critical benefits of digital transformation and significant trends to look out for. 

In the conclusion, the article will consider the future of digital transformation. 

Digital transformation benefits CIOs & IT leaders should consider

The advantages of digital transformation are numerous and varied. For businesses, leveraging digital technologies can help reduce costs, improve operational efficiency, provide better customer service, create new revenue streams, and improve the customer experience. For employees, working more efficiently with digital tools can increase productivity and job satisfaction.

Businesses rolling out their digital transformation strategies in 2023 can expect some of the following ten benefits: 

1. More Extensive Data Collection

Digital transformation will help businesses to gather accurate and detailed data. With more information about customers’ buying journeys, staff engagement, and the company’s resources, organizations can leverage advanced data analysis to unlock the decision-making process.

2. More Effective Resource Management

Organization-wide resource management can showcase the benefits of digital transformation. With improved asset tracking, resource allocation, and strategic planning, businesses can increase their efficiency while keeping costs down.

3. Data-Driven Customer Insights 

When it comes to customers, digital transformation creates many opportunities to monitor, process, and analyze data. Before businesses adopted digital solutions, the relevant information for data-based insights would be fragmented across many different systems and departments. Now, advanced CRM technology means that customer data can be efficiently contained in one place, combining personal customer information, social media metrics, and other information from across the business. 

In 2023, businesses will have more opportunities to observe customer behavior, tailor their marketing solutions, and adjust their product offerings to suit their changing customer base. In doing so, they can improve customer retention and plan for sustained growth. 

4. Enriched Customer Experience 

Companies can use data from the customer’s buying journey to provide the services they need. With access to more accurate customer information, businesses can optimize communications and product offerings, offering individualized experiences that keep customers coming back.

5. Encourages A Digital-First Culture 

A company that’s genuinely embraced its digital transformation will seek digital solutions at every opportunity. They don’t just use software to solve existing problems. Instead, they use innovative digital approaches to structure their work. Digital-first approaches are another method of keeping margins slim and staying ahead of the competition.

6. Higher ROI 

On a small scale, digital transformation can be very cheap. But an all-encompassing digital transformation will incur high costs. Although CEOs and executive leaders are increasingly willing to take risks on digital solutions, they must be able to see how their investment of time and money will lead to results. 

In 2023, the ROI of the digital transformation strategy will be better than ever. With more opportunities to improve operational efficiency, limit human error, and enhance productivity, a company-wide digital culture can quickly implement fantastic results. 

7. Better Operating Model 

Large businesses can expect to dramatically reduce their operational complexity through digital adoption. Digital models can efficiently monitor performance and identify areas of improvement across the business. By eliminating redundancies and creating greater efficiency in operations, companies can increase their productivity and unlock growth potential. Additionally, with digital insights, companies can model multiple scenarios to predict outcomes and make informed decisions quickly.

8. Improved Agility 

When done right, digital transformation is not an isolated set of practices. It represents a new agile mindset that empowers organizations to be highly resilient to change.

Detailed monitoring systems mean businesses can quickly detect and resolve unforeseen events and take advantage of unseen opportunities. And with emerging technologies creating new opportunities all the time, digital transformation allows organizations to integrate that technology into their workflows with ease.

Digital transformation encourages an agile approach that enables businesses to quickly keep up with the ever-changing market.  Ultimately, this improved agility helps companies increase customer satisfaction and improve profits.

9. Enhanced Supply Chain Management 

Each link in a supply chain may be simple. But every stage comes with its own set of risks, opportunities, and knock-on effects. In 2023, digital transformation solutions will take on logistics challenges, making it simple to accept deliveries, monitor inventory, and monitor dispatches. 

Digital tools will help leaders to monitor their entire supply chain from a single platform. 

By streamlining the transportation process, companies can reduce the risk of delays and enhance customer experience. The struggles of supply chain management may be hidden from customers, but the benefits are obvious. When companies can move goods faster at a lower cost, everyone wins. 

10. Improved Competitive Advantage 

A digitally transformed company’s competitive advantage comes from a powerful combination of all the benefits. The following areas are beneficial for finding a competitive edge: 

• Efficient processes that allow them to work harder with less input
• Their ability to respond quickly, accurately, and proactively to customer needs, market trends, and changes in technology
• Effective internal employee systems that secure employee satisfaction and retention

As such, making digital transformation a central component of business strategy in 2023 is in keeping with long-term business goals in a highly competitive marketplace. 

Why Is Digital Transformation Important? 

When a company decides to use new technologies to support its business processes, they are at the start of a digital transformation. When technology makes every single process more efficient, they have reached digital maturity. Although digital transformation may start small, only a few companies achieve digital maturity.

Digital transformation offers a range of benefits. It makes it easier for businesses to access data, measure customer behavior and create better products. It introduces the working practices that help companies to take advantage of new technology, create more efficient processes, and develop customer-centric services. It also helps ensure market longevity and competitive advantage by keeping up with customer demands.

When leaders embrace digital transformation across the entire organization, they are adjusting to a new way of thinking, forging new business strategies that will help them stay ahead of the competition in an ever-changing digital market.

What Does Digital Transformation Look Like In 2023?

Although the aims of digital transformation will not be radically different in 2023, businesses will increasingly set ambitious goals and comprehensive strategies to ensure the outcomes they need. 

Today’s businesses know that digital transformation is essential for long-term growth, and in 2023, the fundamental goals of digital transformation will not change. Companies worldwide will use digital solutions to achieve better value for all stakeholders, improved service for clients and customers, and a more favorable work environment for employees. 

But in 2023, the stakes are higher than ever. Effective digital transformation will be increasingly important in an ongoing economic uncertainty. Companies adopting digital transformation initiatives will need to learn from past failures to ensure future success. 

Companies are increasingly aware of the ambitiousness they need to secure an effective digital transformation. Leaders now know that digitally mature organizations need to attentively join up many specific approaches, using digital business models to change the way a company works. They will need to ensure measurable results for their innovative approaches, clearly demonstrating the benefits they are bringing. 

In short, a robust digital transformation strategy will need to be front-and-center for any company seeking to implement new digital solutions in 2023. 

The post 10 Benefits of Digital Transformation in 2023 appeared first on Digital Adoption.

However, it can be hard to get right and Digital transformation initiatives can easily fail.

Global spending on DX doubled from 2017 to 2022 (as data from Statista shows), and shows no sign of slowing. So any business investing their precious resources into digital transformation has got to learn from the best examples. 

That’s what we’ll do in this article by looking at how IKEA, Armstrong, Capital One, Microsoft, and Nike all found a way to maximize the outcomes of their digital transformation projects. 

Using high-impact digital adoption strategies, these companies set a great example for any organization that wants to improve its digital capabilities.

What is digital transformation?

When a company goes through a digital transformation, it implements digital solutions to make a positive change to the organization. Transformation projects can be tiny, vast, or any size in between. 

Digital transformations can look very different between companies. It might be a new standalone online portal, a centralized system to manage human resources, or a complete re-configuration of a business. But they all count as digital transformations. 

Digital transformation does not happen in isolation from other business activities. Every digital transformation requires an effective and appropriate strategy. This means looking at the entire company and thinking about what changes would benefit the most people. Once you have your goals, you can start developing a plan to make your transformation happen.

Digital transformations can be challenging to implement, but the rewards can be great. With a successful transformation, you can improve your company’s bottom line and make it more agile and responsive to change. 

However, at the start of a project it’s difficult to predict the difference between success and failure. But what do industry insiders have to say about the building blocks of a great digital transformation? Let’s take a look. 

What are the four areas of the digital transformation process

There are many competing ways of judging how to deploy new digital technologies effectively and efficiently. However, the four main areas of digital transformation include: 

• Customer Experience. Digital transformations should improve the service that customers get from a company. Even when the transformation affects internal processes, management should focus carefully on the end result.
• Data & Analytics. Companies can find ways to gather precise data across their systems, providing a stable basis for future decision-making.
• Cloud Computing. The cloud is a vital tool for digital transformation, enabling software provision and data sharing that would have been unthinkable a decade ago.
• Mobility. Software and digital technology are used across many devices. Digital transformation does not just happen on desktop PCs. It travels wherever processes can be improved.

A small-scale digital transformation may develop just one of these areas. But a truly digital workplace will excel in all of them.

The value of digital transformation 

There are huge benefits of digital transformation in 2023. 

As with any innovation, they are intended to improve operational efficiency, increase organizational agility, and create a competitive advantage that leads to revenue growth.

The specific improvements of a digital transformation journey will depend on the business, the transformation strategy, and the intended outcomes. 

However, some benefits can include the following:

• Improved customer experience
• Greater market reach
• More efficient supply chains
• Greater employee productivity and job satisfaction
• Well-targeted marketing campaigns

In short, digital transformation can positively impact every area of a business.

The state of digital transformation in 2023

In 2023, businesses are continuing to imagine and re-imagine what digital transformation should look like. Across different industries, we see improved services, better customer engagement, and company relevance. So, digital laggards now have many examples for inspiration and guidance.

Some recent transformations include:

• McDonald’s in Italy streamlined their procurement processes through an online portal;
• Domino’s Pizza utilized the internet of things to help customers place orders;
• Hasbro used data about their customers to improve their advertising and marketing;
• UCIS reduced paper use by adopting digital applications using AWS cloud computing.

These cases illustrate the varied roles technology can play in an organization. The best companies will not be interested in “off-the-shelf” solutions. Instead, they will find new ways to deal with their fundamental problems. 

The top digital transformation success stories

If you want to know how companies adapt to a changing digital landscape, it’s essential to look at some case studies. From the many success stories out there, the following five companies are incredibly successful examples of large-scale digital transformation that are highly relevant for 2023. Through Ikea, Armstrong, Capital One, Microsoft, and Nike, we get a much better view of how digital transformation works. 

IKEA

IKEA dominates the global furniture industry. The company has done this by adapting to new working practices. Their digital adoption strategy has recently helped them keep their competitive advantage over other companies.

IKEA’s stores used to be very different from an eCommerce platform. But when they started to prioritize the digital side of their business, online sales tripled. Their brick-and-mortar stores now act more like fulfillment centers than retail outlets. Even within stores in selected countries, customers can now pay for their purchases without going through the checkout.

The example of IKEA shows how a full digital transformation process can help a company to stay relevant. If you want to know more, take a look at Thomas Stackpole’s write-up in the Harvard Business Review. 

Armstrong World Industries

AWI is one of the USA’s leading manufacturers of ceilings and walls, bringing in a revenue of over $1 billion in 2021.

Armstrong’s digital transformation started by improving weaknesses in its financial processes. This meant investment in Enterprise Resource Planning (ERP) software, transparent spending, and attention to cybersecurity.

These improvements became the basis of further digital strategies to support customers through their buying journey, with a massively improved website and customer services.

For Armstrong, the digital transformation started with financial systems but ended up providing a fully improved customer experience.

Capital One

Capital One has used new artificial intelligence technologies to provide brilliant customer service. As one of the first banks to manipulate Amazon’s Alexa-enabled devices, their customers can now quickly get the information they need when they need it.

By asking, “what’s my balance?”, “How much is my next car payment?” and “what’s the due date on my next credit card bill?” customers get answers without even logging in to online banking.

Capital one shows how a focused digital adoption strategy can improve customer service. Their digital transformation project reconfigured only part of the business. At the right time, small interventions can produce very effective changes. 

If Capital One sounds like a useful example for you, you can find out more about it in a more detailed analysis in Forbes.  

Microsoft

Microsoft have been leaders in software innovation since the dawn of home computing in the late 1980s. But faced with the advent of cloud-based software systems in the early 2000s, their long-established distribution model suddenly seemed dated.

Their digital strategy was to completely overhaul their delivery systems, using their proprietary cloud solution. They launched Microsoft Azure in 2008. Azure has now become the 2nd biggest cloud provider in the world, providing a vast range of digital services for individuals and companies of all sizes.

As market leaders, Microsoft could have chosen to behave like Blockbuster video. Instead, they made a shrewd decision to completely update their digital strategy. If they never launched that radical change program, they could have been history. 

Our article on Microsoft Azure gives you the full lowdown on this valuable product. 

Nike

Nike, the global sportswear leader, showcases the excellent results that digital transformation initiatives can create.

Nike’s entire approach to branding, sales, and technology has changed.

They now focus on becoming a robust direct-to-consumer brand, reducing their retail partnerships, and increasing their work to create online sales. Programs like Nike Training Club collect detailed consumer data and use advanced analytics to make sense of the patterns. Smaller physical stores now do a lot of work to promote the Nike brand.

Behind the scenes, they use headless commerce to develop multiple online sales channels, with particular expansions into mobile apps and technology.

Like IKEA, Nike has dominated their market section for a long time. Their success in digital transformation means that they will continue to dominate. Instead of sticking with what they know, they’ve taken risks that have paid off. As a result, they’ve become a trend-setter in digital infrastructure, who are even used as a case study for teaching up-and-coming IT change leaders. 

Why are some businesses more successful than others at DX?

Companies like Nike, IKEA, and Microsoft, make digital transformation look easy. These success stories are inspiring. However, not every digital transformation project succeeds. And when digital transformation fails, it fails big, sucking in money, limiting sales, and destroying staff morale.

The problems are rarely just technical. Failure usually comes about when the implementation is poorly planned. Some fundamental issues may include the following:

• No vision for the transformation;
• Poor communications across the organization;
• Lack of buy-in from staff;
• Poor timing.

There are ways of preventing these problems. For example, using a digital adoption platform as the backbone of digital organizational changes can support leaders in making effective decisions when planning organizational change adoption. 

IT consultants and digital transformation frameworks can also significantly impact the chances of success.

How every business can remain transformative in an uncertain climate 

Current business leaders and employees globally have lived through some of the most uncertain years in a generation. 

When a crisis comes, digital transformation initiatives can learn from models of “complex change”. Organizational change is complex when it is made challenging by one or more factors, including crises, employee resistance, and financial demands. 

Advanced managerial models, such as the Lippitt-Knoster model of complex change, can provide the help organizations need to keep moving forwards. 

How To Drive Successful Digital Transformation

Driving a successful transformation is all about developing the right culture and using the right strategies. Here are some important areas that will help you create your own success story: 

• For digital adoption, the employees in an organization can create more problems than the technology itself. At every stage of the process, staff must be encouraged, trained, and listened to. With their investment, it will be possible for a transformation to succeed.
• Digital infrastructure also should be part of the solution. A Gartner report shows that by 2025, up to 85% of business operations will be built on cloud services. Cloud solutions are now a proven way of securely handling transformation. An efficient cloud platform sounds like a big change, but it will help the whole process.
• As the transformation process progresses, collecting data is more critical than ever. Leaders can use data to understand the employee experience and ensure that supply chains are moving appropriately and technology is utilized effectively. A digital adoption platform is one way to make technical data collection much easier.
• Find a management style that will help the business to keep up with the complex change. Agile methods are a proven method of success, giving leaders and employees the tools they need to change and adapt as a change process goes on.

Looking Forward: The Future of Digital Transformation & Business Success 

Businesses that want to use future technology successfully must learn how to embrace change. As new technologies emerge, leaders must find new ways of dealing with their problems. 

Some strategies that will improve the chances of success include: 

• Find opportunities to automate wherever possible. Automating routine tasks is one of the most straightforward applications of new data systems. More importantly, it can be accomplished without overall changes to the business. 
• Create opportunities for continual training and learning. Get staff up to speed on the solutions your leaders are investigating. Send them on specialist courses. Introduce learning opportunities within the company. If staff get stuck in their old ways, they will be less willing to adapt to new challenges. 
• Consider alternative business models and organizational structures. As the examples above illustrate, a complete digital transformation goes hand in hand with significant changes to the organization’s overall working model. When a business continually considers its options, it will be better placed to adapt to changing markets.
• Foster an agile mindset in every employee. Agile management techniques are one of the best ways to achieve successful change. When employees can approach tasks in an agile way, they will be ready for anything. 

Learn How to Drive Growth From Success Stories 

Just like any change management project, digital transformation is complicated and risky. But the best research routinely shows that it’s well worth the trouble. In July 2023, analysts from McKinsey showed that digital leaders could achieve shareholder returns of 8.1% – in comparison to 4.9% for digital laggards. 

When companies proactively look for a digital transformation roadmap that suits their business goals, they unlock new ways of doing business in the modern age. The examples in this article show just a few ways of achieving that goal. Some research suggests that leadership makes the key difference – but really, building a culture of digital transformation is a company-wide priority. 

So if you’ve enjoyed hearing about the top digital transformation success stories, keep on reading, thinking, and exploring, and you’ll find the innovations your company needs. 

The post The Top Digital Transformation Success Stories For 2023 appeared first on Digital Adoption.

Although Adobe OCR does have its use cases, there are plenty of other OCR options on the market. Below we will compare Adobe OCR to other types of popular OCR applications, including hardware and software, both free and paid.

Adobe OCR vs. Other OCR Technologies

Here is a breakdown of Adobe OCR and a wide range of other OCR software tools.

Adobe OCR

Adobe OCR is designed to turn scanned documents into searchable PDFs.

Here’s how it works:

• Adobe Acrobat uses OCR technology to extract written characters from an image file or a scanned document
• Acrobat will do its best to match fonts in the PDF to your scanned document
• PDFs are searchable and the text can be copied and used in other documents
• OCR can scan PDFs to enable document exporting to other formats, such as Word

OCR is incorporated into Adobe and it is automatically performed when you engage in certain activities. For instance, by clicking on the Tools menu and then on “Edit PDF,” Adobe will automatically use OCR to enable editing.

These features can be very useful for transforming scanned documents into PDFs and PDFs into other document formats.

There are, however, drawbacks.

Using Adobe OCR, for instance is not free – you must purchase a subscription to Adobe Acrobat Pro DC.

Also, its preferred format is PDF which may or may not be desirable.

Microsoft OCR

Microsoft Office offers another option for OCR. 

Microsoft OneNote supports OCR, enabling you to print out documents or copy images into OneNote an extract characters from those images.

Simply by right clicking on an image or a printout within a OneNote document you can copy text from the picture and onto your clipboard.

Although there was more support for OCR in past versions of Word, OneNote remains the best option for accessing Microsoft OCR.

Google OCR

Google OCR can be used several ways, either as a software user or as a developer.

Opening an image or a PDF in Google Drive, for instance, enables you to convert that image into a Google Doc, which will automatically extract text from images with OCR.

Gmail also has a feature that allows you to automatically enable OCR for images in your email.

Developers can also use Google’s API to create custom OCR applications.

Free OCR Software

There are also a considerable number of free OCR software tools online. 

Many of them allow you to upload an image or a PDF and they will attempt to automatically extract text from those files.

Although the quality may not be as good as Adobe, they are free. For the casual user who does not want to pay for an Adobe subscription, this may be the best bet.

OCR Hardware

Another OCR option is actually purchasing OCR hardware.

This route is the most expensive, but for digitizing workplaces that need robust OCR capabilities, this may be the right choice.

Typically OCR hardware includes devices such as scanners. These scanners also include OCR software, which may be proprietary.

Use cases for these hardware devices include scanning books, scanning paper documents, digitizing business records, and even scanning art.

Prices for hardware can vary a great deal, ranging from the low hundreds of dollars to several thousand or more for industrial-grade solutions.

For many, purchasing a scanner printer may be the busiest and best solution. They have the capability to both print and scan, and the right ones have OCR technology included. When purchasing a scanner printer, simply read the product details to determine if it includes OCR or not. Those that do will often convert PDFs to word documents, emails, and so forth.

Choosing the Right OCR Software

Not all OCR software is created equal. As we have seen above, there are several options, and each has its pros and cons.

Here are a few to consider:

• Price. Naturally, free is better. However, the higher the price points, the better the quality of the OCR, in general. A business, for instance, that wants a high quality OCR software or hardware setup, may consider spending a great deal. Organizations intent on streamlining business processes and digitizing records, for example, often invest huge sums in OCR technologies.
• Use case. Another point to consider is how you will be using it. For the casual user who scans a document once a week, it may be unnecessary to pay for a robust OCR solution. However, as we just saw, a business or someone working from home may need a much more sophisticated and accurate solution.
• Compatibility. Adobe OCR is naturally focused on PDFs, since PDFs are the company’s proprietary file format. The same goes for do Google Docs, which focuses on translating images into the Google Doc format. If you will be using the same workflow repeatedly, it pays to find a setup that works directly with the filetype you need.

OCR can be a very convenient and valuable automation tool. And although there are free options available, in some cases, it may be necessary to find a work around or invest in a paid solution.

The post Adobe OCR vs. Google OCR vs. Microsoft OCR vs. Other OCRs appeared first on Digital Adoption.

For that matter, what is hyperautomation and how does it differ from automation, intelligent automation, robotic process automation (RPA), and other types of automation?

In this guide, we will look at hyperautomation platforms, their benefits, and how they are set to change the business world.

What Is a Hyperautomation Platform?

Hyperautomation refers to a combination of technologies and techniques, such as AI and RPA, designed to automate manual workflows and even complex business processes that require human judgment.

A hyperautomation platform is a software platform designed to enable AI-driven automation within the business.

For years, top research firms and consultancy’s have identified hyperautomation as being one of the top strategic technology trends.

According to many experts, hyperautomation will become essential to staying competitive in the years ahead.

Given the benefits of automation and hyperautomation, this prediction shouldn’t be surprising. One common question that arises when discussing hyperautomation, however, is around the difference between “standard” automation and hyperautomation. This question, in turn, leads to questions about the advantages of one versus the other.

Hyperautomation vs. Automation

Automation is a general term that refers to the use of machines to perform tasks normally done by humans.

Hyperautomation, on the other hand:

• Uses AI and machine learning (ML) to identify processes that can be automated
• Automates processes that span vertically and horizontally across the organization
• Integrates multiple different types of automation
• Results in the increased automation of cognitive processes

Some even used terms such as “intelligent” to describe automation techniques that tackle cognitive activities.

The real question for many should focus on how hyperautomation will impact the organization and the future of work.

Hyperautomation Exponentially Accelerates Productivity 

Hyperautomation includes the word “hyper” for a reason – this type of automation exponentially increases productivity wherever it is applied.

Machines operate at speeds multiple orders of magnitude greater than humans do, which can result in performance gains that vastly outstrip the performance of humans. 

If, for example, it takes humans several hours or days or even longer to complete a task, an automation platform can perform the same task in significantly less time – often hours, minutes, or seconds. The time frame will naturally depend on the task in question, but such major gains are typical for many types of tasks.

This implies several things:

• Automation platforms can free up human time for more valuable activities, such as strategic tasks
• Organizations can spend less money on human labor and instead invest in automation tools
• Companies leveraging automation can act and react more quickly
• Increased efficiency, speed, and organizational agility can free up resources which can then be used to drive innovation

Ultimately, benefits such as these can result in major competitive advantages. More importantly, as mentioned, many research firms and consultants these believe that the advantages offered by hyperautomation are so great that they will create a gap between those who do and don’t adopt this technology.

The Future of Automation and Hyperautomation

The use of automation and hyperautomation has been increasing for years and it will continue to increase. 

Eventually, hyperautomation platforms will become normal – but what does that mean for the workplace, operating models, and business structures? 

Will humans be out of work? 

Or will we work harmoniously alongside machines?

Predictions vary somewhat, but they do share the same themes. Here are some of the most common:

• Automation will absorb low-skilled jobs, such as administrative positions
• The increased need for automation tools will increase demand for technically skilled IT staff
• The “automated enterprise” will become the norm
• Tasks that have traditionally required human judgment, such as strategic decision-making, will increasingly involve the use of advanced automation platforms, such as hyperautomation platforms

The impact of automation on jobs remains to be seen. Although it will result in a shift in the composition of the current job market, it is difficult to say whether or not the net impact will be negative or positive.

Either way, organizations should begin to prepare now.

Preparing for the Age of Hyperautomation

Some organizations have suggested that humans and machines will work alongside one another. Although this may seem like an exaggeration, the evidence presented so far makes it clear that the future of work will be heavily automated.

Every organization should therefore be ready for this age of automation.

To prepare, organizations should:

• Adopt leading automation and hyperautomation platforms, such as digital adoption platforms (DAPs)
• Become more digitally mature
• Invest in other emerging technologies that work in concert with hyperautomation platforms, such as AI, ML, and IoT
• Understand the technology trends that will define tomorrow’s business landscape
• Develop forward-thinking strategies designed to leverage those technologies to
• Build a digital culture that prioritizes the use of technology
• Embed technology into the organization at every level, from the organizational strategy to the day-to-day workflows of frontline employees

In short, organizations should become digital-first companies that use technology to spearhead their strategies, innovate, increase efficiency, and enhance customer value.

The post What Is a Hyperautomation Platform? appeared first on Digital Adoption.

Below, will look at these terms, as well as a set of other concepts related to performance improvement.

Task Mining to RPA: A Digital Transformation Dictionary

These terms all involve the collection of data, but their usages are slightly different. They do, however, tend to focus on business activities related to process improvement.

Let’s look at the definition of these terms, plus a few other related terms.

Task mining. Task mining refers to the collection of front end user interactions, such as employees’ interaction with software. This data is useful for analyzing employee performance at the level of the workflow.

Process mining. Process mining refers to the collection of back end data from process logs and other data sources. The data collected is typically used to gain insights into the efficiency of business processes. Then, using some of the other tools discussed below, that information Ken help improve those processes.

Data mining. Data mining is a term used in the world of data science. It means extracting data from large datasets, such as web sites. That data is then passed along the data pipeline for further processing.

Process discovery. Process discovery is often used synonymously with task mining. The aim is to extract and analyzed data from software analytics, then use that to understand and improve processes.

Business process management. Business process management, or BPM, is a business discipline dedicated to managing and improving business processes. This discipline will use a variety of techniques and tools to accomplish its aim, including some of those covered here.

Business process improvement. Business process improvement refers to a specific set of techniques within business process management. Unsurprisingly, the aim is to improve business processes incrementally.

Business process modeling. Business process modeling is the practice of graphically representing business processes. Diagrams, flowcharts, and other visual representations make it easier to grasp the components of a process. That understanding can then help business process managers improve those processes.

Continual improvement. Continual improvement, or kaizen, is a concept derived from Japanese management practices. The idea is to gradually and continually enhanced processes over a long period of time, rather than quickly transforming them.

Business process analysis. Business process analysis aims to understand the strengths and weaknesses of existing business processes. It is both a role and a discipline within the organization, and business process analysts will utilize many of the other concepts and tools covered here.

Business transformation. Business transformation refers to a more comprehensive type of organizational change. Process improvement is gradual and incremental, but not transformational. Transformation, on the other hand, is transformational and can take place either slowly or quickly.

Digital process automation. Digital process automation is the process of using digital tools to automate workflows and tasks. Automation and the other concepts covered here go hand in hand – for instance, automation improves process efficiency, relies upon process mining, and drive business transformation. 

Workflow automation. Workflow automation means using digital tools to automate specific day-to-day workflows. For example, digital adoption platforms (DAPs) can be used to automate each step in a digital workflow. This can improve process efficiency and free up employee time for other activities.

Robotic process automation (RPA). RPA uses software robots too automate business processes, usually manual workflows. Like other types of automation, RPA works in concert with process mining, task mining, and other process improvement techniques.

Hyperautomation. While RPA refers to the automation of low-level tasks, hyperautomation refers to the automation of cognitive activities and complex business processes. This type of automation involves the use of artificial intelligence, machine learning, and complex technology solutions.

Business intelligence (BI). BI analyzes business data to gain insights into the organization’s health, process performance, and operational efficiency. This data is then used to inform strategic decisions.

Digitization. Digitization refers to the process of making something digital, such as a paper record. It can also refer to changing analog processes to digital processes, such as moving from fax to email.

Digital transformation. Digital transformation includes digitization, but it takes the process one step further. It also includes the transformation of processes, business strategies, operations, and so forth.

All of the concepts covered here are tools in the toolbox that are used by business analysts, business process managers, executives, and anyone else interested in improving organizational performance.

Putting the Pieces Together

Tasks are the building blocks of workflows, which are the building blocks of processes, which are the building blocks of a business. 

Any organization intent on transformation, either gradual and incremental or radical, will need to examine every aspect of the business, from top to bottom.

This means assessing strategy as well as the resources utilized at the process and workflow levels.Tools and techniques such as those covered above include many of the key concepts related to digital business transformation. Professionals interested in improving their organization’s digital maturity should start by researching some of the concepts described here.

The post Task Mining to RPA: A Digital Transformation Dictionary appeared first on Digital Adoption.

Natural Language Processing (NLP): Meaning and Techniques

Natural language processing (NLP) is an AI discipline that processes, analyzes, and generates natural human language.

More specifically, NLP focuses on areas such as: Data mining. Analyzing large sets of unstructured linguistic data.

• Semantic analysis. Assessing the meaning of texts. 
• Sentiment analysis. Scoring the sentiment, or positive and negative emotions, of a text.
• Generative AI. Producing natural-sounding language.
• Optical character recognition (OCR) and speech recognition. Recognizing written characters or verbal speech. 
• Syntactic analysis. Parsing and analyzing the grammar of a text. 
• Text summarization. Rephrasing or summarizing text.

These are just a few examples of the most common NLP tasks and techniques, And although they may seem esoteric or irrelevant from a business perspective, NLP is being used to create cutting-edge AI apps that can and are adding significant bottom-line value to organizations around the world.

How NLP Can Drive Business Growth

NLP is a type of AI that can automate a number of business tasks, such as:

• The digitization of business records. Physical records are costly, time-consuming to store and process, bad for the environment, and they can also be inaccurate. Using NLP techniques, such as OCR, businesses can save on processing and storing records. 
• Scanning IDs. Certain businesses or government agencies, such as transportation security checkpoints at airports or border stations, will often use OCR technology to scan IDs. This removes the need for humans to manually enter data from the ideas, which can take time and increase the chances of errors. 
• Extracting text from paper forms. Typically, when customers fill out a form at a business, staff will enter that information manually into a computer system. With the right technology, however, OCR and NLP applications can do this work on behalf of humans, saving both time and money.  
• Offering customer support or technical support. Chatbots have become common in many online businesses. They can be used to not only provide information to customers, they can also be programmed to perform tasks automatically. WalkMe’s ActionBot, for example, can be programmed to perform work-related tasks without the need for human intervention.  
• Dictating and transcribing text. There are many scenarios where people are required to transcribe text: business professionals take notes during meetings, stenographers transcribed court proceedings, reporters take notes at press conferences, and more. speech recognition can automate these tasks, saving significant time and money. Otter.ai, For instance, automatically transcribes meeting notes and can export those into text files, word documents, and so forth.  

Additionally, NLP is actually transforming user interfaces for a number of applications, such as search engines. 

Google, for instance, is pioneering the use of NLP for voice user interfaces, the use of voice to perform searches for daily tasks such as scheduling appointments, sending emails, or making calls.

At first glance, these examples may not seem revolutionary or transformative, but they actually can drive significant business growth when used properly – they are, after all, a form of automation, which is being used to transform the way businesses operate. 

Tomorrow’s companies, some argue, will actually be driven by AI and machines, so technology such as this will become a pillar of tomorrow’s digital first organization.

To understand why let’s look at a few of the key advantages of NLP, AI, and automation:

• Automation tools can performed tasks far more efficiently than humans. Not only do machines not make errors, they can perform tasks much more quickly and reliably, twenty-four hours a day, seven days a week. 
• Automation tools cost less than human labor. Software can be scaled infinitely in the cloud, and at a far more affordable rate than human labor. Organizations that can exploit AI and automation, therefore, can generate massive productivity gains while spending less capital than their competitors. 
• Machines perform tasks exponentially faster than people. Perhaps the most important point to note when it comes to automation tools is that they offer exponential gains in terms of cost, productivity, efficiency, and organizational performance. For example, a machine can instantaneously perform tasks that it takes humans minutes, hours, days, or weeks to perform. This creates an entirely new dimension that opens the door for innovations that have never existed before.

Perhaps the most important takeaway from this is that AI and automation tools, such as NLP, open the door to an entirely new type of business model – the AI-powered business.

Key Takeaways

NLP technologies, such as OCR and voice recognition, can automate business activities and generate significant value for organizations. The effective use of these technologies can dramatically improve customer experiences, employee productivity, business processes, and more.

In conjunction with other automation technologies, however, AI-powered tools and techniques promise to significantly transform businesses from the ground up.

Any business professional interested in NLP, therefore, should pay close attention to how this field develops in the coming months and years.

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