What’s New in Technology

Marketing efforts today depend on collecting, analyzing, and leveraging data to make informed decisions. Therefore, business owners need to understand how to harness the power of data and personalization to create targeted campaigns that drive growth.

Importance of Data and Personalization in Modern Business

Businesses today collect loads of data, enabling them to understand their customers’ preferences, behaviors and interests. The data comes from different channels, such as a business website, emails, or social media. It is then used to identify patterns and trends to make informed marketing decisions. This yields valuable insights that help craft highly personalized and effective marketing strategies.

Data is the foundation of personalization strategies. Personalization involves tailoring customer experiences to meet individual interests, needs, and preferences. It aims to build strong customer relationships, encourage engagement, and drive revenue and growth.

Personalization takes different approaches, such as recommendations based on previous purchases, creating unique landing pages, or sending emails based on customer browsing behavior. For example, e-commerce websites recommend products based on user browsing history and search queries.

Business owners can’t afford to ignore personalization since customers today are more informed, can easily access information, have more options, and have more control over purchase decisions. Furthermore, customers are more demanding and want to be recognized as individuals, expecting to receive personalized experiences. This has rendered traditional, one-size-fits-all marketing strategies obsolete.

How Businesses Can Use Data and Personalization for Targeted Campaigns and Growth

Using a data-driven approach, a business can create campaigns that deliver the right message to the right audience at the right time by doing the following:

1. Audience segmentation

Capturing the attention of a specific audience segment leads to higher conversion rates. To do this, a business can leverage data insights to segment the target audience. This means it is possible to categorize potential customers based on demographics, interests, or browsing behavior.

2. Crafting personalized content

Once segmentation is complete, it becomes possible to create tailored campaigns that resonate with each segment’s unique preferences. Aside from addressing customers by their names, it involves delivering content that speaks directly to their needs, interests, and pain points. This could include product recommendations based on past purchases or sending targeted offers that align with customer browsing history.

3. Omnichannel personalization

Customers interact with businesses using various channels, such as a business website, social media, emails, and mobile apps. A business can integrate data and personalization efforts to ensure a seamless journey for customers, regardless of where they engage. Additionally, it is crucial to deliver consistent and personalized experiences across these channels.

4. Continuous improvement in data-driven campaigns

Data insights also help guide businesses on the most suitable content and distribution strategies. They can analyze types of content performing well and in which channels. For example, a business can conduct A/B testing to compare campaign and content variations to identify the most effective approach for each segment.  

5. Measuring and analyzing results

To establish the effectiveness of personalized campaigns, a business will need to develop clear key performance indicators (KPIs) and measurement methods. One way to measure the impact of personalization is through customer engagement. This is done by measures such as click-through rates on personalized emails, customer retention rates, customer lifetime value, customer feedback, and number of sales.

It is worth noting that to make the most out of data insights. It is helpful to invest in advanced analytics tools or collaborate with data experts.

6. Adapting to changing trends

The digital landscape is evolving constantly, with new technologies and trends emerging regularly. Businesses must stay updated on these changes and adapt their personalization strategies accordingly. Remaining flexible and open to innovation ensures that the company’s targeting efforts are relevant and effective.

Data Privacy and Security

Although personalization in modern business is crucial, it must be balanced with privacy concerns. First, a business must be transparent about the data it collects and how it will be used. In addition, businesses need to be careful with the data they collect. They must ensure data security by safeguarding data storage and using safe transmission methods, have access control limits, and regularly audit data privacy policies and practices. Customers should be allowed to opt out of data collection and personalization efforts easily.

Customer data must be well protected to ensure compliance with relevant regulations. It also helps build trust with customers. Besides, a breach of trust can severely affect a business’s reputation and growth.

One of the most devious and often underestimated dangers in cybersecurity comes from within an organization. These dangers originate from individuals within the organization who have access to sensitive data and systems, making them potentially dangerous adversaries capable of causing significant harm. Understanding, identifying, mitigating, and preventing these internal security risks are paramount for safeguarding an organization’s assets and preserving its integrity.

What is an Insider Threat?

Insider threats are security risks posed by employees, contractors, vendors, or anyone who has access to an organization’s data or systems. Accidental or intentional insiders cause internal threats. An accidental insider could unknowingly cause breaches due to negligence, human error or falling prey to social engineering tactics. For example, an employee clicks on a link in a phishing email, causing a malware infection.

On the other hand, insiders can intentionally engage in data theft, sabotage, or intellectual property theft, driven by motives such as financial gain, revenge or espionage.

A good example took place in May 2022 when a Yahoo employee stole trade secrets after receiving a job offer from The Trade Desk, a competitor. Another example is that of an employee fired from Stradis Healthcare who hacked into the former employer’s network in March 2020 and deleted critical shipping data.

According to the 2023 Insider Threat Report by Cybersecurity Insiders, 74 percent of organizations say insider attacks have become more frequent. The same percentage of organizations also believe they are at least moderately vulnerable to insider threats.

Experts attribute the rise in insider threats to various factors, including the effect of economic instability leading to businesses focusing on revenue growth and leaving gaps in security investments. There also has been an increase in layoffs in the tech industry that can result in disgruntled ex-employees doing damage as they leave the workplace. Overworked employees also might cut corners that create security issues, such as configuration, system access or unused accounts. Insider threats are also made more complex as many organizations migrate their workloads to the cloud, introducing new challenges.

How to Identifying Insider Threats

Insider threats are difficult to detect. However, it helps to look out for compromise indicators such as inappropriate behavior. Here is a more specific list of red flags:

• Unusual access and log in, especially from an insider who doesn’t have certain access rights to data or systems.
• Abnormal network search activity for sensitive information on networks, intranets, databases, or applications.
• Unusual copying or downloading of sensitive information to an unauthorized destination such as email or removable media.
• Misuse of tools, either foreign or installed. Detecting unfamiliar tools on a system is a compromise indicator. However, a savvy insider may even use trusted enterprise tools to execute an attack. In such a case, behavior such as access to a system outside regular working hours or access from unusual locations could indicate a compromise.
• Unwillingness to comply with security policies. Employees who consistently disregard security protocols and policies might pose a risk to the organization’s security.

Mitigating Insider Threats

Proactive measures that can help mitigate insider threats include:

• Employee training and awareness: Conduct regular security awareness and training programs to educate employees about the significance of insider threats and their role in preventing them.
• Role-based access control: Implement a robust access control model that ensures individuals have access to only the resources required for their specific job roles, reducing the potential impact of an insider breach.
• Behavioral analytics: Employ advanced analytics tools to monitor user behavior and detect inconsistencies that could indicate suspicious actions.
• Develop clear exit procedures: these include the revocation of access privileges and retrieval of company-owned devices and sensitive information from employees leaving the organization.
• Continuous monitoring and adaptation: Insider threats keep evolving, necessitating ongoing monitoring and constant adaptation of new security measures.

Preventing Insider Threats

• Conduct comprehensive background checks and verify references during the hiring process to minimize the risk of malicious insiders entering the organization.
• Ensure employees have proficient skills in deploying and managing complex cloud solutions.
• Encourage open communication, foster mutual trust, and support employees to reduce the likelihood of disgruntlement.
• Extend security considerations to contractors, suppliers, and partners with access to the organization’s data or systems.
• Implement endpoint security solutions to monitor and analyze activities on user devices such as workstations or laptops.

Conclusion

While staying alert for cyberattacks from outside is critical, organizations must not forget that the most significant risk can come from inside the business. Even with the most comprehensive cybersecurity defenses against external hackers, failing to create proactive measures for internal security leaves critical assets open to hidden dangers within the organization’s walls.

Organizations such as the Cybersecurity and Infrastructure Security Agency (CISA) provide information and resources to assist in developing new or improving existing insider threat mitigation programs.

Over the years, millions of individuals have been affected by data breaches, where their sensitive data is accessed by unauthorized cybercriminals or publicly exposed. A data breach can result in huge financial loss if stolen data is used to compromise consumer identity, which also can affect a credit score.

Unfortunately, there is a great number of people who don’t know what to do if affected by a breach. At the same time, there are those in the know who do nothing.

What is a Data Breach?

A data breach is a cyber security incident that exposes sensitive data such as names, contact details, bank details, Social Security numbers, etc.

Data breaches are the work of criminals who aim to obtain specific data. Criminals do this through various methods, including phishing attacks, malware attacks, targeted attacks, vulnerability exploits, and loss or theft of devices. However, data breaches are also a result of technical or human errors. For example, a misconfiguration error exposed the car location data of 2 million Toyota customers in Japan and overseas for 10 years; and the work of an insider led to Tesla’s massive data breach.

Unfortunately, data breach cases keep rising. May 2023 alone saw numerous breaches from different organizations, including healthcare organizations, education institutions, the transportation department and even tech giants.

For companies, the consequences of data breaches are reputation damage, loss of consumer trust, intellectual property theft, financial loss and fines due to failure to conform with data protection legislation. While cybercriminals mainly target organizations, individuals also experience identity theft and financial crimes. This especially happens when stolen data is sold on the dark web or publicly published.

What action can data-breach victims take?

Unfortunately, no one is immune from a data breach. However, victims can survive a breach with less disruption. Once a data breach has occurred, the U.S. breach notification law requires businesses or governments to notify those affected immediately after its discovery.

Although companies are responsible for securing customer data in their possession, customers also have a role to play in securing their data. Essential steps to take include:

• Being aware of any site claiming to be a data breach check site.
  Such sites could ask for personal information or ask a victim to click a link to verify their details. Hackers also take advantage of a breach and pose as the affected company to lure victims into clicking malicious links, primarily through emails. A user must, therefore, first confirm that a breach happened. This can be in the news or on the affected company’s website.
• Change passwords for accounts exposed.
  In most cases, affected companies will notify victims of their affected accounts, and their security team will provide instructions on how to stay safe. Such instructions include changing passwords on the breached site or any other account that uses similar login credentials.
• Set up two-factor or multi-factor authentication (2FA/MFA).
  This extra security measure will require a one-time user code to log in to an account in addition to the login and password.
• Notify the bank.
  If financial-related data was stolen, such as credit card information, the bank must be notified immediately to freeze the cards.
• Credit freeze.
  Cybercriminals can use stolen data to open new accounts and take loans. To avoid a ruined credit score, individuals can request a credit freeze from major credit bureaus such as Experian, Equifax and TransUnion.
• Monitor personal accounts for any unusual transactions.
  Although it depends on the type of data breach and exposed data, victims must look out for unauthorized transactions, including bank account transactions, medical bills, insurance claims and tax refund claims.
• File a report with the Federal Trade Commission (FTC).
  If criminals have already used personal data, filing an identity theft report will serve as proof to clear one’s name or dispute a fraudulent transaction.
• Practice cyber hygiene.
  These are practices that help individuals remain safe online. Aside from account security, consumers must use up-to-date software and operating systems, antivirus software, and avoid publishing too much personal information to minimize online footprints that fraudsters can easily access, such as on social media.

It is worth noting that data breaches are not detected immediately, which means that by the time users get notified, cybercriminals already have had access to the data for some time. And as technology advances, cybercriminals are taking advantage of new technologies such as generative AI for phishing attacks. This means that more data breaches may continue to be witnessed.

However, users can help prevent future data breaches by using strong passwords, being cautious of phishing scams, and regularly monitoring financial accounts.

Technology has greatly contributed to improving and streamlining everyday life. However, as technology advances, there is an increased reliance on digital tools powered by artificial intelligence and machine learning. Unfortunately, these technologies are also challenging the fundamental notion of human agency. As a result, there are rising concerns about humans losing the ability to make independent decisions.

What is Human Agency?

Human agency refers to the capacity of individuals to act intentionally and make choices that shape their lives. Although the human agency is influenced by various factors, including social, cultural, and environmental contexts, individuals should maintain the ability to exert some degree of control and influence over their lives. As far as technology is concerned, individuals must retain control and decision-making power. This calls for technologies that support humans in making informed decisions rather than controlling the decisions made.

Concerns Over the Effects of Digital Systems on Human Agency

The Pew Research Center and Elon University’s Imagining the Internet Center conducted a nonscientific canvassing to gather expert views about the future of the human agency.

The experts were specifically asked, “By 2035, will smart machines, bots, and systems powered by artificial intelligence be designed to allow humans to easily be in control of most tech-aided decision-making that is relevant to their lives?”

Of the 540 experts from different fields, 56 percent disagreed with the statement, while 44 percent agreed. Some of the main themes raised by the experts who disagreed with the statement include:

• The agendas of commercial interests and governments will determine the future.
• The convenience that comes with automation makes users less vigilant over technology.
• AI technology’s complexity and rapid evolution can be overwhelming, making it difficult for users to assert their agency.

Common themes raised by participants that agreed with the statement include:

• Humans also will evolve with technology, and there is the expectation that AI and tech companies will be regulated.
• Expectations that businesses will protect the human agency to retain public trust and to keep ahead of the competition.
• Technology will allow varying degrees of human agency.

Key Considerations for Upholding Human Agency

Seeing that technology will keep advancing and more automated systems will be witnessed, it’s crucial to implement ways to help uphold human agency. Some considerations include the following:

1. Implement mechanisms that contest AI systems. An AI system is as good as the information fed to it. Therefore, it can be faulty or deliberately flawed, and there should be ways to request redress. This can be through AI policies that allow users to contest or rectify a decision made by AI systems.
2. Empower users through systems that include meaningful choices and controls, enabling users to decide how to interact with them. For example, a system should allow users to adjust preferences, customize settings and choose the features they want. This promotes a sense of ownership and autonomy over digital experiences.
3. Promote digital literacy and education to teach about technology capabilities and limitations. Technology users must develop critical thinking skills to exercise human agency and make informed decisions.
4. Integrate ethical principles into technology design and deployment. This can be done by creating guiding ethical frameworks that consider the likely societal impacts and consequences of digital systems.
5. Guarantee transparency and explainability in technologies and algorithms, providing users with accessible explanations of how decisions are made and what data is utilized. This transparency fosters trust in the technology and empowers individuals to make informed choices.
6. Establish accountability for the design, development, and implementation of digital systems. Holding individuals and organizations accountable for the impact of their technology helps maintain human agency and promotes ethical behavior.
7. Implement robust measures to safeguard individuals’ privacy and protect their data. This includes incorporating strong data protection mechanisms, giving users control over their personal information, and establishing clear consent mechanisms for data collection and usage, accompanied by transparent policies. Respecting privacy rights is paramount for preserving human agency in the digital realm.

Conclusion

The essence of being human lies in exercising control over the nature and quality of an individual’s life. However, technological advances such as artificial intelligence are raising concerns about this human ability. Humans are responsible for actively embracing and comprehending the possibilities and implications of living in a world where digital systems take over various tasks and processes. Instead of surrendering their agency, humans should view partnering with these digital systems as a means to supplement and strengthen their intelligence rather than surrendering it.

The internet keeps evolving. It started with static web pages in Web 1.0 before evolving to interactive and dynamic content in Web 2.0. A new phase of technology is now introducing Web 3.0, or the third generation of The World Wide Web. Although it is a work in progress, it is necessary to understand the new concept and how it will impact the future of online interactions.

What is Web 3.0?

Web 3.0 is a term used to describe the next generation of the internet. Industry experts consider it the next big thing in the evolution of the The Web after Web 2.0. Web 2.0 refers to the Internet era characterized by user-generated content, social networking, and interactive web applications; it is known mainly as the Internet of Information.

Web 3.0, on the other hand, is built on top of the existing infrastructure; however, it introduces new technologies that enable computers to interpret data in a more human-centered manner. It combines disruptive technologies such as blockchain, augmented reality, virtual reality, edge computing, IoT, etc. As a result, the internet will become a more intelligent and efficient tool for finding and processing information.

Web 3.0 is also referred to as the semantic web or decentralized web and aims to create a more meaningful online experience by integrating artificial intelligence (AI), decentralized networks, and semantic understanding.

Key Features of Web 3.0

Decentralization

Web 3.0 makes good the move toward decentralization. Decentralization implies that instead of relying on central authorities, data is simultaneously stored in multiple locations. Since Web 3.0 is built on decentralized networks, such as blockchain technology, it creates a more transparent, secure, and trusted web and gives users more control over their data.

Artificial Intelligence and Machine Learning

Web 3.0 will enable computers to comprehend information similar to the way humans do, using semantic web concepts and natural language processing. It also will utilize machine learning – technology that employs data and algorithms to imitate human learning and enhance accuracy. Web 3.0 is designed to leverage the power of artificial intelligence (AI), making web applications more intelligent and enhancing their capacity to make informed decisions. It also helps automate tasks, improve efficiency, and provide more personalized experiences for users.

Ubiquity and Connectivity

The rise of the Internet of Things (IoT) is another contributing factor, enabling information and content to be more connected and ubiquitous. It also means data is accessible via multiple applications and devices.

3D Visualization

Using augmented reality, virtual reality, and mixed reality combined with technologies such as IoT makes it possible to create a spatial web. This helps maintain real-life scale and experience on the web. A good example is the application of VR technology in e-commerce.

Openness and Accessibility

Web 3.0 is built on open standards and protocols, which make it more accessible to both developers and users. This promotes innovation and collaboration across different sectors and communities.

The Impact of Web 3.0 and Challenges

Web 3.0 will significantly change how users interact with information online and transform different aspects of life, including commerce, health, and education, among others. For instance, decentralization gives users greater control over their personal data. This might help limit the collection of data without user consent or compensation.

With blockchain technology as a foundation of Web 3.0, the data becomes immutable, transparent, and hard to hack. This is because all transactions will use self-executing smart contracts.

Web 3.0 will usher in a new era of automation as intelligent systems and algorithms become increasingly integrated into online experiences. This will include more intelligent chatbots, personalized recommendations, sophisticated predictive analytics, and autonomous systems.

As a result, there will be an improved user experience. Users will have a more personalized and interactive experience online, with applications that can better understand their needs and preferences.

Despite the impressive positive impact, Web 3.0 is still in its early emerging stage and is not without challenges. As more significant work and effort are being put toward its actualization, several issues must be addressed. First, to facilitate specific user functions, additional layers must be built on top of the blockchain to ease its complex operations.

Secondly, decentralization introduces data governance and regulation concerns. With no central control of data, bad actors can take advantage to promote hate speech, misinformation and cybercrime.

Thirdly, this new iteration of the internet also requires implementing new technologies and using advanced devices.

Conclusion

The evolution of the internet is inevitable. Although more effort is still required to realize the full potential of Web 3.0, business leaders should be aware of new developments to ensure they can take advantage of opportunities presented by the spatial web and venture into new avenues to remain competitive.

Emerging technologies, such as artificial intelligence, machine learning, data analytics and biotechnology, greatly transform society and reshape the global economy. However, these technologies also come with a significant challenge regarding ethical and social implications. Global collaboration by governments, regulators and industry leaders can help ensure that emerging technologies are developed and deployed responsibly.

Challenges of Regulating Emerging Technologies

Emerging technologies have led to complex situations that traditional governments might find difficult to manage. For instance, today’s advanced technologies also come with new forms of crime. This requires law enforcement and public safety organizations to keep up with new and innovative crimes. Today’s governments face challenges that affect the development of effective digital laws.

One of these challenges is the independence of technology from physical state territories. The interconnection of technology devices over the internet has no boundaries. This makes it impossible for any country to regulate all aspects of the technologies. Secondly, all states are not the same, and each enhances its technology-related laws according to its capabilities. While strong economies can afford robust IT infrastructure, other countries do not have the technical capacity.

Other factors that complicate technology regulation include the ability of major technology companies to bypass established regulations. Additionally, states are consumers of technology products and services developed by private corporations. Since they are not the innovators, policymakers and regulators do not understand the intricate technology systems that affect the regulatory decisions that must be made.

The above mentioned are only a few of the challenges that make technology regulation complicated. Still, there is a growing need for digital governance and a digital constitution.

Why Global Collaboration is Crucial in Regulating Emerging Technologies

1. Address ethical and social issues – significant ethical and societal issues, like data privacy and security, are brought up by emerging technology. However, international cooperation can help ensure coordinated and efficient responses to these issues.
2. Growing competition for technological dominance – political, societal and economic rivalries are driving technological dominance. Increased competition for elements of technology supremacy can only result in conflict, obstructing technology’s ethical use.
3. Technology diffusing globally – in most cases, new technologies are available for adoption anywhere in the world. Thus, international regulatory frameworks must be coordinated to prevent competing or incompatible laws.
4. Harmonizing standards – global cooperation can assist in harmonizing standards and laws for new technology, making it simpler for businesses to comply and lowering entry barriers for new players.
5. Promote inclusivity – emerging technologies have the potential to make existing social and economic inequalities even worse. Collaboration on a global scale can ensure that these technologies are usable by everyone and do not reinforce or introduce new forms of exclusion.
6. Enhance innovation – collaboration across borders can facilitate the exchange of knowledge, ideas and best practices, leading to more innovation and faster technological advancement.
7. Avoid existential risks – technology can potentially introduce threats that endanger life globally. Such risks might include nanotechnology weapons and engineered pandemics. However, developing strategic global legal frameworks that identify potential risks can help avoid the proliferation of dangerous and harmful technologies.

Existing Efforts for Global Collaboration in Regulating Emerging Technologies

There are numerous initiatives for international cooperation in regulating emerging technologies. For example, the Global Partnership on Artificial Intelligence (GPAI) brings together governments and business executives from across the world. Its goal is to ensure artificial intelligence (AI) is developed and deployed responsibly in a human-centric manner. GPAI’s main focus is on responsible AI, data governance, the future of work, and innovation and commercialization.  

The Organization for Economic Cooperation and Development (OECD) is another international organization where governments work together to solve common challenges and develop global standards. A good example is their recommendation on responsible innovation in neurotechnology, adopted by the OECD Council in December 2019. Other organizations working toward promoting global collaboration and coordination on emerging technology issues include the World Economic Forum (WEF) and the United Nations.

Unfortunately, there is still a lot of work to be done. Continued global cooperation is crucial to ensure that emerging technologies are created and used to benefit society. Currently, there is no global agreement on technology regulation; instead, regulators take different and sometimes conflicting standpoints.

Conclusion

The pace and impact of emerging technologies are likely to keep increasing. Although these developments improve human experiences, the potential for these technologies to disrupt social, economic and political systems worldwide means that it is essential for governments, private companies and civil organizations to work together to ensure that they are developed responsibly.

Customer loyalty is critical to any successful business strategy in today’s digital age. With emerging technologies such as the internet of things (IoT), companies are now leveraging a new approach called the internet of behavior (IoB) to gain deeper insights into their customers’ behavior and preferences.

What is IoB?

The internet of behavior exists because of the internet of things. IoT is the interconnection of physical digital objects that gather and exchange information over the internet. On the other hand, IoB makes sense of the collected data from various sources, including wearable devices, digital household devices, human online activity and social media.

The acronym internet of behavior (IoB) was coined by Gartner, a tech research firm, as identified among the top 10 trends in their strategic technology report for 2021. However, the concept of using data to influence customer behavior was developed in 2012 by Göte Nyman, a psychology professor at the University of Helsinki, long before the internet of things took hold.

Gartner defines IoB as an extension of the internet of things, focusing on capturing, processing and analyzing the “digital dust” of people’s daily lives.

Simply put, IoB interconnects IoT, consumer psychology and data analytics. The data is analyzed in terms of behavioral psychology to capture patterns that marketing and sales teams can use to influence customer behavior.

How IoB can Influence Customer Loyalty

Aside from products and services, customer experience has become a significant factor in business success. By understanding customer behavior, businesses can leverage IoB data to influence customer loyalty in various ways.

Personalization

Personalization has the power to transform customer experience. This is reflected in a survey that revealed 76 percent of Americans are more likely to complete a purchase because of a personalized experience.

To take advantage of IoB, companies study insights extracted from collected data and use it to decipher customer behavior; that is, their practices, preferences, habits, needs, wants and more. The company can then leverage this data to offer personalized product recommendations, such as insurance premiums, saving plans, travel destinations, etc.

For example, an insurance company can have users install apps on their phones that collect data on distance traveled, car speed, etc., and optimize their car’s premium based on driving behavior.

Timely Improvement of Products and Customer Services

IoB also makes studying how customers interact with specific services or products easy. This saves companies from time-consuming surveys that are used to determine consumer preferences. The collected data is analyzed to identify pain points and issues of concern. The company can then address the issues before they become significant problems, such as by improving on products and services. This is an excellent way to build trust and confidence in a brand, leading to customer retention.

Behavioral Retargeting

Since companies can access customer preferences, recent activities, likes, dislikes, and location data, they can send real-time notifications to customers about discounts and new offers in stores nearby. They also can track loyal customers and offer them rewards. This kind of retargeting will make customers feel like a business values them and caters to their interests.

Develop a Tailored Marketing Strategy

Insights from IoB data can help tailor marketing strategies to individual customers. For instance, a retail store can offer products or services based on the mood, age or gender of a customer; thereby providing a satisfying experience that will lead to a stronger emotional connection with the brand.

Key Challenges that must be Addressed for the Success of IoB

Despite the opportunities IoB offers, companies must be aware of some key challenges to fully realize its benefits.

• Privacy Concerns – Although personalization will make consumer lives easier, there is a concern about privacy. Companies must implement strong cybersecurity policies and measures to ensure that customer information is used only for that which a customer has given consent.
• Convincing Users to Share Personal Data – People might not be comfortable sharing their personal data.
• Laws and Regulations – Strict regulations around collecting and using personal data, such as the General Data Protection Regulation (GDPR), require companies to comply in order to avoid fines and legal issues.
• Cybersecurity – As reliance on technology rises, so do cyberattacks. Cybercriminals may access sensitive data on consumer behavior, making consumers susceptible to online scamming and identity theft, among other threats.

Conclusion

Leveraging IoB can provide businesses with a competitive edge and drive revenue growth. Companies seeking continuous success should consider placing IoB at the center of business innovation to create personalized customer experiences. At the same time, they must also examine any challenges that might reduce the effectiveness of IoB.

Natural language processing (NLP) is a technology that allows computers to understand and process human language. Processing of natural language is necessary when you want an intelligent device to follow your instructions. NPL is an artificial intelligence (AI) component with many real-life applications.

As technology advances, business leaders have to figure out how to tap into the new trends to remain relevant, stay ahead of competition, and meet consumer expectations and needs.

How NLP Works in Brief

NLP involves making computers perform tasks with the natural language humans use. The input and output can be spoken or written text. NLP combines computational linguistics – rule-based modeling of human language – with statistical, machine learning, and deep learning models.

NLP aims to build machines that understand and react to text or voice data and then respond with text or speech in a similar manner as humans do. Examples of NLP in real life include voice-operated GPS systems, personal assistant apps, speech-to-text dictation software, and customer service chatbots.

As businesses seek better ways to improve efficiency, NLP is one technology promising huge rewards for enterprises dealing with vast quantities of unstructured text. In accounting, unstructured data include transaction descriptions, invoices, written communication, etc.

The use of NLP is growing significantly in enterprise solutions designed to help streamline business operations. Large companies such as Deloitte, Ernst & Young (EY), and PricewaterhouseCoopers (PwC) have implemented various NLP solutions. A good example is Deloitte, which incorporated NLP into its Audit Command Language to improve contract compliance.

How NLP Can Improve the Efficiency of Accounting Processes

Areas in which NLP helps improve efficiency include:

1. Forensic Investigations
   When CPAs want to perform forensic investigations, they have to deal with significant amounts of data from documents such as bank statements, transaction data tables, and data found in emails or deposition transcripts. Analyzing all the data as they try to look for specific patterns or gain insights is challenging. However, the application of NLP can be helpful in the investigative analysis process. NLP using algorithms can identify patterns automatically and reduce the time it would have taken to analyze the documents.
2. Accounting and Auditing
   Auditing is challenging due to the process of reviewing financial statements and ensuring they match regulations and legal standards. Auditors must have excellent analytical and decision-making skills to spot inaccuracies in financial statements. However, NLP helps to optimize the auditing process.
3. Financial Analysis and Automated Generation of Financial Reports
   NLP can automatically extract financial data from balance sheets, income statements, and cash flow statements. This can cut down on time and error-prone work. At the same time, it can obtain insights from massive financial data sets and financial reports. This enables accountants to make data-driven decisions and quickly identify trends and patterns in the data, hence, making it easy to provide guidance to clients on investments and household finances.
4. Automated Data Entry
   NLP can be used to extract data automatically from unstructured text documents, including bills and receipts. It also can be used to automate the entry of data from tax documents and input it into accounting systems. This can cut down on time and error-prone work.
5. Improve Centralized Data Management Solutions
   Incorporating NLP in accounting and procurement helps improve the ability of a centralized data management system to collect and integrate data from different sources. This enables standardization and collaboration. Additionally, the data provided has higher-quality insights. As a result, there is better financial planning and improved risk assessment and management.
6. Customer Interaction
   NLP can be used to enhance the effectiveness of customer interaction. This is done by automating the procedure for responding to client inquiries, such as concerning invoices, payments, and account balances.

Conclusion

Natural language processing is proving to be a powerful technology that can help improve the efficiency and effectiveness of accounting processes. As it continues to evolve, it will likely become an increasingly important tool for accountants and other financial professionals. Most importantly, these advanced technologies take care of manually reviewing unstructured data. This helps businesses scale and – at the same time – reduce costs.

Technology advancement has brought about great digital transformation. Unfortunately, this has come with a global tech talent shortage. IT executives highlight the shortage as a huge barrier to the adoption of emerging technologies, as reported by this Gartner study.

It is estimated that the demand for tech talent will keep increasing, and this could result in an estimated 85 million global talent shortage by the year 2030. Therefore, companies need to rethink their approach to hiring and retention.

Reasons Behind the Tech Talent Shortage

It is worth trying to first understand what is causing the tech talent shortage. A few of the reasons that have led to the shortage include:

• Advances in technology – technology is advancing at a high speed, requiring workers with skills to match the new technology. Unfortunately, the tech education system can’t keep up with the speed, hence a shortage of people with the required skills.
• The great resignation – this became a buzzword with work from home that came with the Covid pandemic; unfortunately, even after the pandemic people are still leaving jobs. A survey by TalentLMS and Workable found 72 percent of employees working in tech are considering quitting their jobs or exploring other opportunities.
• High demand for tech talent – There has been an increase in the demand for tech workers in recent years as more businesses and industries turn to technology for daily operations. New technology creates new roles such as data professionals, data security specialists and software engineers among others that are highly competitive.
• Challenges in training and development – some companies might not have the resources and time to invest in employee development.

Business Challenges of IT Talent Shortage

Businesses are feeling the effect of the tech talent shortage, especially when it comes to digital transformation. Emerging technologies such as robotic process automation (RPA), artificial intelligence, blockchain and augmented reality that promise to keep a business ahead of its competition require skilled workers.

Hiring new talent or reskilling employees also comes at a cost, and companies struggle to fill positions. On the other hand, failing to have skilled employees results in unrealized annual revenues.

As a result, businesses of all sizes find themselves failing to develop projects on time and hence fail to meet deadlines. In other cases, the existing employees end up overburdened with too much work, and this may lead to them quitting. Eventually, a business experiences slow innovation and slow growth.

How to Handle the Tech Talent Shortage

A few strategies to help address this issue include:

• Investing in employee development and training
  Providing ongoing training and development opportunities for current employees can help them acquire new skills and knowledge. This will not only make them more valuable to your organization, but also less likely to leave.

• Attract top talent through a strong employer brand
  Building a strong employer brand can help in attracting top talent to your organization. This can involve highlighting your company’s culture, values and mission, as well as offering competitive compensation and benefits packages. A good reputation will also help attract new talent.

• Partnering with educational institutions
  A company may also partner with local colleges and universities to gain access to a pool of talented students who are looking for internships or entry-level positions. Additionally, setting up mentorship or internship programs helps build a pipeline of talent for your organization.

• Increase recruitment efforts
  Sometimes it might be difficult to find the right talent, which makes it necessary to increase recruitment efforts. This could involve working with recruitment agencies, posting job openings on job boards and social media platforms, and attending job fairs and industry events.

• Consider hiring remote workers
  Even with all efforts in place, it may still be difficult to find the right talent in a business location. Today, technology has enabled people to work remotely. This offers access to a larger pool of candidates and also can help attract top talent from other parts of the country or even the world. It is also possible to work with freelancers or contractors to fill specific skills gaps on a project-by-project basis.

• Enhance the recruitment process
  An inefficient recruitment process will cost the company good talent. Therefore, any poor communication or delayed communication will affect talent acquisition. A company might need to streamline its recruitment process.

Final Thoughts

The global tech talent shortage is already negatively affecting businesses. Since the shortage is expected to rise, business leaders need to decide on the best way forward so they are not left behind in digital transformation. A good decision should fit business goals whether choosing to hire internal talent, remote workers, or outsource technology needs.

Data has become a primary asset for businesses today. Consequently, the survival of a business in our data-driven environment is highly dependent on the ability to have total control over data storage, extraction, and manipulation.

As businesses continue being bombarded with vast volumes of data, datafication has become a big trend that provides a solution to turn data into quantifiable, usable, and actionable information. 

What is Datafication?  

The term datafication was coined by Kenneth Cukier and Victor Mayer-Schöenberger in 2013 when they explained it as the transformation of social actions into quantifiable data.

Today, much data is collected at the point of contact with any technology device. Aside from data such as text, images, and numbers, there are logins, passwords, device activity logs, clicks, interaction times, and more. Datafication helps translate all of these human activities into data, which is then repackaged in a form that offers value.

In business, datafication means converting every activity of a business model into actionable data. This has been enabled by a rise in technologies such as artificial intelligence, machine learning, big data analytics, and predictive analytics.  

It’s worth noting that datafication is not the same as digitization. While datafication is about taking all aspects of life and turning them into a data format, digitization involves converting analog content, such as images and text, to a digital format.

Examples of Datafication in Real Life

There are various ways datafication has been applied in real life, including:

1. Social media platforms – a lot of data is found on social platforms through profile updates, preferences, reactions, comments and posts. Such information is used for customer profiling.
2. Ad personalization – tech giants such as Facebook, Google, Apple and Amazon are already using collected data in their storage to personalize their ads and target potential customers.
3. In customer relationship management – data collected through language and tone in emails, social media and phone calls are used to understand customer needs and wants as well as buying behavior and personalities.   
4. Human resources – HR uses data obtained from social media or mobile apps to discover characteristics and personalities when looking for potential employees. They also use the data to assess employee productivity. This means that it may no longer be necessary to take personality tests, as the collected data can be analyzed to check if a person matches the company culture and role for which he applies.
5. Insurance and banking – understanding the risk profile of a customer applying for insurance or a loan, as the data is used to assess the client’s trustworthiness.  

Datafication for Competitive Advantage

With the above use cases, it is evident that businesses can leverage datafication to help improve operations, thereby increasing productivity and revenue.

For instance, collecting real-time customer feedback can help improve products and services. Additionally, it becomes easy to determine and predict sales by analyzing data from social platforms such as Facebook, Instagram and Twitter.

The information collected from social media, emails and other digital platforms is then used to create personalized campaigns, effectively targeting the most interested audience.

How Businesses Can Implement Datafication

Any trending technology that presents benefits to a business comes at a cost. Luckily, cloud computing eases datafication for businesses as they don’t have to worry about acquiring necessary hardware and software. With readily available software as a service (SaaS) or platform as a service (PaaS) technologies, businesses need only to define the goal they want to achieve with the data collected.

The main concern of a business remains the proper implementation of datafication. To begin with, it is best to ensure that the right technology – such as mobile devices, voice assistants, wearables, IoT – is used.

Next is to use appropriate platforms. Using the right platform will help effectively extract data that a business needs. Such platforms should also analyze massive amounts of data and produce reports that enhance decision-making.  

Another critical factor is to have a centralized repository where all authorized people in the organization can access the data.

Finally, it’s crucial to have skilled professionals in data infrastructure, data management and data analytics to evaluate and manage the data. This could either be an in-house team or outsourced.

Conclusion

Businesses that wish to remain relevant must consider datafication as part of their digital strategies. However, as datafication enters digital transformation, its successful implementation will require attention to data protection through adhering to legal requirements, technical measures such as access control, and best business practices.