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#ITSM: 2024 Top Trends in IT Service Management

With advancing digitalization and the dynamic landscape, the requirements for IT service management (ITSM) are changing. In 2024 also, it’ll continue to evolve to meet the changing demands of the digital landscape. At the same time, companies are under increasing pressure from global challenges such as supply chain problems, inflation, and recession. To increase the productivity of their IT departments, companies need solutions that can optimize processes with the help of AI & ML. Here are some trends and requirements you can expect:

IT SERVICE management trends 2023

 

    • Automation and Artificial Intelligence (AI): Automation will play a significant role in ITSM, enabling faster incident resolution, proactive problem management, and streamlined processes. The Europe AI market size was valued at USD 33.65 Billion in 2022 and is expected to reach USD 325.29 Billion by 2032. AI-powered chatbots and virtual assistants will become more common, providing self-service options and improving user experience & support. ChatGPT is the biggest trend of this example. If answers to a problem exist in the database, a large proportion of service requests can be answered automatically using AI. The user usually receives a solution immediately via the self-service portal, leading to increased user satisfaction and employee loyalty.

 

    • DevOps Integration: Collaboration between ITSM and DevOps is becoming more critical. ITSM processes will align with DevOps practices, emphasizing collaboration, continuous delivery, streamlined processes, and rapid deployments. This integration will require ITSM professionals to adapt their skills and work in a more agile environment by improving overall communication and enhancing the overall efficiency of IT service delivery.

 

    • Cloud Service Management: In general, cloud use continues to be a trend primarily due to the continuously improved offers and also because the legal and regulatory framework is no longer as complex as it used to be. As cloud adoption continues to grow, organizations will need ITSM frameworks specifically designed for managing cloud-based services. This includes managing infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), and software-as-a-service (SaaS) offerings and ensuring security.

 

    • Security and Compliance: With increasing cybersecurity threats, ITSM will need to prioritize security and compliance. This includes implementing robust security measures, conducting regular audits, and ensuring compliance with industry regulations like GDPR and CCPA.

 

    • User Experience Focus: ITSM will shift its focus to improving user experience by providing intuitive self-service portals, quick response times, and personalized support. Customer satisfaction and feedback will be crucial for evaluating the effectiveness of ITSM processes.

 

    • Data-Driven Decision Making: ITSM will rely more on data analytics to make informed decisions. By leveraging data from various sources like incident records, service request patterns, and user feedback, organizations can identify trends, predict issues, and continuously improve their ITSM practices.

 

    • Service Integration and Management (SIAM): As organizations increasingly rely on multiple suppliers and vendors, implementing effective SIAM practices will become crucial. SIAM helps orchestrate and manage services delivered by various vendors, ensuring seamless integration and efficient service delivery.

AI, improving the digital employee experience and desktop as a service, new technologies, and usage models are changing IT service management in companies. To keep up with these trends and requirements, ITSM professionals should focus on developing skills in automation, AI, DevOps, cloud management, security, data analytics, and SIAM. It is also important to stay updated with industry best practices and certifications such as ITIL 4 (Information Technology Infrastructure Library) and COBIT (Control Objectives for Information and Related Technologies).

Best Ways to Drive Corporate Growth in Uncertain Times

Are you feeling the pressure to drive corporate growth in these uncertain times? You’re not alone. The current business climate is rife with challenges and uncertainties, making it more important than ever for companies to find innovative ways to thrive. Let’s explore some of the best strategies for driving corporate growth during uncertain times. Whether it’s through diversification, innovation, and adaptation, or strategic partnerships and collaborations, there are plenty of avenues to explore!

The importance of driving corporate growth in uncertain times

In today’s ever-changing business landscape, driving corporate growth is crucial, especially during uncertain times. The ability to adapt and thrive in the face of uncertainty can determine the long-term success or failure of a company.  Driving corporate growth allows businesses to stay ahead of their competitors. By continuously seeking opportunities for expansion and improvement, companies can gain a competitive edge that sets them apart from others in their industry.

 

Corporate growth helps create stability and resilience within an organization. In uncertain times, when market conditions are volatile and unpredictable, companies that have focused on growth strategies are better equipped to weather economic downturns and navigate through challenging circumstances.

Additionally, driving corporate growth fosters innovation. When companies actively seek new markets or develop new products/services, they stimulate creativity within their teams. This not only drives profitability but also enables organizations to remain relevant in changing customer demands. Furthermore, sustained growth leads to increased shareholder value. As a company expands its operations and generates higher profits over time, shareholders benefit from increased returns on their investments.

 

Strategies for driving growth during uncertain times:

  • Diversification: One of the most effective strategies for driving corporate growth in uncertain times is diversification. By expanding into new markets or offering new products or services, companies can reduce their reliance on a single source of revenue and mitigate risks associated with economic uncertainty. Diversification allows businesses to tap into untouched customer segments, explore untapped opportunities, and capitalize on emerging trends.
  • Innovation and Adaptation: Another key strategy for driving growth during uncertain times is innovation and adaptation. Companies that are able to quickly identify changing customer needs and market dynamics can adjust their business models, products, or services accordingly. This may involve leveraging technology to streamline processes, developing new solutions tailored to current demands, or even completely pivoting the business model.
  • Strategic partnerships and collaborations: Collaborating with strategic partners can be a powerful way to drive corporate growth in uncertain times. By joining forces with complementary businesses or industry leaders, companies can access new resources, expertise, distribution channels, and customer bases. Strategic partnerships also provide opportunities for shared knowledge transfer and mutual support during challenging times.

 

Case studies of companies that have successfully driven growth during uncertain times

Case studies of companies that have successfully driven growth during uncertain times serve as valuable sources of inspiration and guidance for businesses seeking to navigate through challenging economic landscapes. One such example is Amazon, which experienced significant growth during the 2008 global financial crisis. Instead of retreating, the company recognized the opportunity to expand its product offerings and capitalize on consumers’ increasing preference for online shopping. This strategic move not only helped Amazon maintain its position in the market but also propelled it towards becoming a dominant force in e-commerce.

 

Another notable case study is Netflix, which faced stiff competition from DVD rental stores when it first entered the market. However, instead of succumbing to industry norms, Netflix disrupted the traditional model by introducing a subscription-based streaming service. By focusing on innovation and adapting to changing consumer preferences, Netflix was able to drive substantial growth even during uncertain times.

 

In both these cases, diversification played a crucial role in driving corporate growth amidst uncertainty. These companies identified new opportunities within their respective industries and capitalized on them effectively. Additionally, they prioritized customer-centric strategies by constantly innovating and adapting their business models according to evolving consumer needs.

 

Strategic partnerships and collaborations are another key driver of growth during uncertain times. Take Uber’s partnership with Spotify as an example – this collaboration allowed Uber riders to personalize their trip experience with music while simultaneously providing Spotify access to millions of potential subscribers. By leveraging each other’s strengths and reaching new audiences together, both companies were able to achieve sustained growth even in turbulent times.

These case studies demonstrate that successful corporate growth during uncertain times requires visionary leadership that embraces change rather than shying away from it. It demands an agile mindset that can identify opportunities amidst challenges while remaining focused on delivering value to customers.

 

By studying these success stories closely, businesses can gain insights into effective strategies for driving corporate growth amid uncertainty – whether it be through diversification efforts or innovative partnerships – ultimately helping them thrive despite unpredictable circumstances

Growth doesn’t happen overnight; it requires ongoing effort. Remember that every company’s path to success will differ based on its unique circumstances. Therefore it’s important to have a well-defined strategy that requires continuous evaluation.

From Raw Data to Profitable Insights: Tools and Strategies for Successful Data Monetization

Data monetization has become an increasingly important topic in the world of business and technology. As companies collect more and more data, they are realizing the potential value that this data holds. In fact, according to a report by 451 Research, the global market for data monetization is projected to reach $7.3 billion by 2022. This is achieved through various strategies such as selling raw or processed data, providing analytics services, or creating new products based on the data.

There are many different approaches to data monetization, each with its own unique benefits and challenges. However, many organizations struggle with how to effectively monetize their data assets. In order to effectively monetize data, businesses need the right tools and strategies in place. These tools help collect, analyze, and visualize data to uncover valuable insights that can be turned into profitable opportunities. Below is a short list of essential tools used for successful data monetization.

 

  • Data Collection Tools: The first step in data monetization is collecting relevant and accurate data. This requires efficient and effective data collection tools such as web scraping software, API integrations, IoT sensors, and customer feedback forms. These tools help gather large amounts of structured and unstructured data from various sources like websites, social media platforms, customer interactions, or even physical sensors.

 

  • Data Analytics Platforms: Analytics tools play a crucial role in making sense of complex datasets by identifying patterns and trends that would otherwise go unnoticed. By leveraging these platforms, businesses can gain valuable insights that can be used for decision-making processes. They provide powerful reporting dashboards that allow businesses to visualize their KPIs with interactive charts, graphs, or maps helping them understand how their products are performing in real-time.

 

  • Business Intelligence Tools: These are applications designed specifically for reporting and dashboarding purposes. They allow users to input raw or analyzed data from various sources and present it in a visually appealing manner through charts, graphs or maps.

 

  • Customer Relationship Management Systems: CRM systems are essential tools for gathering customer-related information such as demographics, purchase history or behavior patterns. By analyzing this data, businesses can better understand their customers and tailor their products or services to meet their specific needs.

 

  • Data Management Platforms: DMPs are software solutions that help businesses to store, and manage large volumes of data from different sources. They allow for the integration of various data types, such as first-party and third-party data, which can then be used to create targeted marketing campaigns. It also provides features such as real-time processing capabilities, automated workflows for cleansing and transforming data, ensuring accuracy and consistency.

 

  • Data Visualization Tools: Data visualization tools help businesses present data in a compelling and visually appealing manner, making it easier for decision-makers to understand complex information quickly. These tools provide interactive dashboards, charts, maps, and graphs that can be customized according to the needs of the business.

 

  • Artificial Intelligence & Machine Learning: AI & ML technologies can help organizations extract valuable insights from their data by identifying patterns, predicting trends, and automating processes. AI-powered chatbots also enable businesses to engage with customers in real-time, providing personalized recommendations and increasing customer satisfaction.

 

  • Cloud Computing: Cloud computing provides scalable storage and computing power necessary for processing large amounts of data quickly. It also offers cost-effective solutions for storing and managing data as businesses can pay only for the services they use while avoiding expensive infrastructure costs.

 

  • Demand-side platforms: DSP help organizations manage their digital advertising campaigns by targeting specific audiences based on their browsing behavior or interests. These platforms allow businesses to use their data to segment and target customers with personalized messaging, increasing the chances of conversion and revenue generation.

 

  • Monetization Platforms: Finally, businesses need a reliable monetization platform that helps them package and sell their data products to interested buyers easily.

Data is certainly more than you think! It’s a valuable resource that can be monetized across your organization. So get in touch with us and learn how data monetization can transform your business.

Use of RPA and AI-based Predictive Models in Workforce Automation and Performance Management

 

Robots taking over the world? Well, not exactly. But they are definitely revolutionizing the way we work and increasing efficiency across industries. RPA is a game-changing technology that is streamlining repetitive tasks and freeing up human resources for more meaningful work. From accurate data processing to consistent task execution, automating half of workforce planning, and performance management, leading to various benefits such as increased efficiency, cost reduction, and improved workforce resilience through targeted performance management, RPA offers a wide range of benefits that can transform your business operations.

 

Let’s explore the exciting use cases of robotics process automation and how this non-invasive technology can help achieve your goals:

 

Workforce Planning Automation:

 

  • RPA can automate repetitive and rule-based tasks involved in workforce planning, such as data gathering, analysis, and reporting. For example, it can extract employee data from multiple systems, compile it into a centralized database, and generate reports automatically. One of the key benefits of RPA is its accuracy. Bots follow predefined rules and instructions meticulously, ensuring precise execution every time. This eliminates costly errors caused by human fatigue or oversight. With RPA in place, you can trust that your data will be processed accurately without any discrepancies.

 

  • AI-based predictive models can analyze historical data and external factors to forecast workforce demand and supply. This enables organizations to optimize workforce size, identify skill gaps, and plan for future needs more accurately. Plus with its low technical barrier you don’t need to have extensive programming knowledge or coding skills to implement it within your organization. The intuitive design interfaces make it accessible for non-technical users as well, allowing them to create automated workflows easily.

 

Performance Management Automation:

 

  • RPA can automate administrative tasks related to performance management, such as performance appraisal forms generation, data consolidation, and feedback distribution. This reduces manual effort, improves accuracy, and saves time for HR professionals and managers. Additionally, in terms of productivity gains, RPA enables faster task completion times compared to manual efforts alone. With bots handling repetitive tasks efficiently round-the-clock, employees are freed up from mundane activities and can focus on strategic initiatives that require creativity and critical thinking.

 

  • AI-based models can analyze performance data, feedback, and contextual factors to provide valuable insights and recommendations. For instance, they can identify high-performing employees, flag performance issues, and suggest personalized development plans. Moreover, relying on robots ensures reliability in task execution as they consistently follow standard operating procedures (SOPs) without deviation or shortcuts. This leads not only to increased efficiency but also improves customer satisfaction due to quicker response times and accurate deliverables.

 

 

Cost Reduction through Efficiency:

 

  • By automating workforce planning and performance management processes, organizations can save time and effort, leading to increased productivity and efficiency. This enables HR professionals and managers to focus on higher-value tasks, such as strategic workforce planning and talent development.

 

  • RPA reduces the need for manual data entry and processing, minimizing errors and rework. This improves data accuracy and reduces the associated costs of correcting mistakes.

 

  • AI-based predictive models help optimize resource allocation, workforce utilization, and talent acquisition, ensuring that organizations have the right people in the right roles at the right time. This reduces unnecessary costs and maximizes operational efficiency.

 

Improved Workforce Resilience through Targeted Performance Management:

 

  • AI-based models can analyze performance data and identify patterns, enabling organizations to proactively address performance issues and mitigate risks.

 

  • By providing targeted feedback and personalized development plans, AI can help employees enhance their skills, increase job satisfaction, and improve overall performance. This contributes to a more resilient workforce that can adapt to changing business needs.

 

RPA is also a non-invasive technology that seamlessly integrates with existing systems and applications without disrupting their functionality. This means you don’t have to completely overhaul your IT infrastructure to leverage its benefits. By working alongside your existing tools, RPA enhances operational efficiency without causing any major disruptions or downtime. In summary, the combination of RPA and AI-based predictive models in workforce planning and performance management can automate repetitive tasks, improve efficiency, reduce costs, and enhance workforce resilience through targeted interventions and data-driven insights.

Questions CIOs need to answer before committing to Generative AI

Unlocking the potential of artificial intelligence (AI) is a top priority for many forward-thinking organizations. And one area that has been gaining significant attention in recent years is generative AI. This revolutionary technology holds the promise of creating new and unique content, from art and music to writing and design. But before diving headfirst into the world of generative AI, CIOs (Chief Information Officers) should consider several important questions. How can they ensure success with this powerful tool? Is it right for their business? Below are the key questions and insights into how CIOs can make informed decisions about adopting generative AI within their organizations.

  • Understand your business needs: Before implementing generative AI, CIOs must have a clear understanding of their organization’s specific goals and challenges. What specific business problem or opportunity will generative AI address? CIOs should clearly define the use case or application for generative AI within their organization. This will help determine if generative AI is the right solution and ensure it provides tangible value. By identifying the areas where generative AI can make a tangible impact, CIOs can ensure that its implementation aligns with strategic objectives.
  • What data is required for generative AI? Generative AI models typically require large amounts of high-quality data to learn and generate meaningful outputs. Ensuring access to high-quality datasets is crucial for achieving successful outcomes with generative AI applications. CIOs should identify the data sources available within their organization and assess if they meet the requirements for training and deploying generative AI models. Also, they should work closely with data scientists and domain experts to curate relevant and diverse datasets that reflect the desired output goals.
  • Choose the right tool and platform. Not all generative AI solutions are created equal. CIOs must carefully evaluate different tools and platforms to find one that best suits their business requirements. Factors such as ease of use, scalability, customization options, and integration capabilities should be considered before making a decision.
  • Required expertise and resources: Implementing generative AI may require specialized skills and expertise in areas such as machine learning, data science, and computational infrastructure. CIOs should evaluate if their organization has the necessary talent and resources to develop, deploy, and maintain generative AI systems effectively. Also, generative AI should not replace human creativity but rather augment it. Encouraging cross-functional collaboration between employees and machine learning models can lead to innovative solutions that blend the best of both worlds.
  • Continuously monitor performance: Monitoring the performance of generative AI systems is essential for maintaining quality output over time. Implementing robust monitoring mechanisms will help identify any anomalies or biases in generated content promptly.
  • How will generative AI be integrated with existing systems and technologies? CIOs should consider how generative AI will interface with their organization’s current IT infrastructure and whether any modifications or integrations are necessary. Compatibility with existing systems and technologies is crucial for seamless adoption.

How to determine if generative AI is right for your business

Determining whether generative AI is the right fit for your business requires careful consideration and evaluation. Here are a few key factors to consider before making a decision:

  • Business Objectives: Start by assessing your company’s goals and objectives. What specific challenges or opportunities could be addressed through the use of generative AI? Consider how this technology can align with your long-term vision and help drive innovation.
  • Data Availability: Generative AI relies on large datasets to learn patterns, generate content, or make predictions. Evaluate whether you have access to sufficient high-quality data that can fuel the algorithms behind generative AI models.
  • Industry Relevance: Analyze how relevant generative AI is within your industry sector. Research existing use cases and success stories in similar industries to gain insights into potential benefits and risks associated with implementation.
  • Resource Investment: Implementing generative AI may require significant investment in terms of time, budget, infrastructure, and skilled personnel. Assess if your organization has the necessary resources available or if acquiring them would be feasible.
  • Ethical Considerations: Generative AI raises ethical concerns regarding privacy, bias, fairness, accountability, and transparency aspects since it involves creating synthetic content autonomously using trained models based on real-world data. Evaluate these considerations thoroughly before committing to generative AI solutions. Compliance with data protection, intellectual property, and other applicable laws is essential.
  • Risk Assessment: Conduct a risk assessment to evaluate potential drawbacks such as model limitations, security vulnerabilities, compliance issues or reputational risks that might arise from adopting generative AI technologies.

By evaluating these factors thoughtfully and engaging stakeholders across different areas of expertise within your organization along with external consultants when needed; you will be better positioned to determine if generative AI is suitable for driving innovation in support of achieving your business objectives.

In today’s rapidly evolving technological landscape, the potential of generative AI cannot be ignored. It holds immense promise for transforming industries by unlocking new levels of creativity and innovation. The key lies in understanding your specific business needs before committing fully to this technology. So ask yourself: How can your organization benefit from generating artificial intelligence? And what are the potential risks and challenges that need to be addressed?

 

The biggest challenges of BigData in 2023

The use of big data is on the rise, with organizations investing heavily in big data analytics and technology to gain insights and improve business performance. With the rapid growth of the internet, social media, and the IoT, the amount of data being generated is increasing exponentially. As a result, there is a need for better tools and techniques to collect, store, analyze, and extract insights from this data.

 

Additionally, the growth of the global datasphere and the projected increase in the size of the big data market suggest that big data will continue to be a critical driver of innovation and growth across various industries. In a study by Accenture, 79% of executives reported that companies that do not embrace big data will lose their competitive position and could face extinction.

 

Advancements in big data technologies such as machine learning, artificial intelligence, and natural language processing are also foreseen. These technologies have the goal to enable businesses and organizations to make better decisions, gain a competitive advantage, and improve customer experiences.

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Here are a few examples of how big data is being effectively used in various industries:

 

  • Healthcare: Big data is being used to improve patient care, disease diagnosis, and treatment outcomes. For instance, healthcare providers can analyze electronic health records to identify patterns and trends that may help diagnose diseases earlier and predict patient outcomes. Additionally, big data analytics can help hospitals and healthcare organizations optimize their operations, such as reducing wait times and improving patient flow.
  • Finance: Big data is being used to identify and prevent fraud, assess risk, and personalize financial products and services. For instance, financial institutions can use big data to analyze customer behavior and preferences, in order to develop personalized marketing campaigns and offers. Additionally, big data analytics can help banks and other financial organizations to detect fraudulent activity and reduce the risk of financial crime.
  • Retail: Big data is being used to personalize the shopping experience, optimize inventory management, and improve customer loyalty. For instance, retailers can use big data to analyze customer behavior and preferences, in order to develop targeted marketing campaigns and personalized recommendations. Additionally, big data analytics can help retailers to optimize their inventory levels, reduce waste, and improve supply chain efficiency.
  • Manufacturing: Big data is being used to optimize production processes, reduce downtime, and improve quality control. For instance, manufacturers can use big data to monitor equipment performance and predict maintenance needs, in order to reduce downtime and optimize production schedules. Additionally, big data analytics can help manufacturers to identify quality issues early, reducing waste and improving product quality.
  • Transportation: Big data is being used to optimize transportation networks, reduce congestion, and improve safety. For instance, transportation companies can use big data to analyze traffic patterns and optimize routes, reducing travel time and congestion. Additionally, big data analytics can help transportation companies to monitor vehicle performance and identify potential safety issues, reducing accidents and improving overall safety.

 

Generally, big data is being effectively used across a range of industries to drive innovation and create value, improve operational efficiency, reduce costs, and improve customer satisfaction. Along with the benefits of Bigdata, it’s challenges cannot be ignored. Here below are few potential challenges that bigdata may face in the future:

 

  • Data Privacy and Security: As the amount of data collected and stored increases, so does the risk of data breaches and cyber-attacks. Protecting sensitive information will be critical, particularly as more businesses move towards storing their data in the cloud.
  • Data Quality: As the volume of data grows, so does the risk of inaccuracies and inconsistencies in the data. Ensuring data quality and accuracy will become increasingly challenging, particularly as the data comes from a wide range of sources.
  • Data Management: Managing large amounts of data can be complex and costly. Businesses will need to invest in tools and technologies to help manage and process the data effectively.
  • Talent Shortage: The demand for skilled data professionals is growing rapidly, and there may be a shortage of qualified individuals with the necessary skills to analyze and interpret big data.
  • Data Integration: With data coming from various sources, integrating, and combining the data can be a challenging process. This could lead to delays in data processing and analysis.
  • Ethical Use of Data: As the amount of data collected grows, it becomes increasingly important to ensure that it is used ethically and responsibly. This includes addressing issues related to bias, fairness, and transparency.
  • Scalability: As the volume of data continues to grow, businesses will need to ensure that their infrastructure and systems can scale to accommodate the increased data load.

 

Overall, these challenges could impact the effective use of big data in various industries, including healthcare, finance, retail, and others. Addressing these challenges will require ongoing investment in technologies and skills, as well as a commitment to ethical and responsible use of data.

 

If you are looking for a partner who can give you both strategic and technical advice on everything to do with the cloud, than contact us so we can talk about your cloud project and evaluate the most suitable solution for your business.

GDPR with CIAM: THE devil is in the details

The EU General Data Protection Regulation (GDPR) has been in effect since May 25, 2018, It fundamentally changes the requirements for the processing of personal data and gives EU citizens significantly more control over their personal data – no matter where and how it is processed. Organizations around the world must respect certain guidelines on how to deal with the personal data of EU citizens. Anyone who does not fulfils their obligations risks a fine of up to four percent of the annual turnover achieved worldwide or 20 million euros. With that being said, still many the technical requirements of the EU General Data Protection Regulation seem difficult for companies to implement. An overview of what they are and how Customer Identity & Access Management (Customer-IAM or CIAM) paves the way to compliance.

GDPR with CIAM: THE devil is in the details

The articles of the Basic Regulation essentially define how data is collected, stored, accessed, modified, transported, secured and deleted. So, in the age of digital change, companies must find the right balance between compliance with the legal requirements on the one hand and effective customer care on the other.

 

Not only they must give data subjects extended opportunities to have a say in what happens to their personal data. But also, the person responsible requires documented consent from the data subject for the collection, storage and use of the data. Thus, all personal data must be secured using appropriate technical and organisational measures, depending on the probability of occurrence and the severity of the risk. Here below are few main issues that companies are faced with on the road to compliance:

 

  • Insufficient consent of the data subjects: The previously required basic level of consent to data use, including the opt-out procedure, is no longer sufficient under the provisions of the GDPR.
  • Data silos: Personal data is often stored across multiple systems – for example for analysis, order management or CRM. This complicates compliance with GDPR requirements such as data access and portability.
  • Lack of data governance: Data access processes must be enforced app by app via centralized data access policies. These policies are designed to give equal weight to consent, privacy preferences, and business needs.
  • Poor application security: Customer personal data that is fragmented and unsecured at the data layer is vulnerable to data breaches.
  • Limited self-service access: Customers must be able to manage their profiles and preferences themselves – across all channels and devices.

 

A robust Customer Identity & Access Management (Customer IAM or CIAM) solution are able to solve many of these seemingly insurmountable problems in no time.bThese solutions are able to synchronizes and consolidates data silos with tools such as real-time or scheduled bi-directional synchronization, the ability to map data schemas, support for multiple connection methods/protocols, and built-in redundancy, failover and load balancing.

 

CIAM solutions also facilitates the collection of consent across multiple channels and allows searching for specific attributes. Along with enabling mandatory enforcement of consent collection based on geographic, business, industry or other policies, they also offer the customer the opportunity to revoke their consent at any time. CIAM solutions give customers the ability to view, edit, and assert their preferences across channels and devices through pre-built user interfaces and APIs.

Most of the time these solutions include numerous centralized data-level security features, including data encryption in every state (at rest, in motion, and in use), access to recording restrictions, tamper-proof logging, active and passive alerts, integration with third-party monitoring tools, and more more.

 

In this way, a suitable CIAM solution helps to put many technical requirements of the GDPR into practice. And it even goes beyond the requirements of the basic regulation to create safe, convenient and personalized customer experiences – the basis for trust and loyalty.

 

Sources:

Règles pour les entreprises et les organisations

 

Invoice Management: Introducing the Digital Invoice Processing

 Digital Invoice Management

The cost of classic invoice management, such as costs for paper, printing & shipping material, proper and audit-proof archiving of all tax-relevant documents has been increasing for years. The growing expenses burden gets not only internationally active corporations with hundreds of thousands of billing transactions per month. Also, SMEs with a few hundred or thousands of invoices per year are in chaos and are increasingly looking for cost-effective ways to counteract & reduce the cost of invoices and improve processes.

 

So, it is not surprising that the topic of obvious savings and optimization is on everyone’s lips and that the optimization process of invoices and system support is in high demand. Therefore, Digital Invoice Management is more and more seen as a possible way out of misery. But how much potential is there in the real processes of today?

 

In the digital invoice management solution, invoice receiving, invoice output, and invoice archiving are the main processes that most companies are looking for, regardless of transaction volume or industry focus. The biggest challenge when receiving invoices is usually the effort involved in receiving, opening, distributing, and forwarding incoming invoices of various types, formats, and transmission routes caused. Because those times are long gone when the supplier invoices arrived into the company only via post, the electronic invoice receipts continue to increase parallelly.  In most companies, the invoices still arrive in different departments, making the automation process difficult. With the digital invoicing management system, companies can automate how, in what form, to whom, and where the various invoices are to be received/sent. A central mailbox must also be set and dedicated for all incoming invoices. Employees from different departments can then forward all incoming invoices to this mailbox.

 

Digital invoice management ensures noticeable time savings and reduces the process costs within the company. Digital invoice management has proved to have a positive effect on the waiting and processing times of invoices. With digital invoice management, it’s easy to create the necessary transparency and at the same time ensure that customers, business partners, or suppliers can provide a high level of information. Reporting also provides a real-time overview. So, you always know the exact status of all invoices in your company. Also, as the options for the degree of automation of invoices can be set from simply, knowing the status of the bill, reading out a few metadata to fully automated processes, only relevant data is transferred to the accounting department.

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82% of finance departments are overwhelmed by the high numbers of invoices they are expected to process on a daily basis and the variety of formats they’re received in. Thanks to digital invoice management in combination with a DMS, all documents are automatically filed in the correct digital file. It’s easy to find invoices again quickly at any time and benefit from high availability and the provision of specific information. For example, you can search for a specific invoice number and find it in seconds. After recording/archiving the invoices digitally, employees can have a holistic overview of invoice management in the company. The use of digital invoice management with the right software also complies with all the requirements of GDPR.

 

Although digital invoice management alone has numerous advantages, it is only through intelligent interfaces, e.g., to a document management system (DMS), that the full potential of digital invoice management can be achieved. Once the companies’ entire invoice workflow is digitally mapped and invoice management can become a routine task.

 

Digital invoice processing improves your workflow through automated checking and approval processes. With personalized workflows, you can easily route information to the right person for further processing or approval. By eliminating paper-based and manual processes, you can bring immediate quality improvement and productivity gains. In addition, errors and delays in the recording and processing of invoices can be reduced. It can be stated that you not only save time but also workload through automated invoice processing. With the implementation of digital invoice processing, you make the process simpler, leaner, and more transparent.

 

Would you like to find out more about digital incoming invoice processing? Our competent and experienced consultants are at your disposal.

Security Tips for Remote and Mobile Working

Security tips for remote working

Mobile security plays a big role in staying safe as many companies want to enable their employees to work securely on smartphones or tablets while they are on the road or away from the office – but they often fail due to IT security requirements. In order to achieve the highest possible security and data protection, companies must implement organizational and technical measures, to protect corporate data and systems.

 

Here below is a list of a few tips that can help employees to protect their organization’s security:

 

    • Free Public WiFi: Working on free WiFi can be attempting for employees who pay for their own data plans. They must be aware that these networks are not secure enough to use when logging into secure systems or transmitting sensitive information (customer data, credit card numbers, etc.). They must access companies’ data via their secure connection at home or enable their 4G for secure connectivity when they are on travel.

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    • VPN: companies that have employees using remote access applications, should use a VPN. With its help, employees can get a flexible connection on different online services and protect the traffic. VPNs allow the creation of a secure tunnel by means of data encryption during the connection. And as it grants access to all work applications and information employees haves feeling of working from the office.

 

    • Password management: When it comes to password management, employees use to take it very light. A good password management is the key to remote working security. Access to the applications containing crucial business and customer’s data must be protected with a strong password that contains at least eight characters, among which there must be capitals, low case letters, numbers, and special characters.

 

    • Two-Factor Authentication: Two-factor authentication is also considered for password protection. It adds an additional layer of security to the authentication process and makes it harder for attackers to gain access to employees’ devices or online accounts. It’s used to limit and control unwanted access to sensitive data.

 

    • Remote Access Applications: organizations must define which applications and data employees can use with their mobile devices, email programs including calendars and contacts, a browser, a document repository, and product and pricing databases.

 

    • Data Encryption: Protecting organizations’ and customers’ personal data is vitally important to the success of any organization. Encrypting that data with one of the best practices to be on the safe side. In the case of remote working, sending emails with sensitive data represents a huge risk. It could be intercepted or seen by a third party. If you encrypt the data attached to an email, it will prevent an unintended recipient from viewing the information. Also, be sure your device is set to have all stored data encrypted in the case of theft.

 

    • GDPR: As GDPR requires companies to have a 180-degree overview of the existing data, they must make data roadmaps with information such as, where the data is located, who is using the data – and is that data is being used in office equipment or remote devices.

 

    • Physical security: Employees must pay extra attention to their devices or files that contains companies’ important data once it’s out of the office perimeter and it’s not in use. Devices with important data in it, must not be left unsecured and unattended in any circumstance.

 

Remote employment is becoming more and more famous thanks to the advanced technologies and the flexibility it offers. Business must give extra attention to the security issues that can come along with the deployment of remote work. They must work on strategies that protect employees and business against cybercrime and offers a safe remote workplace.

Convention 108:  The European Data Privacy and Protection Day

Data Protection The European Data Privacy Day

Last Tuesday, January 28th, the European (annual) Data Privacy Day, 40th anniversary of Convention 108 &15th Data Protection Day, was celebrated among the global Data Protection community.

After many years of negotiation, the Convention for the protection of individuals with regard to automatic processing of personal data (Convention 108) was open for signature on 28 January, the date on which we now celebrate Data Protection Day. This day of action and information is launched following the initiative of the Council of Europe and aims to raise awareness of the handling of personal data. The focus is on data protection, so that as many companies, authorities, associations and people who deal with data protection as possible become clear about the importance of data protection.

 

In today’s digital society, user’s personal data is being collected either by companies or by the government. Especially with the emergence of Big Data, governments and businesses are able to collect and process large amounts of data, leaving millions of people unaware and uninformed about how their personal information is being used, collected or shared. Thus, each year a large number of organizations worldwide support this day of action in regard to protect consumer’s fundamental rights and freedom and to sensitize every European for the privilege of protecting their own privacy.

 

Here below are few tips from on how users can protect their online privacy and devices:

 

  • Moving through everyday life completely anonymously is next to impossible these days. Whether on the phone, shopping in the supermarket, booking a vacation, visiting the doctor or surfing the web – a lot of personal data is gathered. Partly obvious, but often even without our knowledge. Therefore, if you visit a web page where you have to enter sensitive information, make sure that the address in the browser matches the page you are trying to access. If the URL is a random arrangement of letters and numbers or looks suspicious, do not enter any information.

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  • Use a VPN and make sure that you remain anonymous online. A VPN helps you to hide your IP address and gives you anonymous access to the Internet. Even tough your data is visible, a VPN encrypts it entirely, routes your connection through secure remote servers, and masks your IP address. With its protective shield, your online data is difficult to crack and almost impossible to track.
  • Implement a Multifactor authentication (MFA) / Two-factor authentication (also known as 2FA). It’s an authentication method in which a user is granted access only after confirming the identities required of users by combining two different factors: something they know, something they have or something they are. If at least one of the components is missing or incorrectly specified during an authentication attempt, the identity of the user will not be established with sufficient certainty and access to the asset will be protected against identity fraud.
  • Whether smartphone, tablet or PC, you should always have an up-to-date virus protection and a firewall. Windows itself has rudimentary virus protection on board with Windows Defender, which is activated by default. However, it does not always do well in laboratory tests. If you don’t want to afford a full-fledged Internet security suite with a combination of firewall, virus protection and surf protection, you can have something similar cheaper or for free.
  • Connecting on a free WiFi can be attempting for anyone. But we must acknowledge that these networks are not secure enough to use when logging into secure systems or transmitting sensitive information (financial data, credit card numbers, etc.). We must access to this sensitive data via their secure connection at home or enable 4G for a secure connectivity outside.
  • Use a password manager to create secure passwords. A good password management is the key of cyber protection. Access to the applications containing crucial data must be protected with a strong password that contains at least eight characters, among which there must be capitals, low case letters, numbers and special characters. Avoid using same password on multiple applications / websites / online accounts. Instead use a secure password when you visit a new website / application.

 

The right to the protection of personal data, is a fundamental right laid down in Article 8 of the EU Charter of Fundamental rights and in article 16 of the Treaty of the Functioning of the EU. The right to the protection of personal data may be considered as one of the most important human rights of the modern age. In fact, topics such as Big Data, Artificial Intelligence, Machine and Deep learning, Internet of Things, Ubiquitous Computing, Surveillance and Data Transfer are examples that demonstrate the need for a right like this. This right also preserves the dignity and self-determination of an individual.

 

Sources:

 

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