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Achieve Sustainable Digital Transformation by investing in Futuristic Data Centres

Imagine a world where organizations can meet their sustainability goals while keeping up with technological advancements. Let’s explore how companies can achieve sustainable digital transformation by making strategic investments in their data centers and revolutionizing their operations, processes, and customer experiences. Achieving sustainable digital transformation through investments in data centers involves adopting practices that prioritize efficiency, environmental responsibility, and long-term viability. This holistic approach allows businesses to not only reduce their carbon footprint but also create long-term value for themselves and society.

Here are several strategies that companies can consider:

 

Energy Efficiency: Implementing energy-efficient technologies and practices within data centers is crucial. This includes using advanced cooling systems, optimizing server utilization, and investing in energy-efficient hardware. Companies can also explore renewable energy sources, such as solar or wind power, to reduce their carbon footprint. Sustainable digital transformation brings about cost savings in the long run. By optimizing energy consumption & reducing waste companies can lower their operational costs while maximizing productivity.

 

Virtualization and Consolidation: Virtualization allows multiple virtual servers to run on a single physical server, leading to better resource utilization. This not only reduces the number of physical servers needed but also contributes to energy savings and a smaller physical footprint.

 

Data Center Design: Companies can design new data centers or retrofit existing ones with sustainability in mind. This involves using materials and designs that enhance energy efficiency, such as efficient airflow management, modular designs, and the use of natural cooling where possible.

 

Cloud Computing and Hybrid Solutions: Leveraging cloud services or adopting a hybrid approach (a combination of on-premises and cloud infrastructure) can contribute to sustainability. Cloud providers often invest heavily in energy-efficient data centers and offer scalable solutions, allowing companies to adjust resources based on demand, and reducing unnecessary energy consumption.

 

Lifecycle Management: Proper management of IT equipment throughout its lifecycle is essential. This includes responsible disposal or recycling of outdated hardware, as well as regular maintenance and upgrades to ensure optimal performance and efficiency.

 

Monitoring and Optimization: Implementing advanced monitoring tools helps in tracking energy usage, server performance, and overall efficiency. This data can be used to identify areas for improvement and optimize resource allocation.

 

Automation: Implementing automation in data center operations can enhance efficiency by dynamically adjusting resources based on demand. Automated systems can optimize energy usage and resource allocation more effectively than manual processes.

 

Employee Training and Awareness: Educating employees on sustainable practices and the importance of energy efficiency can foster a culture of responsibility within the organization. This includes training on best practices for using IT resources, such as shutting down non-essential servers during periods of low demand.

 

Regulatory Compliance: Staying informed about and compliant with environmental regulations related to data centers is crucial. Companies should be aware of local and global standards and work to exceed minimum requirements where possible.

 

Collaboration and Industry Involvement: Engaging with industry organizations, sharing best practices, and collaborating with peers can lead to the development of new, sustainable solutions. Participating in initiatives focused on green IT and sustainable business practices can contribute to positive industry change.

 

Achieving sustainable digital transformation holds immense importance for companies today. It enables organizations to align with global environmental goals and regulations. As governments worldwide are implementing stricter environmental regulations, businesses must adapt their operations accordingly to remain compliant and avoid penalties. By incorporating the above-listed strategies, companies can not only achieve sustainable digital transformation but also position themselves as responsible corporate citizens committed to environmental stewardship.

Digitization: Why should companies invest in Artificial Intelligence training

Technology is a key helper on the way to the digital future. Artificial intelligence is considered a crucial future technology in the worldwide economy and more and more companies see an opportunity for their own business in artificial intelligence (AI). Whether predictive maintenance, process optimization, system control, or individualized products – everyone is talking about the fact that everything will be AI-supported in the future if not even function autonomously. AI can also improve processes in companies from production to sales or serve as the basis for new products and services.

 

Artificial intelligence also gives enormous competitive advantages. A survey conducted by McKinsey highlighted that a majority of survey respondents say their organizations have adopted AI capabilities, as AI’s impact on both the bottom line and cost-saving. Regarding the employees, however, there is an urgent need for action as they are poorly prepared for the use of artificial intelligence in this suddenly changing environment. Employees must perform skilled jobs that require more education and training compared to their normal routine jobs.

 

Another survey conducted by the market research company Statista on behalf of the TÜV Association among 1,000 people aged sixteen and over, including 568 employed people has revealed that 78 percent of employers agree that companies need to invest more in training their employees when it comes to AI. Many companies must invest significantly more in further training in artificial intelligence to make their workforce fit for the digital world. This involves both in-depth knowledge for the use of the technology, but also user knowledge since many tools already work with AI today. According to the results of the survey, a start has been made, 28 percent of the employees surveyed have taken part in further training on AI content in the past two years. And 34 percent of those in employment planned to do so within a year.

 

With basic AI knowledge, TÜV association expert Fliege observes considerable deficits in the companies. “Many employees only have a vague idea of ​​what AI is and where they encounter it.” AI is already in use in many cases, sometimes even unnoticed. “Algorithms work quietly in numerous systems – for example in IT security, where they recognize and resist cyber-attacks,” says Fliehe. AI is perceived more strongly in factories, for example, where it supports production control. The use of AI promises more efficiency and greater process automation in production. That doesn’t have to have a negative impact on employment, says Fliege: “Interesting new fields of work can arise for employees because they are relieved of routine activities.” The development is still in its infancy, and a lot is in flux. “A whole new door is opening for companies and employees.” According to Fliehe, the use of AI for small and medium-sized enterprises (SMEs) is particularly promising. “They usually have to make do with scarcer resources and are committed to high efficiency.”

 

“Knowledge about artificial intelligence is improving as the technology spreads,” said Stenkamp. At the same time, the attitude of the citizens is also improving. Fifty-one percent of respondents feel something positive when they think of AI, compared to the previous study by the TÜV Association in 2019, this is an increase of five percentage points. On the other hand, only 14 percent feel something negative, two years ago this value was twice as high at 28 percent. Thirty-five percent are neutral (up 14 points).

 

However, one thing is certain: the responsibility of the employees will increase, because they will remain the final decision-making authority. “Users in companies must know that AI decisions are not optimal in every situation,” says Fliehe. It may therefore be necessary to check whether an algorithm has captured all the valuable information. “Human expertise and experience will not become less important through the use of AI, but even more important,” emphasizes Fliehe. Employees would have to be able to guide the algorithm and classify the results. “Employees must become designers and also recognize the limits of AI.” In this way, the employees also contributed to the security of AI systems. “AI applications must not endanger or disadvantage people,” says Fliege. Corresponding legal regulations for the use of AI in security-critical areas are currently being developed in the EU as part of the planned “AI Acts”. The “TÜV AI Lab”, founded last year, supports politicians in developing standardized testing tools for artificial intelligence.

 

To prepare workers for more automated workplaces, professional training must be considered as an individual right. The transition to modern technologies and onwards will be a continuous process. Thus, the training and re-training of employees must not be ignored.

Why is Change Management mandatory for Digital Transformation?

The topic of digitization is omnipresent – and is discussed daily in the media. Digital technologies and their unlimited availability via the Internet are fundamentally changing companies. These technological transformations are altering the world of work as never before. The combination of machines and humans is leading to unimaginable innovations. Forcing companies around the globe to reinvent/revolutionize their business models, redraw the boundaries between industries, and create new interfaces for the customer with the help of digital technologies.

 

These digital advancements are the main motive for companies to adapt and deal with the changes in their work environment. Although digitization is now almost in part of everyday life – it brings changes that trigger fears among many employees. Dealing with such changes in companies can be a hurdle without well-defined change management.

 

“Change Management is the general term used to describe the approaches that businesses take when making both short and long-term organizational change, both of which are often necessary for businesses that want to survive and be successful”. Sustainable change management must keep an eye on social and economical challenges. It must not only take into account the digital transformation but also acknowledge the society and demographic changes as well as productivity and social demands.

Change Management helps your Business

Think globally, act locally. Worldwide companies are increasingly doing business in an international context. Therefore, change management must also be able to control, learn and act across cultures and nationalities.

Change is inevitable and is nature’s law. Management often finds it challenging to make employees adapt to the change quickly and often underestimate their employees which results in the downfall of even the biggest business empires. The key question from the company’s point of view should be: How can we ensure, in a continual state of change, that the employees actually have a sustainable mix of skills, to get the best from them, to achieve strategic goals?

 

Following are some easy ways for you to help your employees adapt to change in the workplace:

 

  • The company’s culture influences the pace of innovation within the organization because digital transformation requires both executives and employees who are willing to take risks and seize opportunities. Therefore, the focus must be put on the corporate culture before opting for any corporate changes or every transformation. Employees must be well prepared to accompany the change and support the new digital strategy for the long term.

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  • With digitization, the challenges faced by employees are also changing rapidly. All members of the organization are equally involved in realizing a shared vision. This means that companies are responsible for ensuring that their workforce meets the requirements of tomorrow and develops relevant skills. A training model for employee development in the digital transformation must be elaborated, with which skills are built up in a sustainable and targeted manner. Additionally, everyone at different levels of the company and in different project teams works together to build trust, promote transparency and involve all employees.

 

  • Change is inevitable, it’s not a single project with a beginning and end. As technology is constantly evolving; current processes have to be constantly adapted. Digital businesses never change the company’s core values ​​or offerings. Instead, it is about developing a networked work culture and acquiring digital tools that support the company’s strategic goals. Thus, it is also important for employees to keep learning and developing.

 

In the current digital transformation landscape, the capability to address and adapt to change within an organization is becoming an essential element of survival for worldwide businesses.  If your company is preparing to undertake digital changes or struggling to manage them, Feel free to reach out to our consultants that offer a wide range of business and technical know-how as well as the necessary instinct to solve the individual challenges of your organization. We can’t wait to help you find success.

2021: IPA- RPA & AI a Perfect Combination for your Organization

2021 IPA- RPA & AI a Perfect Combination for your Organization

 

Robotic Process Automation (RPA) is one of the most popular technologies for automating business processes. In recent years, many companies have decided and introduced RPA to drive process optimization and enabled fast and, above all, efficient automation of their standardized processes. In 2021 the trend towards RPA will not stop, because excellent results are possible with little effort. According to a Gartner forecast, the “global Robotic Process Automation (RPA) software revenue is projected to reach $1.89 billion in 2021, an increase of 19.5% from 2020.

 

A great advantage of RPA is that it does not require deep integration into different systems, but works via the existing user or desktop interfaces of the respective applications. Also known as the bridging technology, RPA supports the automation of numerous processes and thus lower costs without having to change or replace existing applications. RPA is used, among other things, for repeated data entry functions as well as for downloads and uploads in the Enterprise Resource Planning (ERP) area.

 

The key driver for RPA projects is their ability to improve and accelerate work process quality. Mimicking rule-based human actions, RPA automates all repetitive manual processes by lowering cost and time while improving quality. However, in this technology, the range of applications is limited by the need for structured data and programmable decision-making. Unstructured data is the main reason why technology is reaching its economic and technical limits. Thus, it becomes more difficult for many companies to find suitable processes for automation with (RPA) after a certain period of use. But this shortcoming can be overcome through the use of artificial intelligence as Intelligent Automation enables companies to take their existing automation strategies to a new level.

 

In the following, we will show you how artificial intelligence can help RPA bots to become smarter.

 

RPA and AI are two key technologies on the way to the intelligent automation of processes. Both technologies complement each other perfectly due to their different focus, so that from the user’s point of view they merge into an intelligent automation (IA).

As mentioned above, RPA need structured data as input, from different sources. It’s one of the biggest limitations of RPA. This means that the data must first be viewed, validated, and put into a structured form. If the input data is unstructured / semi-structured, artificial intelligence can be used to convert the data for the robots into a structured converted format.

 

Where RPA is weak, AI takes over. AI does all the initial work before data is transferred to the RPA. By using natural language processing, AI, extract the relevant data from the available text, even if the text is written in freeform language or if the information in a form looks or is distributed completely different each time. With semi-structured data, the AI ​​is able to extract the data from a document, even if this data is stored in different places on the form, in a different format or only appears occasionally. For example, on the invoices, the date could appear one time in the top right corner and another time in the top left. The invoice may or may not include a VAT rate, etc.

 

Once trained, the AI ​​is able to cope with this high variability with a high degree of confidence. If it doesn’t know how to process the file on its own, then the AI ​​can assign the task to a human who can answer the question, and the AI ​​, in turn, will learn from this interaction so that it can do its job better in the future.

 

The second limitation for RPA is that it cannot make complex decisions. RPA bots cannot make decisions based on their gut feeling. They need a clear set of rules according to which they operate. Some decisions are relatively straightforward and can certainly be handled by RPA, especially when it comes to applying rule-based scores to a small number of specific criteria. But if the required judgment is more complex, then another type of AI commonly referred to as “cognitive reasoning”, can be used to aid and improve the RPA process.

“Cognitive reasoning” programs work by mapping all knowledge, such as facts and experience that an expert has about a process in a model. This model, a kind of knowledge map, can then be queried by other people or by robots in order to make a decision or draw a conclusion.

 

As we’ve seen, RPA can provide some significant benefits on its own, but the real magic doesn’t come into play until the two work together. AI opens up many more processes for Robotic Process Automation and enables a much larger range of processes to be automated, even when complex and well-thought-out decisions have to be made. Everything is positive about this collaboration between RPA and AI: Investing in RPA is absolutely worthwhile. Existing system landscapes can be retained. AI intervenes flexibly and only where processes can be further improved in a targeted manner. A perfect combination of a leading company!

 

 

Sources

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