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Data: A key resource for Digital Business Models

Businesses are generating and collecting large amounts of data, due to the rapid digitalization in all sectors and industries. Digitization has come to stay so not only the volume but also the variety of data – structured and unstructured – is growing exponentially in companies around the globe. New sources of income and growth opportunities are what companies strive for today. The evaluation and analysis of data help significantly and are becoming more and more important for companies – because the results of such analysis are considered as a strategically valuable asset.

Data A key resource for Digital Business Models

Companies don’t just want to collect the data, but their goal is to get real benefit from it. The analysis of data, which arises from individual digital interactions, generates significant added value for companies. This also includes the processing of omnichannel data, regardless of whether they are structured or unstructured, to get better insights into the entire customer journey. In order to unlock this potential in companies, a data strategy is required, i.e. a plan for data value creation in the company. Because only those who use data in a targeted and intelligent way can make better and faster decisions, optimize processes, improve planning or develop new approaches, define new customer-specific offers, or even innovate the entire business model & define short- and long-term objectives.

If implemented correctly, a data strategy offers companies from all industries and, in all areas of the company, sustainable benefits. In the transformation process, management must take into account the data infrastructure, data management, the general data strategy approach, and data analysis and its use.

 

Data infrastructure

The development of future-proof and efficient data infrastructure is based on a high degree of flexibility in data generation, virtualization, and processing. For high-quality data analysis, companies should therefore increasingly focus on independent software components (microservices) that have interfaces with common communication standards and thus enable quick and flexible integration into new applications without detours. Particular attention should be paid to fast network architecture, the prevention of data silos (e.g. by introducing a data lake), and the inclusion of secure cloud solutions.

 

Data strategy

The development and implementation of a data strategy often present companies with challenges. A suitable data strategy must be adapted to an organization and its objectives. It defines how data is handled and which goals are pursued. Since data value creation is not just a technology issue, but rather affects almost all areas of the company as the core of digital transformation, uncoordinated and decentralized approaches often do not lead to success.

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Therefore, a correspondingly fast and agile strategy is required to achieve results quickly. If the decision is made on a static approach, the motto is usually “defense instead of attack”. The focus is clearly on strict regulations in the handling of data and data quality. With a strategic approach, companies choose the middle ground between strict guidelines and targeted data usage. Companies that take a dynamic approach to data handling use a large amount of data in order to be able to react quickly to market changes and to improve their own analytical skills. Fast data access and quick results are important here. In the dynamic approach, cost savings and profitability through the use of data come to the fore. Flexibility in analysis and quick availability of results, for example through user-friendly data visualization, is essential.

 

The data warehouse

No matter what you need your data for and how you ultimately create your data strategy, every modern organization with a lot of data needs modern data warehousing. The data warehouse is the universal place where data from many different sources is collected. If you are planning a suitable data strategy, the data warehouse is one of the most important core elements to be reviewed. In many companies, IT teams are looking for a suitable data strategy that simplifies administration and helps to draw value from all the existing data. A modern data warehouse must therefore be part of a successful data strategy. Companies working on a data strategy cannot avoid modernizing their data warehouse. And one of the most important tasks in this modernization is the automation of the data warehouse.

 

The goal of a strong data strategy should always be to build an organization where agility is an integral part of its DNA. Such an organization works with an operating model that focuses on the employee and the customer. The model equips the company with the ability to quickly recognize changing business requirements and to continuously develop. We support you in designing, implementing, and integrating data correctly into your existing system landscapes and thus into your processes. 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.

 

 

Sources:

SAP White Paper: Digital Transformation – Digital Business Modeling A Structural Approach Toward Digital Transformation

Unlimited Productivity: Why a resilient Hybrid IT is important for post-Covid recovery?

Unlimited Productivity Why a resilient Hybrid IT is important for post-Covid recovery

 

Hybrid IT refers to mixed computing, a combination of cloud and on-premise technology in which storage and services are made available in any combination of MAKE (self-provided) and BUY (provided by the service provider in any form) so that the best functions of on-site solutions can be used in conjunction with the best functions of cloud solutions. In short, a combination of public clouds, on-premises computing, and private clouds in your data center means that you have a hybrid cloud infrastructure.

 

Businesses all around the globe are under pressure to innovate, thus the move to hybrid cloud adoption is motivated not only by cost-saving but in supporting fast-moving digital business transformation within companies. As the key benefit of the hybrid cloud is agility, businesses ’ needs to adapt and change direction quickly are focused. The better integration and interaction work, the more successful your company can operate. Flexera 2021 State of the Cloud Report highlights 87 percent of enterprises have already adopted hybrid cloud strategies and an estimated growth rate of 17% has the hybrid cloud industry pegged to inflate from a valuation of $44.6 billion in 2018 to almost $100 billion by 2023.

 

types-of-clouds-used

 

Hybrid clouds offer the benefits of both public and private clouds and take advantage of existing architecture in a data center which is why a hybrid mixture of cloud services are chosen by forward-thinking companies. Worldwide end-user spending on public cloud services is forecast to grow 23.1% in 2021 to total $332.3 billion, up from $270 billion in 2020, according to the latest forecast from Gartner, Inc.

 

By mixing the different cloud models, their advantages can be combined. With hybrid IT, companies benefit from the flexibility of the public cloud and the high-security standards of the private cloud or the full control of their own data in an on-premise environment. For example, it is possible to operate a database in a private network while the associated application is running in a public cloud. The advantage: the data is very well protected and the performance of the application is practically unlimitedly scalable at the same time. However, companies must make sure that they know exactly where which data is processed and how they distribute which processes to the various operating models. Otherwise, there is a risk that security-critical data will end up in the public cloud. In addition, hybrid cloud solutions are significantly more complex than pure public cloud or private cloud environments.

 

The pandemic has exposed vulnerabilities in business that have been hidden for too long. Companies are finding it hard to continuously adapt when their systems are separated. With work-from-home policies and automation becoming new norms, the Hybrid Cloud is entering the next digital era in exponential dimensions. But in the end, it is primarily the security requirements for your data that decide which cloud model is suitable for you. If you process data that are not linked to any special data protection requirements, a public cloud offers you numerous advantages in terms of flexibility, scalability, and cost structure. If your company processes particularly sensitive data that, for example, may not be transmitted, private clouds or hybrid cloud environments come into question. Hybrid clouds have the advantage that they are even more flexible than private clouds. However, they are much more complex in operation.

 

While hybrid implementations can lead to unprecedented complexity in some cases, we at Xorlogics help enterprises navigate this challenge. Get an individual consultation with our cloud experts to know which path to the cloud is best suited for you.

 

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COVID-19: Companies Journey toward Digital Expansion to become Faster, more Productive and more Responsive

Digital transformation progress

 

Our everyday life and way of doing things are completely changed since COVID19 started. It has accelerated the global digital transformation, according to the most recent F5 State of Application Strategy survey (SOAS). The seventh annual edition of this study is based on a survey of 1,500 participants from various industries, company sizes, and positions.

 

The need to adopt digital services across industries, geographies and communities is accelerated due to the dramatic shift in remote work and social distancing so that companies can improve their connectivity to interact with customers.

Business leaders have recognized digital technology as a key driver of revenue and raced towards digital transformation within their company. Here, below, are the key findings of the F5 survey:

 

  • AI-assisted business has tripled.
  • Applications continue to be modernized rapidly, with APIs a method of choice.
  • The importance of SaaS-delivered security is rising as organizations work to unify security across distributed applications while managing more architectures than ever.
  • Architectural complexity makes multi-cloud availability an imperative, and edge deployments are increasing, too.
  • Telemetry will take us to the future—but now, nearly everyone is missing the insights they need.

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Future-ready organizations are working to improve connectivity, reduce latency times, guarantee security and use data-driven insights. There is increasing interest in public cloud and SaaS, edge computing, and seeking application security and delivery technologies that are easy to deploy and provide data for decisions.

Modernization remains the top priority when it comes to operating on both modern and traditional application architectures for more than 87% of organizations that’s 11 percent more than in 2020. Additionally, almost half of all companies – 30 % more than last year – manage at least five different architectures.

 

Since last year’s SOAS report, the growth of AI and machine learning has more than tripled to 56%. This means that more and more companies are in the late phase of digital transformation. 57 % of those surveyed have begun digital expansion, an increase of 37 % compared to the previous year. This shows an increased focus on business process automation, orchestration, and digital workflows to integrate applications. 77% are already modernizing internal or customer-oriented apps, which is 133% more than in the previous year.

 

Additionally, two-thirds of respondents use at least two methods to create modern workloads, a mixture of traditional and modern application components. Of the companies with only one method, 44% say they use modern interfaces, either via APIs or components such as containers. More than half of the respondents already use infrastructure as code. Organizations using this approach are twice as likely to deploy applications even when using automation. They are also four times more likely to use fully automated application pipelines.

 

Companies are realizing the potential of edge computing. It enables new services and better performance by placing applications as close as possible to the sources and users of data, situation may vary for each industry and business function. Of course, COVID-19 is an accelerator due to the distribution of labor. No less than 76 % of those surveyed are using or planning edge implementations. The top reasons are to improve application deployment, performance and data available for analysis. In addition, 39% believe that edge computing will be strategically important in the years to come. 15% already host technology for app security and delivery at the edge. More than a third of companies (42%) will support a fully remote workforce for the foreseeable future. Only 15% plan to bring all employees back to the office.

 

Companies are creating and collecting more data than they have at any point in the past. All this data is coming from different sources. However, according to surveys, sufficient data does not necessarily deliver the insights companies really need. More than half of the respondents already have tools that assess the current state of applications. But an alarming 95 % say that they are missing important findings from the existing monitoring and analysis solutions. Accordingly, the collected data is primarily used for troubleshooting, followed by the early detection of performance problems. Almost two-thirds of respondents (62%) measure performance in terms of response times. Less than a quarter of companies use them to uncover degradation in performance. And only 12 percent forward the data to business areas.

 

More than 80% of respondents believe that data and telemetry are “very important” to their security, and over half are excited about the positive effects of AI. Participants also named platforms that combine big data and machine learning (also known as AIOps) as the second most important strategic trend in the next two to five years.

 

In many ways, the coronavirus pandemic has challenged businesses and governments around the world. In order to rise to the challenges caused by the pandemic, businesses have modernized and distributed applications in short term. Digital technologies have allowed many organizations to avoid a complete standstill, due to unexpected and urgent shifts in work. Companies must continue to discover and implement AI and other digital technologies for the continuity of their business.

 

The full report can be downloaded here: The State of Application Strategy in 2021

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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Is Your Digital Business 100% Secure?

Is Your Digital Business 100% Secure?

Digital transformation is creating unprecedented opportunity for organizations today. Along with its far-reaching impact and significant changes in business models, it also comes with unprecedented risk. There are companies that are completely digital. Digital technologies such as mobile, cloud and IoT make it possible to offer new conveniences to customers, operate more efficiently than ever and gain other benefits. With the changed way of working, the demands on security have also changed, as those same technologies have also open doors to a new and special type of cyber-attacks. Here below are few security guidelines that must be carefully considered in pursuing digital initiatives.

 

Cybercrime: The Importance of Prevention!
One of the best and reliable way to guard your company against cybercrime is by educating and informing your staff about cybercrime prevention. It wasn’t long ago that data theft was classified as a social phenomenon somewhere between fun and crime. But cybercrime has now developed into a growth market – in a negative sense.
In a there  2020 Cyberthreat Defense Report, CyberEdge Group found that 81% of surveyed organizations were affected by a successful cyber attack in 2019. The average downtime due to a ransomware attack was 16.2 days in Q4 of 2019 compared to 12.1 days in Q3.
As more and more data is available digitally, the total volume of criminal activity increases. Computers and smartphones are affected equally. Therefore, by teaching your employees to recognize warning signs, you could also enhance your cybercrime prevention strategy.

 

Hardware Security Is a Must!
When it comes to protecting your device, wo-factor authentication (or 2FA offer a whole new level of security for your personal or business devices. It’s a software-based system that send you a text message or email to confirm your identity. In addition to 2FA, you should also invest in a degree of physical protection for your secure hardware in order to prevent disasters. You may also get a tailor-made insurance coverage for your devices. Protecting the hardware alone is too short-sighted. Ultimately, it’s about the corporate data, some of which is stored on the device, some in the cloud somewhere on the network.

 

Secure Basic Configuration

The basic settings for  Internet-enabled devices such as smartphones and laptops include the security settings in the device. These can vary from manufacturer to manufacturer. Apps and operating system should always be kept up to date on one device. The automatic setup for installing available updates is indispensable, because many attacks come via known security holes on the devices.

 

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Protecting organization’s and customers’ personal data is vitally important to the success of any organization. Encrypting that data is one of the best practices to be on the safe side. In 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.

 

Avoid Public Hotspots!

Working on a free WiFi can be attempting for employees who pay for their own data plans. Public hotspots in a café or in the airport are often unencrypted. Employees 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 to companies’ data via their secure connection at home or enable their 4G for a secure connectivity when they are on travel.

 

Regularly Perform a Backup Copy

Regularly back-up important data and information. Determine which data should be backed up, how often it should be backed up and where the copy will be saved. Keep this backup in a safe place and make sure it is always disconnected from the network. Also, if you notice that you have been infected, immediately disconnect from the network.
Also, keep information on your computer that is not connected to the network or on paper, such as important e-mail addresses and phone numbers, or information about your Internet service provider.

 

Cyber Crime Insurance

Cybercrime insurance is suitable for protecting companies against the consequences of IT attacks. Either the attack is internal or external, it can lead to a complete shutdown of operations and digital business activities to a standstill, resulting in downtime costs. In these cases, cybercrime insurance steps in and pays the costs. Extendedand personalized policies also bear the expenses incurred for data recovery or legal advice. In short, crime policies cover the direct loss of your funds, whether through maleficence, employee dishonesty or social engineering. So that things don’t get out of hands, business must take basic protective measures.

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