How To Approach The Testing of ERP Application

ERP applications have become critical for the smooth running of enterprises. Since these comprise myriad modules, functions, and processes, the need to validate them becomes critical.

Enterprises are realizing the need to leverage the SMAC (Social, Mobile, Analytics, and Cloud) model to accelerate growth. However, overhauling core processes administered by legacy ERP applications is equally critical. ERP applications help enterprises manage various functions, departments, and processes, including the data generated therein.

These applications help enterprises to run as one single unit and, in the process, generate outcomes such as improved productivity, better efficiency, reduced waste, enhanced customer experience, and increased ROI. In view of the criticality of ERP applications for organizations, they should be tested and validated. Testing ERP applications can ensure the smooth functioning of multiple tasks within organizations. These may include tracking inventory and customer transactions, managing finances and human resources, among many others.

What is ERP?

Enterprise Resource Planning aka ERP is a comprehensive software that integrates the various functions of an organization into a single system. The software has a shared database containing all information pertaining to the various functions or units of an organization. The ERP system helps to streamline the processes and access to information across the organization 24×7.

Why is ERP software testing needed?

ERP software is cost-intensive and requires a lot of investment in time and effort. Every ERP software comes with multiple versions and requires customization to suit specific business requisites. Moreover, since every element in the application is connected to some other module, upgrading them can be a challenging task. For example, creating a sales order would need access to the inventory management module. If any of the modules does not function to its optimum, the entire ERP application may be impacted. This can have a cascading effect on the performance of the company as well as create bad customer experiences. Hence, testing ERP applications shall ensure the correct implementation of the software and prevent crashes.

ERP software testing, besides checking the software’s functionalities, should ensure the generation of reports and forms accurately. By identifying and removing bugs during the testing phase, testers can avoid facing post-implementation blues. Moreover, it can lead to an early adoption of software and ensure its smooth running. ERP application testing services validate business processes, functions, and the rules governing them. They help reduce operational risks within the constraints of available resources and time.

The importance of automated ERP testing

Since the ERP system contains huge volumes of data, testing the manual procedures can be time and cost intensive. Automated testing can help to validate all the features and functionalities in minimum time and cost. Also, since multiple business units of an organization can have different processes or procedures, automated testing can check the accuracy of their output against specific parameters. Further, the ERP system needs to be updated periodically with the advent of new technologies like Cloud, Big Data, and Mobility, among others. Such updates help the organization to validate transactions in real-time, which is not possible manually.

Best available ERP testing tools

Since the ERP systems are available in multiple versions targeting multiple domains, units, and customers, the best testing tools available are:

·         Microsoft Dynamics NAV – For SMEs

·         SAP Insurance – For insurance companies

·         Microsoft Dynamics AX – For large scale enterprises

·         SAP Banking – For the banking sector

Approaching the testing of ERP applications

It is imperative for enterprises to set up a robust testing strategy. The strategy should prioritize the testing of processes depending on the short and long-term goals.

Setting up KPIs:

At the outset, testers should setup the KPIs or performance metrics and evaluate how they will impact the overall organizational goal as well as departmental objectives. Thus, establishing the KPIs will help derive the right ROI for the organization.

All-encompassing:

ERP implementation for a large organization with many departments and processes can be a complex and challenging job. However, it is important that all stakeholders are taken into confidence and involved in the process. The process also includes making the necessary investment in training. When everyone is involved in ERP implementation, there is more cohesiveness in the administration of the software.

Data migration:

An organization can plan its strategic moves if it can make use of its data emanating from various processes over a period. To ensure real data is not lost or distorted in any way during ERP validation and testing, its proper migration process should be planned beforehand.

Selecting the right automation tools:

As ERP software can have myriad variables interfacing with various processes, they need to be validated. This requires choosing the right test automation tools – open-source or premium ones. Automated ERP testing can validate many variables for various processes against expected outcomes. The right automation tool will help testers to write and execute test cases.

Identifying test cases:

Since it is not possible to test every sinew of an ERP application, proper test cases should be written to ensure the maximum test coverage. Thus, testers should identify the test cases for each test and document them as well. Also, since ERP processes are linked to each other, and even to third-party applications or modules, they should undergo automated ERP testing.

Conducting performance, regression, and security tests:

As an ERP system helps to run the operations of an enterprise as a single unit, it should run some critical tests. These include regression, performance, integration, security, and usability tests. This way the enterprise can ensure continuous monitoring of the system, save time and cost, and prevent any sudden downtime or latency.

Proper documentation:

Post testing of components in the ERP system, the documented glitches ought to be analyzed to preempt any failure in a real environment. Moreover, the reports can be used for future reference.

Conclusion

To sustain in the competitive business environment of today, businesses need to take digital initiatives such as implementing an ERP solution. However, to ensure the successful running of such a solution and derive benefits out of it, enterprises should carry out ERP testing. The approach for such a testing should involve automation and carrying out various types of testing.

This article is already published on softwaretestingmaterial.com

How to address the Performance Testing challenges of IoT

The digital age aka industry 4.0 has been redefined by intelligent solutions that are merging the digital and physical worlds across verticals. These intelligent solutions are leveraged by organizations to enhance scalability, enable customization, realize efficiencies, improve customer experience, and achieve ROI. The Internet of Things or IoT technology is driving synergies between smart machines, industrial processes, and software applications. This requires organizations to build end-to-end systems with enhanced capabilities, driving outcomes such as product enhancement, innovation through collaboration, greater operational visibility, better equipment performance, and quicker decision making - all based on contextual data obtained in real-time.

The Internet of Things (IoT) connects smart devices to the internet using sensors. It also connects such devices to digital technologies constituting big data, artificial intelligence, and wireless networks. The main objective of establishing such a network is to collate and share intelligence among devices without any human intervention. The data obtained from IoT helps organizations to analyze their digital ecosystem and pre-empt equipment malfunction, downtime, and other glitches. It gives them insights into the performance of products and how they are utilized by the users. The insights can be leveraged to enhance the differentiating features of products, create value chains, and build new business models to drive growth.

IoT helps organizations to

• Track and monitor assets in real-time with respect to their performance and availability
• Analyze data from sensors for predictive maintenance
• Take critical business decisions
• Generate greater efficiency, enhance safety and customer experience and create new business models and revenue streams

However, IoT can present a host of challenges, especially concerning performance testing.

Challenges in application performance testing of IoT devices

• Increased complexity: Since data communication takes place between smart devices such as televisions, air conditioners, washing machines, refrigerators, or smartphones, they need to be considered for performance testing. However, the plethora of devices can increase the level of complexity while drawing a specific performance testing strategy. Also, recording data from mobile devices, and web browsers, among others by using a load tester is relatively easy compared to testing the above-mentioned devices without changing their settings.
• Tackling the impact of factors: In IoT, factors such as network bandwidth, load, latency, or packet loss, among others can be critical when it comes to executing application performance testing. For example, if the above-mentioned factors are not tested for a web or mobile application, the same may crash.
• Stateless operation: Typical software applications are connected through a sequence of steps aka context or state. However, since IoT sensors do not follow any well-defined context, the IoT applications ought to manage such context or state elements.
•  Diverse device interfaces: With changes in IoT devices and the addition of new ones with different connection protocols and data formats, the performance testing methodology needs to change as well. This is because every new addition would require the execution of performance testing. 
• Absence of subjective feedback: In most testing procedures, data can be inserted to test the effectiveness of UI or response time. However, the same cannot be provided by the IoT networks.

The performance testing approach to tackle the challenges?

To begin with, testers should prioritize test cases, especially the key areas that can take the longest testing time. Testers must understand to choose such areas as the consequences of performance issues can be devastating for some businesses compared to the rest. Also, given the fact that a great deal of standardization has taken place in the technology field, the testers should ensure their compliance while providing performance testing services. Any updates being pushed for these devices would present challenges of security and usability. The core functionality of IoT devices should include monitoring their current status as they are connected to a network 24x7.

Implementing IoT can include devices that do not have IoT in them. These may include communication networks, instrumentation, and storage, among others. The complexity of such devices and the lack of an IoT label would require testers to first understand how the pieces would fit in the jigsaw. Thereafter, testers should streamline the complexity and communicate the importance of each device and make it work.

Conclusion

The efficient way of driving the performance of an IoT based application is to implement a robust testingplan. It should be followed by determining the peak load factor faced by the device at any point in time. The testers should use appropriate testing tools to validate performance efficiently. By implementing performance testing, businesses can integrate IoT in their processes and achieve success.

This article is already published on medium.com.

How to Secure your Web Applications - Complete Guide

Digitization has led to the development of web applications, websites, and other tools. Besides changing the way that we share information, interact, or do business, these digital elements have transformed our lives for the better. Enterprises, in order to stay flexible, profitable, and competitive, are moving their operations online. This way, they allow their employees, clients, customers, and other stakeholders to stay connected 24x7. Also, employees working in remote offices across countries can interact and collaborate in real-time by using such technologies.

The introduction of Web 2.0 has brought convenience, speed, choices, and quality on a platter for the customers. The growing customers’ appetite for top-notch web applications has led businesses or entities to share sensitive data all across the value chain. The examples of e-commerce stores and online banking exemplify this trend. If such advancements have brought enormous benefits for individuals, businesses, and organizations, they have attracted hackers and scammers as well.

The news about malware, ransomware, trojans, and viruses playing havoc has become common now. In fact, cybercrime has become a $1.5 trillion industry as we move into the year 2020. It has the potential to push individuals, businesses, and organizations into a downward spiral. The cumulative effect of cybercrime has given rise to the industry of web application security.

Let us take you through the ways to secure your web applications in the form of a guide. Here, the focus would be on conducting a comprehensive web application security audit encompassing web application security testing.

Assessing the Target Web Application: The process can involve the use of an automated web vulnerability scanner provided the pre-scan activities are already done. However, the procedure is not foolproof and can give rise to several false positives as well. This happens as the web vulnerability scanners are meant to scan a number of complex web applications. The users, thus, need to align these scanners to the specific business needs.

The web application security testing can begin by conducting a manual assessment of the target web application. Thus, you can get familiarized with the architecture and topology of the web application. Find out about the directory, file structure, number of pages, and files present in the application. Also, know about the application’s root directory, source code, online forms, and URL structure. Since there are a number of vulnerabilities specific to web technologies, it is better you know the one used to develop the application - PHP and .NET, among others. Find out if the web application had crawled from the black-box scanner before launching the scan. Remember, if the web application is not crawled and leaves out some parts or parameters, then securing the application will not happen.

Denial of Service (DOS) Checklist: Web applications cannot distinguish between valid traffic and a malicious attack. Among the reasons, the uselessness of IP addresses as identification credentials comes at the top. For example, during a distributed attack the web application cannot identify a real attack from multiple users reloading at the same time. In this type of software application security testing, the number of sessions per user should be checked and regulated, if need be.

Penetration Testing: Make sure all the web penetration tools are available in a centralized repository supporting the import and export of data. The application security testing services should use penetration testing - manually as well as using tools to check for logical vulnerabilities and to audit the application.

Web Application Firewall (WAF): It can analyze web traffic emanating from IP addresses containing both HTTP and HTTPS. This way WAF can identify malicious traffic that works at the application layer. It can block connections to known vulnerabilities in a web application thereby preempting any malicious attack. However, it comes with a few shortcomings as well:

• Ability to detect only known security vulnerabilities
• Depends on the expertise of the user
• No fixing of security holes in web applications

The software application security testing should be conducted throughout the SDLC and not when the application goes live. It comprises of several methods such as:

• Using a black-box scanner
• Conducting a manual source code audit
• Identifying coding issues using an automated white-box scanner
• Penetration testing
• Conducting a manual security audit

Conclusion

Web applications can be the ideal conduit for the ingress of malicious codes into an IT system. However, the quality of such applications can be enhanced, and security strengthened by using the right vulnerability scanner. By employing a focused application security testing methodology, both logical and technical vulnerabilities can be identified and fixed. The other avenues include limiting remote access, switching off unnecessary functionalities, using accounts with limited privileges, segregating live environments from development and testing, installing security patches, and staying informed.

How to ensure Digital Transformation by Testing Transformation

Digital technologies, no matter how complex or challenging for businesses to implement, have been accepted as an inevitable facet of modern times. The examples of hovering drones delivering products, virtual assistants like Siri or Alexa answering customer queries, or smart devices like Google Home or Amazon Echo has become commonplace. The advent of new technologies is a testimony to the growing customer expectations of glitch-free products or services. Enterprises, in order to stay competitive and deliver great customer experiences, are embracing digital transformation in a big way. Accordingly, legacy systems are being replaced or upgraded with newer technologies embracing SMAC (Social media, mobility solutions, Analytics, and Cloud).

As customer experience becomes the catalyst for driving enterprises to invest in competitive solutions for sustainable growth, QA assumes significance. To make digital transformation implementation effective on the ground, the software and systems need to be tested rigorously. This is all the more important as digital transformation services touch the most important aspect of people’s lives. Rigorous QA testing helps in identifying glitches in software and makes it fit for customer acceptance. The success of any digital transformation journey is underpinned on the usage of the right tools, standards, processes, protocols, and methodologies. When the ultimate objective is to deliver a superior customer experience, then QA should be a part of the digital transformation strategy. In fact, enterprises should look at the quality transformation to realize the impact of digital transformation implementation.

Why quality transformation is required to deliver digital transformation?

Quality, as the most critical attribute of a product, can only be ensured if every process or department in an organization enforces it. It calls for implementing a set of protocols and regulations cutting across departments or processes for every transaction or activity. It is important to realize the DevOps outcomes of Continuous Integration and Continuous Delivery of builds. So, how to achieve quality transformation in the first place?

Achieve a speed of testing through test automation: Since the testing of codes should be for multiple channels, the QA teams should use test automation. The automated test suites can run quick tests by leveraging virtual users to achieve DevOps and Agile goals.

Activate the feedback loop: Silo-driven processes can often be the impediments in giving the right feedback about a product. This leads enterprises to identify any fault later in the SDLC and rendering mitigation, time-consuming and costly. However, by incorporating the shift-left approach where the development and QA teams work in tandem, feedback on glitches can be exchanged fast.

Incorporate AI-driven analytics: Artificial Intelligence has come as a shot in the arm for testers and developers. It analyzes past patterns of data to identify the presence of glitches in processes. This helps in speeding up the QA process and ensuring a seamless CI/CD pipeline. Moreover, when the security of applications has become a critical quality requisite, AI-driven analytics can help in creating robust software.

Let us understand with an example as to why testing transformation is essential to realize the benefits of digital transformation solutions:

A retail chain going for digital transformation implementation to deliver great customer experiences can court trouble if the software contains glitches. This can expose the software to security breaches and the loss of sensitive customer data. If not addressed in time, the same can have implications for the retail chain. These may include the loss of customer trust, inviting regulatory censure or penalties, or class suits from clients/customers.

Implementing the right digital testing strategy

To gain a competitive edge in the market and deliver the right customer experiences, enterprises need to tune into the latest trends. These include big data, mobility services, AI-driven analytics, and cloud services, among others. In fact, QA transformation can help enterprises to adopt new and disruptive technologies.

Digital transformation envisions the adoption and integration of disruptive technologies to provide an omnichannel experience to the customers. However, enterprises face a slew of challenges when embracing such technologies. These are mainly related to the integration of both technologies (new and existing), changing the work culture, and training the workforce, among others. This is where QA transformation can help enterprises to take a gradual approach in managing, measuring, and implementing technologies.

Conclusion

To address the diverse needs and challenges concerning digital transformation, the quality testing process should be changed accordingly. It is only by testing the transformation of processes or workflows that the fruits of digital transformation can be obtained. This encompasses the conduct of rigorous testing across the value chain comprising cloud, web portals, devices, browsers, operating systems, and networks.

This article is originally published on digitaldoughnut.com

Building the right Performance Testing strategy

In our digitally-connected world where companies are churning out umpteen number of products or services to be accessed over digital devices, performance becomes a sticky issue. The word ‘sticky’ has been used deliberately as the performance of a product or service depends on a host of factors. And delivering a glitch-proof product is no guarantee of its smooth performance. In fact, factors like responsiveness, network bandwidth, and others can deal a body blow to the performance of an application. Just think of an airlines portal catering to thousands of transactions every second. If the portal does not follow a robust performance testing strategy and selects a threshold for load, it is likely to crash midway or show latency. This can adversely impact the user experience.

What is performance testing?

It is a form of software testing where the application under test needs to be checked for its load handling capacity. The load performance testing process determines the stability, speed, throughput, and responsiveness of an application or system when working under a load. It is a non-functional testing that comprises various tests such as load test, capacity test, scalability test, soak/endurance test, volume test, and spike test.

To build the right performance testing strategy, one must be aware of the associated challenges. These include

·         Testing the software under realistic scenarios

·         Picking the right tool to simulate real users

·         Lack of test data

·         Limited test coverage area

·         Poor scalability not allowing the handling of concurrent tasks

·         Poor network configuration

·         Insufficient hardware resources like low performing CPUs

·         Insufficient capacity to handle the workload

The performance testing methodology should define the scope, load policy, and SLAs surrounding the application. Since everything about the software cannot be tested, a decision should be taken to identify the specific area, feature, or functionality of the application for testing. It has been observed that around 10-15% of test scenarios contain around 75-90% of bugs. So, it is better to focus on those scenarios and mitigate the lion’s share of glitches.

How to build the right Application Performance Testing strategy?

Selecting the right strategy would determine if the performance of the application covers all the right areas and load scenarios.

Test environment: Set up a robust test environment by identifying elements like hardware, network configurations, and test tools. This will help the QA team to identify challenges pertaining to performance testing early on in the SDLC. In fact, QA experts can have a number of options in setting up the test environment. These include:

·         A production system containing a smaller number of servers of lower specification

·         A production system comprising a smaller number of servers of similar specification

·         Using the actual production system or its replica

Baseline for user experience: At the beginning of conducting load performance testing, the QA testers should know the level of user satisfaction. So, it is not merely about the number of load times or responsiveness of the application. Identify a baseline for user experience that the application should be tested for.

Performance metrics: Choosing the right performance metrics is important to plan for testing. These include throughput, response time, and constraints. For example, response metrics deal with measuring the performance of an application from a user’s perspective. While volume metrics is about measuring traffic generated by the load testing tool vis-a-vis the application.

Realistic tests: Allowing umpteen number of virtual users to face a server or cluster of servers may not be the right way of measuring load in a real-world scenario. While setting up such a scenario, the focus should be on choosing the devices or environments that would be used to access the application in real-time. This is important because the traffic is likely to come from a host of mobile devices, operating systems, and browsers. Also, the realistic test scenario should vary the test environment. This is to allow the organization to become resilient to the changing market dynamics.

Performance testing a part of Agile: Performance testing should not be conducted at the end of the development process. This makes it too late and expensive to fix glitches. So, load performance testing should be integrated with the development process a la Agile. In fact, performance engineering should be a part of the scrum and entrusted with measuring the performance of code during development.

Conclusion

In a competitive business environment where the quality of software application determines the latter’s success, building the right strategy for performance testing is critical. It ensures the smooth performance of application against a definitive user load scenario.

What does 2020 has in store for Software Automated Testing

The quality of software has become the single most important element in ushering success for any enterprise. However, ensuring quality can be a big challenge and involves following the latest software automated testing trends. Also, with the advent of new technologies and apps having SMAC (Social Media, Analytics, and Cloud) interface, testing is not the same anymore.

The objectives of testing are guided by a slew of considerations. These include achieving faster time-to-market, delivering products based on customers’ feedback, and generating better ROI. Given the criticality of automated testing services, more and more enterprises are embracing the end-to-end shift-left testing methodology. Further, the emergence of Industry 4.0, driven by IoT and other technologies, has prefaced the role of software automated testing.

In the last few years, trends like Agile/DevOps have dominated the testing landscape. The year 2020 is likely to be the continuation (and consolidation) of the earlier trends, but with more sophisticated technologies, wider adoption, and better innovative solutions. Let us check them out.

The software automated testing trends to expect in 2020

Automation has continued to dominate the testing industry for the past few years. In fact, it has allowed the validation of various testing methodologies by using virtual users. Further, it can be extrapolated to test software incorporating new technologies such as AI and ML.

Artificial Intelligence and Machine Learning (AI and ML): With intelligent devices generating humongous quantum of data, artificial intelligence and machine learning can be leveraged to draw business intelligence. These technologies make testing faster, smarter, and effective.

If earlier, AI and ML were leveraged to prioritize test cases, predict the quality of tests, or classify defects, among others, 2020 will see the inclusion of more testing areas. In fact, the forecast of investments in AI and ML testing is likely to reach a whopping $200 billion by 2025.

Rise in Cyber Security Testing: The omnipresent and ever-growing security challenges concerning digital revolution have brought automated testing services w.r.t security to the fore. In fact, business stakeholders like the CIOs, CEOs, and CFOs have understood the gravity of the challenge. The thrust, therefore, in any test automation strategy is to offer total protection to the critical data. This can safeguard systems, databases, and the overall business from suffering losses or losing customer trust.

In the year 2020, DevSecOps will attract the traction of business stakeholders. In such a case, everyone in the organization shall be expected to be accountable in upholding security. Thus, the software application coming out of the SDLC will be more resilient to cyber threats. No wonder, the efforts to uphold cybersecurity will move a few notches higher.

Performance Testing and Performance Engineering: If product testing had a strong element of performance testing in 2019, then 2020 will see a greater move towards performance engineering. In the latter, there is a collaboration among various processes and elements to deliver the highest level of quality. These include software, hardware, security, performance, usability, and configuration, among others. Since delivering superior customer experiences has become critical for the success of a product, then a move towards performance engineering is likely to deliver customer delight.

IoT Testing: With automation becoming the leitmotif of the techno-driven world of ours, the use of IoT devices has been on the rise. According to an estimate by Gartner, the number of IoT devices with embedded software at their core may rise to 20.5 billion by 2020. Since smart systems are likely to drive the world of tomorrow, the embedded software inside systems needs to be validated for quality. For example, unless the sensors are validated for their quality in a self-driven automobile, the consequences can be catastrophic.

IoT testing involves the testing of devices with embedded software. This is about ensuring device authenticity, security, data integrity, compatibility, performance, scalability, and usability. The challenges faced by IoT test engineers is monitoring communication between sets of software running on various device platforms and operating systems. The challenges in forming a test automation strategy for IoT mainly revolve around the lack of expertise in testing IoT functionality.

Big Data Testing: The increasing use of digital devices is giving rise to big data. These are mostly needed to be processed in real-time to derive suitable insights including business intelligence. The usage of big data is seen across sectors like healthcare, banking, technology, retail, telecom, media, and many others. The processing of such data leads to the optimization of workflows and better decision making. Big data testing deals with a humongous quantum of disparate sets of data. As more companies embrace digital transformation, the possibility of data generated from various areas will increase. Thus, implementing an automated testing strategy around big data is likely to dominate the testing landscape in the year 2020.

Conclusion

As software becomes more complicated and interfaces with myriad third-party applications, software testing needs to follow suit. In the year 2020, automated testing will harness existing technologies as mentioned above to deliver high-quality products. To create new-gen products, enterprises should use the next level of testing trends in the year 2020.

This article is originally published on readdive.com

Why the Media Industry needs QA Automation Services?

Like other industry segments, the media industry is transforming to improve the quality of its services. In a fast-changing world, disseminating information in real-time can be a challenge. The media has to be at the forefront of everything as an entire global ecosystem related to the world of economics, politics, foreign policy, and many others is dependent on it. So, unless the media dishes out accurate information seamlessly in double-quick time, the implications for the ecosystem could be immense.

Importantly, media companies are facing serious cost escalation in delivering services. This is due to the rising competition from Over-The-Top (OTT) players and other overhead costs. However, these challenges can be addressed by identifying and leveraging the value trapped across organizations and reinvesting them to fuel new growth avenues.

The media of today uses a plethora of technologies to collect, process, and transmit information in real-time. This leaves no scope for errors as the implications can be huge. Media too is grappling with challenges that others are facing. These include working with legacy systems, which do not lend themselves to quick real-time processing. Further, the digitally savvy consumers of today use a range of devices to access information. This means the news distributed over multiple channels should be accurate, secure, and responsive. So, how to overcome such challenges that a globalized world has brought about? The answer is digital transformation induced QA automation services that make the final product dynamic, richer, responsive, and secure.

The media industry encompasses a host of techno-driven scenarios, activities, products, and services. Some of them include OTT, IPTV, set-top boxes, video transcoding, buffering, streaming, closed captioning, and video editing. To ensure their quality, software QA automation should be made part of the workflow. However, care must be taken to ensure software test automation services include the below-mentioned conditions:

·         Be technology and tool agnostic

·         Capability to run tests across devices and platforms

·         Provide an expansive test coverage area

·         Ensure quality in the quickest possible time

·         The automated QA testing tool should accommodate various file formats, payment processing methods, security protocols, or streaming scenarios.

How QA automation services can help the media industry?

The media industry is increasingly driven by changing customer behavior. It includes rising expectations among the younger generation demanding quick access to quality content in real-time, anytime and anywhere. Also, the media industry is facing various other types of challenges, which include:

·         Consumers becoming savvy to identify marketing campaigns disguised as editorial content.

·         Consumers becoming aware of the information about them being monetized by third parties. In fact, complicated privacy policies are turning consumers to media players who provide better data privacy and transparency.

The digital transformation initiatives comprising software QA automation can help media companies in addressing the above-mentioned challenges and deliver the following benefits:

·         Simplifying Operations: There is a lot of trapped value in silo-driven departments and processes. These increase the Opex budget of media companies as they end up duplicating efforts across traditional and digital channels. Media companies can become efficient, focused, and better performing by centralizing their processes. This shall simplify operations and release value for the companies to drive growth. Developing an ERP solution customized to the specific needs of the media industry can achieve the above-mentioned outcomes. And by running automation testing services, each and every feature and functionality of the solution can be validated.

·         Real-time Content Management using Data Analytics: Media companies are increasingly delivering services built around content. In doing so, they are expected to provide meaningful customer experiences. Data analytics can derive meaningful inferences about consumer preferences from a variety of channels and devices. And automated QA testing can check the data for any hidden glitch or bug and turn it glitch-free. It is only when structured and glitch-free data is analyzed that proper business intelligence can be derived. This can help media organizations to plan suitable strategies and stay up the winning curve.

·         Contextualization and Personalization: Content creators and marketers need to generate personalized content to garner consumer attention. This can be a challenge given the information overload consumers are subjected to. However, while doing this, issues of data privacy and security ought to be tackled in a transparent manner. A robust QA process can ensure if the sensitive consumer information is secure or the delivery process adheres to the existing security protocols or regulations.

Conclusion

The media industry is churning due to the advent of new technologies, growing competition, and changing customer preferences. Moreover, since disseminating content over multiple channels needs to be assured of quality and security, media companies can engage QA automation services.