enabling business responsiveness with intelligent

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Benefit from Comprehensive Testing with Analytics to Adapt Dynamically Create Intelligent Overarching Test Strategy with Automation for Dynamic Deployment An IDC Infographic, sponsored by Micro Focus Enabling Business Responsiveness with Intelligent Continuous Testing Respond to Breadth of Coverage Demanded for High-Quality Applications Establish Performance Engineering Strategies for Governance Across the Software Portfolio Leverage AI for Agile Execution to Extend Reach, Increase Efficiency, Cut Costs, Improve Quality Rapid digital transformation (DX) for business survival demands upfront velocity testing across multiple areas — for example: Multiplicity of systems and technologies across myriad platforms for multimodal deployment poses compound challenges that mandate automation. AI and advanced analytics adoption can: IDC sees use of artificial intelligence and machine learning to address core areas: For digital innovation, organizations must “shift left” and test software rapidly across a complex plethora of environments to keep pace with DevOps pipelines. “Smarter” testing and quality strategies leveraging artificial intelligence can help increase efficiency, resilience, and business optimization. Security Source: IDC, CIO Sentiment Survey, September 2020 Sources: IDC, U.S. DevOps Survey of Enterprise Organizations, December 2019, n = 102; and IDC, PaaSView and the Developer, May 2020, n = 2,500 Source: IDC, U.S. DevOps Survey of Enterprise Organizations, December 2019, n = 102 Source: IDC, U.S. DevOps Survey of Enterprise Organizations, December 2019, n = 102 Reduce maintenance costs Increase test coverage and deployment speed Extend testing reach to non-technical business users Enable visible, actionable metrics of respondents cited manual efforts associated with testing as the leading challenge. Project replanning and change management were the next most frequently cited challenges. 40% of organizations are interested in being a digital solution hub or part of a community that collaborates to create and share digital solutions of organizations seek tools that support both modern applications and mainframe 70% 90% Scale automation with AI technology to keep pace with pipeline, data, and business dynamism and complexity. Increase coverage rates and efficiency via computer vision and machine learning for object identification and location to mitigate maintenance efforts; gain testing benefits from AI. Enable efficient script management and metrics to help address skills barrier with natural language processing. AI models enable self-learning, evolving over time as additional data is gathered to augment capabilities and increase efficiency. 29% App development pipeline optimization 24% Delivery bottlenecks 19% New app development outcomes 16% Accelerating testing 12% Exploring AI cognitive ecosystems Increasing demand for efficiency drives functional testing with emerging AI usage and analytics. Performance engineering and performance testing enable rapid scaling with the shift to digital transformation and remote work. Management of tests, test environments, and test data is vital for visibility, coverage, governance, and compliance. Resilient app design and security vulnerability analysis and testing help protect businesses for DevSecOps. Robotic process automation for operations automation and quality coordination help automate mundane, error-prone tasks. Unite performance, functional, and nonfunctional testing across complex ecosystems of apps and technologies. Remain relevant in today’s economy through adaptive, high-quality execution with performance engineering. Incorporate organizational and agile process change with appropriate quality automation strategies for success. All IDC research is © 2021 by IDC. All rights reserved. All IDC materials are licensed with IDC’s permission and in no way does the use or publication of IDC research indicate IDC’s endorsement of Micro Focus’s products and/or strategies. This infographic was produced by: January 2021 | IDC Doc. #US47015420 Learn more about digital transformations and how to deliver value at high speed with low risk. Message from the Sponsor Visit the Micro Focus Accelerate Application Delivery solutions Functionality Customer experience Performance Testing imperatives exist for safe, relevant, high-quality software to avoid the reputational and business costs of poorly performing, broken, porous, irrelevant, and ugly software (produced at DevOps speeds). As complexity evolves, it demands business alignment, automation, and leverage of artificial intelligence/machine learning (AI/ML) augmentation. AI/analytics is the top area of investment for IT-focused spending; COVID-19 is boosting AI usage via automation for improved decision making, modeling, and monitoring in dramatically changing environments. Sustainable software-based innovation demands that companies deliver value faster than technical debt is accrued. Businesses must respond to changes to their enterprise resource planning (ERP) platforms, which constitute their “central nervous system” along with related systems-of-record (SOR) dependencies. SAP-mandated shift to S/4HANA by 2027 compels timely, comprehensive quality strategy to successfully migrate while also providing business continuity.

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Page 1: Enabling Business Responsiveness with Intelligent

Benefit from Comprehensive Testing withAnalytics to Adapt Dynamically

Create Intelligent Overarching Test Strategywith Automation for Dynamic Deployment

An IDC Infographic, sponsored by Micro Focus

Enabling BusinessResponsiveness withIntelligent Continuous Testing

Respond to Breadth of CoverageDemanded for High-Quality Applications

Establish Performance Engineering Strategiesfor Governance Across the Software Portfolio

Leverage AI for Agile Execution to Extend Reach,Increase E�ciency, Cut Costs, Improve Quality

Rapid digital transformation (DX) for business survival demandsupfront velocity testing across multiple areas — for example:

Multiplicity of systems and technologies acrossmyriad platforms for multimodal deployment poses

compound challenges that mandate automation.

AI and advanced analytics adoption can:

IDC sees use of artificial intelligenceand machine learning to address core areas:

For digital innovation, organizations must “shift left” and test softwarerapidly across a complex plethora of environments to keep pacewith DevOps pipelines. “Smarter” testing and quality strategiesleveraging artificial intelligence can help increase e�ciency, resilience,and business optimization.

Security

Source: IDC, CIO Sentiment Survey, September 2020

Sources: IDC, U.S. DevOps Survey of Enterprise Organizations, December 2019, n = 102; and IDC, PaaSView and the Developer, May 2020, n = 2,500

Source: IDC, U.S. DevOps Survey of Enterprise Organizations, December 2019, n = 102

Source: IDC, U.S. DevOps Survey of Enterprise Organizations, December 2019, n = 102

Reducemaintenance costs

Increase test coverage anddeployment speed

Extend testing reach tonon-technical business users

Enable visible, actionable metrics

of respondentscited manual e�orts associated with testing as the leadingchallenge. Project replanning and change management were the next most frequently cited challenges.

40%

of organizationsare interested in being a digital solution hub or part of a community that collaborates to create andshare digital solutions

of organizationsseek tools that support both modern applications and mainframe

70%

90%

Scale automation with AI technology to keep pace with pipeline, data, andbusiness dynamism and complexity.

Increase coverage rates and e�ciency via computer vision and machine learningfor object identification and location to mitigate maintenance e�orts;gain testing benefits from AI.

Enable e�cient script management and metrics to help address skills barrierwith natural language processing.

AI models enable self-learning, evolving over time as additional data is gatheredto augment capabilities and increase e�ciency.

29%

App developmentpipeline

optimization

24%

Deliverybottlenecks

19%

New appdevelopment

outcomes

16%

Acceleratingtesting

12%

Exploring AIcognitive

ecosystems

Increasing demand for e�ciency drives functional testing with emergingAI usage and analytics.

Performance engineering and performance testing enable rapid scaling with the shift to digital transformation and remote work.

Management of tests, test environments, and test data is vital for visibility,coverage, governance, and compliance.

Resilient app design and security vulnerability analysis and testing help protectbusinesses for DevSecOps.

Robotic process automation for operations automation and qualitycoordination help automate mundane, error-prone tasks.

Unite performance, functional, and nonfunctional testing across complexecosystems of apps and technologies.

Remain relevant in today’s economy through adaptive, high-qualityexecution with performance engineering.

Incorporate organizational and agile process change with appropriate qualityautomation strategies for success.

All IDC research is © 2021 by IDC. All rights reserved. All IDC materials are licensed with IDC’s permission and in no way does the use or publication of IDC research indicate IDC’s endorsement of Micro Focus’s products and/or strategies.

This infographic was produced by:

January 2021 | IDC Doc. #US47015420

Learn more about digital transformations andhow to deliver value at high speed with low risk.

Message from the Sponsor

Visit the Micro Focus AccelerateApplication Delivery solutions

Functionality Customer experiencePerformance

Testing imperatives exist for safe, relevant, high-quality software toavoid the reputational and business costs of poorly performing, broken, porous, irrelevant, and ugly software (produced at DevOps speeds).

As complexity evolves, it demands business alignment, automation,and leverage of artificial intelligence/machine learning (AI/ML)augmentation.

AI/analytics is the top area of investment for IT-focused spending;COVID-19 is boosting AI usage via automation for improved decisionmaking, modeling, and monitoring in dramatically changing environments.

Sustainable software-based innovation demands that companiesdeliver value faster than technical debt is accrued.

Businesses must respond to changes to their enterprise resourceplanning (ERP) platforms, which constitute their “central nervoussystem” along with related systems-of-record (SOR) dependencies.

SAP-mandated shift to S/4HANA by 2027 compels timely,comprehensive quality strategy to successfully migrate whilealso providing business continuity.