Reimagining HR with Digital Platforms and Applications

Reimagining HR with Digital Platforms and Applications

Reimagining HR with Digital Platforms and Applications


16th September 2021

The all-digital world is changing how we live, how we work, and how business is organized and conducted. For HR and business leaders, this digital transformation poses two fundamental challenges.

First, HR can help business leaders and employees shift to a digital mindset by envisaging a digital way of managing, organizing and leading change. Second, HR can revolutionize the entire employee experience by transforming the face of HR using digital platformsapps and ways of delivering HR services. Our discussion of this trend focuses on the second part of the digital HR challenge: how to reimagine HR and the employee experience in a digital world.

  • Today there are more than 7 billion mobile devices in the world, and more than 40 percent of all Internet traffic is driven by devices. Yet HR teams remain far behind in deploying mobile solutions. Fewer than 20 percent of companies deploy their HR and employee productivity solutions on mobile apps today.1
  • Designing mobile apps and considering the end-to-end user experience are new disciplines for HR, combining design thinking with apps, video, social, and mobile technologies.
  • Digital HR, which brings together social, mobile, analytics, and cloud (SMAC) technologies, represents a new platform for improving the employee and candidate experience. While vendors are now delivering solutions, companies should build their own integrated digital HR strategies and programs.

Just as digital technology has changed our everyday lives, it’s now transforming HR. It enables HR to:

  • Use data and analytics:

Organizations are adopting a more data driven approach to managing people at work. Pre-selection, learning & development (L&D), employee engagement; there’s HR technology to measure every single part of the employee lifecycle.

  • Future-Proof recruitment:

Recruitment technology is evolving and forcing HR to evolve with it. It helps target the right candidates and speeds up the process mostly using artificial intelligence. A smooth mobile (application) experience, a data-driven pre-selection process and a personalized, AI-based onboarding program — are a few technological shifts happening in the recruitment space.

  • Improve the employee experience

There is a very thin line between the employee’s professional and personal life. With the next-gen employees expecting personalized experiences at their workplaces, they are the organization’s first set of customers. They will check their personal accounts during their work hours and with equal fervor check their work emails during the weekend.

  • Offer self-service tools to employees

Employees are the owners of their data within the organization. Today’s workforce is looking for centralized repository that gives the flexibility to update and manage their data securely.

  • Be competitive in the war for talent

Companies that use these digital technologies for various HR purposes – think sourcing, pre-selection and learning and development for instance – have a significant competitive advantage when it comes to seducing this demanding generation of workers.

Focus on Digital HR is what gives Incture® the edge and acceptability amongst its customers and their employees. Incture is helping customers build a Unified Digital Workforce platform for enhancing the employee experience using SAP technologies. The platform includes a unified digital workbench which simplifies HR workflows with intelligent services, data analytics and conversational AI. The USP of this digital platform is the UX, which is built on deeper understanding of how people engage with technology on the web and mobile devices. It’s flexible, easy, and people-centric –tailored to every employee. Incture has delivered 240+ complex and custom cloud-based projects successfully on the SAP Cloud Platform, which have resulted in an increase in user adoption and employee productivity as high as 70% and reduced the processing time to less than 5 seconds!


Raghu Pavan TS

About the Author: The Director of HR Apps at Incture, Raghu Pavan has 16+ years of experience working with some of the biggest names in the technology sector. He started as an industrial engineer and then moved on to become an SAP consultant for SRIT and then IBM. He then worked in a managerial position at Accenture for 7 years. Raghu Pavan brings with him a high level of expertise in the SAP HR domain.

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Redefining Asset Maintenance & Failures in Utilities with Predictive Analytics

Redefining Asset Maintenance & Failures in Utilities with Predictive Analytics

Redefining Asset Maintenance & Failures in Utilities with Predictive Analytics


Sandeep Vyas
3rd March 2020

Asset downtime has always been a big burden to most of the Utilities and Manufacturing firms. The emergency repairs and heavy maintenance takes away enough productive time from these firms, hitting revenues and productivity of the firm. Research suggests that 58% of utilities want a mechanism for asset maintenance in all phases, starting from installation to decommissioning of the asset.

All companies are looking for answers to the following:

  • Is it possible to know upcoming issues in assets before they become real?
  • Can we reduce maintenance costs on assets?
  • Can we ensure the business will see fewer downtimes?
    According to research by ARC Advisory Group, only 18% of assets have a failure pattern that increases with use or age. This means that Preventive maintenance alone is not enough to avoid failure in the other 82 percent of assets and a more advanced approach is required. These issues can be minimized to a large extent by performing Predictive analytics on a large amount of data being generated by smart sensors attached to Utility/Manufacturing assets. Making the right prediction of failures beforehand turns out to be one of the most efficient ways to keep a watch on the health of critical assets.

Using machine learning algorithms and data mining techniques, Utility companies can leverage present and historical data to create data analytics models to take timely decisions pertaining to asset health.

Cherrywork® Predictive asset analytics app. can:

  • Perform data acquisition and storage either on the cloud or on-premise systems
  • Perform data analysis/transformation i.e. conversion of raw data for machine learning models
  • Evaluate Asset health i.e. generating diagnostic records based on trend analysis
  • Generate predictions of failure through custom machine learning models, and estimating assets life
  • Generate decision support system i.e. recommendations of best actions based on given inputs
  • Visualize i.e. Making information accessible in an easy-to-understand format

In our experience, we see all this work resulting in a good cost-saving for our customers where they are moving rapidly from Reactive maintenance or Preventive Maintenance to Predictive Maintenance.

As per Mckinsey’s Digital Utilities report, adopting advanced analytics to power predictive maintenance offers a new avenue to improve performance, while reducing asset-management costs by as much as 10% to 20%, plus conservative estimates supported by various use-case analysis suggest that such advanced analytics can boost profitability by 5-10% while increasing satisfaction for customers.

Our experience shows that such ‘predictive asset analytics apps’ can help utilities sector navigate the ever-shifting landscape, take advantage of new opportunities arising from these developments, and manage new challenges.

Sandeep Vyas

About the Author:

Sandeep is Business Architect with Incture. He is a seasoned professional focused on increasing IT solution footprints for global clients and passionate to drive digital growth for the business. He has formidable experience in leading Solution Consulting & IT Programs in Data Analytics & Supply Chain space. He has strong exposure to working in multiple geographies.

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