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TCS Focuses on Human Challenge to Drive Enterprise Digital Transformation

NelsonHall recently attended the TCS Innovation Forum 2019 in New York. The forum demonstrated clear progress in TCS’ thinking and approach to Business 4.0 since last year’s conference – TCS has identified human engagement and buy-in with the principles of Business 4.0 as critical to successful implementation and value realization in business transformation. And human buy-in is applicable at multiple levels in an enterprise’s journey, not just the initial buy decision.

Successful Business 4.0 projects are different from traditional projects at three key levels:

  • Approach to technology: the approach changes from large project scope with minimal component transparency (using long development roadmaps, employing siloed teams using waterfall development methods) to small project scope with high, ongoing stakeholder feedback (employing scrum teams using agile development methodologies)
  • Use of solutions: effective use of solutions requires the employment of meta-frameworks to articulate business metrics and technical criteria for solution selection and deployment. Large libraries of experience-sourced benchmarks underpin the weighting of each criterion for specific environments considered  
  • Sourcing solutions: the emphasis shifts from standardization on a solution suite, to selecting the optimum solution for a specific task. Because much of the functionality is only available from emerging product vendors it is necessary for integrators to use larger ecosystems of product partners, which are continually evolving. 

Multiple client conversations presented at the conference highlighted how digitalization of the business has changed the approach required to solve operational challenges. Key examples given across sessions included:

  • Data management KPIs are changing as processing data is less of a challenge, while curating data is becoming more of a challenge: deep learning can use vast quantities of data. Today, the algorithms to analyze data are robust, but data quality remains a key challenge. Several clients discussed their efforts to reduce the amount of data analyzed and draw conclusions from a more limited, but much higher quality data set
  • Testing simulations to reduce resource and time requirements while increasing learning feedback:  systems do not work in silos, but planners and controllers operate in task silos. Globally optimized system development requires analytics support to allow developers to understand complex system-wide interactions. Increasingly advanced enterprises are using digital twins to allow technologists to shorten their learning curve in real-time to produce effective project deliverables
  • Data democratization: Harvesting greater value from data requires more stakeholders to access and process that data. Advanced enterprises are increasing appropriate access to the use of data while masking components which need to remain private. Increasingly, enterprises are developing sophisticated strategies for determining what, where, when, and how access is granted 
  • Reverse innovation: Innovation on large legacy systems is proving to be less effective than de novo projects where there are no legacy systems, procedures, or fiefdoms to defend. Enterprises are launching new ideas in emerging markets and then they (or TCS) bring those projects back to mature markets when fully vetted.

TCS and several clients provided a deeper dive into their data activities in a breakout session. TCS’ data services strategy is underpinned by three offerings:

  • DATOM: a data and analytics maturity assessment, consulting, and advisory framework that enables customers to drive their growth and transformation strategies at the board level or CxO level, leading to multiple downstream initiatives
  • DAEZMO: a framework that includes Machine First accelerators and leverages cloud, containerization, DevOps, data virtualization, etc. to modernize the existing data landscape to be business 4.0-ready  
  • Decision Fabric: a cognitive business engine that enables the automation of complex business processes and powers contextual industry offerings.

The underlying solution accelerators support the move to cloud-delivered, agile data management services. TCS sees the following shifts occurring in data management activities:

  • Data gathering and curating: currently consuming 50% of enterprise applied effort, this will shift to just 10%
  • Data analysis and decision: currently consuming 10% of enterprise applied effort, this will shift to 50%.

Repeatedly, clients stated that they did not find the move to cloud saved them money. However, it did make real-time and near real-time analytic computations possible, which created significant differentiation in time-dependent processes. Often these processes were customer-facing, which increased sales closure and/or increased CSAT. Effective cost control required a shift in management focus from the cost of provisioning services (old model) to cost of controlling usage (new model).

The challenge in innovating operational systems has become a challenge of changing people’s mindset to focus on the key levers that new technology offers. Therefore, emerging markets are often producing the fastest adoption of digital technology, as there is no legacy mindset to overcome. TCS works with the largest institutions to support this type of change. It is just now creating the productized offerings that will be able to support mid-market firms adopting digital technologies (business 4.0) en masse.

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