White Paper: WNS
Today, enterprises need to look beyond cost savings, while service providers need new sources of competitive differentiation and margin levers. In Business Process Management (BPM), Finance and Accounting Outsourcing (FAO) has historically followed FTE-based pricing. However, in recent times, some areas have seen a very gradual shift towards new, value-based models such as transaction-based and — in a more limited way — outcome-based pricing.
An enterprise-wide process modeling is the most agile way to conduct a successful digital transformation as it requires a top-down examination of the performance, quality and sustainability. Digital transformation is an essential step in the evolution of many businesses today. Process modeling has grown from creating a diagram or report figure that explains a business problem to a transformational practice that can organize the way a business is monitored, controlled, and measured. This whitepaper discusses why businesses should consider an enterprise-wide process modeling approach for competing through digital transformation. Key takeaways of this white paper: Take Process Models out of isolation within your business Nurturing digital business transformation by focusing on your process From business process mapping to enterprise business process modeling Ways to instigate enterprise-wide process modeling
Organizations need a business intelligence solution that combines both back-end and front-end functionality addresses all the requirements and goes beyond front-end only data visualization products, to allow your enterprise to make the most of the current and future business intelligence possibilities. Many organizations lack the tools to transform gold mine of data into business results since they only look at “business intelligence” label on a solution at face value that focus only on data visualization. This white paper about “Full-Stack vs. Front-End-Only BI Software” explores the differences in the two approaches of singlestack BI vs. data visualization while highlighting the challenges in performing important BI tasks. Some of them are as below: Preparing data Joining data sources Analyzing data Scaling Collaboration