Subscribe To Newsletter Business Transformation Integrating People, Process and Technology People, process and technology are the key components of our outsourcing world. These entities interact with each other through data exchange and we are talking about a lot of data exchange. Automation and advanced analytics are the best bet to optimize interactivity and in designing business improvement measures from a strategic perspective. The lack of sustainability in the business can be traced back to the absence of good data analysis. Good practices go unnoticed, best practices remain unidentified and opportunities for an innovate improvement are lost from visibility. Ineffective activities analyze how to save costs, how to identify root causes for complex problems in process management, which are very often encompassed in the unspoken and extremely specialized habits of the business process. Those problems are complicated to address because they link to different specialized sources of information, with an accumulated experience of hundreds of years of practice. We need a smart, adaptive and cognitive approach to be able to suggest new insights. Fortunately, Infosys offers a synchronized package of three High-End Services: Business Transformation Services, Data Mining Centre and Robotics & Automation. They seamlessly support Outsourced Operations, also called Infosys Engagements to offer new services with a strong added value to their Clients. We are talking about ambitious, end-to-end cases in which added value- at first is undetectable or unmeasurable. Where can we save a significant amount of money by analyzing a dataset of 20 million invoices/PO over 4 years? Bringing new insights to the business means, simultaneously matching up to global standards as well as understanding the current services being delivered to the client. Such a customer-centric approach obliges operations to push the Client's core business to higher levels of maturity: acceptance, that there is a need for improvement on both sides of the service (service provider/Client), acceptance that the service provider is closer to the client's core business. Once the processes are better controlled, almost automated, next steps are to set an adaptive business improvement. Thanks to smart business-driven data analytics and continuous recommendations for improved practices, the collaborative efforts of business experts and processes are constantly analyzed and weak points are identified. We just entered the cycle of cognitive services, where intelligence and experience pit their wits against each other to create the added value. Seamless and efficient cooperation between high-end engagements is vital in identifying the value added to the client. Business Transformation Services drives the change on a global level; it provides an insight into the evolution of the organization and defining the right course for the transformation. It designs new efficient ways for the organization to operate, (among other things, people accept to share their data) and suggests a hypothesis for higher competitiveness. Then, the various hypothesis made for process maturity improvement need to be checked. This is where the Data Mining Center is involved. It uses prescriptive and predictive analysis. Its data scientists and data engineers change business behaviors from "reactive" to "proactive". They support a more effective human decision-making process and detect opportunities for cost reduction, process compliance increase with, for instance, fraud detection. It is now possible to simulate, to work-shadow, to analyze different realistic scenarios enough without endangering nor slowing down the current process being analyzed. Once process and data are analyzed, what happens after we eliminate the problematic cases in our everyday activities? Robotics Process Automation is the current answer. Processes are made less labor-dependent, more accurate and less risky. High-end engagements become extremely and exclusively competitive towards the service of the client. Professionals from Operations receive updated skills and are able to encompass statistical challenges such as : How to qualify, analyze and improve the result of the work faster? How to solve difficult issues that could not be automated? The time has come for Client Transformation, Process Adaptation, People Reskilling, as the information we process is done so through complex analytics, the continuous -and quick- capacity of business value creation must be ready for tomorrow, if not already for today. AI, ChatBots, Augmented Reality, quantum computing are a few emerging examples of the daily components we will have to deal with and all of them rely on a common factor: integration.