Future of Work

This an area where Robotic Process Automation (RPA) may be the best answer. The first step in designing a “Forget Robot” is to document the details of all the places where data is stored (RPA 101 – requirements and process documentation).

Data quality is generally measured on aspects of completeness, accuracy, integrity, consistency, uniqueness, and timeliness.

Customers want goods made to order and delivered as soon as possible, in a way that suits their flexible lifestyles. That’s a byproduct of the mobile, app-driven, on-demand age. But for many organisations and their warehousing and logistics experts, those customer wants can shine a harsh spotlight on legacy business models. Today’s smart warehouses are increasingly rolling out transformation strategies that deploy sensors connected to the IoT – so that robots, workers, managers, and even smart vehicles, know the location of every item and can track them on their journeys.

Ready to learn Machine Learning? Browse courses like Machine Learning Foundations: Supervised Learning developed by industry thought leaders and Experfy in Harvard Innovation Lab. Thanks to a boom in modern technology deployments involving machine learning, artificial intelligence and cloud computing, we’re seeing a lot of growth with their connected platforms and systems too. Big data and data

Ready to learn Machine Learning? Browse courses like Robotics Application Machine Learning developed by industry thought leaders and Experfy in Harvard Innovation Lab. 3 Skills for Succeeding in a New World of Smart Machines Picture on a banner of PwC’s digital campaign at Schiphol Airport in the Netherlands Millennials and smart machines are building our future. Yet, recently, I

Closing the distance between an organization and its customers is where long-term loyalty can be built. This will mean empowering customers to self-serve in a variety of functions without the requirement of visiting a brick-and-mortar office. Let’s look at five trends likely to guide organizational transformations (and the customer journey) in this year

This list aims to address some of the key challenges and ‘steps to success’ when implementing lab automation.

As we approach 2018, it is not just a New Year that we are talking about but also innovative ways of automating in newer domains.

When it comes to building your career today, there are way too many fields to choose from. You’re not just struggling to beat your competition, but also how you can get an edge over them in the industry. Working with experts from across the world, we realized that the only solution to making a name for your industry is actually to constantly learn – in popular terms, upskill yourself. After all, a popular saying from Charlie Munger says, “those who keep learning, will keep rising in life“. 

Banking runs on a set of regulatory guidelines and deals with numbers, it was only about time that it would board the AI bus. Secondly, there is this deviation angle. As we fully realize the fact that anything handled by a human is prone to deviation or personal discretion; so to be vigilant, all inputs are to be taken with a generous pinch of salt. In other words, everything must undergo a reviewing pair of eyes. How about implementing a system that can auto-understand and auto-function and auto-verify without or with minimal human intervention barring some very delicate cases?

The key question is what is so different about the latest wave of RPA? The answer lies with the maturity of both the technology being used as well as the business processes that it is being applied to. RPA is transforming organisations across all industries, leading experts to believe that it is one of the most transformational tools in current times. In this article we explore the benefits of RPA and why it is so transformational, along with an analysis of where it can be applied within the financial services sector.