Since the financial crisis of 2008, the financial services industry has been inundated with new rules and regulations that have consumed resources and increased spend on compliance. All of this is occurring at a time when the industry has also been under increasing competition from financial technology (fintech) firms. Whilst the fintech industry is booming by providing new innovative products at a rapid pace, traditional incumbents have appeared less agile at adopting these.
More and more companies are using strategic sourcing platforms as a fulcrum for digital transformation within the department (and the enterprise as a whole, but that’s another story for another day). How?
Cloud adoption is on the rise. According to a recent Gartner prediction, the worldwide public cloud services market will grow 18 percent in 2017 to $246.8B, up from $209.2B in 2016. As more and more organizations move to the cloud, many IT teams are tasked with identifying the right infrastructure framework to ensure they meet their business and operational requirements – a challenging task considering there are so many options.
Recently, supply chain professionals have recognized that better data collection and increased computing power can track sourcing, scheduling and routing better and faster than any human. Applying big data to thorny supply chain problems is still an emerging art as companies adapt their internal processes to rely on algorithms rather than rules of thumb. Here’s what you need to know to understand how big data is changing the supply chain and improving efficiency.
Leading companies are working to extend management of the corporate risk profile to road safety. This is achieved by acknowledging key challenges, understanding the big picture and launching well-targeted strategic programs that consider local challenges and solutions. Such programs include driver management (driver selection, development and monitoring), vehicle management (including best use of new technologies) and assessing and managing route risks.
There is no doubt that cloud, big data and artificial intelligence will be trending in 2017, just as they were in 2016, and will likely be in 2018. These are multi-year endeavours because the true implementation of technologies under these umbrellas have just begun, and challenges - like finding quality resources and better understanding of the technologies to fit into the business use cases - remain.