2013 has certainly been an interesting year, and as it comes to a close, here are some of my thoughts regarding the supply chain trends we are likely to see emerge in 2014. Not surprisingly, analytics is at the top of the list. Here is what I expect to see next year:
A huge global audience of analytics professionals joined us live for the unveiling of the 2014 IIA Analytics Predictions, to hear our faculty talk about what is in store for the new year. I personally found our conversations about predictions relating to automating and operationalizing analytics to be fascinating. We not only expect to see more use of these techniques, but we also expect to see organizations starting to bump up against the balance point of where we end up “over automating” our business processes.
Organizations succeed with analytics only when good data and insightful models are put to regular and productive use by business people in their decisions and their work. We don’t declare victory when a great model or application is developed – only when it’s being used to improve business performance and create new value.
Just like our children or grandchildren, anxiously awaiting that big day when they get to open holiday presents, we here at IIA are in the final countdown to the release of our 2014 Analytics Predictions. It is the time when our faculty gather round the virtual crystal ball and share their insights into where the world of analytics is headed in the next year.
A short while ago I wrote a post suggesting that human analysts would not be disappearing anytime soon. As important as hiring good analytical people, however, is taking advantage of all of the current possibilities for improving their productivity in analytical work. Machine learning tools and platforms are the most promising approach to creating analytical models at the pace required by big data.
We recently had a senior data analytics professional from a large financial services organization speak in my MBA Supply Chain relationships class. The scope of the datasets his team was working on was limited to supply management, but the sheer volume of data was staggering in its complexity and fragmentation.
You think big data is big today? Just wait until next year…or the year after that…or the year after that. It is growing exponentially. Whatever seems big now will likely seem relatively small just a short time from now. My inner analytics geek is thrilled when several times per week I see an article or have a discussion that calls my attention to yet another company or industry with yet another source of data growing explosively. It is just amazing how quickly these sources of data are growing. With that comes an explosion of analytic potential as well.
Each year, IIA gathers its faculty and leadership to look at the evidence and personal experience and provide a perspective on what the future holds in the world of analytics. Last year, we predicted that data visualization tools would become more prevalent, suggested that personalized customer analytics would transcend product driven analytics, and posed that the lines between data scientists and other analytics professionals would blur.