by Shawn Rogers, Chief Research Officer, Dell Statistica
As advanced analytics continue the trajectory from buzzworthy idea to business imperative, we will see companies and consumers alike beginning to optimize their processes for data gathering and analysis in new ways. From healthcare to manufacturing, virtually no industry will be untouched as advanced analytics reach a new level of maturity in the coming year. Here are four specific ways I expect advanced analytics to evolve and impact businesses this year:
1. Analytics at the edge becomes the new normal as the Internet of Things (IOT) expands.
Thanks largely to advancements in modern data technology, more organizations than ever before are putting the right data on the right platform for the right reason. This new level of data efficiency greatly reduces – and, ultimately, may eliminate – the need to pull data into a centralized source, such as a data warehouse or analytic sandbox, for the purpose of analysis. Instead, given the distributed nature of connected devices and the explosive growth of IoT infrastructures, more organizations will look to execute analytics on the data-gathering devices themselves, a model commonly known as analytics at the edge. Applying a predictive model and running the analytics where the data lives eliminates the time, bandwidth and expense required to transport the data, enabling immediate action to be taken in response to insights. For example, if surveillance cameras have the ability to distinguish between routine and non-routine video images, they can transmit only the suspicious images to long-term storage, reducing cost and avoiding bandwidth issues. In 2016, the growth of IoT in particular will spur the movement of analytics out to the edge, in order to give companies the ability to harness and use IoT data quickly and economically. The power of IoT ultimately lies with the ability to analyze data and move at the real-time speed of a specific workflow. Analytics at the edge makes that possible.
2. “Citizen data scientists” continue to emerge across the workplace and shape applications of analytics.
We are starting to see a new breed of analytics users cropping up throughout organizations – non-analyst employees known as citizen data scientists. These every-day, non-technical users typically leverage a basic background in math or social sciences to analyze data as an add-on to their other workplace responsibilities, helping to fill the gap between the amount of data companies need crunched and the number of trained data scientists they can hire. Citizen data scientists are going to play a large role this year in increasing the demand for processes and interfaces that make analytics more easily digestible. As citizen data scientists experience a learning curve in wrangling data, running the optimal analytics and presenting the outcome of those insights, vendors will need to focus on delivering quick-start analytics templates and reusable workflows. Once the learning curve has been overcome and the right capabilities have been delivered, citizen data scientists will be the driving force behind the use of analytics to drive innovation.
3. Analytics will show the highest ROI for targeted, vertical market use cases.
We’ve already seen evidence that advanced analytics produce the highest ROI when applied to targeted, vertical markets. Regulated manufacturing in particular will continue to lead other industries in advanced analytics adoption and ROI in 2016, as this industry features not only numerous processes that greatly impact the precision and quality of a given production run, but often a large number of regulatory requirements necessitating data and documentation. As such, regulated manufacturers will increasingly rely on advanced analytics platforms to help them identify strengths and weaknesses in their processes, while also documenting the information they need to meet regulatory requirements. For example, pharmaceutical manufacturers might leverage advanced analytics to optimize the drug creation process and avoid catastrophic batch losses, while also using analytics tooling to confirm that their processes have been tested and validated as required by governing regulatory bodies.
4. Analytics will become the starting point for virtually all innovations.
Advanced analytics not only help companies optimize and improve processes but also better serve their customers through new innovations. This trend will grow exponentially in 2016 as organizations continue to realize the true value in leveraging predictive analytics. Service departments will have the ability to take prescribed actions to prevent issues from arising. Doctors will increasingly run analytics to offer precision healthcare and personalized medicine that better serves patients. Patients themselves will bring their own data to the table, creating a new layer of both challenges and opportunities for data-driven healthcare leaders. This trend of data-driven analytics advancing each and every aspect of the business – from inception to completion – will only continue to evolve until, ultimately, all forms of innovation trace back to analytics in some way.
If your company hasn’t begun to incorporate advanced analytics, bear in mind that 2016 is poised to mark a tipping point in the evolution of corporate data science. Until now, having the ability to leverage advanced analytics has been a competitive advantage. By this time next year, it will be status quo. Not only will companies without advanced analytics find themselves falling behind their competition, but they will have an extremely difficult time catching back up, as their competitors with analytics improve and optimize operations at an exponential, not linear, rate. It’s a time of great opportunity for those prescient enough to make bold, decisive moves. And it’s a year that will define who owns the future of innovation and who gets left behind.
About the Author
Shawn Rogers is Chief Research Officer, Dell Statistica, Dell Software. He is an internationally recognized thought leader, speaker, author and instructor on the topics of big data, cloud, data integration, analytics, data warehousing and social analytics. Prior to joining Dell, he was Vice President of Research for Business Intelligence and Analytics at Enterprise Management Associates, a leading analyst firm. He co-founded the BeyeNETWORK, a global online publication covering business intelligence, data warehousing and analytics. He was also a partner at DMReview magazine and has held various executive level positions with technology companies.
As advanced analytics continue the trajectory from buzzworthy idea to business imperative, we will see companies and consumers alike beginning to optimize their processes for data gathering and analysis in new ways. From healthcare to manufacturing, virtually no industry will be untouched as advanced analytics reach a new level of maturity in the coming year. Here are four specific ways I expect advanced analytics to evolve and impact businesses this year:
1. Analytics at the edge becomes the new normal as the Internet of Things (IOT) expands.
Thanks largely to advancements in modern data technology, more organizations than ever before are putting the right data on the right platform for the right reason. This new level of data efficiency greatly reduces – and, ultimately, may eliminate – the need to pull data into a centralized source, such as a data warehouse or analytic sandbox, for the purpose of analysis. Instead, given the distributed nature of connected devices and the explosive growth of IoT infrastructures, more organizations will look to execute analytics on the data-gathering devices themselves, a model commonly known as analytics at the edge. Applying a predictive model and running the analytics where the data lives eliminates the time, bandwidth and expense required to transport the data, enabling immediate action to be taken in response to insights. For example, if surveillance cameras have the ability to distinguish between routine and non-routine video images, they can transmit only the suspicious images to long-term storage, reducing cost and avoiding bandwidth issues. In 2016, the growth of IoT in particular will spur the movement of analytics out to the edge, in order to give companies the ability to harness and use IoT data quickly and economically. The power of IoT ultimately lies with the ability to analyze data and move at the real-time speed of a specific workflow. Analytics at the edge makes that possible.
2. “Citizen data scientists” continue to emerge across the workplace and shape applications of analytics.
We are starting to see a new breed of analytics users cropping up throughout organizations – non-analyst employees known as citizen data scientists. These every-day, non-technical users typically leverage a basic background in math or social sciences to analyze data as an add-on to their other workplace responsibilities, helping to fill the gap between the amount of data companies need crunched and the number of trained data scientists they can hire. Citizen data scientists are going to play a large role this year in increasing the demand for processes and interfaces that make analytics more easily digestible. As citizen data scientists experience a learning curve in wrangling data, running the optimal analytics and presenting the outcome of those insights, vendors will need to focus on delivering quick-start analytics templates and reusable workflows. Once the learning curve has been overcome and the right capabilities have been delivered, citizen data scientists will be the driving force behind the use of analytics to drive innovation.3. Analytics will show the highest ROI for targeted, vertical market use cases.
We’ve already seen evidence that advanced analytics produce the highest ROI when applied to targeted, vertical markets. Regulated manufacturing in particular will continue to lead other industries in advanced analytics adoption and ROI in 2016, as this industry features not only numerous processes that greatly impact the precision and quality of a given production run, but often a large number of regulatory requirements necessitating data and documentation. As such, regulated manufacturers will increasingly rely on advanced analytics platforms to help them identify strengths and weaknesses in their processes, while also documenting the information they need to meet regulatory requirements. For example, pharmaceutical manufacturers might leverage advanced analytics to optimize the drug creation process and avoid catastrophic batch losses, while also using analytics tooling to confirm that their processes have been tested and validated as required by governing regulatory bodies.
4. Analytics will become the starting point for virtually all innovations.
Advanced analytics not only help companies optimize and improve processes but also better serve their customers through new innovations. This trend will grow exponentially in 2016 as organizations continue to realize the true value in leveraging predictive analytics. Service departments will have the ability to take prescribed actions to prevent issues from arising. Doctors will increasingly run analytics to offer precision healthcare and personalized medicine that better serves patients. Patients themselves will bring their own data to the table, creating a new layer of both challenges and opportunities for data-driven healthcare leaders. This trend of data-driven analytics advancing each and every aspect of the business – from inception to completion – will only continue to evolve until, ultimately, all forms of innovation trace back to analytics in some way.
If your company hasn’t begun to incorporate advanced analytics, bear in mind that 2016 is poised to mark a tipping point in the evolution of corporate data science. Until now, having the ability to leverage advanced analytics has been a competitive advantage. By this time next year, it will be status quo. Not only will companies without advanced analytics find themselves falling behind their competition, but they will have an extremely difficult time catching back up, as their competitors with analytics improve and optimize operations at an exponential, not linear, rate. It’s a time of great opportunity for those prescient enough to make bold, decisive moves. And it’s a year that will define who owns the future of innovation and who gets left behind.
About the Author
Shawn Rogers is Chief Research Officer, Dell Statistica, Dell Software. He is an internationally recognized thought leader, speaker, author and instructor on the topics of big data, cloud, data integration, analytics, data warehousing and social analytics. Prior to joining Dell, he was Vice President of Research for Business Intelligence and Analytics at Enterprise Management Associates, a leading analyst firm. He co-founded the BeyeNETWORK, a global online publication covering business intelligence, data warehousing and analytics. He was also a partner at DMReview magazine and has held various executive level positions with technology companies.
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