Do more, with less. That has been a guiding principle of many businesses over the years and doesn’t look to be changing soon. To accomplish this, companies have been largely seeking and implementing operational efficiencies using Six Sigma or Lean methodologies. It is likely that you have felt this downward pressure in your role and have had to find creative or painstaking ways to get it done!!
Considering the future, the definition of “with less” may actually mean “with more”. Doing more, with MORE data, MORE processing power, MORE autonomous systems and MORE insights – with LESS manual effort!
Artificial intelligence theory and algorithms have been around a long time, dating back to the mid-20th century, so why is this important now? Well, while the theory did exist, we were not quite ready for widespread machine/deep learning. That has changed for several reasons:
- Availability of Data – many businesses now have a wealth of the precise data points that are essential to creating accurately trained models that produce meaningful outputs. Companies now have the ability to bring in new data sets to use as variables that have not been used before to drive decisions. Bringing in new data sources may aid in identifying previously unknown patterns, relationships, and clusters that can be used for classification, recommendation, or prediction.
- Computing Power – significant technological advancements have led to immense processing power at affordable costs.
- The Cloud – massive infrastructures have been made available to the public without requiring significant capital investment.
- Platforms – development of commercial “off-the-shelf” machine intelligence platforms make the application of machine intelligence and neural networks more user-friendly and enables integration to drive action.
- All Things are Connected – Connected Computers, Mobile Devices and the IoT makes these outputs even more usable and actionable across many industries.
How does this help you?
Without the “why”, there is no “do”. All of these advancements in data and technology provide us with attainable opportunities to effectively transform data into real business action, autonomously. We are now better equipped to streamline processes that we have spent great amounts of resources to run, or just never executed on due to lack of bandwidth. For example, continuous updates of event-based content, weather-driven advertising, and demand forecasting.
Beyond the automation of difficult processes lies the possibility of leveraging deep learning to brace against change and disruption. There is an opportunity for machines to connect data points in order to recognize patterns and identify relationships that we would not have been able to detect, without significant effort, before deep learning. All industries are at risk of change and digital disruption today, but imagine being able to recognize changes and adjust to them as they are happening. This is the reality of machine learning and automation.
Taking advantage of deep learning & machine intelligence by initiating autonomous capabilities reduces or eliminates the tasks and processes that are time-consuming, manual, require significant data preparation, or are highly analytical. Granted, this isn’t a simple flip of a switch, and there are many nuances to consider, but what once seemed impossible is now very real. By deploying “smarter” processes or systems, we can apply greater focus to the core of our businesses – providing seamless, beautiful, and personalized user/customer experiences or products leading to increased sales, productivity, and customer satisfaction!
It’s time to leapfrog the competition and get it done, or rather… have the machines do it!
Anexinet is a leading professional consulting and services company, providing a broad range of services and solutions around digital disruption, analytics (and big data), and hybrid and private cloud strategies. Anexinet brings insight into how technology will impact how business decisions will be made and how our clients interact with their customers in the future.
Chris Young, Strategy Solutions, [email protected]