Did you ever notice that your organization has always been trying and in most cases struggling to derive meaningful and actionable insight from data to power-boost your business? This is true since the days of legacy systems and ERPs to the present day of Big Data & Cloud, and will be a challenge in the future where you have billions of connected devices and things transmitting zettabytes of data.
In Internet of Things era, companies failing to leverage analytics are bound to be irrelevant and many would face competition from analytics-enabled start-ups. Thus leaving them struggling for survival.
So, how are companies transforming using analytics?
Companies are heavily investing in analytics with a focus on advanced analytics to make better decisions based on insights. Just look at telecom firms that use predictive analytics to help prevent customer churn. Or how Google, Amazon, Netflix, and others have eclipsed competitors with powerful new business models that derive from an ability to exploit data using advanced analytics.
Even companies like GE, John Deere, Rio Tinto, etc. are diversifying their current business model and are venturing into products and services based on analytics or leveraging the data they are collecting through their existing products.
Even advanced analytics is impacting how consumers interact and consume products and services. Today’s connected customer expects companies to offer personalized interactions that are relevant to them at that point of time and with an unparalleled experience.
Advanced analytics enables you to do multiple things – predict customer’s next buy, customize product or service offerings, drive product and process innovation, and take informed strategic and tactical decisions faster – as per your business needs.
BI does not equal to Advanced Analytics
Let’s not confuse traditional business intelligence (BI) with advanced analytics, a most common myth among business leaders. BI is about reports, dashboards, advanced visualizations whereas, advanced analytics uses machine learning algorithms on large and small data sets to forecast future events and behaviors. Thus enabling businesses to conduct what-if analysis and predict the effects of potential changes in business strategies. It also enables real-time data analytics to provide instant insight to end-users and helps democratize the analytics access and usage through cloud-based analytics.
So, how to embark on an advanced analytics journey?
Firstly, identify, combine, and manage multiple data sources. Secondly, invest in capabilities to build advanced analytics models for predicting and optimizing outcomes. Once you begin your analytics journey, expand your efforts to move from using only traditional BI that addresses descriptive analytics (what happened) to advanced analytics, which complements by answering the “why,” the “what will happen,” and “how we can address it“.
Let’s start your “Advanced Analytics Journey” with our Microsoft Azure based advanced analytics services and see how we helped Rockwell Automation.