This is a guest blogpost by Arijit Sengupta, head of Einstein Discovery, Salesforce
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The business world has largely forgotten why we need analytics: for action. Employees spend hours each week, month and quarter crunching hundreds of thousands of data points, but all too often the pretty charts and insights are never looked at again. Maybe those insights are on a slide that is presented and discussed in a meeting, but since analytics aren’t incorporated in the workstream, nothing ends up happening. Or maybe the data is about last quarter, and it’s too late to do anything with the knowledge. The point is, analysis is useless when it doesn’t result in specific actions.
We need analytics because it is supposed to guide us to the right decisions. Analytics has the power to tell us what we need to do and how to do it at the moment we need to make a business decision: to increase sales next month, double-down efforts on a certain region, decrease customer churn or recreate a successful campaign. Of course, analytics can guide decisions at the most senior, strategic levels — what new markets to tackle or new products to develop — but as with any technology, the most impact is going to come when everyone is empowered with the analytics needed to make the most intelligent decisions.
True technological revolutions happen when everyone is empowered. The invention of the computer was innovative but not revolutionary. It became revolutionary when the average person, with little experience with computers, could go to the store, pick a Mac off the shelf, and plug it in at home.
The Internet browser faced a similar trajectory. The Internet had existed for years before it truly became accessible to everyone. I remember learning how to use the earliest browsers, like Nexus and Lynx, that were text-oriented and required the user to write queries; the knowledge required barred the majority of people from ever using them. The Netscape browser drastically changed that. Whatever you saw on the screen, you could click and more would appear. This was the fundamental shift: when the Internet truly became easy enough for just about anyone who could read and write to understand and use it, it transformed society.
We’re at a similar inflection point with analytics today as it is rapidly moving from the realm of expert data scientists to the larger business community. The early days of analytics meant only specially trained experts could build models and perform statistical tests to ensure findings were accurate. Self-service business intelligence (BI) soon followed, giving everyone the chance to do basic analytics. It let you draw a graph and make your data look pretty, but that’s where we forgot the real significance of analytics — those graphs didn’t necessarily spur action, they were just visualizations of what had already happened. Not to mention, self-service BI could lead you down a wrong path all too easily. Say the standard deviation was so high that the whole graph could change if you removed one data point! The rigor of statistical testing that data scientists use never made it to the self-service technology.
But today, artificial intelligence (AI) in advanced analytics is the key to spurring the democratization of data-driven insights. Now AI makes it possible for the computer to do complex statistical tests for you. AI can recommend which graph to look at if the one you’re using has unclean data. It can find insights across multiple variables that the untrained eye would not notice. It puts protective systems in place to ensure the user doesn’t make poor decisions based on a misleading graph.
Augmented analytics, also known as smart data discovery, takes it even further by using the power of machine learning to surface actionable insights and recommendations, and shows tremendous promise. In fact, Gartner calls it the “next wave of disruption in the data and analytics market.” Gartner states that automated insights embedded in enterprise applications will “enable operational workers to assist in business transformation.” Most business users do not have the adequate training needed to read complex charts and graphs, but leaders are discovering there is an untapped benefit to putting data-driven insights in the hands of employees in sales, service and marketing. If I’m a sales manager, my dashboard can tell me that the Western Region is underperforming. With a few clicks, I can understand why and how to fix it: I can see that we’re losing large deals against a certain competitor, and identify my top-performing AEs to train others on how to approach these deals in the future. Suddenly I’m able to trust the findings when I understand the context behind them. Every employee can feel confident they’re taking the most beneficial actions to achieve the desired outcome, thanks to an intelligent analytics experience that recommends what to do the moment they need to make a decision.
Like the PC or the browser of the 90s, the presence of AI in advanced analytics has untold promise to be the democratizing force for data-driven and actionable insights. The power of AI plus augmented analytics means that data becomes digestible and easy for anyone with a basic understanding of numbers and the business problems at hand. Imagine the potential of each and every employee empowered by data science at every decision point — that’s the reality of AI for everyone.