Eyes and Ears, and Beyond
The easiest argument for using data analytics is that they provide you thousands of eyes and ears into your business and your environment. While all this information is available in different systems and sources, Data Analytics is about bringing all these information together such that it is accessible and usable across the enterprise in real-time, with proper security permissions in place. In essence, it is a comprehensive sensory system for your company. Using machine learning / AI techniques, data analytics can perform many tasks that hitherto required human intervention. While these tasks are currently limited to simple tasks such as image recognition, speech recognition, language translation, etc., they can be woven together into business solutions that can provide highly automated, intelligent applications. For example, a company with 1000+ outlets can monitor video feeds from all 1000+ stores in real time, using solutions built around machine vision and analytics.
The Case Against Experience
In a rapidly changing environment such as in industries under disruption or in the case of start-up companies, experience is sometimes not very reliable and may even prove counterproductive. Data, on the other hand, is not easily misled. Take the case of car companies like Uber and AirBnB, that have used intelligent algorithms and analytics to eliminate entire rungs of bureaucracy and replaced them with relatively painless, streamlined, and cost effective experience to the delight of the customer. Such companies did not enter unknown geographies on the back of business experience, they used data analytics instead.
De-risking the organization, sometimes from its brightest
In many organizations, the brightest employees are the ones with intimate knowledge of the company’s processes, customers, etc. Over time, organizations come to rely excessively on the experience of such people, and unconsciously setting the performance bar based on the performance of the brightest. Let’s take a quasi-academic example that has striking similarities with what happens in organizations. The Whale Detection Challenge, conducted in partnership with Kaggle and Cornell University, offered a total prize pool of $10,000 to the teams who created the most effective algorithm for detecting North Atlantic right whale calls. In a two-month period, over 300 participants submitted 3,333 entries. The winning entry increased the researchers’ detection model accuracy from 72% to 98%, a significant improvement that makes a real-world impact by preventing collisions with shipping traffic in Massachusetts Bay. What’s more, the best solution was found by data scientists who had little background in marine biology.
Finding Untapped Markets
The majority of customer targeting systems in most countries are based on traditional experience driven models of customer engagement, leaving hundreds of millions of customers unserved and underserved. This stark comparison is seen between traditional banking and credit card companies and FinTech companies. ZestFinance puts this very succinctly as follows
Today, the majority of lenders use the same approach to credit decisions that was developed 50 years ago. That approach is predicated on the assumption that it’s hard to get large volumes of data, expensive to store it, and nearly impossible to use it….
…This new technology is able to consume vast amounts of data to more accurately identify good borrowers — enabling higher repayment rates for lenders and lower-cost credit for consumers.
At ZestFinance, there is no human interaction of any kind involved in underwriting. Instead, we rely on several mathematical models running in parallel to make underwriting decisions. While many creditors take hours, or even days, to make credit decisions, we make them — accurately — in less than 10 seconds.
Doing it At Scale
When companies employ intelligent applications to automate all mundane tasks, to collect and clean data and identify interesting patterns, it allows them to scale and disrupt established players in the industry with far lower capital investments and operating expenses. Such companies can deploy their gains to truly focus on customer intimacy and innovation, and create strong barriers for the competition.
Our 2 Cents
Analytics will transform businesses in the days to come. This blog gives a number of examples to set you thinking about how analytics can be used in different contexts. We believe that businesses will benefit if they ask the following questions
1. Where can we automate with a bit of intelligence, to get things done faster, better, cheaper?
2. How can we build organizational intelligence and wisdom, and not completely depend on select individuals?
3. Where are opportunities for innovation and transforming business as usual?
Going back to the original question, i.e. “Why should we use AI and Analytics based solutions?”. We believe that the answer to this is increasingly going to be a rhetorical one…”Can you afford not to?”
