According to a Forrester study, the majority of companies estimate they are analyzing just 12% of their data, missing insights from a large chunk of the data they routinely collect. Other research suggests the digital universe will grow from 3.2 zettabytes in 2014 to 40 zettabytes in just six years (a single zettabyte is roughly one billion terabytes).
Businesses that start putting their data to work for them now will continue to reap benefits for years to come as the available data and the industry itself grows.
Benefits of Big Data in Business
The biggest benefits of big data in business include better decision-making capabilities and process changes that can improve efficiency. It can also be used to create a tailored customer experience, which in theory should drive higher conversion rates and profits.
For instance, customer data already collected can be a pain to analyze by hand to determine the most valuable customers and the most popular products or services. Big data tools can handle all the data collection and analysis so you can get a bird’s eye view of what’s going on, and make better-educated decisions for your business at a much faster rate.
With the right tools, businesses can automate various parts of this process, from updates to their computer systems and pricing, to marketing updates to improve conversion rates, avoiding credit card fraud, and more.
Tools for Big Data Automation
So what are these tools that facilitate automation, what do they do, how easy are they to implement, and how exactly can they benefit business in various industries?
Panaya helps improve the efficiency of enterprise resource plan (ERP) updates, upgrades, and patches. It works by automating the testing process, using big data gathered from a bigger set of ERP activities, in order to identify possible pain points, errors, and other issues that may happen over the course of an upgrade. This saves time and money for businesses that are handling ERP upgrades, with or without a dedicated IT department.
Aibel, an engineering company that deals with production facilities in the oil and gas industry uses Panaya’s Cloud Quality Suite, and as such, has reduced its SAP testing time by 30%. By removing code that’s not affected, any unnecessary tests are eliminated, saving time and money.
Wiser is a pricing automation platform that automates product pricing based on a number of factors. Useful for businesses that run ecommerce or even brick-and-mortar stores, the platform gathers real-time pricing data, which can be used to automatically customize pricing rules and automate repricing according to what competitors are doing.
Otterbox, a well-known smartphone case manufacturer, uses Wiser to identify price trends, find violators of the minimum advertised price (MAP) in real-time, and track reseller violation over time.
Feedzai is a company that puts big data to use to prevent credit card fraud, in real time. It works by combining machine learning and behavioral analysis to determine if anything is out of the ordinary and send an alert.
According to a recent case study, a top-20 U.S. merchant acquirer was able to eliminate 80% of fraud loss from the automated system, which was able to detect and prevent fraud at least 10 days earlier than the previous system.
Zapier is a task automation tool that allows you to create “zaps” triggered by an action in another app. For instance, you can create a zap to post your Facebook status to Twitter or send emails from someone to Evernote. Zapier uses big data to determine the apps it should add to the platform next to better serve their clients.
The Future of Big Data and IoT
There is much optimism about how big data will influence productivity in enterprises of all sizes, especially at the onset of the Internet-of-Things, which involves connected devices, appliances and sensors of all sizes. While companies are able to amass big amounts of data from processes, user interactions, communications and data at large, the future will involve much more data inputs from IoT, which can involve inputs of all kind, including motion/movement, location, environment, and the like.
At this point, businesses are currently establishing capability in terms of collecting more and more data through these inputs, giving IoT-oriented device makers a big boost. This, in turn, will help grow the industry, further enhancing the way data is collected.
Thus, it’s not only the cloud-based platforms and data-driven software makers that benefit from big data and automation. Even hardware companies that faced obsolescence are getting a second lease on life as providers of data inputs from embedded machines.
The future, then, leans toward machine learning. With big data sets, automated processes and the ability to affect real-world situations (and not just software), the next step will involve machine learning, wherein software and hardware will be able to adopt as the need arises, learning new ways to accomplish tasks better. For some, this means further innovation in developing platforms for artificial intelligence.
The drawback is that with machines becoming more intelligent, people are worried that automation will take away jobs that used to require complex thought and decision-making abilities that only humans are capable of. From self-driving cars to legal software finding the best decisions by analyzing years’ worth of court cases in few seconds, University of Oxford researchers estimate that machines will take almost half of U.S. jobs, at a fraction of the cost.
These concerns aside, the end-game will likely involve human work becoming more oriented toward skill sets and capabilities that require more value than analysis-based output done by artificial intelligence. Thus, even while AI has taken the place of humans even in white-collar professions, there is still hope for humanity to remain relevant in an increasingly automated environment.
The Road Ahead
Fears of job loss and human irrelevance aside, Big Data, automation, IoT and artificial intelligence are the next frontier in business. For organizations looking to enhance productivity, expand and innovate, these are areas to focus on.
In early 2015, data showed companies will spend an average of $7.4 million on data related initiatives over the course of the year, with large enterprises investing $13.8 million, and small to medium sized businesses investing $1.6 million. 80% of large enterprises either already have, or are planning to deploy a big data project by the end of the year, and 63% of small businesses are doing the same. It’s clear big data is making a big impact on business, and companies of all sizes should take heed.
