Three Technologies That Benefit Legacy Businesses More Than Startups

With many technological advancements, startups have the inherent advantage compared to more established companies. With less overhead, infrastructure, data and complex processes already in place, emerging companies are able to be more nimble and quickly apply new technologies to displace legacy businesses. In fact, continued innovation depends on startups’ unique ability to easily and continually incorporate new technology in new ways.

However, in our company, which works with event-based data stream storage and search capabilities, we have observed that a segment of crucial new technologies is turning this reality upside down. Because these tools are only as useful as the quality and quantity of data readily available, startups face the disadvantage compared to larger companies that have been operating and collecting rich data sets for years. When applied effectively, these technologies can provide enterprises with a much-needed competitive edge by enabling productive new business models and more streamlined operational processes that significantly drive profit levels.

Below are three key technologies enterprises should prioritize, as they can benefit industry leaders far more than emerging companies.

Agile Reporting

Having continual, real-time visibility into your data is critical, and unsurprisingly, larger companies with massive amounts of data stand to gain the most intelligent, forward-looking insights. Since most enterprises are working with multiple data sources (such as ERP, CRM, maintenance logs and internet of things), agile reporting can prove even more valuable as various data sources can be fused together to pinpoint correlations between departments, processes or events. For instance, by analyzing a time period of maintenance log data alongside a slightly later time period of customer service data, a company could quickly deduce that a lack of scheduled maintenance led to a rise in customer complaints, and swiftly rectify the issue.

Data Forensics

A technology that works alongside agile reporting, data forensics allows companies to detect anomalies across a variety of data streams and make one-off discoveries. For example, an effective implementation of data forensics could enable a company to answer the question, “Why did this shipment fail?” Or even, “Why did my customer success rates dip at this point in time?” Data forensics, and generally accessing data in real-time, requires ample infrastructure, however, and any given analysis request can’t impact network availability. Few startups have the resources on hand to support these requirements, however, most established enterprises can confidently support the larger infrastructures needed for data reporting and forensic technologies.

Machine Learning

The truth is, it’s more difficult for startups to learn how to build the right channels and scale data sets than it is for established enterprises (with existing channels and extensive datasets) to learn how to incorporate machine learning technology. Also, while the value of machine learning has clearly been proven, the return on investment (ROI) is dependent on quickly scaling the application of machine learning across as many channels as possible so the models drive real returns. For larger companies with deep customer, sales and/or manufacturing channels and connected equipment already deployed across operations, the ROI of machine learning becomes a simple function of roll-out speed and capacity. For instance, by leveraging existing maintenance or equipment logs, a company could apply machine learning to predict which devices will be in need of servicing or forecast required inventory levels across warehouse locations.

Considering the extraordinary business benefits enterprises stand to gain, implementing agile reporting, data forensics and machine learning should be top priorities, regardless of the company’s industry. Established businesses already have the quantity and quality of data required to make these technologies useful, and to curb security risks like Shadow IT, it’s in larger companies’ best interest to work with their IT departments to provide and manage these technologies so employees don’t access them elsewhere.

Looking ahead, established enterprises are in the promising position of reaping even more technological benefits over startups as the IoT continues to grow over the next several years. With larger companies well equipped to effortlessly and constantly bring more machines and devices online, their existing data sets can perpetually augment and get stronger, thereby becoming even more valuable and advanced, particularly compared to the developing data sets of startups.

This post originally appeared on forbes.com