A Guide to Automated Data Processing

Companies across all types of industries use automated data processing to collect, store and manage the data they need to run their business. Here are a few examples of how organizations in different sectors are using ADP.

Banks rely heavily on ADP to detect fraud. Instead of requiring a team of analysts to sift through millions of transactions to find fraudulent activity  —  which is not only time consuming but also very expensive  —  banks are using machine learning models to analyze transaction data in real time, flagging anomalies based on customers’ historical patterns. This ability to automatically detect and act on suspicious activity can save millions of dollars a year that would otherwise be lost to fraud.

The retail industry uses ADP for everything from inventory management to sales tracking to understanding customer behavior. Many e-commerce platforms use ADP to gather and manage data about customers’ browsing behavior and purchase history, which allows them to automatically generate product recommendations on the fly. This automation not only increases customer engagement and sales, it also reduces how much effort marketing teams need to spend to achieve the same results.

Manufacturers are broadly using ADP for predictive maintenance on machinery. For example, sensors on factory equipment collect performance data and feed it into automated data processing systems that keep an eye out for issues. These ADP systems can predict when a machine is likely to fail and can alert technicians before a costly breakdown occurs, saving time and money.

When considering which ADP system to use, selecting the right tools is just one consideration. To be successful, you also need to have the right ADP strategy. Here are three of the most essential ADP strategies that nearly every organization should pursue.

To maintain a competitive edge today, organizations need data insights immediately. Even a delay of a few minutes can be catastrophic in some industries. Real-time data processing allows businesses to analyze data as it arrives, so they can make critical decisions fast. Whether monitoring customer behavior or equipment performance, the real-time nature of ADP can create business value and improve customer satisfaction.

While traditional ADP workflows rely on rule-based logic to gather, process and analyze data, more modern AI algorithms can dynamically adapt to changing data inputs. That means AI-powered ADP systems can learn, adapt and even anticipate business needs over time.

Today, there are many powerful ADP platforms and tools on the market to choose from. Here are a few solutions to consider: 

Snowflake is an out-of-the-box, advanced data and AI platform provided as a fully-managed service. It includes data storage, processing and analytics solutions that are fast, easy to use and flexible. Snowflake offers enterprises seamless cross-cloud and cross-region connections and data sharing with nearly unlimited scalability.

Segment is a customer data platform that collects, cleans and routes data to various tools in your stack automatically. It’s built for marketing and product teams that are looking to unify customer data from multiple channels without having to write complex pipelines.

Implementing an ADP system can transform your business in a number of ways. Here are some of the most essential benefits.

Automating workflows means employees don’t have to focus on time-consuming manual work. This frees up teams to focus on higher-value work such as developing strategy and innovating new products and services. Once an ADP system is up and running, teams can complete tasks in minutes that once took days. 

When it comes to accurate reporting and analysis, having consistent and trustworthy data is critical. With built-in validation, transformation and standardization rules, ADP systems help lower the odds that a human will make a mistake that may impact the business, and also help make sure your data stays clean and usable.

Being able to process and analyze data in real time rather than having to wait on manual processes can help deliver insights more quickly — ultimately allowing decision-makers to make smarter business decisions.

As with any new tech implementation, the initial setup of an ADP system may require some up-front investment, but leaders can’t ignore the savings it provides on long-term operational costs. ADP can streamline operations, thereby reducing the need for manual work and lowering staffing costs, as well as infrastructure expenses.