Analytics for the everyman

June 11, 2018
Data-driven approach allows workers to explore production data and create new analytics in real time without the need for data professionals

Digital technologies provide a wealth of opportunities for industrial companies right where their information is born. However, too many opportunities have been missed because data management is difficult and creating analytics can be even more taxing. What is turned into useful information is a fraction of what’s in your enterprise.

There’s so much data to start with, only a portion of it might be useful for any given question. Then you need data professionals to clean and organize your data, which typically is time-consuming. This explains why spreadsheets are still used by 57% of companies when analyzing sensor data.

Those companies that do have preconfigured analytics and dashboards often find they offer too narrow a view. The analytics are rigid; workers can’t explore or dig deeper into the information they receive, so they revert to spreadsheets.

Instead of spending time working your data, your data should work for you. Here, we examine a new generation of analytics software designed to do that. It’s designed to create analytics that are more agile and flexible, so workers can keep up with production needs.

Your inner data scientist

Data professionals have long been the gatekeeper to analytics. They define what data is relevant, how it moves through your facility and who gets what information.

However, this professional-driven approach makes analytics a challenge. For example, employees who want data outside of the standard reports must make specific requests to their IT teams. They then wait for the professional to prepare the data, and only then get their hands on a report that mightanswer their questions.

With such a cumbersome process for creating analytics, it’s no surprise that 64% of manufacturers still rely more on experience than data analysis to address key business issues.

Instead, you need empowered teams that can find their own information instead of relying on an professional. You need a data-driven analytics approach that turns production personnel into self-serving data scientists.

By switching from an professional-driven to a data-driven approach, your teams can tap into the wealth of structured and unstructured data in your operations to create ad hoc analytics and dashboards. This provides a whole new way to think about data in your enterprise.

Expand the value of analytics

At the heart of a data-driven approach is software that takes advantage of the smart devices and connected systems spreading across industrial enterprises. The software lets users explore their operations, using and fusing data from any existing source — be it controllers, historians, enterprise resource planning (ERP) systems and everything in between.

Previously, building a dashboard started with a data-integration plan that detailed how raw data would be transformed into production intelligence. It required manually mapping out current data sources, key performance indicators (KPIs) and other details.

A data-driven approach automatically discovers and indexes structured or unstructured data.

This process saves time and reduces the risk of human error compared to the manual process. It also provides access to more details than you would get from manually mapping a device’s name, line location, facility location and other specifics. Using data modeling, machine learning, predictive analysis and third-party analytics tools to massage and analyze data, data-driven software can create relationships among indexed data sets and calculate answers across billions of data points.

In other words, with minimal setup, you can access real-time, situation-relevant analytics that can address questions the moment they arise.

That flexibility is a tool for better understanding your operations. On a single screen, workers can access all their favorite “storyboards.” Storyboards present operational data in a preferred format and can include predefined dashboards plus any storyboard shared by a colleague.

Analytics on the fly

The storyboard helps team members begin to understand or investigate analytics.

A data-driven approach shouldn’t limit teams to static storyboards. Beyond their preferred information, they can open the reporting environment to reveal the data behind whatever you’re monitoring.

In that open environment, they can sort the data however they want. A few clicks is all it takes to dig deeper into a specific data point, aggregate historical values against current performance, filter by different variables, apply different chart styles and more.

As changes are made, the software can process and remind them to create a dynamic report. For example, an employee who wants to understand a batch system’s performance based on which operator is managing the process can simply select the relevant variables such as shift or employee ID. The software will then mash the data together and build a report with the correlated data.

The worker can then act based on the findings they receive. They can also share the report with colleagues or save it as a default storyboard on their home screen.

Most importantly, your team can do all this without waiting days or months for an professional to add data sources or adjust models. Now, analytics can flex and adjust with your operational needs. And your team can answer questions and solve problems on their own, in the moment, using hard data.

Search data with ease

In some cases, you might not be able to find the specific data you want in a storyboard. When this happens, new analytics software frees you from the structured query language of data professionals.

Search engines are how you explore the world outside the facility. Now you can use natural-language processing to scour operations for useful information. Simply ask questions like you do in Google searches.

Once data sources are identified, users can quickly search them — even if they haven’t been previously visualized. This capacity provides a broad view of operations through storyboards and the ability to explore all data sources for additional insights.

A production manager, for example, can track the plant’s overall energy usage on a storyboard. If consumption spikes, the manager can search for energy usage by machine, batch or shift to identify the culprit.

When significant pieces of information are discovered in a search, you can add those new insights to storyboards with a single click.

A tool that grows with you

Your analytics platform should be able to grow with your business. After all, your business is constantly changing, and your digital-transformation journey is an ongoing one that regularly brings modern technologies into operations. The new advanced analytics platform can grow with your hardware and software ecosystem.

All these capabilities — greater flexibility, simple searchability and scalability — work toward the same goal: To make sure your team always has access to relevant data to solve questions and challenges as they arise. And isn’t that how analytics should be in the era of big data and connectivity?