How to start unlocking value from your IoT data with Tableau

Implementing the right IoT solution can bring tremendous value to your organization, but the key question is—where do you start?

If you are reading this post, you are either on course to deploy an Internet of Things (IoT) Solution or you are among the thousands of business leaders that sees the potential that this technology is promising to deliver in the near future. Implementing the right IoT solution can bring tremendous value to your organization, but the key question is—where do you start?

Marius and I both work as Tableau Solutions Consultants, based in London, UK. We have been involved in a number of IoT projects to date. For instance, Marius has worked hand in hand with a large telecommunications provider building an embedded self-service IoT analytics solution that allows Network Operations Managers to optimize performance and maintain superior network quality. I myself have had the incredible opportunity to help trackside engineers from a leading racing team to leverage the power of real-time telemetry data to optimize car and driver performance during the races.

In this post, we’ll review four steps to getting started with an IoT project. If you’re already leveraging an IoT solution but want to hear how other companies are finding success, join us for our session at Tableau Conference in New Orleans.

Let’s dive in.

Step 1: Be data-driven first—with executive buy-in

There is lots of hype around more advanced analytic applications such as predictive maintenance with IoT sensors, but you need to walk before you can run. Based on our experience, the first, critical requirement before starting an IoT journey is creating a data-driven environment.

Let’s remember the true value that the Internet provides. It allows people to get immediate access to information to make faster, better decisions. If we wanted to take a new product to market 25 years ago, it would take us months, if not years, to study the market, understand customer requirements, research competitors and competing products—and the list goes on and on. Today, we have all of this information at our fingertips.

The concept of the Internet of Things is very similar. It aims to help organizations make better decisions faster. “Faster” is a key word here. These “things”—devices or sensors—collect more data than was ever possible before and allow us to collect more relevant data and at incredible speeds. But the real value of the Internet of Things comes when you can interpret the data and take action. This starts with solving the last-mile problem—the reality that IoT solutions often fail because people ultimately can’t see or understand the data they mine.

Companies are addressing this problem through self-service analytics software, building dashboards to detect trends and anomalies. They can also set alerts to notify stakeholders when things go wrong. For example, a large car manufacturer is using Tableau to analyze operational quality data to understand the source of degraded factory performance, including defect types, affected parts, production locations, people, and other variables. The company now has immediate access to this information, allowing them to quickly understand the state of affairs and adjust the business accordingly.

The foundation of the company’s success lies in their dedication to identify and standardize key operational metrics all the way up to the executive board level. After establishing this foundational work, the company decided to embark on their first IoT initiative. They added IoT sensors to collect more frequent data points from their production line, allowing them to automate preventive maintenance tasks, minimize number of defects, and significantly increase car production output at a much lower cost.

Sensor data presents opportunities to solve problems and address question after question. But before this can happen, organizations need to make analytics a priority—a coordinated effort, backed and fully vetted by top management. Only then can you expand IoT across the whole enterprise.

Step 2: Decide on an implementation plan

The next important decision is deciding whether to continue the IoT pursuit on our own or get help from a system integrator or an industrial IoT provider.

Companies such as Amazon, Microsoft, and Google are investing heavily in cloud infrastructure and tools that help arm companies to deploy IoT initiatives on their own. These days, more and more enterprises choose deploy their own IoT solutions on top of these cloud IoT platforms, without help from specialized tech partners.

On the other hand, some organizations are consulting system integrators (SI) to overcome the challenges of integrating existing business processes with new data sources like high infrastructure costs or low availability of skilled resources. System Integrators (SI) have been acting in this space for years and they can help accelerate IoT projects and minimize risk.

Other companies choose to collaborate with Industrial IoT Platform (IIoT) providers. These providers offer a comprehensive suite of IIoT functionality on a single platform, which can serve as the foundation for an industrial company to get the most value from their IIoT investments. Their platforms usually offer very similar middleware capabilities to cloud infrastructure vendors but tend to specialize on industrial verticals. They can be a great partner to help accelerate the time-to-insight by means of pre-packaged, industry-focused solutions.

Step 3: Find opportunities to streamline

A lot of companies collect sensor data that they’re not harnessing to its full extent. After proving out the value of IoT to stakeholders, assess your company’s scope of opportunity for IoT use cases.

Let’s use the example of a railway company. Railways consist of thousands of miles of tracks that need to be monitored and maintained due to shifts in the environment, including seismic activity. When these shifts affect the structural integrity of the railway, it can lead to dangerous consequences. Railway companies are tracking these occurrences through sensors and mining the data through business intelligence dashboards. Instead of companies sending out maintenance crews to check whether or not a railway track lies within acceptable thresholds (as per original railroad design specifications), they can identify variances through data visualization and send crews only when the track is at risk, saving companies millions in labor costs and ultimately, keeping tracks safer.

This is just one example of streamlining operations. To start assessing opportunities, ask yourself what is the top metric that everyone in the company understands and lives by and then show how IoT could significantly improve this metric. If people have a stake in it, they will be more willing to adjust to the change and go the extra mile to help make the project successful. Our key goal here is to gain support for an IoT initiative from the entire team so we can provide real outcomes from day one.

Step 4: Think big

Regardless if you choose to get help from an SI or an IIoT provider to accelerate your IoT journey, or you if you are the DIY type, down the line you might realize that other players in the market might also find value in a similar solution. Companies are starting to productionalize use cases and sell IoT solutions-as-a-service.

For example, oil and gas company Zedi manages managing 1.3 million sensors that generate over 47 million daily data points. Their SaaS remote asset management solution, Zedi Access, helps customers track the health of production equipment along with the production process that these assets support. Zedi’s CTO chose to embed Tableau Server into the Zedi Access platform, enabling customers to quickly spot equipment or production issues and prevent monetary loss.

We see more and more companies take this route to maximize their IoT investment after identifying
the ideal IoT model for their business.

Hear more use cases in the Tableau Conference session

Watch the recording of our Tableau Conference session to learn more about how to jump-start your IoT project. We also show you how tangible it is to start your own DIY IoT project in your organization. We have built our own IoT Solution from scratch based on Amazon AWS IoT and we show you how you can easily add sensors and start increasing your business’ operational efficiency.

We also present real IoT customer journeys, ranging from their first IoT Analytics use cases, all the way up to a connected enterprise. Last, but not least, you have the opportunity to see how a company that designs and builds clean energy power plant equipment leverages some of the world’s most advanced IIoT ecosystems in the market, helping their customers maximize productivity and reduce maintenance costs.