You know where the industry is going and how your product needs to evolve. It’s going to involve data, analytics, machine learning, and a new way of doing business. The tech is challenging, but making your case to key stakeholders of the organization may be just as hard, if not more so.

The good news is that you are in the same boat as every other innovation leader within established industrial and manufacturing players. The bad news is that you still face an uphill battle convincing your board to free up budget and business-unit leaders to grant you access to the subject-matter expertise you’ll need to get your IoT initiative off the ground.

Early in your project, you want to build credibility and generate excitement. Here are three key elements you’ll need to make a slam-dunk case for your IoT analytics project.

Proof of User Interest

“Our customers need and want this.”

Demonstrate evidence that your hypotheses about customer pain points and interests are correct. This is best demonstrated by user tests where you walk a random user through a prototype and interview.

User interview excerpts and impressions go a long way in showing stakeholders how much the user will value the new product or service.

It’s rarely too early to get feedback from potential users and customers. It’s often too late.

Functional Analytics Prototype

“We can build this.”

Confirm that you have adequate data and algorithms to bring your solution to fruition.

You can show this to stakeholders in one of two ways.

1. Programming script. This is a bare-bones programing script put together by a data scientists that steps through the different parts of an analytics workflow:

Collect data → Clean Data → Process Data → Feed into an Algorithm → Deliver Insights

This early in the process, you are looking to complete each step in the process and look for major redflags. For example, not having enough data. This will surface issues with data quality and algorithm complexity. However, some stakeholders may lack the technical know-how to make much sense out of a data scientist code.

2. Web app. This is my preferred method: a light-weight, clickable web application. This option has the added bonus of showing how users might interact with the analytics you have in mind. Also, a web app presents much better to non-technical stakeholders.

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IoT Business Models

“Here’s how we’ll make money.”

IoT technology is opening new ways of doing business. Make it clear to your audience how you plan to generate a return on the company’s investment. Here are the three popular IoT business models to consider.

1--IoT product: your existing product plus connectivity. An IoT product will allow you to improve your product remotely (i.e.,, over-the-air software updates) and collect data to inform additional services down the line. If your product line is not already connected, this approach won’t change your business model much. As a result, this is a low-risk way to kick off your product’s IoT journey.

2--IoT product + service: your IoT product comes with add-on / upgrade services. For example, an asset utilization or predictive analytics service can be offered as additional services for a piece of machinery.

3--IoT service: your customer doesn’t buy a machine; they buy a service. This can present a dramatic shift in operations for your company. If you are early in your IoT transformation journey, consider starting with previous business models.

IoT initiatives are more than IT upgrades. They evolve new ways of generating value to the customer and business models. Hitting these three elements in your pitch will go a long way in helping you communicate your vision and the value of your IoT analytics initiative.